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The emerging field of diverse intelligence seeks an integrated view of problem-solving in agents of very different provenance, composition, and substrates. From subcellular chemical networks to swarms of organisms, and across evolved, engineered, and chimeric systems, it is hypothesized that scale-invariant principles of decision-making can be discovered. We propose that cognition in both natural and synthetic systems can be characterized and understood by the interplay between two equally important invariants: (i) the remapping of embedding spaces, and (ii) the navigation within these spaces. Biological collectives, from single cells to entire organisms (and beyond), remap transcriptional, morphological, physiological, or 3D spaces to maintain homeostasis and regenerate structure, while navigating these spaces through distributed error correction. Modern Artificial Intelligence (AI) systems, including transformers, diffusion models, and neural cellular automata enact analogous processes by remapping data into latent embeddings and refining them iteratively through contextualization. We argue that this dual principle – remapping and navigation of embedding spaces via iterative error minimization – constitutes a substrate-independent invariant of cognition. Recognizing this shared mechanism not only illuminates deep parallels between living systems and artificial models, but also provides a unifying framework for engineering adaptive intelligence across scales.

Life is one of the most fascinating features of the physical world. Despite centuries of scientific study, experts still disagree about the definition, and even the possibility or utility of a definition, of this field. In a recent paper, we used AI to analyze the conceptual space formed by definitions of life given by a select set of modern workers in the life sciences and related fields. However, some of the most interesting material emerged as real-time conversations among those polled. In order to ensure that these ideas are not lost to the peer-reviewed scientific record, we here provide a minimally-edited (largely verbatim) transcript of the email chain among leading thinkers, containing numerous clarifications, disagreements, and challenges that enrich the topic of Life. It is our hope that this case study serves as an example for future papers, since the exchange of ideas among scientists is at least as interesting and valuable as formal scientific manuscripts written from a single perspective.

Humans routinely offload cognitive tasks to their environments. Here we show, employing just basic physics and the Free Energy Principle, that all time-persistent information-processing systems offload information-processing tasks to their environments. Hence all cognitive systems engage in cognitive offloading. We show how ecological niche construction, kinematic replication, bioelectric signaling, the development of communication systems based on shared semantics, and the ability of LLMs to demonstrate fluent language use in the absence of extra-linguistic input all exemplify this offloading process. We conclude that both theoretical understanding of problem-solving abilities and the engineering of such abilities into artifacts will be improved by considering active computation by the environment as a ubiquitous adjunct to cognition in both living and artificial systems.

“When using Granger causality to assess causal directional associations between cell markers and participant’s physiological parameters, EEG measurements showed significant bidirectional causal effects with cell metrics, especially β-actin and intracellular Ca2+ levels (p < 0.000001).”

We argue here that the Origin of Life (OOL) problem is not just a chemistry problem but is also, and primarily, a cognitive science problem. When interpreted through the lens of the Conway-Kochen theorem and the Free Energy Principle, contemporary physics characterizes all complex dynamical systems that persist through time as Bayesian agents. If all persistent systems are to some - perhaps only minimal - extent cognitive, are all persistent systems to some extent alive, or are living systems only a subset of cognitive systems? We argue that no bright line can be drawn, and we re-assess, from this perspective, the Fermi paradox and the Drake equation. We conclude that improving our abilities to recognize and communicate with diverse intelligences in diverse embodiments, whether based on familiar biochemistry or not, will either resolve or obviate the OOL problem.

This paper examines the constraints that the free-energy principle (FEP) places on possible model of consciousness, particularly models of attentional control and imaginative experiences, including episodic memory and planning. We first rehearse the classical and quantum formulations of the FEP, focusing on their application to multi-component systems, in which only some components interact directly with the external environment. In particular, we discuss the role of internal boundaries that have the structure of Markov blankets, and hence function as classical information channels between components. We then show how this formal structure supports models of attentional control and imaginative experience, with a focus on (i) how imaginative experience can employ the spatio-temporal and object-recognition reference frames employed in ordinary, non-imaginative experience and (ii) how imaginative experience can be internally generated but still surprising. We conclude by discussing the implementation, phenomenology, and phylogeny of imaginative experience, and the implications of the large state and trait variability of imaginative experience in humans.

Abstract In the classical theory of computation, e.g. , in the Turing Machine model, computational processes employ only local space and time resources, and their resource usage can be accurately measured by us as users. General relativity and quantum theory, however, introduce the possibility of computational processes that employ nonlocal spatial or temporal resources, raising the question of how these relate to classical resources. Operational, i.e. , device-independent, protocols to certify the use of entanglement as a resource are well known. We prove, however, that the independence of spatially separated systems cannot be operationally certified. The verifier (C) in a multiple interactive provers with shared entanglement (MIP*) protocol cannot, therefore, operationally demonstrate that the “multiple” provers are independent, i.e. , cannot operationally distinguish a MIP* machine from a monolithic quantum computer. Thus C cannot operationally distinguish a MIP* machine from a quantum TM, and hence cannot operationally demonstrate the solution to arbitrary problems in RE. Any claim that a MIP* machine has solved a TM-undecidable problem, e.g. , that of Ji Z. et al. , Commun. ACM , 64 (2020) 131, is therefore operationally circular, as the problem of deciding whether a physical system is a MIP* machine is itself TM-undecidable. We then prove a similar result showing that whether a system employs a closed time-like curve (CTC) as a resource is operationally undecidable. In such settings, therefore, theoretical analyses of resource usage cease to be reliable indicators of practical computational capability.

We argue here that the Orgin of Life (OOL) problem is not just a chemistryproblem, but is also, and primarily, a cognitive science problem. When interpretedthrough the lens of the Conway-Kochen theorem and the Free Energy Principle, con-temporary physics characterizes all complex dynamical systems that persist throughtime as Bayesian agents. If all persistent systems are to some – perhaps only minimal– extent cognitive, are all persistent systems to some extent alive, or are living sys-tems only a subset of cognitive systems? We argue that no bright line can be drawn,and we re-assess, from this perspective, the Fermi paradox and the Drake equation.We conclude that improving our abilities to recognize and communicate with diverseintelligences in diverse embodiments, whether based on familiar biochemistry or not,will either resolve or obviate the OOL problem.

Multiple theoretical models of dissociative experiences have been formulated over the last century. These theories are clinically useful; however, it remains unclear if common factors exist in various pathways leading to an onset of dissociations. In this paper we provide a framework for building an integrated, dynamical model of dissociative experiences. This framework combines a first-principles-based perspective with nonlinear dynamical systems, clinical, and neurobiological perspectives. We propose that a substantial change in the parameter we call "temporal depth" can be a common factor in dissociative episodes of any etiology, moreover, we consider such a change to have causal power. In the follow-up series of papers, we will provide empirical data supporting the collapse of temporal depth in various kinds of dissociative experiences, a computer simulation that would test this model's computational components, and preliminary ideas for therapeutic applications.

Computational complexity characterizes the usage of spatial and temporal resources by computational processes. In the classical theory of computation, e.g. in the Turing Machine model, computational processes employ only local space and time resources, and their resource usage can be accurately measured by us as users. General relativity and quantum theory, however, introduce the possibility of computational processes that employ nonlocal spatial or temporal resources. While the space and time complexity of classical computing can be given a clear operational meaning, this is no longer the case in any setting involving nonlocal resources. In such settings, theoretical analyses of resource usage cease to be reliable indicators of practical computational capability. We prove that the verifier (C) in a multiple interactive provers with shared entanglement (MIP*) protocol cannot operationally demonstrate that the "multiple" provers are independent, i.e. cannot operationally distinguish a MIP* machine from a monolithic quantum computer. Thus C cannot operationally distinguish a MIP* machine from a quantum TM, and hence cannot operationally demonstrate the solution to arbitrary problems in RE. Any claim that a MIP* machine has solved a TM-undecidable problem is, therefore, circular, as the problem of deciding whether a physical system is a MIP* machine is itself TM-undecidable. Consequently, despite the space and time complexity of classical computing having a clear operational meaning, this is no longer the case in any setting involving nonlocal resources. In such settings, theoretical analyses of resource usage cease to be reliable indicators of practical computational capability. This has practical consequences when assessing newly proposed computational frameworks based on quantum theories.

The existence and practical utility of operational protocols that certify entanglement raises the question of whether operational protocols exist that certify the absence of entanglement, i.e. that certify separability. We show, within a purely topological, interpretation-independent representation, that such protocols do not exist. Classicality is therefore, as Bohr suggested, purely a pragmatic notion.

Abstract Topological quantum field theories (TQFTs) provide a general, minimal‐assumption language for describing quantum‐state preparation and measurement. They therefore provide a general language in which to express multi‐agent communication protocols, e.g., local operations, classical communication (LOCC) protocols. Here, LOCC protocols are constructed using TQFT and it is shown that LOCC protocols generically induce quantum error‐correcting codes (QECCs). Using multi‐observer scenarios described by quantum Darwinism and Bell/EPR experiments as examples, it is shown how these LOCC‐induced QECCs effectively convert entanglement into classical redundancy. In the accompanying Part II, it is shown that such QECCs can be regarded as implementing, or inducing the emergence of, spacetimes on the boundaries between interacting systems. The connection between inter‐agent communication and spacetime using BF and Chern‐Simons theories, and then using topological M‐theory is investigated.

Abstract Topological quantum field theories (TQFTs) provide a general, minimal‐assumption language for describing quantum‐state preparation and measurement. They therefore provide a general language in which to express multi‐agent communication protocols, e.g., local operations, classical communication (LOCC) protocols. In the accompanying Part I, we construct LOCC protocols using TQFT, and show that LOCC protocols induce quantum error‐correcting codes (QECCs) on the agent‐environment boundary. Such QECCs can be regarded as implementing or inducing the emergence of spacetimes on such boundaries. Here connection between inter‐agent communication and spacetime is investigated, by exploiting different realizations of TQFT. The authors delved into TQFTs that support on their boundaries spin‐networks as computational systems: these are known as topological quantum neural networks (TQNNs). TQNNs, which have a natural representation as tensor networks, implement QECC. The HaPPY code is recognized to be a paradigmatic example. How generic QECCs, as bulk‐boundary codes, induce effective spacetimes is then shown. The effective spatial and temporal separations that take place in QECC enables LOCC protocols between spatially separated observers. The implementation of QECCs in BF and Chern‐Simons theories are then considered, and QECC‐induced spacetimes are shown to provide the classical redundancy required for LOCC. Finally, the topological M‐theory is considered as an implementation of QECC in higher spacetime dimensions.

We show that in the operational setting of a two-agent, local operations, classical communication (LOCC) protocol, Alice and Bob cannot operationally distinguish monogamous entanglement from a topological identification of points in their respective local spacetimes, i.e. that ER = EPR can be recovered as an operational theorem. Our construction immediately implies that in this operational setting, the local topology of spacetime is observer-relative. It also provides a simple demonstration of the non-traversability of ER bridges. As our construction does not depend on an embedding geometry, it generalizes previous geometric approaches to ER = EPR.

Binz et al. propose a general framework for meta-learning and contrast it with built-by-hand Bayesian models. We comment on some architectural assumptions of the approach, its relation to the active inference framework, its potential applicability to living systems in general, and the advantages of the latter in addressing the explanation problem.

In this case study, a self-described biofield therapy (BT) practitioner (participant) took part in multiple ( n = 60) treatment and control (non-treatment) sessions under double-blind conditions. During the treatment phases, the participant provided BT treatment at a distance of about 12 inches from the cells, alternating with rest phases where no such efforts were made. Human pancreatic cancer cell activity was assessed using three markers – cytoskeleton changes (tubulin and β-actin) and Ca 2+ uptake. The study examined changes in the participant’s physiological parameters including electroencephalogram (EEG) and heart rate measures during the treatment of: (1) live cells and (2) either dead cells or medium only with no cells (control group). Changes in cellular outcomes and if there was an association between the participant’s physiological parameters and cellular outcomes were examined. The experimental setup was a 2 × 2 design, contrasting cell type (live vs. control) against session type (treatment vs. non-treatment). Parallel sham-treated control cells were examined for changes in the cell parameters over time while controlling for the presence of a person in front of the cells mimicking the distance and movements of the participant. The participant’s physiological data, including 64-channel EEG and heart rate, were continuously monitored throughout these sessions. We observed significant ( p < 0.01) spectral changes in the participant’s EEG during BT treatment in all frequency bands of interest, as well as in heart rate variability (HRV) (RMSSD measure; p < 0.01). We also observed significant differences in beta and gamma EEG and HRV (pNN50 measure) when the participant treated live but not control cells ( p = 0.02). However, no interaction between treatment and cell type (live vs. dead cells/medium-no cells) was observed. We observed Ca 2+ uptake increased over time during both BT and sham treatment, but the increase was significantly less for the BT group relative to the sham-treatment controls ( p = 0.03). When using Granger causality to assess causal directional associations between cell markers and participant’s physiological parameters, EEG measurements showed significant bidirectional causal effects with cell metrics, especially β-actin and intracellular Ca 2+ levels ( p < 0.000001). These outcomes suggest a complex relationship between physiological responses and cellular effects during BT treatment sessions. Given the study’s limitations, follow-up investigations are warranted.

Multiple theoretical models of dissociative experiences have been formulated over the last century. These theories are clinically useful; however, it remains unclear if common factors exist in various pathways leading to an onset of dissociations. This article is the first in a series of papers, where we provide a framework for building an integrated model of dissociative experiences. This framework combines a first-principles-based perspective with dynamical systems perspective. We propose that temporal depth collapse can be a possible common factor in dissociative episodes of any etiology, moreover, we consider this factor to have causal power. In a follow-up paper, we will examine this model from the standpoint of clinical practice and neurobiological theories of dissociations. We will also provide empirical data in support of this model and present ideas for therapeutic applications.

Statistically significant violations of the Clauser–Horne–Shimony–Holt (CHSH) inequality are the “gold standard” test for quantum entanglement between spatially separated systems. Here, we report an experimental design that implements a CHSH test between bioelectric state variables for a human subject and bioelectric and/or biochemical state variables for cultured human cells in vitro. While we were unable to obtain evidence for entanglement with this design, observing only classical correlation, we report lessons learned and suggest possible avenues for future studies.

The ideas of self-observation and self-representation, and the concomitant idea of self-control, pervade both the cognitive and life sciences, arising in domains as diverse as immunology and robotics. Here, we ask in a very general way whether, and to what extent, these ideas make sense. Using a generic model of physical interactions, we prove a theorem and several corollaries that severely restrict applicable notions of self-observation, self-representation, and self-control. We show, in particular, that adding observational, representational, or control capabilities to a meta-level component of a system cannot, even in principle, lead to a complete meta-level representation of the system as a whole. We conclude that self-representation can at best be heuristic, and that self models cannot, in general, be empirically tested by the systems that implement them.

When describing Active Inference Agents (AIAs), the term "energy" can have two distinct meanings. One is the energy that is utilized by the AIA (e.g., electrical energy or chemical energy). The second meaning is so-called Variational Free Energy (VFE), a statistical quantity which provides an upper bound on surprisal. In this paper, we develop an account of the former quantity-the Thermodynamic Free Energy (TFE)-and its relationship with the latter. We highlight the necessary tradeoffs between these two in a generic, quantum information-theoretic formulation, and the macroscopic consequences of those tradeoffs for the ways that organisms approach their environments. By making this tradeoff explicit, we provide a theoretical basis for the different metabolic strategies that organisms from plants to predators use to survive.

We start from the fundamental premise that any physical interaction can be interpreted as a game. To demonstrate this, we draw upon the free energy principle and the theory of quantum reference frames. In this way, we place the game-theoretic Nash Equilibrium in a new light in so far as the incompleteness and undecidability of the concept, as well as the nature of strategies in general, can be seen as the consequences of certain no-go theorems. We show that games of the generic imitation type follow a circularity of idealization that includes the good regulator theorem, generalized synchrony, and undecidability of the Turing test. We discuss Bayesian games in the light of Bell non-locality and establish the basics of quantum games, which we relate to local operations and classical communication protocols. In this light, we also review the rationality of gaming strategies from the players’ point of view.

Topological quantum field theories (TQFTs) provide a general, minimal-assumption language for describing quantum-state preparation and measurement. They therefore provide a general language in which to express multi-agent communication protocols, e.g. local operations, classical communication (LOCC) protocols. In the accompanying Part I, we construct LOCC protocols using TQFT, and show that LOCC protocols induce quantum error-correcting codes (QECCs) on the agent-environment boundary. Such QECCs can be regarded as implementing or inducing the emergence of spacetimes on such boundaries. Here we investigate this connection between inter-agent communication and spacetime, exploiting different realizations of TQFT. We delve into TQFTs that support on their boundaries spin-networks as computational systems: these are known as topological quantum neural networks (TQNNs). TQNNs, which have a natural representation as tensor networks, implement QECC. We recognize into the HaPPY code a paradigmatic example. We then show how generic QECCs, as bulk-boundary codes, induce effective spacetimes. The effective spatial and temporal separations that take place in QECC enables LOCC protocols between spatially separated observers. We then consider the implementation of QECCs in BF and Chern-Simons theories, and show that QECC-induced spacetimes provide the classical redundancy required for LOCC. Finally, we consider topological M-theory as an implementation of QECC in higher spacetime dimensions.

We show that in the operational setting of a two-agent, local operations, classical communication (LOCC) protocol, Alice and Bob cannot operationally distinguish monogamous entanglement from a topological identification of points in their respective local spacetimes, i.e. that ER = EPR can be recovered as an operational theorem. Our construction immediately implies that in this operational setting, the local topology of spacetime is observer-relative. It also provides a simple demonstration of the non-traversability of ER bridges. As our construction does not depend on an embedding geometry, it generalizes previous geometric approaches to ER = EPR.

Replicating or exceeding human intelligence, not just in particular domains but in general, has always been a major goal of Artificial Intelligence (AI). We argue here that “human intelligence” is not only ill-defined, but often conflated with broader aspects of human psychology. Standard arguments for replicating it are morally unacceptable. We then suggest a reframing: that the proper goal of AI is not to replicate humans, but to complement them by creating diverse intelligences capable of collaborating with humans. This goal renders issues of theory of mind, empathy, and caring, or community engagement, central to AI. It also challenges AI to better understand the circumstances in which human intelligence, including human moral intelligence, fails.

This paper concerns the distributed intelligence or federated inference that emerges under belief-sharing among agents who share a common world-and world model. Imagine, for example, several animals keeping a lookout for predators. Their collective surveillance rests upon being able to communicate their beliefs-about what they see-among themselves. But, how is this possible? Here, we show how all the necessary components arise from minimising free energy. We use numerical studies to simulate the generation, acquisition and emergence of language in synthetic agents. Specifically, we consider inference, learning and selection as minimising the variational free energy of posterior (i.e., Bayesian) beliefs about the states, parameters and structure of generative models, respectively. The common theme-that attends these optimisation processes-is the selection of actions that minimise expected free energy, leading to active inference, learning and model selection (a.k.a., structure learning). We first illustrate the role of communication in resolving uncertainty about the latent states of a partially observed world, on which agents have complementary perspectives. We then consider the acquisition of the requisite language-entailed by a likelihood mapping from an agent's beliefs to their overt expression (e.g., speech)-showing that language can be transmitted across generations by active learning. Finally, we show that language is an emergent property of free energy minimisation, when agents operate within the same econiche. We conclude with a discussion of various perspectives on these phenomena; ranging from cultural niche construction, through federated learning, to the emergence of complexity in ensembles of self-organising systems.

If episodic memory is constructive, experienced time is also a construct. We develop an event-based formalism that replaces the traditional objective, agent-independent notion of time with a constructive, agent-dependent notion of time. We show how to make this agent-dependent time entropic and hence well-defined. We use sheaf-theoretic techniques to render agent-dependent time functorial and to construct episodic memories as sequences of observed and constructed events with well-defined limits that maximise the consistency of categorisations assigned to objects appearing in memories. We then develop a condensed formalism that represents episodic memories as pure constructs from single events. We formulate an empirical hypothesis that human episodic memory implements a particular time-symmetric constructive functor, and discuss possible experimental tests.

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. In this Part I, we introduce the free-energy principle (FEP) and the idea of active inference as Bayesian prediction-error minimization, and show how the control problem arises in active inference systems. We then review classical and quantum formulations of the FEP, with the former being the classical limit of the latter. In the accompanying Part II, we show that when systems are described as executing active inference driven by the FEP, their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implemented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. In Part I, we introduced the free-energy principle (FEP) and the idea of active inference as Bayesian prediction-error minimization, and show how the control problem arises in active inference systems. We then review classical and quantum formulations of the FEP, with the former being the classical limit of the latter. In this accompanying Part II, we show that when systems are described as executing active inference driven by the FEP, their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implemented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. We show here that when systems are described as executing active inference driven by the free-energy principle (and hence can be considered Bayesian prediction-error minimizers), their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implmented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.

This paper presents a model of consciousness that follows directly from the free- energy principle (FEP). We first rehearse the classical and quantum formulations of the FEP. In particular, we consider the “inner screen hypothesis” that follows from the quantum information theoretic version of the FEP. We then review applications of the FEP to the known sparse (nested and hierarchical) neuro-anatomy of the brain. We focus on the holographic structure of the brain, and how this structure supports (overt and covert) action.

This paper aims to assess whether the recently proposed "inner screen model" of consciousness that follows from the free-energy principle (FEP) can be regarded as a minimal unifying model (MUM) of consciousness, thereby providing a common foundational model for consciousness studies, and integrating approaches to consciousness based on the FEP. We first present the inner screen model, which follows from applying the quantum information theoretic version of the FEP to the known sparse (nested and hierarchical) neuroanatomy of the brain. We then review models of consciousness that are premised on the FEP. Specifically, we review Bayesian versions of the global workspace and attention schema theories, theories premised on world-models and self-models, and models formalizing the computational structure and properties of time-consciousness. We then discuss how extant FEP-theoretic models of consciousness can be situated with respect to the candidate MUM.

If episodic memory is constructive, experienced time is also a construct. We develop an event-based formalism that replaces the traditional objective, agent-independent notion of time with a constructive, agent-dependent notion of time. We show how to make this agent-dependent time entropic and hence well-defined. We use sheaf-theoretic techniques to render agent-dependent time functorial and to construct episodic memories as sequences of observed and constructed events with well-defined limits that maximize the consistency of categorizations assigned to objects appearing in memories. We then develop a condensed formalism that represents episodic memories as pure constructs from single events. We formulate an empirical hypothesis that human episodic memory implements a particular time-symmetric constructive functor, and discuss possible experimental tests.

This paper introduces a variational formulation of natural selection, paying special attention to the nature of 'things' and the way that different 'kinds' of 'things' are individuated from-and influence-each other. We use the Bayesian mechanics of particular partitions to understand how slow phylogenetic processes constrain-and are constrained by-fast, phenotypic processes. The main result is a formulation of adaptive fitness as a path integral of phenotypic fitness. Paths of least action, at the phenotypic and phylogenetic scales, can then be read as inference and learning processes, respectively. In this view, a phenotype actively infers the state of its econiche under a generative model, whose parameters are learned via natural (Bayesian model) selection. The ensuing variational synthesis features some unexpected aspects. Perhaps the most notable is that it is not possible to describe or model a population of conspecifics per se. Rather, it is necessary to consider populations of distinct natural kinds that influence each other. This paper is limited to a description of the mathematical apparatus and accompanying ideas. Subsequent work will use these methods for simulations and numerical analyses-and identify points of contact with related mathematical formulations of evolution.

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. We show here that when systems are described as executing active inference driven by the free-energy principle (and hence can be considered Bayesian prediction-error minimizers), their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implmented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.

Topological quantum field theories (TQFTs) provide a general, minimal-assumption language for describing quantum-state preparation and measurement. They therefore provide a general language in which to express multi-agent communication protocols, e.g. local operations, classical communication (LOCC) protocols. Here we construct LOCC protocols using TQFT, and show that LOCC protocols generically induce quantum error-correcting codes (QECCs). Using multi-observer scenarios described by quantum Darwinism and Bell/EPR experiments as examples, we show how these LOCC-induced QECCs effectively convert entanglement into classical redundancy. In the accompanying Part II, we show that such QECCs can be regarded as implementing, or inducing the emergence of, spacetimes on the boundaries between interacting systems. We investigate this connection between inter-agent communication and spacetime using BF and Chern-Simons theories, and then using topological M-theory.

We study the relationship between assumptions of state separability and both preparation and measurement contextuality, and the relationship of both of these to the frame problem, the problem of predicting what does not change in consequence of an action. We state a quantum analog of the latter and prove its undecidability. We show how contextuality is generically induced in state preparation and measurement by basis choice, thermodynamic exchange, and the imposition of a priori causal models, and how fine-tuning assumptions appear ubiquitously in settings characterized as non-contextual.

This paper presents a model of consciousness that follows directly from the free-energy principle (FEP). We first rehearse the classical and quantum formulations of the FEP. In particular, we consider the inner screen hypothesis that follows from the quantum information theoretic version of the FEP. We then review applications of the FEP to the known sparse (nested and hierarchical) neuro-anatomy of the brain. We focus on the holographic structure of the brain, and how this structure supports (overt and covert) action.

Abstract We introduce novel methods for implementing generic quantum information within a scale‐free architecture. For a given observable system, we show how observational outcomes are taken to be finite bit strings induced by measurement operators derived from a holographic screen bounding the system. In this framework, measurements of identified systems with respect to defined reference frames are represented by semantically‐regulated information flows through distributed systems of finite sets of binary‐valued Barwise‐Seligman classifiers. Specifically, we construct a functor from the category of cone‐cocone diagrams (CCCDs) over finite sets of classifiers, to the category of finite cobordisms of Hilbert spaces. We show that finite CCCDs provide a generic representation of finite quantum reference frames (QRFs). Hence the constructed functor shows how sequential finite measurements can induce TQFTs. The only requirement is that each measurement in a sequence, by itself, satisfies Bayesian coherence, hence that the probabilities it assigns satisfy the Kolmogorov axioms. We extend the analysis too develop topological quantum neural networks (TQNNs), which enable machine learning with functorial evolution of quantum neural 2‐complexes (TQN2Cs) governed by TQFTs amplitudes, and resort to the Atiyah‐Singer theorems in order to classify topological data processed by TQN2Cs. We then comment about the quiver representation of CCCDs and generalized spin‐networks, a basis of the Hilbert spaces of both TQNNs and TQFTs. We finally review potential implementations of this framework in solid state physics and suggest applications to quantum simulation and biological information processing.

Abstract We show how any finite physical system with morphological, i.e. three-dimensional embedding or shape, degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve over time towards a neuromorphic morphology that supports hierarchical computations in which each ‘level’ of the hierarchy enacts a coarse-graining of its inputs, and dually, a fine-graining of its outputs. Such hierarchies occur throughout biology, from the architectures of intracellular signal transduction pathways to the large-scale organization of perception and action cycles in the mammalian brain. The close formal connections between cone-cocone diagrams (CCCD) as models of quantum reference frames on the one hand, and between CCCDs and topological quantum field theories on the other, allow the representation of such computations in the fully-general quantum-computational framework of topological quantum neural networks.

We show in this pedagogical review that far from being an apparent law of physics that stands by itself, the holographic principle is a straightforward consequence of the quantum information theory of separable systems. It provides a basis for the theories of measurement, time, and scattering. Utilizing the notion of holographic screens, which are information encoding boundaries between physical subsystems, we demonstrate that the physical interaction is an information exchange during which information is strictly conserved. Then we use generalized holographic principle in order to flesh out a fully-general quantum theory of measurement in which the measurement produces finite-resolution, classical outcomes. Further, we show that the measurements are given meaning by quantum reference frames and sequential measurements induce topological quantum field theories. Finally, we discuss principles equivalent to the holographic principle, including Markov blankets and the free-energy principle in biology, multiple realizability and virtual machines in computer science, and active inference and interface theories in cognitive science. This appearance in multiple disciplines suggests that the holographic principle is not just a fundamental principle of physics, but of all of science. Quanta 2022; 11: 72–96.

One of the most salient features of life is its capacity to handle novelty: to thrive and adapt to new circumstances and changes of both environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems, and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine, and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.

Using the formal framework of the Free Energy Principle, we show how generic thermodynamic requirements on bidirectional information exchange between a system and its environment can generate complexity. This leads to the emergence of hierarchical computational architectures in systems that operate sufficiently far from thermal equilibrium. In this setting, the environment of any system increases its ability to predict system behavior by “engineering” the system towards increased morphological complexity and hence larger-scale, more macroscopic behaviors. When seen in this light, regulative development becomes an environmentally-driven process in which“parts” are assembled to produce a system with predictable behavior. We suggest on this basis that life is thermodynamically favorable and that human engineers are acting like a generic “environment” when designing artificial living systems.

This edited collection explores current approaches to understanding space, time, and gravity within a quantum-theoretical framework. &nbsp;In most such approaches, the three-dimensional space of ordinary perception and action is physically fundamental, but is rather emergent from underlying structures or dynamics that can, in general, be described in terms of information flows. &nbsp;Processes such as measurement and computation are, therefore, fundamental to the notion of physical space. &nbsp;

Evolution is full of coevolving systems characterized by complex spatio-temporal interactions that lead to intertwined processes of adaptation. Yet, how adaptation across multiple levels of temporal scales and biological complexity is achieved remains unclear. Here, we formalize how evolutionary multi-scale processing underlying adaptation constitutes a form of metacognition flowing from definitions of metaprocessing in machine learning. We show (1) how the evolution of metacognitive systems can be expected when fitness landscapes vary on multiple time scales, and (2) how multiple time scales emerge during coevolutionary processes of sufficiently complex interactions. After defining a metaprocessor as a regulator with local memory, we prove that metacognition is more energetically efficient than purely object-level cognition when selection operates at multiple timescales in evolution. Furthermore, we show that existing modeling approaches to coadaptation and coevolution-here active inference networks, predator-prey interactions, coupled genetic algorithms, and generative adversarial networks-lead to multiple emergent timescales underlying forms of metacognition. Lastly, we show how coarse-grained structures emerge naturally in any resource-limited system, providing sufficient evidence for metacognitive systems to be a prevalent and vital component of (co-)evolution. Therefore, multi-scale processing is a necessary requirement for many evolutionary scenarios, leading to de facto metacognitive evolutionary outcomes.

One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.

Nicolas Gisin [...]

We introduce novel methods for implementing generic quantum information within a scale-free architecture. For a given observable system, we show how observational outcomes are taken to be finite bit strings induced by measurement operators derived from a holographic screen bounding the system. In this framework, measurements of identified systems with respect to defined reference frames are represented by semantically-regulated information flows through distributed systems of finite sets of binary-valued Barwise-Seligman classifiers. Specifically, we construct a functor from the category of cone-cocone diagrams (CCCDs) over finite sets of classifiers, to the category of finite cobordisms of Hilbert spaces. We show that finite CCCDs provide a generic representation of finite quantum reference frames (QRFs). Hence the constructed functor shows how sequential finite measurements can induce TQFTs. The only requirement is that each measurement in a sequence, by itself, satisfies Bayesian coherence, hence that the probabilities it assigns satisfy the Kolmogorov axioms. We extend the analysis so develop topological quantum neural networks (TQNNs), which enable machine learning with functorial evolution of quantum neural 2-complexes (TQN2Cs) governed by TQFTs amplitudes, and resort to the Atiyah-Singer theorems in order to classify topological data processed by TQN2Cs. We then comment about the quiver representation of CCCDs and generalized spin-networks, a basis of the Hilbert spaces of both TQNNs and TQFTs. We finally review potential implementations of this framework in solid state physics and suggest applications to quantum simulation and biological information processing.

We show how any system with morphological degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve toward a neuromorphic morphology that supports hierarchical computations in which each level of the hierarchy enacts a coarse-graining of its inputs, and dually a fine-graining of its outputs. Such hierarchies occur throughout biology, from the architectures of intracellular signal transduction pathways to the large-scale organization of perception and action cycles in the mammalian brain. Formally, the close formal connections between cone-cocone diagrams (CCCD) as models of quantum reference frames on the one hand, and between CCCDs and topological quantum field theories on the other, allow the representation of such computations in the fully-general quantum-computational framework of topological quantum neural networks.

Deep Neural Networks miss a principled model of their operation. A novel framework for supervised learning based on Topological Quantum Field Theory that looks particularly well suited for implementation on quantum processors has been recently explored. We propose using this framework to understand the problem of generalisation in Deep Neural Networks. More specifically, in this approach, Deep Neural Networks are viewed as the semi-classical limit of Topological Quantum Neural Networks. A framework of this kind explains the overfitting behavior of Deep Neural Networks during the training step and the corresponding generalisation capabilities. We explore the paradigmatic case of the perceptron, which we implement as the semiclassical limit of Topological Quantum Neural Networks. We apply a novel algorithm we developed, showing that it obtains similar results to standard neural networks, but without the need for training (optimisation).

We show in this pedagogical review that far from being "an apparent law of physics that stands by itself" (R. Bousso, Rev. Mod. Phys. 74 (2002), 825-874), the holographic principle (HP) is a straightforward consequence of the quantum information theory of separable systems. It provides a basis for the theories of measurement, time, and scattering. Principles equivalent to the HP appear in both computer science and the life sciences, suggesting that the HP is not just a fundamental principle of physics, but of all of science.

Theories of consciousness and cognition that assume a neural substrate automatically regard phylogenetically basal, nonneural systems as nonconscious and noncognitive. Here, we advance a scale-free characterization of consciousness and cognition that regards basal systems, including synthetic constructs, as not only informative about the structure and function of experience in more complex systems but also as offering distinct advantages for experimental manipulation. Our "minimal physicalist" approach makes no assumptions beyond those of quantum information theory, and hence is applicable from the molecular scale upwards. We show that standard concepts including integrated information, state broadcasting via small-world networks, and hierarchical Bayesian inference emerge naturally in this setting, and that common phenomena including stigmergic memory, perceptual coarse-graining, and attention switching follow directly from the thermodynamic requirements of classical computation. We show that the self-representation that lies at the heart of human autonoetic awareness can be traced as far back as, and serves the same basic functions as, the stress response in bacteria and other basal systems.

Abstract Regeneration requires the production of large numbers of new cells, and thus cell division regulators, particularly ERK signaling, are critical in regulating this process. In the highly regenerative planarian flatworm, questions remain as to whether ERK signaling controls overall regeneration or plays a head-specific role. Here we show that ERK inhibition in the 3 days following amputation delays regeneration, but that all tissues except the head can overcome this inhibition, resulting in headless regenerates. This prevention of head regeneration happens to a different degree along the anterior-posterior axis, with very anterior wounds regenerating heads even under ERK inhibition. Remarkably, 4 to 18 weeks after injury, the headless animals induced by ERK inhibition remodel to regain single-headed morphology, in the absence of further injury, in a process driven by Wnt/β-catenin signaling. Interestingly, headless animals are likely to exhibit unstable axial polarity, and cutting or fissioning prior to remodeling can result in body-wide reversal of anterior-posterior polarity. Our data reveal new aspects of how ERK signaling regulates regeneration in planaria and show anatomical remodeling on very long timescales.

Philosophy and AI have had a difficult relationship from the beginning. The “classic” period from 1950 to 2000 saw four major conflicts, first about the logical coherence of AI as an endeavor, and then about architecture, semantics, and the Frame Problem. Since 2000, these early debates have been largely replaced by arguments about consciousness and ethics, arguments that now involve neuroscientists, lawyers, and economists as well as AI scientists and philosophers. We trace these developments, and speculate about the future.

We show that a generalized version of the holographic principle can be derived from the Hamiltonian description of information flow within a quantum system that maintains a separable state. We then show that this generalized holographic principle entails a general principle of gauge invariance. When this is realized in an ambient Lorentzian space-time, gauge invariance under the Poincaré group is immediately achieved. We apply this pathway to retrieve the action of gravity. The latter is cast à la Wilczek through a similar formulation derived by MacDowell and Mansouri, which involves the representation theory of the Lie groups SO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>3,2</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math> and SO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>4,1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math> .

Any interaction between finite quantum systems in a separable joint state can be viewed as encoding classical information on an induced holographic screen. Here we show that when such an interaction is represented as a measurement, the quantum reference frames (QRFs) deployed to identify systems and pick out their pointer states induce decoherence, breaking the symmetry of the holographic encoding in an observer-relative way. Observable entanglement, contextuality, and classical memory are, in this representation, logical and temporal relations between QRFs. Sharing entanglement as a resource requires a priori shared QRFs.

<JATS1:p>An entertaining introduction to the clashes between philosophy and AI over the last 70 years, from claims and counter-claims about the ability to implement consciousness, to arguments about cognitive architecture and ChatGPT.</JATS1:p> <JATS1:p>Now updated to include the latest developments in AI, this is an exploration of the most famous philosophical arguments against building a machine with human-level intelligence. The arguments are organized into four central AI wars, showing how the debate that played out between the philosophers, AI scientists and engineers building AI systems.</JATS1:p> <JATS1:p>Here is your guide to the major philosophical questions and attacks AI has received throughout its history. Packed with fresh insights and supporting material, this second edition features new content on: – Language Learning Models (LLMs) and the existence of generative AI– Sustainable AI and its ability to regulate our climate– The theoretical, ethical and legislative issues around ‘computational creativity’– The uncanny valley effect and its potential consequences for AI</JATS1:p> <JATS1:p>Are we on the brink of a new AI War? This introduction is for anyone looking to understand the debates that have shaped the philosophy of AI and the arguments that will define its future. It shows us what AI has been doing since its invention in the 1950s – pointing us back, repeatedly, to the philosophical questions humans have always faced: questions about knowledge, meaning, and how we should behave toward each other and toward the rest of the world.</JATS1:p> <JATS1:p>https://bibliores.bloomsbury.com/getimage.aspx?bibliologin=1&amp;s=ad6d3224-1829-46e2-8081-ae850d5649a0&amp;cat=default&amp;class=books&amp;type=jpg&amp;mode=&amp;size=original&amp;id=902094</JATS1:p>

This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets science, and the role of philosophy in the culture in which it is embedded. Organising the arguments into four core topics – ‘Is AI possible’, ‘Architectures of the Mind’, ‘Mental Semantics and Mental Symbols’ and ‘Rationality and Creativity’ – this book shows the debate that played out between the philosophers on both sides of the question, and, as well, the debate between philosophers and AI scientists and engineers building

Galileo's Error (Goff, 2019) leaves important questions unasked and hence unanswered. I focus on two of these: the question of what a theory of consciousness is supposed to accomplish, and the question of what the materialism–dualism–panpsychism debate is actually about.

When the history of life on earth is viewed as a history of cell division, all of life becomes a single cell lineage. The growth and differentiation of this lineage in reciprocal interaction with its environment can be viewed as a developmental process; hence the evolution of life on earth can also be seen as the development of life on earth. Here, in reviewing this field, some potentially fruitful research directions suggested by this change in perspective are highlighted. Variation and selection become, for example, bidirectional information flows between scales, while the notions of "cooperation" and "competition" become scale relative. The language of communication, inference, and information processing becomes more useful than the language of causation to describe the interactions of both homogeneous and heterogeneous living systems at any scale. Emerging scale-free theoretical frameworks such as predictive coding and active inference provide conceptual tools for reconceptualizing biology as the study of a unified, multiscale dynamical system.

Gilead et al. propose an ontology of abstract representations based on folk-psychological conceptions of cognitive architecture. There is, however, no evidence that the experience of cognition reveals the architecture of cognition. Scale-free architectural models propose that cognition has the same computational architecture from sub-cellular to whole-organism scales. This scale-free architecture supports representations with diverse functions and levels of abstraction.

Recent theories developing broad notions of context and its effects on inference are becoming increasingly important in fields as diverse as cognitive psychology, information science and quantum information theory and computing. Here we introduce a novel and general approach to the characterisation of contextuality using the techniques of Chu spaces and Channel Theory viewed as general theories of information flow. This involves introducing three essential components into the formulism: events, conditions and measurement systems. Incorporating these factors in relationship to conditional probabilities leads to information flows both in the setting of Chu spaces and Channel Theory. The latter provides a representation of semantic content using local logics from which conditionals can be derived. We employ these features to construct cone-cocone diagrams, commutativity of which enforces inferential coherence. With these we build a scale-free architecture incorporating a Bayesian-like hierarchical structure, in which there is an interpretation of active inference and Markov blankets. We compare this architecture with other theories of contextuality which we briefly review. We also show that this development of ideas conveniently accommodates negative probabilities, leading to the notion of signed information flow, and address how quantum contextuality can be interpreted within this model. Finally, we relate contextuality to the Frame Problem, another way of characterising a fundamental limitation on the observational and inferential capabilities of finite agents.

Metazoan body plans combine well-defined primary, secondary, and in many bilaterians, tertiary body axes with structural asymmetries at multiple scales. Despite decades of study, how axis-defining symmetries and system-defining asymmetries co-emerge during both evolution and development remain open questions. Regeneration studies in asexual planaria have demonstrated an array of viable forms with symmetrized and, in some cases, duplicated body axes. We suggest that such forms may point toward an ancestral eumetazoan form with characteristics of both cnidarians and placazoa.

Animals that can reproduce vegetatively by fission or budding and also sexually via specialized gametes are found in all five primary animal lineages (Bilateria, Cnidaria, Ctenophora, Placozoa, Porifera). Many bilaterian lineages, including roundworms, insects, and most chordates, have lost the capability of vegetative reproduction and are obligately gametic. We suggest a developmental explanation for this evolutionary phenomenon: obligate gametic reproduction is the result of germline stem cells winning a winner-take-all competition with non-germline stem cells for control of reproduction and hence lineage survival. We develop this suggestion by extending Hamilton's rule, which factors the relatedness between parties into the cost/benefit analysis that underpins cooperative behaviors, to include similarity of cellular state. We show how coercive or deceptive cell-cell signaling can be used to make costly cooperative behaviors appear less costly to the cooperating party. We then show how competition between stem-cell lineages can render an ancestral combination of vegetative reproduction with facultative sex unstable, with one or the other process driven to extinction. The increased susceptibility to cancer observed in obligately-sexual lineages is, we suggest, a side-effect of deceptive signaling that is exacerbated by the loss of whole-body regenerative abilities. We suggest a variety of experimental approaches for testing our predictions.

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EDITORIAL article Front. Psychol., 27 October 2020 | https://doi.org/10.3389/fpsyg.2020.606046

The open-domain Frame Problem is the problem of determining what features of an open task environment need to be updated following an action. Here we prove that the open-domain Frame Problem is equivalent to the Halting Problem and is therefore undecidable. We discuss two other open-domain problems closely related to the Frame Problem, the system identification problem and the symbol-grounding problem, and show that they are similarly undecidable. We then reformulate the Frame Problem as a quantum decision problem, and show that it is undecidable by any finite quantum computer.

A theory of consciousness, whatever else it may do, must address the structure of experience. Our perceptual experiences are richly structured. Simply seeing a red apple, swaying between green leaves on a stout tree, involves symmetries, geometries, orders, topologies, and algebras of events. Are these structures also present in the world, fully independent of their observation? Perceptual theorists of many persuasions-from computational to radical embodied-say yes: perception veridically presents to observers structures that exist in an observer-independent world; and it does so because natural selection shapes perceptual systems to be increasingly veridical. Here we study four structures: total orders, permutation groups, cyclic groups, and measurable spaces. We ask whether the payoff functions that drive evolution by natural selection are homomorphisms of these structures. We prove, in each case, that generically the answer is no: as the number of world states and payoff values go to infinity, the probability that a payoff function is a homomorphism goes to zero. We conclude that natural selection almost surely shapes perceptions of these structures to be non-veridical. This is consistent with the interface theory of perception, which claims that natural selection shapes perceptual systems not to provide veridical perceptions, but to serve as species-specific interfaces that guide adaptive behavior. Our results present a constraint for any theory of consciousness which assumes that structure in perceptual experience is shaped by natural selection.

Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.

The ideas of classical communication and holographic encoding arise in different parts of physics. Here, we show that they are equivalent. This allows for us to reformulate the holographic principle independently of spacetime, as the principle that holographic screens encode interaction eigenvalues.

Descriptions of measurement typically neglect the observations required to identify the apparatus employed to either prepare or register the final state of the “system of interest.” Here, we employ category-theoretic methods, particularly the theory of classifiers, to characterize the full interaction between observer and world in terms of information and resource flows. Allocating a subset of the received bits to system identification imposes two separability constraints and hence breaks two symmetries: first, between observational outcomes held constant and those allowed to vary; and, second, between observational outcomes regarded as “informative” and those relegated to purely thermodynamic functions of free-energy acquisition and waste heat dissipation. We show that breaking these symmetries induces decoherence, contextuality, and measurement-associated disturbance of the system of interest.

We show that a generalized version of the holographic principle can be\nderived from the Hamiltonian description of information flow within a quantum\nsystem that maintains a separable state. We then show that this generalized\nholographic principle entails a general principle of gauge invariance. When\nthis is realized in an ambient Lorentzian space-time, gauge invariance under\nthe Poincare group is immediately achieved. We apply this pathway to retrieve\nthe action of gravity. The latter is cast a la Wilczek through a similar\nformulation derived by MacDowell and Mansouri, which involves the\nrepresentation theory of the Lie groups SO(3,2) and SO(4,1).\n

Standard semi-classical models of decoherence do not take explicit account of the classical information required to specify the system - environment boundary. I show that this information can be represented as a finite set of reference eigenvalues that must be encoded by any observer, including any apparatus, able to distinguish the system from its environment. When the information required for system identification is accounted for in this way, decoherence can be described as a sequence of entanglement swaps between reference and pointer components of the system and their respective environments. Doing so removes the need for the a priori assumptions of ontic boundaries required by semi-classical models.

exposure has been documented for a variety of agents with the most commonly studied compounds exhibiting mutagenic and genotoxic carcinogen properties. Age-dependent adjustment factors (ADAFs) are applied by the US Environmental Protection Agency to many such carcinogens when assessing cancer risk from early postnatal (PN) exposures; however, this approach has not been widely considered for transplacental (TP) exposure. To explore this question and further evaluate prenatal susceptibility a database of early life animal studies developed by California Office of Environmental Health Hazard Assessment (OEHHA) enhanced with additional literature searching was evaluated. Nine genotoxic carcinogens and one mixture (cigarette smoke) have data available via TP only, PN only and adult-only protocols. Potency comparisons across these lifestages displayed similarly greater potency in male liver and brain compared to adult-only exposure. Both TP and PN exposures were not markedly different than adult-only for other targets such as female liver and blood-borne tumors. Similarity in TP and PN targets and potency for carcinogen action suggests that a 10-fold ADAF may be applied for TP exposure as is currently applied to PN exposure. A similar conclusion was reached by OEHHA. The implications of this heightened TP vulnerability are greatest for less-than-lifetime exposure and this approach might be used to assess the level of cancer risk from exposures during pregnancy. A case example employing a mutagenic flame retardant was used to exemplify application of a TP ADAF for evaluating risks during pregnancy.

Adaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive power. Here, we argue that this fundamental drive provides a novel perspective on the origin of multicellularity. One way for unicellular organisms to minimize surprise with respect to external inputs is to be surrounded by reproductively-disabled, i.e. somatic copies of themselves - highly predictable agents which in effect reduce uncertainty in their microenvironments. We show that the transition to multicellularity can be modeled as a phase transition driven by environmental threats. We present modeling results showing how multicellular bodies can arise if non-reproductive somatic cells protect their reproductive parents from environmental lethality. We discuss how a somatic body can be interpreted as a Markov blanket around one or more reproductive cells, and how the transition to somatic multicellularity can be represented as a transition from exposure of reproductive cells to a high-uncertainty environment to their protection from environmental uncertainty by this Markov blanket. This is, effectively, a transition by the Markov blanket from transparency to opacity for the variational free energy of the environment. We suggest that the ability to arrest the cell cycle of daughter cells and redirect their resource utilization from division to environmental threat amelioration is the key innovation of obligate multicellular eukaryotes, that the nervous system evolved to exercise this control over long distances, and that cancer is an escape by somatic cells from the control of reproductive cells. Our quantitative model illustrates the evolutionary dynamics of this system, provides a novel hypothesis for the origin of multicellular animal bodies, and suggests a fundamental link between the architectures of complex organisms and information processing in proto-cognitive cellular agents.

Steve Kupina, Chris Fields, Mark C Roman, Sharon L Brunelle; Determination of Total Phenolic Content Using the Folin-C Assay: Single-Laboratory Validation,

Nervous systems are traditionally thought of as providing sensing and behavioral coordination functions at the level of the whole organism. What is the evolutionary origin of the mechanisms enabling the nervous systems' information processing ability? Here, we review evidence from evolutionary, developmental, and regenerative biology suggesting a deeper, ancestral function of both pre-neural and neural cell-cell communication systems: the long-distance coordination of cell division and differentiation required to create and maintain body-axis symmetries. This conceptualization of the function of nervous system activity sheds new light on the evolutionary transition from the morphologically rudimentary, non-neural Porifera and Placazoa to the complex morphologies of Ctenophores, Cnidarians, and Bilaterians. It further allows a sharp formulation of the distinction between long-distance axis-symmetry coordination based on external coordinates, e.g., by whole-organism scale trophisms as employed by plants and sessile animals, and coordination based on body-centered coordinates as employed by motile animals. Thus we suggest that the systems that control animal behavior evolved from ancient mechanisms adapting preexisting ionic and neurotransmitter mechanisms to regulate individual cell behaviors during morphogenesis. An appreciation of the ancient, non-neural origins of bioelectrically mediated computation suggests new approaches to the study of embryological development, including embryological dysregulation, cancer, regenerative medicine, and synthetic bioengineering.

Abstract The relationship between philosophy and research on artificial intelligence (AI) has been difficult since its beginning, with mutual misunderstanding and sometimes even hostility. By contrast, we show how an approach informed by both philosophy and AI can be productive. After reviewing some popular frameworks for computation and learning, we apply the AI methodology of “build it and see” to tackle the philosophical and psychological problem of characterizing perception as distinct from sensation. Our model comprises a network of very simple, but interacting agents which have binary experiences of the “yes/no”-type and communicate their experiences with each other. When does such a network refer to a single agent instead of a distributed network of entities? We apply machine learning techniques to address the following related questions: i) how can the model explain stability of compound entities, and ii) how could the model implement a single task such as perceptual inference? We thereby find consistency with previous work on “interface” strategies from perception research. While this reflects some necessary conditions for the ascription of agency, we suggest that it is not sufficient. Here, AI research, if it is intended to contribute to conceptual understanding, would benefit from issues previously raised by philosophy. We thus conclude the article with a discussion of action-selection, the role of embodiment, and consciousness to make this more explicit. We conjecture that a combination of AI research and philosophy allows general principles of mind and being to emerge from a “quasi-empirical” investigation.

The cover image, by Chris Fields and Michael Levin, is based on Overview Multiscale memory and bioelectric error correction in the cytoplasm–cytoskeleton‐membrane system , DOI: 10.1002/wsbm.1410 . image

Chu Spaces and Channel Theory are well-established areas of investigation in the general context of category theory when applied to semantically-based information flow. In this Part I of a two-part work, we review a range of related concepts and examples showing how these methods can be applied to logic and computer science, including Formal Concept Analysis, distributed systems and ontology development. We also discuss spatial coarse-graining in relationship to information, and in this direction we establish some basic simplicial and categorical techniques which will supplement the other methods of this Part I when they are applied to characterise visual object identification and the inference of mereological (i.e. part-whole) complexity in Part II.

In this Part II of a two-part work, we proceed from the survey of concepts and techniques of Chu spaces and Channel Theory in Part I to the characterisation of human visual object identification, beginning with the construction of uncategorised object files and proceeding through categorisation, individual object identification and the tracking of object identity through time. We investigate the relationship between abstraction and mereological categorisation, particularly as these affect object-identity tracking. This we accomplish in terms of information flow that is semantically structured in terms of local logics, providing an inferential mechanism for object identification and tracking. We introduce categorical Cone-Cocone Diagrams to explicitly capture a bidirectional duality between ‘token’ roles and ‘type’ roles, and show that all representations can be considered to play both roles. We discuss the emergence of mereotopology from the representation of classifications with underlying simplicial complexes, and briefly explore the emergence of geometric relations and interactions between objects. Throughout we discuss the empirical support for the utility of this descriptive mechanism, particularly as a scale-free organisation that is applicable to cognition and to AI systems in general, and raise open issues and problems.

The concept of a "system" is foundational to physics, but the question of how observers identify systems is seldom addressed. Classical thermodynamics restricts observers to finite, finite-resolution observations with which to identify the systems on which "pointer state" measurements are to be made. It is shown that system identification is at best approximate, even in a finite world, and that violations of the Leggett-Garg and Bell/CHSH (Clauser-Horne-Shimony-Holt) inequalities emerge naturally as requirements for successful system identification.

Multiple sciences have converged, in the past two decades, on a hitherto mostly unremarked question: what is observation? Here, I examine this evolution, focusing on three sciences: physics, especially quantum information theory, developmental biology, especially its molecular and “evo-devo” branches, and cognitive science, especially perceptual psychology and robotics. I trace the history of this question to the late 19th century, and through the conceptual revolutions of the 20th century. I show how the increasing interdisciplinary focus on the process of extracting information from an environment provides an opportunity for conceptual unification, and sketch an outline of what such a unification might look like.

Chu Spaces and Channel Theory are well established areas of investigation in the general context of category theory. We review a range of examples and applications of these methods in logic and computer science, including Formal Concept Analysis, distributed systems and ontology development. We then employ these methods to describe human object perception, beginning with the construction of uncategorized object files and proceeding through categorization, individual object identification and the tracking of object identity through time. We investigate the relationship between abstraction and mereological categorization, particularly as these affect object identity tracking. This we accomplish in terms of information flow that is semantically structured in terms of local logics, while at the same time this framework also provides an inferential mechanism towards identification and perception. We show how a mereotopology naturally emerges from the representation of classifications by simplicial complexes, and briefly explore the emergence of geometric relations and interactions between objects.

A single-laboratory validation of a method using Folin & Ciocalteu's phenol reagent (Folin-C reagent) for determination of total phenolic content of selected dietary supplement extracts was performed. The method is composed of a water extraction of dried extracts with sonication followed by reaction with the Folin-C reagent. The resulting colorimetric reaction is measured at 765 nm and compared with a standard curve generated with gallic acid standard solutions. The validation results were compared with Standard Method Performance Requirement (SMPR®) 2015.009, developed by the Stakeholder Panel on Dietary Supplements. The method demonstrated acceptable within-day RSDr of 1.96-7.47% for the five matrixes studied (grape seed extract, grape skin extract, black tea extract, green coffee extract, and cocoa extract). When gallic acid was spiked into maltodextrin (a surrogate dietary supplement carrier) at 30 or 70%, the recovery ranged from 91 to 104%, within the acceptable range established by SMPR 2015.009. Selectivity testing with glucose, fructose, and sucrose demonstrated no positive interference by these compounds. Finally, ruggedness studies demonstrated no significant effects due to changes in the heating apparatus, test material weight, read time after reaction, amount of Folin-C reagent, reaction time, reaction temperature, and amount of Na2CO3. The single-laboratory validation results support adoption of the method as First Action Official MethodSM 2017.13 and further evaluation in a collaborative study.

Science requires memory, but memory is constructive. Kordes and Demsar appeal to historical constraints on memory to address this paradox. Yet history, even an imagined history, involves a third-…

While instantaneous phenomenal consciousness may be (and I would argue should be) regarded as fundamental, as soon as consciousness is extended in time and memory is invoked, the resulting notion …

A fundamental aspect of life is the modification of anatomy, physiology, and behavior in the face of changing conditions. This is especially illustrated by the adaptive regulation of growth and form that underlies the ability of most organisms-from single cells to complex large metazoa-to develop, remodel, and regenerate to specific anatomical patterns. What is the relationship of the genome and other cellular components to the robust computations that underlie this remarkable pattern homeostasis? Here we examine the role of constraints defined at the cellular level, especially endogenous bioelectricity, in generating and propagating biological information. We review evidence that the genome is only one of several multi-generational biological memories. Focusing on the cell membrane and cytoplasm, which is physically continuous across all of life in evolutionary timeframes, we characterize the environment as an interstitial space through which messages are passed via bioelectric and biochemical codes. We argue that biological memory is a fundamental phenomenon that cannot be understood at any one scale, and suggest that functional studies of information propagated in non-genomic cellular structures will not only strongly impact evolutionary developmental biology, but will also have implications for regenerative medicine and synthetic bioengineering. WIREs Syst Biol Med 2018, 10:e1410. doi: 10.1002/wsbm.1410 This article is categorized under: Developmental Biology > Stem Cell Biology and Regeneration Physiology > Physiology of Model Organisms Models of Systems Properties and Processes > Cellular Models.

We show that regenerating planarians' normal anterior-posterior pattern can be permanently rewritten by a brief perturbation of endogenous bioelectrical networks. Temporary modulation of regenerative bioelectric dynamics in amputated trunk fragments of planaria stochastically results in a constant ratio of regenerates with two heads to regenerates with normal morphology. Remarkably, this is shown to be due not to partial penetrance of treatment, but a profound yet hidden alteration to the animals' patterning circuitry. Subsequent amputations of the morphologically normal regenerates in water result in the same ratio of double-headed to normal morphology, revealing a cryptic phenotype that is not apparent unless the animals are cut. These animals do not differ from wild-type worms in histology, expression of key polarity genes, or neoblast distribution. Instead, the altered regenerative bodyplan is stored in seemingly normal planaria via global patterns of cellular resting potential. This gradient is functionally instructive, and represents a multistable, epigenetic anatomical switch: experimental reversals of bioelectric state reset subsequent regenerative morphology back to wild-type. Hence, bioelectric properties can stably override genome-default target morphology, and provide a tractable control point for investigating cryptic phenotypes and the stochasticity of large-scale epigenetic controls.

Context: The evolution of perceptual systems and hence of observers remains largely disconnected from the question of the emergence of classical objects and spacetime. This disconnection between …

Upshot: Formal models lead beyond ordinary experience to abstractions such as black holes and quantum entanglement. Applying such models to experience itself makes it seem unfamiliar and even …

EDITORIAL article Front. Psychol., 22 March 2016Sec. Perception Science Volume 7 - 2016 | https://doi.org/10.3389/fpsyg.2016.00400

The Ollivier-Poulin-Zurek definition of objectivity provides a philosophical basis for the environment as witness formulation of decoherence theory and hence for quantum Darwinism. It is shown that no account of the reference of the key terms in this definition can be given that does not render the definition either empty or circular. It is argued that this is not the fault of the language used, but of the assumption that the laws of physics are independent of Hilbert-space decomposition. All evidence suggests that this latter assumption is true. If it is, decoherence cannot explain the emergence of classicality.

A time‐dependent centrality metric for disciplinary coauthorship graphs, the “ N obel number” for a discipline, is introduced. A researcher's N obel number for a given discipline in a given year is defined as the researcher's average coauthorship distance to that discipline's N obel laureates in that year. Plotting N obel numbers over several decades provides a quantitative as well as visual indication of a researcher's proximity to the intuitive “center” of a discipline as defined by recognized scientific achievement. It is shown that the N obel number distributions for physics of several researchers both within and outside of physics are surprisingly flat over the five‐decade span from 1951 to 2000. A model in which N obel laureates are typically connected by short coauthorship paths both intergenerationally and between subdisciplines reproduces such flat N obel number distributions.

In addition to the immediate microenvironment, long-range signaling may be an important component of cancer. Molecular-genetic analyses have implicated gap junctions-key mediators of cell-cell communication-in carcinogenesis. We recently showed that the resting voltage potential of distant cell groups is a key determinant of metastatic transformation and tumor induction. Here, we show in the Xenopus laevis model that gap junctional communication (GJC) is a modulator of the long-range bioelectric signaling that regulates tumor formation. Genetic disruption of GJC taking place within tumors, within remote host tissues, or between the host and tumors significantly lowers the incidence of tumors induced by KRAS mutations. The most pronounced suppression of tumor incidence was observed upon GJC disruption taking place farther away from oncogene-expressing cells, revealing a role for GJC in distant cells in the control of tumor growth. In contrast, enhanced GJC communication through the overexpression of wild-type connexin Cx26 increased tumor incidence. Our data confirm a role for GJC in tumorigenesis, and reveal that this effect is non-local. Based on these results and on published data on movement of ions through GJs, we present a quantitative model linking the GJC coupling and bioelectrical state of cells to the ability of oncogenes to initiate tumorigenesis. When integrated with data on endogenous bioelectric signaling during left-right patterning, the model predicts differential tumor incidence outcomes depending on the spatial configurations of gap junction paths relative to tumor location and major anatomical body axes. Testing these predictions, we found that the strongest influence of GJ modulation on tumor suppression by hyperpolarization occurred along the embryonic left-right axis. Together, these data reveal new, long-range aspects of cancer control by the host's physiological parameters.

Within the quantum Darwinist framework introduced by W. H. Zurek ({\em Nat. Phys.}, 5:181-188, 2009), observers obtain pointer-state information about quantum systems by interacting with a local sample of the surrounding environment, e.g. a local sample of the ambient photon field. Because the environment encodes such pointer state information uniformly and hence redundantly throughout its entire volume, the information is equally available to all observers regardless of their location. This framework is applied to the observation of stellar center-of-mass positions, which are assumed to be encoded by the ambient photon field in a way that is uniformly accessible to all possible observers. Assuming Landauer's Principle, constructing such environmental encodings requires $(ln2) kT$ per encoded bit. For the observed 10$^{24}$ stars and a uniform binary encoding of center-of-mass positions into voxels with a linear dimension of 5 km, the free energy required at the current CMB temperature T = 2.7 K is $\sim$ 2.5 $\cdot$ 10$^{-27}$ kg $\cdot$ m$^{-3}$, strikingly close to the observed value of $Ω_Λ ρ_{c}$. Decreasing the voxel size to $(l_{P})^{3}$ results in a free energy requirement 10$^{117}$ times larger.

Within the quantum Darwinist framework introduced by W. H. Zurek ({\em Nat. Phys.}, 5:181-188, 2009), observers obtain pointer-state information about quantum systems by interacting with the surrounding environment, e.g. the ambient photon field. This framework is applied to the observation of stellar center-of-mass positions, which are assumed to be encoded in a way that is uniformly accessible to all observers regardless of their location. Assuming Landauer's Principle, constructing such environmental encodings requires $\sim$ kT per bit. For 10$^{25}$ stars and a binary encoding of center-of-mass positions into 10 km$^{3}$ voxels, the free energy required at T = 2.7 K is $\sim$ 5 $\cdot$ 10$^{-27}$ kg $\cdot$ m$^{-3}$, in striking agreement with the observed value of $\Omega_{\Lambda} \rho_{c}$. Decreasing the voxel size to $l_{P}^{3}$ results in a free energy requirement 10$^{117}$ times larger.

The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a "social brain". Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model is correct, overriding the bias toward agency to construct mechanistic explanations of observed events requires structure-mapping inferences, implemented by the pre-motor action planning system, that replace agents with mechanisms as causes of unobserved changes in contextual or featural properties of objects. Experiments that would test this model are discussed.

The symbol grounding problem is the problem of specifying a semantics for the representations employed by a physical symbol system in a way that is neither circular nor regressive. The quantum system identification problem is the problem of relating observational outcomes to specific collections of physical degrees of freedom, i.e., to specific Hilbert spaces. It is shown that with reasonable physical assumptions these problems are equivalent. As the quantum system identification problem is demonstrably unsolvable by finite means, the symbol grounding problem is similarly unsolvable.

By taking the need for quantum reference frames into account, it is shown that Hilbert-space factorization is a dissipative process requiring on the order of kT to reduce by one bit an observer's uncertainty in the provenance of a classically-recorded observational outcome. This cost is neglected in standard treatments of decoherence that assume that observational outcomes are obtained by interacting with a collection of degrees of freedom identified a priori. Treating this cost explicitly leads to a natural measure of the probability of any particular quantum reference frame.

The Human Genome Project introduced large-scale collaborations involving dozens to hundreds of scientists into biology. It also created a pressing need to solve discrete mathematics problems involving tens of thousands of elements. In this paper, we use minimal path lengths in the Erdős Collaboration Graph between prominent individual researchers as a measure of the distance between disciplines, and we show that the Human Genome Project brought laboratory biology as a whole closer to mathematics. We also define a novel graph reduction method and a metric that emphasizes the robustness of collaborative connections between researchers; these can facilitate the analysis of both within- and between-community connectivity in collaboration graphs.

Decompositional equivalence is the principle that there is no preferred decomposition of the universe into subsystems. It is shown here, by using simple thought experiments, that quantum theory follows from decompositional equivalence together with Landauer's principle. This demonstration raises within physics a question previously left to psychology: how do human - or any - observers agree about what constitutes a system of interest?

It is shown that no-signalling, a quantum of action, unitarity, detailed balance, Bell's theorem, the Hilbert-space representation of physical states and the Born rule all follow from the assumption of an additive Hamiltonian together with Landauer's principle. Common statements of the classical limit of quantum theory, as well as common assumptions made by interpretations of quantum theory, contradict additivity, Landauer's principle, or both.

Decompositional equivalence is the principle that there is no preferred decomposition of the universe into subsystems. It is shown here, by using simple thought experiments, that quantum theory follows from decompositional equivalence together with Landauer's principle. This demonstration raises within physics a question previously left to psychology: how do human - or any - observers agree about what constitutes a system of interest?

Human beings do not observe world from outside, but rather are fully embedded in it. The sciences, however, often give observer both a god's eye perspective and substantial a~priori knowledge. Motivated by W. Ross Ashby's statement, the theory of Black Box is merely theory of real objects or systems, when close attention is given to question, relating object and observer, about what information comes from object, and how it is obtained (Introduction to Cybernetics, 1956, p. 110), I develop here an alternate picture of world as a black box to which observer is coupled. Within this framework I prove purely-classical analogs of no-go theorems of quantum theory. Focussing on question of identifying macroscopic objects, such as laboratory apparatus or even other observers, I show that standard quantum formalism of superposition is required to adequately represent classical information that an observer can obtain. I relate these results to supporting considerations from evolutionary biology, cognitive and developmental psychology, and artificial intelligence.

Concerns have been raised that diacetyl (DA) might be a respiratory sensitizer based on its LUMO energy similar to that of the respiratory allergen toluene-2,4-diisocyanate (TDI) and results of a local lymph node assay (LLNA) that reported an EC3 of 1.9%. To better understand the concerns, we performed a systematic literature review and experimental competition reactions between DA and TDI. The experimental evidence demonstrates that DA is at least 400-fold less reactive than TDI. The literature review finds evidence that the EC3 for DA is actually >11%. We conclude that DA is unlikely to have significant respiratory sensitization potential.

Both standard formulations of the frame problem and standard solutions implicitly assume that the re-identification of objects as persisting individuals between pre- and post-action contexts is unproblematic. In the case of human beings, this assumption is false: humans dedicate considerable cognitive resources to object re-identification. An analysis of both the phenomenology and neurocognitive implementation of object re-identification is used to show that in humans, all of the information architecturally available to solve the frame problem is in fact deployed for object re-identification. The frame problem is, therefore, equivalent to the object re-identification problem in the case of human problem solving.

It is shown that the paradoxes of quantum theory can be traced to an assumption that observers can know which physical degrees of freedom are causally responsible for each of their experiences. The untenability of this assumption is demonstrated, and a quantum theory without it is proposed. Removing this assumption from quantum theory sheds new light on the nature of semantics, and perhaps also on the nature of freedom.

Infant abilities to re-identify objects through time have been characterized in terms of a ‘‘principle of persistence'' [Baillargeon (2008): &lt;i&gt;Perspectives on Psychological Science, 3,&lt;/i&gt; 2-13]. It is argued that the proposed principle of persistence has neither theoretical content nor explanatory power, and that object persistence is itself not an explanatory principle but rather an effect to be explained. The computational task of object re-identification across gaps in observation is characterized, and shown to be computationally intractable and hence solvable only by means of heuristics. It is argued that understanding infant abilities to re-identify objects requires focused investigation of the object re-identification heuristics that infants actually deploy and their neurocognitive implementation.

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By imposing system-observer symmetry on the von Neumann description of measurement, it is shown that the quantum measurement problem is structurally equivalent to a familiar reverse-engineering problem: that of describing the behavior of an arbitrary physical device as algorithm instantiation. It is suggested that this problem can at best be given a relational solution.

The question of what constitutes a ‘system’ is foundational to quantum measurement theory. Environment-induced superselection or ‘einselection’ has been proposed as an observer-independent mechanism by which apparently classical systems ‘emerge’ from physical interactions between degrees of freedom described completely quantum mechanically. It is shown here that einselection can only generate classical systems if the ‘environment’ is assumed a priori to be classical; einselection therefore does not provide an observer-independent mechanism by which classicality can emerge from quantum dynamics. Einselection is then reformulated in terms of positive operator-valued measures acting on a global quantum state. It is shown that this reformulation enables a natural interpretation of apparently classical systems as virtual machines that requires no assumptions beyond those of classical computer science.

Quantum Bayesianism (``QBism'') has been put forward as an approach to quantum theory that avoids foundational problems by altogether disavowing the objective existence of quantum states. It is shown that QBism suffers its own versions of the familiar foundational problems, and that these QBist versions are illuminating not just for QBism, but for more traditional foundational approaches as well.

The contributions of feature recognition, object categorization, and recollection of episodic memories to the re-identification of a perceived object as the very same thing encountered in a previous perceptual episode are well understood in terms of both cognitive-behavioral phenomenology and neurofunctional implementation. Human beings do not, however, rely solely on features and context to re-identify individuals; in the presence of featural change and similarly-featured distractors, people routinely employ causal constraints to establish object identities. Based on available cognitive and neurofunctional data, the standard object-token based model of individual re-identification is extended to incorporate the construction of unobserved and hence fictive causal histories (FCHs) of observed objects by the pre-motor action planning system. It is suggested that functional deficits in the construction of FCHs are associated with clinical outcomes in both autism spectrum disorders and later-stage stage Alzheimer's disease.

Observations of quantum systems carried out by finite observers who subsequently communicate their results using classical data structures can be described as “local operations, classical communication” (LOCC) observations. The implementation of LOCC observations by the Hamiltonian dynamics prescribed by minimal quantum mechanics is investigated. It is shown that LOCC observations cannot be described using decoherence considerations alone, but rather require the a priori stipulation of a positive operator-valued measure (POVM) about which communicating observers agree. It is also shown that the transfer of classical information from system to observer can be described in terms of system-observer entanglement, raising the possibility that an apparatus implementing an appropriate POVM can reveal the entangled system-observer states that implement LOCC observations.

Alzheimer's disease the contributions of feature recognition, object categorization, and recollection of episodic memories to the re-identification of a perceived object as the very same thing encountered in a previous perceptual episode are well understood in terms of both cognitive-behavioral phenomenology and neurofunctional implementation. human beings do not, however, rely solely on features and context to re-identify individuals; in the presence of featural change and similarly-featured distractors, people routinely employ causal constraints to establish object identities. Based on available cognitive and neurofunctional data, the standard object-token based model of individual reidentification is extended to incorporate the construction of unobserved and hence fictive causal histories (Fchs) of observed objects by the pre-motor action planning system. it is suggested that functional deficits in the construction of Fchs are associated with clinical outcomes in both autism spectrum disorders and later-stage stage Alzheimer's disease.

The ubiquitous assumption that ``systems'' can be taken as ``given'' is wrong.  Viewing observation physically as entanglement allows this assumption to be dropped.  In the framework that results, initial conditions play no role, time is emergent, observers are ubiquitous, and both ``systems'' and the theories that describe them are purely model-theoretic entities.

Interpretations of quantum theory have traditionally assumed a “Galilean” observer, a bare “point of view” implemented physically by a quantum system. This paper investigates the consequences of replacing such an informationally-impoverished observer with an observer that satisfies the requirements of classical automata theory, i.e., an observer that encodes sufficient prior information to identify the system being observed and recognize its acceptable states. It shows that with reasonable assumptions about the physical dynamics of information channels, the observations recorded by such an observer will display the typical characteristics predicted by quantum theory, without requiring any specific assumptions about the observer’s physical implementation.

It is shown that the restrictions of what can be inferred from classically recorded observational outcomes that are imposed by the no-cloning theorem, the Kochen–Specker theorem and Bell's theorem also follow from restrictions on inferences from observations formulated within classical automata theory. Similarities between the assumptions underlying classical automata theory and those underlying universally unitary quantum theory are discussed.

1. The role of upper cervical inspiratory (UCI)-modulated neurons in respiratory muscle control during vomiting was examined by recording the impulse activity of these neurons during fictive vomiting in decerebrate, paralyzed cats. Fictive vomiting was identified by a characteristic series of bursts of coactivation of phrenic and abdominal muscle nerves, elicited either by electrical stimulation of supradiaphragmatic vagal nerve afferents or by emetic drugs, which would be expected to produce expulsion of gastric contents in nonparalyzed animals. 2. Data were recorded from 43 propriospinal UCI neurons, located in the C1-C3 spinal segments near the border of the intermediate gray matter and lateral funiculus, which were antidromically activated with floating pin electrodes placed in the ipsilateral lateral funiculus, usually at T1-T3. Some cells (9/21 tested) were also activated from the upper lumbar cord (L1). During respiration, most neurons (n = 40) had an augmenting discharge pattern during inspiration. In addition, more than one-half (55%) fired tonically during the remainder of the respiratory cycle. About 40% of UCI neurons showed variations in their firing pattern during the noninspiratory portion of respiration. These latter two properties of UCI neurons were not observed in dorsal and ventral respiratory group (DRG and VRG-, respectively) bulbospinal inspiratory (I) neurons previously recorded under similar conditions. 3. During fictive vomiting, the firing pattern of most UCI neurons fell into one of three main categories. More than one-half (53%) were active in phase with bursts of phrenic discharge and were thus classified as Active-type cells.(ABSTRACT TRUNCATED AT 250 WORDS)

The perception of persisting visual objects is mediated by transient intermediate representations, object files, that are instantiated in response to some, but not all, visual trajectories. The standard object file concept does not, however, provide a mechanism sufficient to account for all experimental data on visual object persistence, object tracking, and the ability to perceive spatially disconnected stimuli as continuously existing objects. Based on relevant anatomical, functional, and developmental data, a functional model is constructed that bases visual object individuation on the recognition of temporal sequences of apparent center-of-mass positions that are specifically identified as trajectories by dedicated "trajectory recognition networks" downstream of the medial-temporal motion-detection area. This model is shown to account for a wide range of data, and to generate a variety of testable predictions. Individual differences in the recognition, abstraction, and encoding of trajectory information are expected to generate distinct object persistence judgments and object recognition abilities. Dominance of trajectory information over feature information in stored object tokens during early infancy, in particular, is expected to disrupt the ability to re-identify human and other individuals across perceptual episodes, and lead to developmental outcomes with characteristics of autism spectrum disorders.

Multiple observers who interact with environmental encodings of the states of a macroscopic quantum system S as required by quantum Darwinism cannot demonstrate that they are jointly observing S without a joint a priori assumption of a classical boundary separating S from its environment E. Quantum Darwinism cannot, therefore, be regarded as providing a purely quantum-mechanical explanation of the "emergence" of classicality.

Five physical assumptions are proposed that together entail the general qualitative results, including the Born rule, of non-relativistic quantum mechanics by physical and information-theoretic reasoning alone. Two of these assumptions concern fundamental symmetries of physical interactions. The third concerns the Hilbert-space dimensions and the fourth and fifth the self-interaction Hamiltonians of the systems that function as "observers" within the theory. These assumptions are shown to provide a sufficient motivation for the usual Hilbert-space formalism, and to obviate the observation-related axioms and most interpretative assumptions with which minimal quantum mechanics is typically supplemented.

Quantum Bayesianism ("QBism") has been put forward as an approach to quantum theory that avoids foundational problems by altogether disavowing the objective existence of quantum states. It is shown that QBism suffers its own versions of the familiar foundational problems, and that these QBist versions are illuminating not just for QBism, but for more traditional foundational approaches as well.

The Ollivier-Poulin-Zurek definition of objectivity provides a philosophical basis for the environment as witness formulation of decoherence theory and hence for quantum Darwinism. It is shown that no account of the reference of the key terms in this definition can be given that does not render the definition either empty or circular. It is argued that this is not the fault of the language used, but of the assumption that the laws of physics are independent of Hilbert-space decomposition. All evidence suggests that this latter assumption is true. If it is, decoherence cannot explain the emergence of classicality.

Quantum Bayesianism (“QBism”) has been put forward as an approach to quantum theory that avoids foundational problems by altogether disavowing quantum states. It is shown that QBism suffers its own versions of the familiar foundational problems, and that these QBist versions are illuminating not just for QBism, but for more traditional foundational approaches as well.

Both classical and quantum mechanics assume that physical laws are invariant under changes in the way that the world is labeled. This Principle of Decompositional Equivalence is formalized, and shown to forbid finite experimental demonstrations that given pointer states |p1&gt; and |p2&gt; refer to the same physical system S. It is then shown that any extra-theoretical assumption that given pointer states |p1&gt; and |p2&gt; with indistinguishable coefficients in a Schmidt basis for the universe refer to the same physical system S is stronger than the assumption of classicality. Standard interpretations of quantum mechanics make such as assumption in analyzing measurement; hence they are logically inconsistent.

Model-independent semantic requirements for user specification and interpretation of data before and after quantum computations are characterized. Classical computational costs of assigning classical data values to quantum registers and to run-time parameters passed across a classical-to-quantum application programming interface are derived. It is shown that the classical computational costs of data definition equal or exceed the classical computational cost of solving the problem of interest for all applications of quantum computing except computations defined over the integers and the simulation of linear systems with linear boundary conditions.

Decompositions of the world into systems have typically been regarded as arbitrary extra-theoretical assumptions in discussions of quantum measurement. One can instead regard decompositions as part of the theory, and ask what conditions they must satisfy for self-consistency. It is shown that self-consistent decompositions that specify a measurement context (i.e. von Neumann decompositions) must represent apparatus as containing internal decohering environments and as having known pointer components and ready states. Under these circumstances a von Neumann decomposition can function as a component of the ready state of the observer. Minimal no-collapse quantum mechanics supplemented by these consistency requirements on von Neumann decompositions avoids the measurement problem.

A functional analysis of the task of observing multiple macroscopic quantum systems over an extended period of time and then reporting the accumulated results is used to investigate the information that must be encoded in the "ready" state |O^r&gt; of any finite, macroscopic observer O capable of performing this task. Decoherence considerations show that this task can be considered as involving local observations under classical conditions (LOCC), allowing the use of classical automata theory to define a minimal observer. It is shown that such a minimal observer must implement a functional architecture equivalent to a classical Turing machine and must encode in |O^r&gt; a classical specification of the complete set of reportable apparatus states. The observation task is then re-characterized employing an explicit model of such a minimal observer, and it is shown that both the assumption that external systems have well-defined boundaries against the environment and the assumption of decoherence are unnecessary for the characterization of measurements made by a minimal observer. It is shown that the observables available to a minimal observer are positive operator-valued measures (POVMs) and that the measurement results reported by a minimal observer comply with the Born rule. The differences in underlying physical assumptions between this "systems-free" treatment of observation and that traditionally employed in analyses of quantum measurement and quantum communication are discussed.

A re-analysis of data from electron-pair production following 160 A GeV 207Pb bombardment of nuclear emulsions indicates the production and decay of neutral particles of significantly lower invariant mass and shorter lifetimes than previously claimed (J. Phys. G: Nucl. Part. Phys. 34 (2007) 129-138).

The generation of novel conceptual combinations is an effective strategy for solving unfamiliar problems only if it is accompanied by a mechanism that identifies potential solutions as such. Both mechanistic studies and common phenomenology suggest that in humans this mechanism involves, and is experienced as, an attachment of strong positive emotional response to a candidate solution. Thus, key questions are how such responses can be indicators of solution correctness, how and at what stage of problem solving they are generated, and how and at what stage of problem solving they are attached to representations of candidate solutions. These questions were investigated in an aesthetic problem solving task environment requiring the synthesis of visual and verbal components. The phenomenology observed in this environment suggests that generation and attachment of a sufficient emotional response is necessary for binding of nascent visual and verbal representation components to form a candidate solution, and that executive-driven attentional amplification of nascent representations suppresses the attachment of emotional valence. It also suggests that a complex, multivalent emotional response is characteristic of correct solutions. If this proves to be correct, it will require a re-thinking of the role of executive attention and predefined goals in creative problem solving.

Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from microarrays, we have made progress by combining very different analytic approaches.

Simple frequency and phase relation systems based on hybrid analog-digital processing elements (PEs) are examined. The systems utilize the temporal characteristics of the input signals and the systems themselves to produce fast low hardware solutions to problems commonly encountered in signal processing. Circuit level simulations of the systems were used to verify system functionality and demonstrate the basic waveforms produced by the hybrid processing element. It is shown that these PEs can be applied very naturally to temporal signal processing problems involving frequency and/or phase detection and shifting.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Abstract When stripped of its everyday familiarity, the virtually constant inner dialogue experienced by virtually everyone presents a mystery: why do we use language to communicate to ourselves. When examined from a design perspective in light of currently plausible cognitive neuroscience, language seems highly non-optimal as an internal communication medium. Other than its role in maintaining the privacy of thought, proposed functions for self-dialogue raise more questions than they answer. Therefore, it is appropriate to question the role played by the familiarity of self-dialogue in shaping our intuitions about consciousness. Keywords: ModularityLanguage Of ThoughtConsciousness

The authors have developed an integrated software system for analyzing, managing, and distributing data from high-throughput, steady-state expressed sequence tag (EST) projects. The system employs existing public and commercial software where available. Custom software has been developed and integrated as needed. The system was designed to facilitate sequence analysis on remote servers, complex queries of the data, and interactive browsing by nonexpert users. The design of the system was driven by the requirements of providing functionality with a short development time. The analysis procedures and database structures used in this system are not specific to a laboratory and could be used by an EST project or other project directed toward sequencing and mapping short sequence tags, including genomic sequence-tagged sites or tags generated by random amplification of polymorphic DNA mapping.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The Genome Sequence DataBase (GSDB) has completed its conversion to an improved relational database. The new database, GSDB 1.0, is fully operational and publicly available. Data contributions, including both original sequence submissions and community annotation, are being accomplished through the use of a graphical client-server interface tool, the GSDB Annotator, and via GIO (GSDB Input/Output) files. Data retrieval services are being provided through a new Web Query Tool and direct SQL. All methods of data contribution and data retrieval fully support the new data types that have been incorporated into GSDB, including discontiguous sequences, multiple sequence alignments, and community annotation.

The characterization of an organism’s genome is an essential and fundamental step toward understanding its biochemistry, lifestyle, and history. The genome encodes the structures of an organism’s RNAs and proteins explicitly, subunit by subunit; hence the molecular memory maintained by the genome describes the organism not just as a member of a species but also as a functional individual. The genome, with its mutable structure, is the locus for evolutionary change at the individual level. The genome, however, is also a spatially-organized macro-molecular complex. Together with the cytoskeleton and membranes, the genome organizes the cell and its dynamics in space and time. Genomics, the study of genomes, encompasses not just the study of individual genes and their structures, expression patterns, and functions but also encompasses the study of the structural and regulatory roles played by the genome as a whole.

Abstract The mathematical theory of computation does not directly address the questions of whether, and if so, how physical processes might be characterized as computations, or physical systems characterized as computers. These questions lie at the heart, however, of the technology of computer design, and of empirical investigations in cognitive science, computational neuroscience, and other sciences concerned with the processing of information. Addressing these questions requires a theory not of computation per se, but of the computational description of physical systems. My purposes in the present paper are, first, to outline a theory of computational description that is based explicitly on the theory of physical measurement, and, second, to examine some consequences of this theory for some questions in the philosophy of computer science and artificial intelligence.

A feasibility study to develop a requirements analysis and functional specification for a data management system for large-scale DNA sequencing laboratories resulted in a functional specification for a Sequencing Information Management System (SIMS). This document reports the results of this feasibility study, and includes a functional specification for a SIMS relational schema. The SIMS is an integrated information management system that supports data acquisition, management, analysis, and distribution for DNA sequencing laboratories. The SIMS provides ad hoc query access to information on the sequencing process and its results, and partially automates the transfer of data between laboratory instruments, analysis programs, technical personnel, and managers. The SIMS user interfaces are designed for use by laboratory technicians, laboratory managers, and scientists. The SIMS is designed to run in a heterogeneous, multiplatform environment in a client/server mode. The SIMS communicates with external computational and data resources via the internet.

The objective of this project is the development of practical software to automate the identification of genes in anonymous DNA sequences from the human, and other higher eukaryotic genomes. A software system for automated sequence analysis, gm (gene modeler) has been designed, implemented, tested, and distributed to several dozen laboratories worldwide. A significantly faster, more robust, and more flexible version of this software, gm 2.0 has now been completed, and is being tested by operational use to analyze human cosmid sequence data. A range of efforts to further understand the features of eukaryoyic gene sequences are also underway. This progress report also contains papers coming out of the project including the following: gm: a Tool for Exploratory Analysis of DNA Sequence Data; The Human THE-LTR(O) and MstII Interspersed Repeats are subfamilies of a single widely distruted highly variable repeat family; Information contents and dinucleotide compostions of plant intron sequences vary with evolutionary origin; Splicing signals in Drosophila: intron size, information content, and consensus sequences; Integration of automated sequence analysis into mapping and sequencing projects; Software for the C. elegans genome project.

It is shown that the Fodor's interpretation of the frame problem is the central indication that his version of the Modularity Thesis is incompatible with computationalism. Since computationalism is far more plausible than this thesis, the latter should be rejected.

(1995). The role of the frame problem in Fodor's modularity thesis: a case study of rationalist cognitive science. Journal of Experimental & Theoretical Artificial Intelligence: Vol. 7, No. 3, pp. 279-289.

Small-subunit rRNA (SSU rRNA) sequencing is a powerful tool to detect, identify, and classify prokaryotic organisms, and there is currently an explosion of SSU rRNA sequencing in the microbiology community. We report unexpectedly high levels of intraspecific variation (within and between strains) of prokaryote SSU rRNA sequences deposited in GenBank. A total of 82% of the prokaryote species with two published SSU rRNA sequences had more variable positions than a 0.1% random sequencing error would predict, and 48% of these sequence pairs had more variable positions than predicted by a 1.0% random sequencing error. Other sources of sequence variability must account for some of this intraspecific variation. Given these results, phylogenetic studies and biodiversity estimates obtained by using prokaryotic SSU rRNA sequences cannot proceed under the assumption that rRNA sequences of single operons from single isolates adequately represent their taxa. Sequencing SSU rRNA molecules from multiple operons and multiple isolates is highly recommended to obtain meaningful phylogenetic hypotheses, as is careful attention to accurate strain identification.

An approach for genome analysis based on sequencing and assembly of unselected pieces of DNA from the whole chromosome has been applied to obtain the complete nucleotide sequence (1,830,137 base pairs) of the genome from the bacterium Haemophilus influenzae Rd. This approach eliminates the need for initial mapping efforts and is therefore applicable to the vast array of microbial species for which genome maps are unavailable. The H. influenzae Rd genome sequence (Genome Sequence DataBase accession number L42023) represents the only complete genome sequence from a free-living organism.

Judith A. Blake, Carol J. Bult, Michael J. Donoghue, Julian Humphries, Chris Fields; Interoperability of Biological Data Bases: A Meeting Report, Systemati

This Report concludes the DOE Human Genome Program project, ``Identification of Genes in Anonymous DNA Sequence.`` The central goals of this project have been (1) understanding the problem of identifying genes in anonymous sequences, and (2) development of tools, primarily the automated identification system gm, for identifying genes. The activities supported under the previous award are summarized here to provide a single complete report on the activities supported as part of the project from its inception to its completion.

Heterologous DNA sequences from rearrangements with the genomes of host cells, genomic fragments from hybrid cells, or impure tissue sources can threaten the purity of libraries that are derived from RNA or DNA. Hybridization methods can only detect contaminants from known or suspected heterologous sources, and whole library screening is technically very difficult. Detection of contaminating heterologous clones by sequence alignment is only possible when related sequences are present in a known database. We have developed a statistical test to identify heterologous sequences that is based on the differences in hexamer composition of DNA from different organisms. This test does not require that sequences similar to potential heterologous contaminants are present in the database, and can in principle detect contamination by previously unknown organisms. We have applied this test to the major public expressed sequence tag (EST) data sets to evaluate its utility as a quality control measure and a peer evaluation tool. There is detectable heterogeneity in most human and C.elegans EST data sets but it is not apparently associated with cross-species contamination. However, there is direct evidence for both yeast and bacterial sequence contamination in some public database sequences annotated as human. Results obtained with the hexamer test have been confirmed with similarity searches using sequences from the relevant data sets.

We have investigated the possibility of using the polymerase chain reaction to detect deletions of coding elements in the unc-22-let-56 interval on chromosome IV in the nematode Caenorhabditis elegans. Our analysis of approximately 13 kb of genomic sequence immediately to the left of the unc-22 gene resulted in the identification of four possible genes. Partial cDNAs have been identified for three of them. To determine whether any of these coding elements are essential for development, we required a method for the induction and selection of mutations in these elements. Our approach was to identify a set of formaldehyde and gamma radiation induced unc-22 mutations that mapped to the unc-22-let-56 region, and then employ polymerase chain reaction methodology to identify deficiencies that affected one or more of the four identified coding elements. Two small deficiencies were identified in this manner. Characterization of these deficiencies shows that there are no coding elements between unc-22 and let-56 (the nearest mutationally identified gene to the left of unc-22), which are required in development under laboratory conditions. We conclude that the polymerase chain reaction is a practical tool for the detection of deletions of coding elements identified in this region, and that characterization of such deficiencies provides a method for assessing whether or not these elements are required for development.

A database of 209 Drosophila introns was extracted from Genbank (release number 64.0) and examined by a number of methods in order to characterize features that might serve as signals for messenger RNA splicing. A tight distribution of sizes was observed: while the smallest introns in the database are 51 nucleotides, more than half are less than 80 nucleotides in length, and most of these have lengths in the range of 59-67 nucleotides. Drosophila splice sites found in large and small introns differ in only minor ways from each other and from those found in vertebrate introns. However, larger introns have greater pyrimidine-richness in the region between 11 and 21 nucleotides upstream of 3' splice sites. The Drosophila branchpoint consensus matrix resembles C T A A T (in which branch formation occurs at the underlined A), and differs from the corresponding mammalian signal in the absence of G at the position immediately preceding the branchpoint. The distribution of occurrences of this sequence suggests a minimum distance between 5' splice sites and branchpoints of about 38 nucleotides, and a minimum distance between 3' splice sites and branchpoints of 15 nucleotides. The methods we have used detect no information in exon sequences other than in the few nucleotides immediately adjacent to the splice sites. However, Drosophila resembles many other species in that there is a discontinuity in A + T content between exons and introns, which are A + T rich.

A hybrid analog-digital neural processing element with the time-dependent behavior of biological neurons has been developed. The hybrid processing element is designed for VLSI implementation and offers the best attributes of both analog and digital computation. Custom VLSI layout reduces the layout area of the processing element, which in turn increases the expected network density. The hybrid processing element operates at the nanosecond time scale, which enables it to produce real-time solutions to complex spatiotemporal problems found in high-speed signal processing applications. VLSI prototype chips have been designed, fabricated, and tested with encouraging results. Systems utilizing the time-dependent behavior of the hybrid processing element have been simulated and are currently in the fabrication process. Future applications are also discussed.

The gm (gene mapper) system provides a tool which automates the analysis and identification of candidate genes within an anonymous DNA sequence. Only a small, biased set of all genes are known; from this sampling it is not possible to know the composition of all genes. Consequently, it is not currently possible to develop software to detect all genes. gm is capable of detecting large regions of many genes and provides an exploratory tool for looking at anonymous DNA sequences. The first release of gm has been distributed to several dozen user sites, who have provided feedback which is being integrated into gm v.2. This paper discusses the problems encountered in gene identification software, the performance of gm v1.0, and the new features in gm v.2 that will enhance its use as an exploratory tool.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A database of209Drosophila introns wasextracted fromGenbank (release number64.0) andexamined by anumberofmethods inorder tocharacterize features that might serve assignals formessenger RNAsplicing. A tight distribution ofsizes wasobserved: while the smallest introns inthedatabase are51nucleotides, morethanhalf areless than80nucleotides inlength, andmostofthese havelengths intherangeof59-67 nucleotides. Drosophila splice sites foundinlarge and small introns differ inonly minor waysfromeachother andfromthosefoundinvertebrate introns. However, larger introns havegreater pyrimidine-richness inthe region between 11and21nucleotides upstream of3' splice sites. TheDrosophila branchpoint consensus matrix resembles CTAAT(in whichbranch formation occursattheunderlined A),anddiffers fromthe corresponding mammalian signal intheabsence ofG attheposition immediately preceding thebranchpoint. Thedistribution ofoccurrences ofthissequence suggests aminimumdistance between 5'splice sites andbranchpoints ofabout38nucleotides, anda minimumdistance between3'splice sitesand branchpoints of15nucleotides. Themethods wehave useddetect noinformation inexonsequences other thaninthefewnucleotides immediately adjacent tothe splice sites. However, Drosophila resembles many other species inthat there isadiscontinuity inA+T content between exonsandintrons, whichareA+T

A Hybrid Temporal Processing Element (HTPE) has been developed and implemented in VLSI circuitry. The HTPE closely models the spatio-temporal processing of biological neurons. Asynchronous spike-like action potentials (APs) robustly transmit data between neurons, which continuously convolve relatively slow time-varying post-synaptic potentials (PSPs) induced by impinging APs. The HTPE VLSI circuitry and model functionality have been refined over five generations of models. The present model is well suited for application to temporal signal processing problems. The resulting systems provide small, high-speed solutions to complex scientific and engineering problems. This dissertation is the cumulation of four years of research into the implementation of biologically-realistic neuron models in integrated electronics. The original contributions of this work include: (1) The HTPE is the first silicon-based model of the entire neuron; pre-synaptic region, post-synaptic region, dendritic tree, cell body (SOMA), axon hillock, axon, and collaterals. (2) The HTPE is the most biologically-realistic silicon-based neuron model, producing both APs and PSPs. The HTPE also maintains the continuous/asynchronous dynamics of biological neurons. (3) The custom VLSI circuitry of the HTPE has several unique features: (a) custom design and a novel design methodology have produced minimal sized circuits that operate at the maximal rate allowed by the particular VLSI process used for implementation, (b) external DC biases can be used to program the complete behavior of the HTPE, which allows for wide flexibility in system design, and (c) the HTPE CMOS devices are allowed to operate in all four modes of operation (cutoff, subthreshold, saturation, and ohmic), which allows the HTPE to process at speeds ranging from seconds to nanoseconds. (4) The DC biases that control the HTPE behavior can be modulated using hardware adaptation units that increment or decrement a bias voltage a small amount in response to input APs. The adaptation units provide an embedded hardware mechanism for network learning and programming. (5) Multi-HTPE systems have been developed for application to high-speed spatio-temporal signal processing problems. These systems are capable of processing on both the transient and steady-state components of their input signals. (6) The heuristic approach taken to HTPE system design requires a designer to have a knowledge of HTPE dynamics. This approach, however, has laid the foundation for the formation of a general-purpose methodology for HTPE system design.

Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

This document reports the development of the MERCURY mesoscale meteorological data fusion system between 1 October 1989 and 30 September 1990. MERCURY will function as an intelligent, autonomous software interface between the data ingestion and management facilities of a future version of the integrated meteorological system, or a similar system, and tactical decision aids that require meteorological data as input. This report describes the current state of MERCURY and the procedures being used for evaluation. It also presents representative test results obtained in the Los Angeles basin area during July 1990.

The gm (gene modeler) program automates the identification of candidate genes in anonymous, genomic DNA sequence data. gm accepts sequence data, organism-specific consensus matrices and codon asymmetry tables, and a set of parameters as input; it returns a set of models describing the structures of candidate genes in the sequence and a corresponding set of predicted amino acid sequences as output, gm is implemented in C, and has been tested on Sun, VAX, Sequent, MIPS and Cray computers. It is capable of analyzing sequences of several kilobases containing multi-exon genes in less than 1 min execution time on a Sun 4/60.

A database of sequences of 139 introns from the nematode Caenorhabditis elegans was analyzed using the information measure of Schneider et al. (1986) J. Mol. Biol. 128: 415-431. Statistically significant information is encoded by at least the first 30 nt and last 20 nt of C. elegans introns. Both the quantity and the distribution of information in the 5' splice site sequences differs between the typical short (length less than 75 nt) and rarer long (length greater than 75 nt) introns, with the 5 sites of long introns containing approximately one bit more information. 3' splice site sequences of long and short C. elegans introns differ significantly in the region between -20 and -10 nt.

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Abstract

Abstract Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a.continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

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Model -Generative Reasoning (MGR) is an automated problem solving architecture designed for application in task environments in which problems are novel and data arc noisy, incomplete, or of uncertain relevance (Hartley et al., 1987; Coombs and Hartley, 1987; Fields ct al., in press). The current prototype MGR system employs a sequential reasoning strategy, the MGR algorithm (Coombs and HartIcy, 1987). This problem solver is capable of generating models of events for which it has no stored schema by decomposing stored schemata representing similar events, and recombining the components into a new model. It can, therefore, function successfully in task environments in which a restricted class of novel events can arise, and in which irrelevant as well as relevant information is included in both the input and the knowledge base. The prototype has been applied to process control (Coombs and Hartley, 1988) and robot path planning (Eshner et al., in press) problems; current application areas include meteorological data fusion (Coombs et al., 1988) and DNA sequence analysis. The problem solving strategy employed by the current MGR prototype is useful in some domains; however, it does not permit sufficiently plastic behavior in the face of some forms of novelty or incomplete data. If plasticity in the face of novelty is regarded as a measure of intelligence (Fields and Dietrich, 1987a), the use of a fixed strategy must be regarded as a deficit in a problem solver. One approach to alleviating the limitations imposed by a fixed problem solving strategy is to design a strategy that allows the problem solver to emulate the behavior that would result from applying a task-appropriate to each individual task. This is the general approach taken by Newell’s group in the design of their Universal Weak Method (Laird and Newell, 1983; Laird et al., 1987). The approach that we have taken has similar motivations; however, instead of designing a universal symbolic weak method that allows emulation of alternative strategics, we have designed a concurrent, dynamic control structure that allows the arbitrary superposition of strategies within a single execution cycle. This structure will allow problem solvers based on the MGR architecture to, in effect, arbitrarily integrate alternative strategies into new methods customized to the particular problem at hand.

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(1987). Human‐computer interaction: A critical synthesis. Social Epistemology: Vol. 1, No. 1, pp. 5-25.

Ecological realism and cognitivism are the two major current contenders in the field of cognitive perceptual theory. This thesis examines these theories, and the debate between them. It shows that the debate, as it exists in the literature, is inconclusive, primarily because of problems in the current formulations of the two contending theories. The most obvious difficulties in the two theories are removed, leaving reconstructed versions of both. The debate is then re-examined in the context of the reconstructed theories. It is shown that ecological realism is a special case of cognitivism dealing with the detection of properties of objects in the environment by resonant transduction. It is also shown that neither theory, as it stands, can adequately describe changes in the perceptual abilities of even very simple animals

The fission of nuclei with $159\ensuremath{\le}A\ensuremath{\le}232$ induced by the bombardment of 19.1 to 44.5 MeV $^{3}\mathrm{He}$ ions has been measured using solid-state detectors with time-of-flight measurements. Analysis with statistical fission theory, including precompound nucleon emission, indicates fission barriers which decrease only slightly relative to the liquid-drop model values with decreasing $Z$, approaching about 90% of the liquid-drop model barrier for $A\ensuremath{\approx}160$. These results are in contrast with measurements at higher angular momenta which indicate much lower fission barriers (60 to 70% of the liquid-drop model) for this mass region. The angular correlations indicate complete, or slightly greater than complete momentum transfer to the compound system. This is in opposition to that observed using heavier projectiles where incomplete momentum transfer is probable.NUCLEAR REACTIONS, FISSION $^{159}\mathrm{Tb}$, $^{165}\mathrm{Ho}$, $^{169}\mathrm{Tm}$, $^{\mathrm{nat}}\mathrm{Ta}$, $^{\mathrm{nat}}\mathrm{Re}$, $^{194,195}\mathrm{Pt}$, $^{197}\mathrm{Au}$, $^{202}\mathrm{Hg}$, $^{205}\mathrm{Tl}$, $^{206,208}\mathrm{Pb}$, $^{\mathrm{nat}}\mathrm{Bi}$, $^{\mathrm{nat}}\mathrm{Th}$($^{3}\mathrm{He}$,f), $E(^{3}\mathrm{He})=19.1 \mathrm{to} 44.5$ MeV; measured ${\ensuremath{\sigma}}_{F}(\ensuremath{\theta}, E)$, angular correlations, coincident fragment kinetic energies; deduced relative mass division, total kinetic energy release, statistical-model fission parameters.

Decay properties of $^{194,195,196}\mathrm{Pb}$ were studied using singles and coincident $\ensuremath{\gamma}$-ray spectroscopy. Sources were produced by the 95 MeV $^{197}\mathrm{Au}$($^{6}\mathrm{Li}$,$\mathrm{xn}$) reactions. No direct evidence for the decay of a low-spin isomer of $^{195}\mathrm{Pb}$ was observed. Several new levels were observed in $^{195,196}\mathrm{Tl}$, and are interpreted in terms of a rotational model.RADIOACTIVITY $^{194,195,196}\mathrm{Pb}$ [from $^{197}\mathrm{Au}$($^{6}\mathrm{Li}$,$\mathrm{xn}$), $E=95$ MeV]. Measured ${E}_{\ensuremath{\gamma}}$, ${I}_{\ensuremath{\gamma}}$, $\ensuremath{\gamma}\ensuremath{-}\ensuremath{\gamma}$ coin; deduced $log\mathrm{ft}$. $^{194,195,196}\mathrm{Pb}^{m}$ deduced ${t}_{\frac{1}{2}}$. $^{194,195,196}\mathrm{Tl}$ deduced levels, $J$, $\ensuremath{\pi}$, Nilsson configurations. Ge(Li) detectors.

The interactions between a ${K}^{\ensuremath{\pi}}={5}^{\ensuremath{-}}$ aligned two-quasineutron band and two octupole bands have been observed in $^{164}\mathrm{Er}$. Band crossings occur in both even- and odd-spin sequences. The members of all three bands are observed from the bandheads (${I}^{\ensuremath{\pi}}={1}^{\ensuremath{-}}, {2}^{\ensuremath{-}}, \mathrm{and} {5}^{\ensuremath{-}}$) to about ${12}^{\ensuremath{-}}$.NUCLEAR REACTIONS $^{162}\mathrm{Dy}(\ensuremath{\alpha}, 2n\ensuremath{\gamma})^{164}\mathrm{Er}$, $E=24$ MeV; measured ${E}_{\ensuremath{\gamma}}$, ${I}_{\ensuremath{\gamma}}(\ensuremath{\theta}, t)$, $\ensuremath{\gamma}\ensuremath{-}\ensuremath{\gamma}$ coin. Deduced levels, ${K}^{\ensuremath{\pi}}$, ${I}^{\ensuremath{\pi}}$, configurations. Two-band mixing analysis.

The anomalous feature in $^{8}\mathrm{Be}$ reported at ${E}_{x}\ensuremath{\approx}0.6$ MeV has been investigated using $^{9}\mathrm{Be}$($p$,$d$)$^{8}\mathrm{Be}$ at 14.3 and 26.2 MeV bombarding energy. Analyses of the spectral shape and transfer cross sections as a function of scattering angle are consistent with this feature being part of the ${J}^{\ensuremath{\pi}}={0}^{+}$ $^{8}\mathrm{Beg}$.s. Approximately 6% of the g.s. transfer strength is contained in the anomaly. Also, the line width observed for the ${J}^{\ensuremath{\pi}}={2}^{+}$ level (${E}_{x}=2.94$ MeV) appears to be independent of bombarding energy for ${E}_{p}=14 \mathrm{to} 180$ MeV.NUCLEAR REACTIONS $^{9}\mathrm{Be}$($p$,$d$)$^{8}\mathrm{Be}$, ${E}_{p}=14.3 \mathrm{and} 26.2$ MeV; measured $\ensuremath{\sigma}({E}_{x},\ensuremath{\theta})$, ${E}_{x}=0, 0.6, 2.94, \mathrm{and} 11.4$ MeV; deduced $\ensuremath{\Gamma}$, ${\ensuremath{\gamma}}^{2}$ and ${S}_{n}$; inferred properties of ghost anomaly at ${E}_{x}\ensuremath{\approx}0.6$ MeV; FRDW analysis; $\ensuremath{\Delta}E\ensuremath{-}E$ counter telescope and magnetic spectrometer.

This work was supported by the National Science Foundation Grants NSF PHY 78-22774 A03, NSF PHY 81-14339, and by Indiana University

States in $^{89}\mathrm{Y}$ with spins between $\frac{9}{2}$ and $\frac{27}{2}$ have been observed with the $^{87}\mathrm{Rb}$($\ensuremath{\alpha}$,$2n\ensuremath{\gamma}$) reaction at 35.9 MeV. The previously reported $^{89}\mathrm{Y}$ decay scheme is corrected.NUCLEAR REACTIONS $^{87}\mathrm{Rb}$($\ensuremath{\alpha}$,$2n\ensuremath{\gamma}$)$^{89}\mathrm{Y}$; measured $\ensuremath{\gamma}\ensuremath{-}\ensuremath{\gamma}$ coincidence, $I({E}_{\ensuremath{\alpha}},{\ensuremath{\theta}}_{\ensuremath{\gamma}})$, ${E}_{\ensuremath{\gamma}}$; deduced ${J}^{\ensuremath{\pi}}$. Enriched target, Ge(Li) detectors.