The program of “neurophenomenal structuralism” is presented as an agenda for a genuine structuralist neuroscience of consciousness that seeks to understand specific phenomenal experiences as strictly relational affairs. The paper covers a broad range of topics. It starts from considerations about neural change detection and relational coding that motivate a solution of the Newman problem of the brain in terms of spatiotemporal relations. Next, phenomenal quality spaces and their Q-structures are discussed. Neurophenomenal structuralism proclaims a homomorphic mapping of the (...) structures of self-organized neural maps in the brain onto Q-structures, and it will be demonstrated how this leads to a new and special version of structural representationalism about phenomenal content. A methodological implication of neurophenomenal structuralism is that it proposes measurement procedures that focus on the relationships between different stimuli (as, for instance, similarity ratings or representational geometry methods). Finally, it will be shown that neurophenomenal structuralism also has strong philosophical implications, as it leads to holism about phenomenal experiences and serves to reject inverted qualia scenarios. (shrink)

The emphasis placed by H. Atlan, like G. Bateson, on the reception of messages during communication between subsystems leads to a conception of learning, and more generally of human memory, surprisingly close to that proposed by I. Rosenfield on the basis of the work of G. M. Edelman. The authors stressed the close and reciprocal link between the theory of functional localization and the conception of memory, which they have just seen, radically refuted by Rosenfield. The theory of functional localization (...) therefore considers as established the existence of a whole series of rigid relationships between specific locations in the brain and certain major functions performed by the body. Thus briefly summarized, the theory of neural Darwinism provides positive evidence in favor of the Rosenfield's theory of human memory. All these characteristics make the functioning of human memory an outstanding example of the natural complexity of a self‐organized system in the sense of Atlan. (shrink)

A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be constituted by self-organized comparative operations across a network of unimodal and multimodal sensory areas. However, such network interactions alone cannot answer the question how sensory feature detectors collectively account for an integrated, yet phenomenally differentiated (...) experiential content. This problem turns out to be different from, although related to, the binding problem. It is proposed that the neural correlate of an enriched, multimodal experience is constituted by the attractor state of a dynamic associative network. Within this network, unimodal and multimodal sensory maps continuously interact to influence each other’s attractor state, so that a feature change in one modality results in a fast re-coding of feature information in another modality. In this scheme, feature detection is coded by firing-rate, whereas firing phase codes relational aspects. (shrink)

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human (...) observers. To this end, we exploit a neural network metric in the output of a biologically inspired Self- Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data. (shrink)

In this article I suggest how we might conceptualize some kind of artificial consciousness as an ultimate development of Artificial Life. This entity will be embodied in some sort of constructed (biological or non-biological) body. The contention is that consciousness within self-organized entities is not only possible but inevitable. The basic sensory and interactive processes by which an organism operates within an environment are such as to be the basic processes that are necessary for consciousness. I then look (...) at likely criteria for consciousness, and point to an architecture of the cognitive which maps onto the physiological layer, the brain. While evolutionary algorithms and neural nets will be at the heart of the production of artificial intelligences there is a particular architectural organization that may be necessary in the production of conscious artefacts. This involves the operations of multiple layers of feedback loops in the anatomy of the brain, in the social construction of the contents of consciousness and in particular in the self-regulation necessary for the continued operation of metabolically organized systems. Finally I make some comments on the ethics of such a procedure. (shrink)

In this paper I suggest how we might conceptualize some kind of artificial consciousness as an ultimate development of Artificial Life. This entity will be embodied in some sort of constructed (biological or non-biological) body. The contention is that consciousness within self-organized entities is not only possible but inevitable. The basic sensory and interactive processes by which an organism operates within an environment are such as to be the basic processes that are necessary for consciousness. I then look (...) at likely criteria for consciousness, and point to an architecture of the cognitive which maps onto the physiological layer, the brain. While evolutionary algorithms and neural nets will be at the heart of the production of artificial intelligences there is a particular architectural organization that may be necessary in the production of conscious artefacts. This involves the operations of multiple layers of feedback loops in the anatomy of the brain, in the social construction of the contents of consciousness and in particular in the self-regulation necessary for the continued operation of metabolically organized systems. Finally I make some comments on the ethics of such a procedure. (shrink)

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are implemented through (...) lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia. (shrink)

On May 11th a round table discussion was held on the subject "The Interactions of Science and Art under the Conditions of the Revolution in Science and Technology ," organized by the editorial boards of the journals Voprosy filosofii and Voprosy literatury.

Neural devices have the capacity to enable users to regain abilities lost due to disease or injury – for instance, a deep brain stimulator (DBS) that allows a person with Parkinson’s disease to regain the ability to fluently perform movements or a Brain Computer Interface (BCI) that enables a person with spinal cord injury to control a robotic arm. While users recognize and appreciate the technologies’ capacity to maintain or restore their capabilities, the neuroethics literature is replete with examples (...) of concerns expressed about agentive capacities: A perceived lack of control over the movement of a robotic arm might result in an altered sense of feeling responsible for that movement. Clinicians or researchers being able to record and access detailed information of a person’s brain might raise privacy concerns. A disconnect between previous, current, and future understandings of the self might result in a sense of alienation. The ability to receive and interpret sensory feedback might change whether someone trusts the implanted device or themselves. Inquiries into the nature of these concerns and how to mitigate them has produced scholarship that often emphasizes one issue – responsibility, privacy, authenticity, or trust – selectively. However, we believe that examining these ethical dimensions separately fails to capture a key aspect of the experience of living with a neural device. In exploring their interrelations, we argue that their mutual significance for neuroethical research can be adequately captured if they are described under a unified heading of agency. On these grounds, we propose an “Agency Map” which brings together the diverse neuroethical dimensions and their interrelations into a comprehensive framework. With this, we offer a theoretically-grounded approach to understanding how these various dimensions are interwoven in an individual’s experience of agency. (shrink)

Adult stem cell populations must coordinate their own maintenance with the generation of differentiated cell types to sustain organ physiology, in a spatially controlled manner and over long periods. Quantitative analyses of clonal dynamics have revealed that, in epithelia, homeostasis is achieved at the population rather than at the single stem cell level, suggesting that feedback mechanisms coordinate stem cell maintenance and progeny generation. In the central nervous system, however, little is known of the possible community processes underlying neural (...) stem cell maintenance. Recent work, in part based on intravital imaging made possible in the adult zebrafish, conclusively highlights that homeostasis in neural stem cell pools may rely on population asymmetry and long‐term spatiotemporal coordination of neural stem cell states and fates. These results suggest that neural stem cell assemblies in the vertebrate brain behave as self‐organized systems, such that the stem cells themselves generate their own intrinsic niche. (shrink)

In this paper I argue that radiological attempts to elucidate the properties of self -- an endeavor currently popular in the social neurosciences -- are fraught with conceptual difficulties. I first discuss several philosophical criteria that increase the chances we are posing the “right” questions to nature. I then discuss whether these criteria are met when empirical efforts are directed at one of the central constructs in the social sciences – the human self. In particular, I consider whether (...) recent attempts to map the neural correlates of self and its assumed properties using brain scanning technology satisfy the conceptual conditions minimally required to ask well-formed, theoretically satisfying questions of nature. I conclude that much theoretical work remains to be done. (shrink)

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) (...) Function: Control of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. (3) Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. Key Words: cognitive maps; computational neuroscience; dynamics; hippocampus; memory; modular architectonics; neural modeling; neural organization; neural plasticity; rhythmogenesis; Szentágothai. (shrink)

The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series and in time series of satellite images. Here, the functional properties of the quantization error in SOM are explored further to show that the metric is capable of reliably discriminating between the finest differences in local contrast intensities and contrast signs. While this capability of the QE (...) is akin to functional characteristics of a specific class of retinal ganglion cells (the so-called Y-cells) in the visual systems of the primate and the cat, the sensitivity of the QE surpasses the capacity limits of human visual detection. Here, the quantization error in the SOM is found to reliably signal changes in contrast or colour when contrast information is removed from or added to the image, but not when the amount and relative weight of contrast information is constant and only the local spatial position of contrast elements in the pattern changes. While the RGB Mean reflects coarser changes in colour or contrast well enough, the SOM-QE is shown to outperform the RGB Mean in the detection of single-pixel changes in images with up to five million pixels. This could have important implications in the context of unsupervised image learning and computational building block approaches to large sets of image data (big data). (shrink)

With no precise boundaries, always on the move and too complex to be defined by space and time, is it possible to map the human subject? This book attempts to do just this, exploring the places of the subject in contemporary culture. The editors approach this subject from four main aspects--its construction, sexuality, limits and politics--using a wide ranging review of literature on subjectivity across the social and human sciences. The first part of the book establishes the idea that the (...) subject is constructed through detailed histories of the subject. The second part shows that sexuality cannot be assumed to be natural through the contributors' research on the place of sexuality in subjectivity and subjectivity in sexuality. The essays in the third part take issue with the idea of a singular, self-contained identity. Power relations and the effects of power are consistent themes throughout the book and the final section deals explicitly with relations of power, whether organized around gender, race, class or other kinds of difference. Contributors: Steve Pile, Nigel Thrift, Miles Ogborn, Carolyn Steedman, David Matless, David Sibley, David Bell, Julia Cream, Vic Seidler, Hester Parr, Chris Philo, Marcus Doel, Paul Rodaway, Nigel Rapport, Stephen Frosh, Valerie Walkerdine, Gillian Rose and Michael Keith. (shrink)

This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is (...) distributed control with rich commands, defended by proponents of massive modularity hypothesis; the other is centralized control with simple commands. My goal is to develop a hybrid account that combines aspects of the second alternative position and that of the embodied cognitive science (i.e., centralized and distributed controls with simple commands). Before developing my account, I discuss the virtues and challenges of the first three. This discussion results in a set of criteria for successful neural control mechanisms. Then, I develop my account through analyzing neuroscientific models of decision-making and control with the theoretical lenses provided by formal decision and social choice theories. I contend that neural processes can be productively modeled as a collective of agents, and neural self-organization is analogous to democratic self-governance. In particular, I show that the basal ganglia, a set of subcortical structures, contribute to the production of coherent and intelligent behaviors through implementing “democratic" procedures. Unlike the Fodorian central system—which is a micro-managing “neural commander-in-chief”—the basal ganglia are a “central election commission.” They delegate control of habitual behaviors to other distributed control mechanisms. Yet, when novel problems arise, they engage and determine the result on the basis of simple information (the votes) from across the system with the principles of neurodemocracy, and control with simple commands of inhibition and disinhibition. By actively managing and taking advantage of the wisdom-of-the-crowd effect, these democratic processes enhance the intelligence and coherence of the mind’s final "collective" decisions. I end by defending this account from both philosophical and empirical criticisms and showing that it meets the criteria for successful solution. (shrink)

In the present paper we present a short review of some recent neuro- physiological and neuropsychological findings which suggest that self-generated actions and actions of others are mapped on the same neural substratum. Since this substratum is neutral with respect to the agent, correctly attributing an action to its proper author requires the co-activation of areas specific to the self and the other. A conceptual analysis of the empirical data will lead us to conclude that from a (...) neurobiological point of view the problem is not 'how is it possible to share the intentions of others', but rather 'how one can distinguish one's own action/intention from those of other people'. (shrink)

Love is an essential biological, psychological, sociological, and religious phenomenon. Using various conceptual models, philosophers have often distinguished between different types of love, such as self-love, romantic love, friendship love, love of God, and neighborly love. Psychologists and neuroscientists on the other hand have thus far focused predominantly on understanding the emotions and behavioral and neural mechanisms associated with romantic love and parental love. We do not yet know how the models construed by philosophers are related to actual (...) experiences of love, and to which extent they are merely nominal creations connecting phenomena that in fact have little to do with each other. We lack empirical knowledge of how different types of love are experienced as embodied feelings, and how these experiences are related to one another. Here we distinguished between 27 different types of love. Using self-report methods, we measured 1) how subjective feelings of different types of love are topographically embodied; 2) how different types of love are associated with self-reported emotional valence, strength of the bodily and mental experience, association with touch, time elapsed since last experienced, and controllability; and 3) how similar different types of love feel. Our study provides the first mapping of embodied experiences associated with different types of love. The results show that the subjective feelings associated with the love types form a continuum from strongly to weakly felt loves. (shrink)

The scientific relationship among self, mind and brain is still not clearly known. Self’s subjective experience of perception and cognition of words, feelings, thoughts etc. is supported by the integrity of human brain. Consequently, neuroscientists, psychologists, psychiatrists, physicists and philosophers have been investigating to find the scientific relationship between mind and brain, consciousness and quantum physics. Recent experimental evidence suggests that the neural correlate of consciousness is located in certain parts of the cortico-thalamic system. But it is (...) not known specifically which parts of the human brain are involved in the human cognitive activity. In this study, the author proposed a tree-pattern architecture of the cerebral neural substrate in cognitive understanding of words, feelings, and thoughts on the basis of the author’s hypothesis of the ultron-logotron theory to explain the neural correlate of consciousness. (shrink)

The purpose of the present study was to identify and categorize career motivations in highly educated married Korean women. Twenty five participants who are working were interviewed and asked why they continue their work despite various difficulties. Sixty-seven career persistence motivations were elicited and reliably organized into 6 categories: low interest in childcare and household labor, family-related motives, high need for achievement, financial problems/needs, self-actualization and job satisfaction, and positive perception of working women. This study is significant as (...) it conceptualizes the motivation for career persistence as the major variable affecting highly educated married women’s decision to continue their careers and establishes the theoretical basis for future research. (shrink)

A network of gene regulation organized in a hierarchical and combinatorial manner is crucially involved in the development of the neural network, and has to be considered one of the main substrates of genetic change in its evolution. Though qualitative features may emerge by way of the accumulation of rather unspecific quantitative changes, it is reasonable to assume that at least in some cases specific combinations of regulatory parts of the genome initiated new directions of evolution, leading to (...) novel capabilities of the brain. These notions are applied, in this paper, to the evolution of the capability of cognition-based human empa­thy. It is suggested that it has evolved as a secondary effect of the evolution of strategic thought. Development of strategies depends on abstract representations of one’s own pos­sible future states in one’s own brain to allow assessment of their emotional desirability, but also on the representation and emotional evaluation of possible states of others, allowing anticipation of their behaviour. This is best achieved if representations of others are con­nected to one’s own emotional centres in a manner similar to self-representations. For this reason, the evolution of the human brain is assumed to have established representations with such linkages. No group selection is involved, because the quality of strategic thought affects the fitness of the individual. A secondary effect of this linkage is that both the actual states and the future perspectives of others elicit vicarious emotions, which may contribute to the motivations of altruistic behaviour. (shrink)

Despite the lack of invariance problem (the many‐to‐many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side‐stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real‐world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to (...) provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two‐layer network that borrows one element from ASR, long short‐term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human‐like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR. (shrink)

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. Function: Control (...) of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. (shrink)

A technique for the bilateral activation of neural nets that leads to a functional asymmetry of two simulated ''cerebral hemispheres'' is described. The simulation is designed to perform object recognition, while exhibiting characteristics typical of human consciousness-specifically, the unitary nature of conscious attention, together with a dual awareness corresponding to the ''nucleus'' and ''fringe'' described by William James (1890). Sensory neural nets self-organize on the basis of five sensory features. The system is then taught arbitrary symbolic labels (...) for a small number of similar stimuli. Finally, the trained network is exposed to nonverbal stimuli for object recognition, leading to Gaussian activation of the ''sensory'' maps-with a peak at the location most closely related to the features of the external stimulus. ''Verbal'' maps are activated most strongly at the labeled location that lies closest to the peak on homologous sensory maps. On the verbal maps activation is characterized by both excitatory and inhibitory Gaussians (a Mexican hat), the parameters of which are determined by the relative locations of the verbal labels. Mutual homotopic inhibition across the ''corpus callosum'' then produces functional cerebral asymmetries, i.e., complementary activation of homologous ''association'' and ''frontal'' maps within a common focus of attention-a nucleus in the left hemisphere and a fringe in the right hemisphere. An object is recognized as corresponding to a known label when the total activation of both hemispheres (nucleus plus fringe) is strongest for that label. The functional dualities of the cerebral hemispheres are discussed in light of the nucleus/fringe asymmetry. (shrink)

The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networks – neural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically motivated. Moreover, (...) the self-taught neural network is the product of the interplay between evolution and learning. We simulate a multi-agent system in which neural networks are used to control autonomous agents. These agents have to forage for resources and compete for their own survival. Experimental results show that the interaction between evolution and the ability to teach oneself in self-taught neural networks outperform evolution and self-teaching alone. More specifically, the emergence of an intelligent foraging strategy is also demonstrated through that interaction. Indications for future work on evolving neural networks are also presented. (shrink)

The present paper analyzes the regularities referred to via the concept 'self.' This is important, for cognitive science traditionally models the self as a cognitive mediator between perceptual inputs and behavioral outputs. This leads to the assertion that the self causes action. Recent findings in social psychology indicate this is not the case and, as a consequence, certain cognitive scientists model the self as being epiphenomenal. In contrast, the present paper proposes an alternative approach (i.e., the (...) event-control approach) that is based on recently discovered regularities between perception and action. Specifically, these regularities indicate that perception and action planning utilize common neural resources. This leads to a coupling of perception, planning, and action in which the first two constitute aspects of a single system (i.e., the distal-event system) that is able to pre-specify and detect distal events. This distal-event system is then coupled with action (i.e., effector-control systems) in a constraining, as opposed to 'causal' manner. This model has implications for how we conceptualize the manner in which one infers the intentions of another, anticipates the intentions of another, and possibly even experiences another. In conclusion, it is argued that it may be possible to map the concept 'self' onto the regularities referred to in the event-control model, not in order to reify 'the self' as a causal mechanism, but to demonstrate its status as a useful concept that refers to regularities that are part of the natural order. (shrink)

While univariate functional magnetic resonance imaging data analysis methods have been utilized successfully to map brain areas associated with cognitive and emotional functions during viewing of naturalistic stimuli such as movies, multivariate methods might provide the means to study how brain structures act in concert as networks during free viewing of movie clips. Here, to achieve this, we generalized the partial least squares analysis, based on correlations between voxels, experimental conditions, and behavioral measures, to identify large-scale neuronal networks activated during (...) the first time and repeated watching of three ∼5-min comedy clips. We identified networks that were similarly activated across subjects during free viewing of the movies, including the ones associated with self-rated experienced humorousness that were composed of the frontal, parietal, and temporal areas acting in concert. In conclusion, the PLS method seems to be well suited for the joint analysis of multi-subject neuroimaging and behavioral data to quantify a functionally relevant brain network activity without the need for explicit temporal models. (shrink)

Neuronal aggregates involved in conscious awareness are not evenly distributed throughout the CNS but comprise key components referred to as the neural network correlates of consciousness (NNCC). A critical node in this network is the posterior cingulate, precuneal, and retrosplenial cortices. The cytological and neurochemical composition of this region is reviewed in relation to the Brodmann map. This region has the highest level of cortical glucose metabolism and cytochrome c oxidase activity. Monkey studies suggest that the anterior thalamic projection (...) likely drives retrosplenial and posterior cingulate cortex metabolism and that the midbrain projection to the anteroventral thalamic nucleus is a key coupling site between the brainstem system for arousal and cortical systems for cognitive processing and awareness. The pivotal role of the posterior cingulate, precuneal, and retrosplenial cortices in consciousness is demonstrated with posterior cingulate epilepsy cases, midcingulate lesions that de-afferent this region and are associated with unilateral sensory neglect, observations from stroke and vegetative state patients, alterations in blood flow during sleep, and the actions of general anesthetics. Since this region is critically involved in self reflection, it is not surprising that it is similarly a site for the NNCC. Interestingly, information processing during complex cognitive tasks and during aversive sensations such as pain induces efforts to terminate self reflection and result in decreased processing in posterior cingulate and precuneal cortices. (shrink)

Consciousness has long been a subject of interest in philosophy and religion but only relatively recently has it become subject to scientific investigation. Now, more than ever before, we are beginning to understand this mental state. Developmental psychologists understand when we first develop a sense of self; neuropsychologists see which parts of the brain activate when we think about ourselves and which parts of the brain control that awareness. Cognitive scientists have mapped the circuitry that allows machines to have (...) some form of self awareness, and neuroscientists investigate similar circuitry in the human brain. Research that once was separate inquiries in discreet disciplines is converging. List serves and small conferences focused on consciousness are proliferating. New journals have emerged in this field. A huge number of monographs and edited treatises have recently been published on consciousness, but there is no recognized entry point to the field, no comprehensive summary. This encyclopedia is that reference. Organized alphabetically by topic, coverage encompasses a summary of major research and scientific thought regarding the nature of consciousness, the neural circuitry involved, how the brain, body, and world interact, and our understanding of subjective states. The work includes contributions covering neuroscience, psychology, philosophy, and artificial intelligence to provide a comprehensive backdrop to recent and ongoing investigations into the nature of conscious experience from a philosophical, psychological, and biological perspective. (shrink)

Self-organized criticality (SOC) is based upon the idea that complex behavior can develop spontaneously in certain multi-body systems whose dynamics vary abruptly. This book is a clear and concise introduction to the field of self-organized criticality, and contains an overview of the main research results. The author begins with an examination of what is meant by SOC, and the systems in which it can occur. He then presents and analyzes computer models to describe a number of (...) systems, and he explains the different mathematical formalisms developed to understand SOC. The final chapter assesses the impact of this field of study, and highlights some key areas of new research. The author assumes no previous knowledge of the field, and the book contains several exercises. It will be ideal as a textbook for graduate students taking physics, engineering, or mathematical biology courses in nonlinear science or complexity. (shrink)

Self-organized complexity in the physical, biological, and social sciences Donald L Turcotte*f and John B. Rundle* *Department of Earth and Atmospheric ...

The present paper analyzes the regularities referred to via the concept 'self.' This is important, for cognitive science traditionally models the self as a cognitive mediator between perceptual inputs and behavioral outputs. This leads to the assertion that the self causes action. Recent findings in social psychology indicate this is not the case and, as a consequence, certain cognitive scientists model the self as being epiphenomenal. In contrast, the present paper proposes an alternative approach (i.e., the (...) event-control approach) that is based on recently discovered regularities between perception and action. Specifically, these regularities indicate that perception and action planning utilize common neural resources. This leads to a coupling of perception, planning, and action in which the first two constitute aspects of a single system (i.e., the distal-event system) that is able to pre-specify and detect distal events. This distal-event system is then coupled with action (i.e., effector-control systems) in a constraining, as opposed to 'causal' manner. This model has implications for how we conceptualize the manner in which one infers the intentions of another, anticipates the intentions of another, and possibly even experiences another. In conclusion, it is argued that it may be possible to map the concept 'self' onto the regularities referred to in the event-control model, not in order to reify 'the self' as a causal mechanism, but to demonstrate its status as a useful concept that refers to regularities that are part of the natural order. (shrink)

The human self model comprises essential features such as the experiences of ownership, of body-centered spatial perspectivity, and of a long-term unity of beliefs and attitudes. In the pathophysiology of schizophrenia, it is suggested that clinical subsyndromes like cognitive disorganization and derealization syndromes reflect disorders of this self model. These features are neurobiologically instantiated as an episodically active complex neural activation pattern and can be mapped to the brain, given adequate operationalizations of self model features. In (...) its unique capability of integrating external and internal data, the prefrontal cortex (PFC) appears to be an essential component of the neuronal implementation of the self model. With close connections to other unimodal association cortices and to the limbic system, the PFC provides an internally represented world model and internal milieu data of the organism, both serving world orientation. In the pathophysiology of schizophrenia, it is the dysfunction of the PFC that is suggested to be the neural correlate for the different clinical schizophrenic subsyndromes. The pathophysiological study of psychiatric disorders may contribute to the theoretical debate on the neuronal basis of the self model. (shrink)

The idea of a self-organized system brings both political and biological discourses together, for they both aim at explaining how a certain compound can achieve self-unity out of plurality. Whereas biological metaphors in politics have been much examined, political metaphors in biology have not. In this paper I intend to show how political metaphors can enlighten biological discourses, taking the work of Aristotle as a case-study. The relationship between the main elements of a living-body could be better (...) understood within a political scheme: the soul rules over the body through pneuma, its prime minister. This scheme entails, thus, to re-examine Aristotle’s definition of soul in the light of the key concept of pneuma, and to replace the hylemorphic explanation with a triadic one. On the one hand, soul is the entelecheia of the body as it keeps both the form and the end of the organism, which is its unity. On the other hand, the moving-efficacious principle that performs unity by circulating through the body, and by linking the body to its environment is pneuma. Therefore, the political formula: “the king does not govern” could shed light upon the structure of the living body: whereas the soul rules the body, pneuma governs it. Although Aristotle does not build his biology upon political concepts, metaphors are already there, shaping his explanations, within the bio-theo-political paradigm of autarchy. (shrink)

In nature, gregarious animals, insects, or bacteria usually exhibit paradoxical behaviors in the form of group fission and fusion, which exerts an important influence on group’s pattern formation, information transfer, and epidemiology. However, the fission-fusion dynamics have received little attention compared to other flocking behavior. In this paper, an intermittent selective interaction based control algorithm for the self-organized fission-fusion behavior of flocking system is proposed, which bridges the gap between the two conflicting behaviors in a unified fashion. Specifically, (...) a hybrid velocity coordination strategy that includes both the egalitarian and selective interactions is proposed, where the egalitarian interaction is to maintain the flock’s order and achieve the fusion behavior while the selective interaction strategy is for the response to external stimulus information and generates the fission behavior. Numerical simulations demonstrate that the proposed control algorithm can realize the self-organized fission-fusion behavior of flocking system under a unified framework. The influences of the main control parameters on the performance of the fission-fusion behavior are also discussed. In particular, the trade-off parameterαbalances the exploration and exploitation behaviors of flocking system and significantly enhances its movement flexibility and environmental adaptivity. (shrink)

There is a number of studies, in which it is established that the observed flows of microposts generated by microblogging social networks are characterized by avalanche-like behavior. Time series of microposts depicting such streams are the time series with a power-law distribution, with 1/f noise and long memory. Despite this, there are no studies devoted to the detection and analysis of self-organized critical state, subcritical phase, and supercritical phase. The presented paper is devoted to the detection and investigation (...) of such critical states and phases. An algorithm is proposed that allowed to detect of critical phases and critical conditions on Twitter, based on the analysis of retweets time series corresponding to the three debates of the 2016 United States Presidential Election, as the most popular debate in the history of America, collecting 84 million live views. (shrink)

Definition of the problem The acquisition of technical and research skills can be promoted in particular in courses that confront students with complex problems. In this article, we present didactic reflections on learning through self-organized inquiry in empirical medical ethics. Arguments Based on the theory of pragmatism, we show how a specific form of research-based learning courses can be realized to promote medical ethical skills. We focus on projects in which students can experience the process of conducting empirical–ethical (...) research. Conclusion Research-based learning through self-organized inquiry courses offer great potential, especially with regard to expanding students’ reflexive and reflective competencies. We discuss the inclusion of such facultative courses in the medical ethics curriculum with regard to its contextual challenges. (shrink)