Although there is empirical evidence of neural filling-in, this does not necessarily entail “isomorphic” theory. Most cortical neurons do not respond to a uniform surface and are instead sensitive to surface size and quality. I propose that a population of such neurons encodes the presence of a surface. This scheme is different from either the “cognitive” or “isomorphic” theories.

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all (...) those convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)

This paper begins to develop a conception of ecological subjectivity and hence of social-political practice that can promote social justice across diverse populations and situations. It urges a provocative posing of the question “who do we think we are?” to direct attention to often unspoken assumptions about subjectivity and agency that tend silently to inform current philosophical inquiry. Drawing attention to the often-unconscious processes of “we-saying.” it aims to highlight and to prompt contestation of the silent assumptions that tend to (...) inform that “we.” In so doing, it appeals to humility as an epistemic and moral virtue. (shrink)

If there is one rationality there must be a plurality of them. This conclusion follows, I argue, partly from the extreme and ineradicable vagueness of the fundamental concepts that every would‐be rational explanation must presuppose. Logicistic/scientistic assaults on this vagueness are doomed to fail partly because they are unable to acknowledge the imaginative dimension of rational thought. Being limited to the play of “outward appearances,” scientific investigations are also dependent on “inward imaginings” on their speculative side. The upshot is that (...) schools of philosophy should be characterized by the kind of imaginary they adopt rather than by their logics. In which case, every attempt to get and tell something right about the world is bound to incorporate mythopoeic elements in its explanations. (shrink)

If there is one rationality there must be a plurality of them. This conclusion follows, I argue, partly from the extreme and ineradicable vagueness of the fundamental concepts that every would‐be rational explanation must presuppose. Logicistic/scientistic assaults on this vagueness are doomed to fail partly because they are unable to acknowledge the imaginative dimension of rational thought. Being limited to the play of “outward appearances,” scientific investigations are also dependent on “inward imaginings” on their speculative side. The upshot is that (...) schools of philosophy should be characterized by the kind of imaginary they adopt rather than by their logics. In which case, every attempt to get and tell something right about the world is bound to incorporate mythopoeic elements in its explanations. (shrink)

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all (...) those convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)

In recent years, a number of different disciplines have begun to investigate the fundamental role context appears to play in a number of cognitive phenomena. Traditionally, linguistics, and the fields of communication and pragmatics in particular, have been the areas that have focused the most on contextual effects. Context has increasingly been studied for its role in influencing mental concepts, for some scholars being considered constitutive for most – if not all – concepts. Cognitive neuroscience is now starting to consider (...) in a systematic way how context interacts with neural responses, although this research is still scattered and concentrated in a small number of specific cases only. In this chapter, we attempt to tie these three levels together, since only from their integration can a comprehensive explanation of how context affects cognition be constructed. The way context drives language comprehension depends on the effects of context on the conceptual scaffolding of the listener, which in turn, is the result of his neural responses in combination to context. These neural responses derive from learning throughout the history of experiences of the individual, and the association between possible contexts and heard utterances. The road we take to accomplishing the multi-level integration between what appear to be distant domains, is a computational one. This approach meets with the mechanistic framework of explanation, which is currently held as the most appropriate way of approaching cognitive phenomena that is often characterized by a multiplicity of levels, as is the case with context. The core underlying concept of the neurocomputational framework here proposed, is an account of neural representation, based on structural similarity. Structural representations are still the best option on the market in cognitive science, but in their traditional form, derived from classical measurement theory, are affected by a number of serious drawbacks, including not being able to account for context. We suggest a different account of structural similarity, one informed by current neuroscience, where the homomorphic relations required for structural similarity are derived from neural population coding. In a preliminary mathematical sketch, we indicate how this approach can construct neural aggegations that are sensitive to context. (shrink)

Recent work combining cognitive neuroscience with computational modelling suggests that distributed patterns of neural firing may represent probability distributions. This paper asks: what makes it the case that distributed patterns of firing, as well as carrying information about (correlating with) probability distributions over worldly parameters, represent such distributions? In examples of probabilistic population coding, it is the way information is used in downstream processing so as to lead to successful behaviour. In these cases content depends on factors (...) beyond bare information, contra Brian Skyrms’ (2010) view that representational content can be fully characterised in information-theoretic terms. (shrink)

This book is a comprehensive and unique text and reference in medical ethics. By far the most inclusive set of primary documents and articles in the field ever published, it contains over 100 selections. Virtually all pieces appear in their entirety, and a significant number would be difficult to obtain elsewhere. The volume draws upon the literature of history, medicine, philosophical and religious ethics, economics, and sociology. A wide range of topics and issues are covered, such as law and medicine, (...) truth-telling by the physician, research, population policy, genetics, abortion, dying, and individual rights in medical care. The selections span the centuries, beginning with material from the works of Hippocrates, continuing through Thomas Percival, John Stuart Mill, and Claude Bernard, down to modern commentators like Henry K. Beecher, Walsh McDermott, David L. Bazelon, Paul Freund, H. L. A. Hart, John Rawls, Paul Ramsey, Richard McCormick, Rashi Fein, and Bernard Barber. The text has eight major divisions, beginning with sections on the ethical dimensions of the physician-patient relationship in history; the moral bases of medical ethics; and regulation, compulsion, and protection of the consumer in clinical medicine and public health. Each of these sections includes key essays that appear for the first time. All of the book's major divisions contain primary documents: codes such as the Hippocratic Oath, Medieval Law for the Regulation of Medicine, and the first as well as the most recent code of the American Medical Association; court decisions, including those on Karen Quinlan and on abortion in the United States and West Germany; government documents such as the statement of the National Commission on the Protection of Human Subjects, the Tuskegee Syphilis Report, the British Parliamentary debate on euthanasia, and the Council of Europe on rights of the sick and dying; and various published guidelines such as the Harvard Medical School brain death criteria, the American Hospital Association on patient's rights, and Pope Pius XII on the prolongation of life. Cases that illustrate moral dilemmas are provided for discussion purposes. Each section is preceded by a succinct editor's introduction. The documents and essays are of practical value for practitioners and students in medicine, law, ethics, and counselling, and for individual patients and groups concerned with medical care. Through encompassing divergent viewpoints, the essays and primary documents were selected to encourage humane practices and deepen understanding of the multiple traditions that shaped and do shape the development of medicine. (shrink)

This book examines the concept of “ Neurosemantics”, a term currently used in two different senses: the informational meaning of the physical processes in the neural circuits, and semantics in its classical sense, as the meaning of language, explained in terms of neural processes. The book explores this second sense of neurosemantics, yet in doing so, it addresses much of the first meaning as well. Divided into two parts, the book starts with a description and analysis of the (...) mathematics of the brain, including computational units, representational mechanisms and algorithmic principles. This first part pays special attention to the neural architecture which has been used in developing models of neurosemantics. The second part of the book presents a collection of models, and describes each model reproducing specific aspects of the semantics of language. Some of these models target one of the core problems of semantics, the reference of nouns, and in particular of nouns with a strong perceptual characterization. Others address the semantics of predicates, with a detailed analysis of colour attributes. While this book represents a radical shift from traditional semantics, it still pursues a line of continuity that is based on the idea that meaning can be captured, and explained, by a sort of computation. (shrink)

Specialized neural systems for encoding faces and face emotion cues are found in sheep which are very similar to those described in human and non-human primates. Sheep exhibit highly sophisticated face identity and face emotion discrimination skills, use configural cues, and also show right hemisphere dominance in face processing. Findings provide evidence for both sparse and population-based encoding with small populations of cells encoding selectively for specific individuals or categories of individual but nevertheless with widespread and overlapping neuronal (...) activity changes occurring across temporal cortex networks during the presentation of different faces. A number of studies have been carried out to map the neuroanatomical substrates involved in face recognition in sheep using quantification of expression changes in gene markers of neural activation. The face recognition system brings into sharp focus the ongoing debate as to whether sparse or population based codes or both are operating in the various cortical and subcortical networks involved. (shrink)

Using the concepts of chaotic dynamical systems, we present an interpretation of dynamic neural activity found in cortical and subcortical areas. The discovery of chaotic itinerancy in high-dimensional dynamical systems with and without a noise term has motivated a new interpretation of this dynamic neural activity, cast in terms of the high-dimensional transitory dynamics among “exotic” attractors. This interpretation is quite different from the conventional one, cast in terms of simple behavior on low-dimensional attractors. Skarda and Freeman (1987) (...) presented evidence in support of the conclusion that animals cannot memorize odor without chaotic activity of neuron populations. Following their work, we study the role of chaotic dynamics in biological information processing, perception, and memory. We propose a new coding scheme of information in chaos-driven contracting systems we refer to as Cantor coding. Since these systems are found in the hippocampal formation and also in the olfactory system, the proposed coding scheme should be of biological significance. Based on these intensive studies, a hypothesis regarding the formation of episodic memory is given. Key Words: Cantor coding; chaotic itinerancy; dynamic aspects of the brain; dynamic associative memory; episodic memory; high-dimensional dynamical systems; SCND attractors. (shrink)

Depersonalization and derealization refer to states of dissociation in which one feels a sense of alienation in relation to one’s self and environment, respectively. Whilst transient episodes often diminish without treatment, chronic experiences of DP and DR may last for years, with common treatments lacking a strong evidence base for their efficacy. We propose a theoretical explanation of DP and DR based on interoceptive predictive coding, and discuss how transient experiences of DP and DR may be induced in the (...) non-clinical population using virtual reality. Further, we review the use of heartbeat evoked potentials in detecting the neural correlates of DP and DR allowing for an objective measure of these experiences in the non-clinical population. Finally, we discuss how the induction and detection of transient experiences of DP and DR in the non-clinical population could shed light on how the brain constructs one’s sense of self and reality. (shrink)

The Cognitive Reserve (CR) hypothesis suggests that the brain actively attempts to cope with neural damages by using pre-existing cognitive processing approaches or by enlisting compensatory approaches. This would allow an individual with high CR to better cope with aging than an individual with lower CR. Many of the proxies used to assess CR indirectly refer to the flexibility of thought. The present paper aims at directly exploring the relationships between CR and creativity, a skill that includes flexible thinking. (...) We tested a sample of 72 adults (aged between 45 and 78) assessing both their level of CR and their creativity. To evaluate CR we used the proxies commonly used in literature, namely, three subtests from the WAIS (vocabulary, similarities, and digit span) and the years of education. We also used an ad-hoc test asking people to report how frequently they tend to perform activities that are believed to increase CR. We used verbal creativity tasks (alternative uses and generation of acronyms) to assess individual levels of creativity. We asked participants to describe their main occupation (present or past) and coded each occupation as creative or not creative. Results (controlling for age-related differences) showed that scores from the WAIS correlated positively with creativity performance, even though correlations varied across the subtests. Focusing on the frequency and type of activities that people perform, and comparing individuals who have or had a creative job to those with a routine job, a clear relationship between creativity and CR emerged. This effect was more relevant than the level of job complexity. Implications for the study of CR and aging are discussed. (shrink)

Page's “localist” code, a population code with occasional, maximally firing elements, does not seem to us usefully or testably different from sparse population coding. Some of the evidence adduced by Page for his proposal is not actually evidence for it, and coding by maximal firing is challenged by lower firing observed in neuronal responses to natural stimuli.

The dynamics of neural populations capture the laws of the mindThis paper focuses on the level of neural networks. Examining the case of recurrent neural networks, the paper argues that the dynamics of neural populations form a privileged level of explanation in cognitive science. According to Schöner, this level is privileged, because it enables cognitive scientists to discover the laws governing organisms’ cognition and behaviour.

It is worthwhile to search for forms of coding, processing, and learning common to various cortical regions and cognitive functions. Local cortical processors may coordinate their activity by maximizing the transmission of information coherently related to the context in which it occurs, thus forming synchronized population codes. This coordination involves contextual field (CF) connections that link processors within and between cortical regions. The effects of CF connections are distinguished from those mediating receptive field (RF) input; it is shown (...) how CFs can guide both learning and processing without becoming confused with the transmission of RF information. Simulations explore the capabilities of networks built from local processors with both RF and CF connections. Physiological evidence for synchronization, CFs, and plasticity of the RF and CF connections is described. Coordination via CFs is related to perceptual grouping, the effects of context on contrast sensitivity, amblyopia, implicit influences of color in achromotopsia, object and word perception, and the discovery of distal environmental variables and their interactions through self-organization. Cortical computation could thus involve the flexible evaluation of relations between input signals by locally specialized but adaptive processors whose activity is dynamically associated and coordinated within and between regions through specialized contextual connections. Key Words: cell assemblies; cerebral cortex; context; coordination; dynamic binding; epistemology; functional specialization; learning; neural coding; neural computation; neuropsychology; object recognition; perception; reading; self-organization; synaptic plasticity; synchronization. (shrink)

The neural coding metaphor is so ubiquitous that we tend to forget its metaphorical nature. What do we mean when we assert that neurons encode and decode? What kind of causal and representational model of the brain does the metaphor entail? What lies beneath the neural coding metaphor, I argue, is a bureaucratic model of the brain.

Sustained neural activity during the delay phase of spatial working memory tasks is compelling evidence for the neural correlate of active storage and maintenance of spatial information, however, it does not provide insight into specific mechanisms of spatial coding. This activity may reflect a range of processes, such as maintenance of a stimulus position or a prepared motor response plan. The aim of our study was to examine neural evidence for the use of different coding (...) strategies, depending on the characteristics and demands of a spatial working memory task. Thirty-one and 44 participants performed a spatial working memory task while we measured their brain activity using fMRI in two separate experiments. Participants were asked to remember the position of a briefly presented target stimulus and, after a delay period, to use a joystick to indicate either the position of the remembered target or an indicated non-matching location. The task was designed so that the predictability of the response could be manipulated independently of task difficulty and memory retrieval process. We were particularly interested in contrasting conditions in which participants could use prospective coding of the motor response or had to rely on retrospective sensory information. Prospective motor coding was associated with activity in somatomotor, premotor, and motor cortices and increased integration of brain activity with and within the somatomotor network. In contrast, retrospective sensory coding was associated with increased activity in parietal regions and increased functional connectivity with and within secondary visual and dorsal attentional networks. The observed differences in activation levels, dynamics of differences over trial duration, and integration of information within and between brain networks provide compelling evidence for the use of complementary spatial working memory strategies optimized to meet task demands. (shrink)

Pointing to similarities between challenges encountered in today's neural coding and twentieth-century behaviorism, we draw attention to lessons learned from resolving the latter. In particular, Perceptual Control Theory posits behavior as a closed-loop control process with immediate and teleological causes. With two examples, we illustrate how these ideas may also address challenges facing current neural coding paradigms.

Both distributed coding, with its implication of neural reuse, and more specialized function have been recognized since the beginning of brain science. A controversy over imageless thought threw introspection into disrepute as a scientific method, making more objective methods dominate. It is known in information science that one element, such as a bit in a computer, can participate in coding many independent states; in this commentary, an example is given.

Recent computer simulations of evolving neural networks have shown that population-level behavioral asymmetries can arise without social interactions. Although these models are quite limited at present, they support the hypothesis that social pressures can be sufficient but are not necessary for population lateralization to occur, and they provide a framework for further theoretical investigation of this issue.

Brette presents arguments that query the existence of the neural code. However, he has neglected certain evidence that could be viewed as proof that a neural code operates in the brain. Albeit these proofs show a link between neural activity and cognition, we discuss why they fail to demonstrate the existence of an invariant neural code.

In Posner & Raichle's (1994) book, two essential and strictly related limitations of cognitive neurophysiology are not sufficiently enhanced: (1) The problem of “coding,” namely the capability of a natural brain to redefine its own “basic symbols” as a function of a changing environment; (2) the inadequacy of a Hebbian rule to reckon with complex computational problems such as those solved by real brains.

Two universal functional principles of Grossberg’s Adaptive Resonance Theory decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level, long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are re-visited (...) in this concept paper on the basis of examples drawn from the original code and from some of the most recent related empirical findings on contextual modulation in the brain, highlighting the potential of Grossberg’s pioneering insights and groundbreaking theoretical work for intelligent solutions in the domain of developmental and cognitive robotics. (shrink)

Brains are information processing systems whose operational principles ultimately cannot be understood without resource to information theory. We suggest that understanding how external signals are represented in the brain is a necessary step towards employing further engineering tools to understand the information processing performed by brain circuits during behaviour.

We extend the discussion in the target article about distinctions between extrinsic coding and the alternative we and the target article both favor, intrinsic coding. Central to our thinking about intrinsic coding is population coding and the concept of high-dimensional neural response spaces.

Two universal functional principles of Grossberg’s Adaptive Resonance Theory [19] decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are (...) re-visited in this concept paper here on the basis of examples drawn from the original code and from some of the most recent related empirical findings on contextual modulation in the brain, highlighting the potential of Grossberg’s pioneering insights and groundbreaking theoretical work for intelligent solutions in the domain of developmental and cognitive robotics. (shrink)

Barlow's concept of the exploitation of environmental statistical regularities may be more plausibly related to brain mechanisms than Shepard's notion of internalisation. In our view, Barlow endorses a bottom-up approach to neural coding and processing, whereas we suggest that feedback interactions in the visual system, as well as chaotic correlation dynamics in the brain, are crucial in exploiting and assimilating environmental regularities. We also discuss the “conceptual tension” between Shepard's ideas of law internalisation and evolutionary adaptation. [Barlow; Shepard].

We argue that Brette's arguments, or some variation on them, work only against the immodest codes imputed by neuroscientists to the signals they study; they do not tell against “modest” codes, which may be learned by neurons themselves. Still, caution is warranted: modest neural codes likely lead to only modest explanatory gains.

Tsuda's article suggests several plausible concepts of neurodynamic representation and processing, with a thoughtful discussion of their neurobiological grounding and formal properties. However, Tsuda's theory leads to a holistic view of brain functions and to the controversial conclusion that the “binding problem” is a pseudo-problem. By contrast, we stress the role of chaotic patterns in solving the binding problem, in terms of flexible temporal coding of visual scenes through graded and intermittent synchrony.

Susan Hurley's impressive article about the shared circuit model (SCM) raises two important issues. First, I suggest that the SCM presupposes relational coding rather than translational coding as neural code. Second, the SCM being the basis for self implies that the self may be characterized as format, relational, and embodied and embedded, rather than by specific and isolated higher-order cognitive contents.

The convincing argument that Brette makes for the neural coding metaphor as imposing one view of brain behavior can be further explained through discourse analysis. Instead of a unified view, we argue, the coding metaphor's plasticity, versatility, and robustness throughout time explain its success and conventionalization to the point that its rhetoric became overlooked.

Representation and computation are the best tools we have for explaining intelligent behavior. In our program, we explore the space of representations present in the mind by constraining them to explain data at multiple levels of analysis, from behavioral patterns to neural activity. We argue that this integrated program assuages Brette's worries about the study of the neural code.

Shannon's theory lays the foundation for understanding the flow of information from world into brain: There must be a set of possible messages. Brain structure determines what they are. Many messages convey quantitative facts. It is impossible to consider how neural tissue processes these numbers without first considering how it encodes them.