The use of the computer metaphor has led to the proposal of mind architecture (Pylyshyn 1984; Newell 1990) as a model of the organization of the mind. The dualist computational model, however, has, since the earliest days of psychological functionalism, required that the concepts mind architecture and brain architecture be remote from each other. The development of both connectionism and neurocomputational science, has sought to dispense with this dualism and provide general models of consciousness – a (...) uniform cognitive architecture –, which is in general reductionist, but which retains the computer metaphor. This paper examines, in the first place, the concepts of mind architecture and brain architecture, in order to evaluate the syntheses which have recently been offered. It then moves on to show how modifications which have been made to classical functionalist mind architectures, with the aim of making them compatible with brain architectures, are unable to resolve some of the most serious problems of functionalism. Some suggestions are given as to why it is not possible to relate mind structures and brain structures by using neurocomputational approaches, and finally the question is raised of the validity of reductionism in a theory which sets out to unite mind and brain architectures. (shrink)

Introduction -- Historical essays -- The humanist brain : Alberti, Vitruvius, and Leonardo -- The enlightened brain : Perrault, Laugier, and Le Roy -- The sensational brain : Burke, Price, and Knight -- The transcendental brain : Kant and Schopenhauer -- The animate brain : Schinkel, Bötticher, and Semper -- The empathetic brain : Vischer, Wölfflin, and Göller -- The gestalt brain : the dynamics of the sensory field -- The neurological brain (...) : Hayek, Hebb, and Neutra -- The phenomenal brain : Merleau-Ponty, Rasmussen, and Pallasmaa -- Neuroscience and architecture -- Anatomy : architecture of the brain -- Ambiguity : architecture of vision -- Metaphor : architecture of embodiment -- Hapticity : architecture of the senses -- Epilogue: The architect's brain. (shrink)

In our contribution we will observe phenomenal architecture of a mind and operational architectonics of the brain and will show their intimate connectedness within a single integrated metastable continuum. The notion of operation of different complexity is the fundamental and central one in bridging the gap between brain and mind: it is precisely by means of this notion that it is possible to identify what at the same time belongs to the phenomenal conscious level and to the (...) neurophysiological level of brain activity organization, and what mediates between them. Implications for linguistic semantics, self-organized distributed computing algorithms, artificial machine consciousness, and diagnosis of dynamic brain diseases will be discussed briefly. (shrink)

What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such system, guided and limited by associative memory, is similar to the stream of consciousness. Minimal requirements for an artificial system that will claim to be conscious were given in form of specific architecture (...) named articon. Nonverbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the inner state flows of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills, when conscious information processing is replaced by subconscious, is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute claims articon’s claims. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human. (shrink)

What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such systems, guided and limited by associative memory, is similar to the stream of consciousness. A specific architecture of an artificial system, termed articon, is introduced that by its very design has to claim (...) being conscious. Non-verbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the flow of inner states of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills — when conscious information processing is replaced by subconscious — is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute articon’s claims that it is conscious. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human. (shrink)

Neuroarchitecture uses neuroscientific tools to better understand architectural design and its impact on human perception and subjective experience. The form or shape of the built environment is fundamental to architectural design, but not many studies have shown the impact of different forms on the inhabitants’ emotions. This study investigated the neurophysiological correlates of different interior forms on the perceivers’ affective state and the accompanying brain activity. To understand the impact of naturalistic three-dimensional (3D) architectural forms, it is essential to (...) perceive forms from different perspectives. We computed clusters of form features extracted from pictures of residential interiors and constructed exemplary 3D room models based on and representing different formal clusters. To investigate human brain activity during three-dimensional perception of architectural spaces, we used a mobile brain/body imaging (MoBI) approach recording the electroencephalogram (EEG) of participants while they naturally walk through different interior forms in virtual reality (VR). The results revealed a strong impact of curvature geometries on activity in the anterior cingulate cortex (ACC). Theta band activity in ACC correlated with specific feature types (rs (14) = 0.525, p = 0.037) and geometry (rs (14) = - 0.579, p = 0.019), providing evidence for a role of this structure in processing architectural features beyond their emotional impact. The posterior cingulate cortex and the occipital lobe were involved in the perception of different room perspectives during the stroll through the rooms. This study sheds new light on the use of mobile EEG and VR in architectural studies and provides the opportunity to study human brain dynamics in participants that actively explore and realistically experience architectural spaces. (shrink)

In the last decades, the rapid growth of functional brain imaging methodologies allowed cognitive neuroscience to address open questions in philosophy and the social sciences. At the same time, novel insights from cognitive neuroscience research have begun to influence various disciplines, leading to a turn to cognition and emotion in the fields of planning and architectural design. Since 2003, the Academy of Neuroscience for Architecture has been supporting ‘neuro-architecture’ as a way to connect neuroscience and the study (...) of behavioral responses to the built environment. Among the many topics related to multisensory perceptual integration and embodiment, the concept of hapticity was recently introduced, suggesting a pivotal role of touch and haptic imagery in architectural appraisal. Arguments have thus risen in favor of the existence of shared cognitive foundations between hapticity and the supramodal functional architecture of the human brain. Precisely, supramodality refers to the functional feature of defined brain regions to process and represent specific information content in a more abstract way, independently of the sensory modality conveying such information to the brain. Here we highlight some commonalities and differences between the concepts of hapticity and supramodality according to the distinctive perspectives of architecture and cognitive neuroscience. This comparison and connection between these two different approaches may lead to novel observations in regard to people-environment relationships, and even provide empirical foundations for a renewed evidence-based design theory. (shrink)

La plupart des projets d’architectures cognitives dans les sciences cognitives et des explications des processus cérébraux dans les neurosciences interprètent l’esprit/cerveau comme réactif : le processus est déclenché par un stimulus et se termine par une réponse. Mais il y a de plus en plus de données laissant penser que le cerveau est endogéniquement actif : des oscillations de l’activité électrochimique à de multiples fréquences ont lieu dans le cerveau même en l’absence de stimuli et ceux-ci servent plutôt à moduler (...) ces oscillations qu’à déclencher l’activité. De plus, des données montrent que cette activité endogène est utilisée dans diverses activités de traitement de l’information. Je m’appuie sur les données issues des enregistrements cellulaires unitaires, de l’EEG et de l’IRMf en situation passive, afin de soutenir la thèse d’un comportement oscillatoire continu dans le cerveau et d’identifier plusieurs manières dont ce comportement peut contribuer à la cognition. Si les sciences cognitives ont pour but de comprendre comment nous effectuons des tâches cognitives, elles ont besoin de développer des architectures cognitives qui intègrent le type d’activité endogène dynamique présentée par le cerveau. (shrink)

La plupart des projets d’architectures cognitives dans les sciences cognitives et des explications des processus cérébraux dans les neurosciences interprètent l’esprit/cerveau comme réactif : le processus est déclenché par un stimulus et se termine par une réponse. Mais il y a de plus en plus de données laissant penser que le cerveau est endogéniquement actif : des oscillations de l’activité électrochimique à de multiples fréquences ont lieu dans le cerveau même en l’absence de stimuli et ceux-ci servent plutôt à moduler (...) ces oscillations qu’à déclencher l’activité. De plus, des données montrent que cette activité endogène est utilisée dans diverses activités de traitement de l’information. Je m’appuie sur les données issues des enregistrements cellulaires unitaires, de l’EEG et de l’IRMf en situation passive, afin de soutenir la thèse d’un comportement oscillatoire continu dans le cerveau et d’identifier plusieurs manières dont ce comportement peut contribuer à la cognition. Si les sciences cognitives ont pour but de comprendre comment nous effectuons des tâches cognitives, elles ont besoin de développer des architectures cognitives qui intègrent le type d’activité endogène dynamique présentée par le cerveau. (shrink)

This book is the integrated presentation of a large body of work on understanding the operation of biological brains as systems.

The overarching guiding principle of Alan Turing’s work was directed towards modelling the human mind as a machine. It is extraordinary that Turing introduced, in his early papers, ideas that are only now beginning to be investigated. Throughout his life, he considered conjectures to be of great importance because they suggest useful lines of research. In my own conjecture, I am asking the question: what is the brain’s geometry? Can it ever be unravelled, or does its complexity defy any (...) form of visual representation? Recent research reveals that the detailed workings of the brain take place in a ‘global workspace’, where conscious contents appear to be disseminated globally to a great multitude of networks throughout the brain that are unconscious. During conscious tasks, neurons contributing to the global workspace enter into a coherent activation pattern by being tightly connected through long axons. Is it possible, therefore, that my proposed geometric pattern (an Islamic latticework) can be envisaged as a useful means of interconnecting multiple long axons in a unified global workspace dedicated to conscious thought? I share and communicate my idea through a process that combines visual imagery with musical performance (i.e. visual music). It is a method that can assist in clarifying concepts that might otherwise remain elusive or esoteric. (shrink)

Standard semantic information processing models—information in; information processed; information out —lend themselves to standard models of the functioning of the brain in terms, e.g., of threshold-switch neurons connected via classical synapses. That is, in terms of sophisticated descendants of McCulloch and Pitts models. I argue that both the cognition and the brain sides of this framework are incorrect: cognition and thought are not constituted as forms of semantic information processing, and the brain does not function in terms (...) of passive input processing units organized as neural nets. An alternative framework is developed that models cognition and thought not in terms of semantic information processing, and, correspondingly, models brain functional processes also not in terms of semantic information processing. As alternative to such models: I outline a pragmatist oriented, interaction based, model of representation; derive from this model a fundamental framework of constraints on how the brain must function; show that such a framework is in fact found in the brain, and develop the outlines of a broader model of how mental processes can be realized within this alternative framework. Part I of this discussion focuses on some criticisms of standard modeling frameworks for representation and cognition, and outlines an alternative interactivist, pragmatist oriented, model. In part II, the focus is on the fact that the brain does not, in fact, function in accordance with standard passive input processing models—e.g., information processing models. Instead, there are multiple endogenously active processes at multiple spatial and temporal scales across multiple kinds of cells. A micro-functional model that accounts for, and even predicts, these multi-scale phenomena in generating emergent representation and cognition is outlined. That is, I argue that the interactivist model of representation outlined offers constraints on how the brain should function that are in fact empirically found, and, in reverse, that the multifarious details of brain functioning entail the pragmatist representational model—a very strong interrelationship. In the sequel paper, starting with part III, this model is extended to address macro-functioning in the CNS. In part IV, I offer a discussion of an approach to brain functioning that has some similarities with, as well as differences from, the model presented here: sometimes called the predictive brain approach. (shrink)

The first paper in this pair (Bickhard in Axiomathes, 2015) developed a model of the nature of representation and cognition, and argued for a model of the micro-functioning of the brain on the basis of that model. In this sequel paper, starting with part III, this model is extended to address macro-functioning in the CNS. In part IV, I offer a discussion of an approach to brain functioning that has some similarities with, as well as differences from, the (...) model presented here: sometimes called the Predictive Brain approach. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

According to Darwinian thinking, organisms are (for the most part) designed by natural selection, and so are (for the most part) integrated collections of adaptations, where an adaptation is a phenotypic trait that is a specialized response to a particular selection pressure. For animals that make their living in the Arctic, one adaptive problem is how to maintain body temperature above a certain minimum level necessary for survival. Polar bears' thick coats are a response to that selection pressure (surviving in (...) extreme cold). A thick coat makes a positive difference to a polar bear's fitness, since polar bears with very thin coats left fewer offspring than those with thicker coats. The foundational idea ofevolutionary psychologyis that brains are no different from any other organ with an evolutionary function, insofar as brains too are systems shaped by natural selection to solve adaptive problems. Thus brains have a particular functional organization because their behavioural effects tend, or once tended, to help maintain or increase the fitness of organisms with those brains. Prominent evolutionary psychologists (for example: Cosmides and Tooby, 1987; Cosmides and Tooby, 1994 and Symons, 1992) have endorsed the view that the last time any significant modifications were made by natural selection to the human brain's functional architecture, we were hunter-gatherers, inhabiting a world quite different from that which we now inhabit. That world was the Pleistocene epoch, between about 2 million years ago and 10 thousand years ago. On this view, then, the Pleistocene constitutes what evolutionary psychologists often call ourenvironment of evolutionary adaptedness(or EEA), and the information- processing structure and organization of our present-day cognitive architecture is no different from that of our recent huntergatherer ancestors. (shrink)

The notion that the mind is a physical symbol system (Newell) with a determinate functional architecture (Pylyshyn) provides a compelling conception of the relation of cognitive inquiry to neuroscience inquiry: cognitive inquiry explores the activity within the symbol system while neuroscience explains how the symbol system is realized in the brain. However, the view the the mind is a physical symbol system is being challenged today by researchers in artificial intelligence who propose that the mind is a connectionist (...) system and not simply a rule processing system. I describe this challenge and offer evidence that indicates the challenge may be well motivated. I then turn to the question of how such changes in the conception of the activity of the mind will affect our understanding of the relation of neuroscience to cognitive inquiry and sketch a framework in which the cognitive system consists of several levels and in which both neuroscience and cognitive science can make contributions at several of these levels. (shrink)

The notion that the mind is a physical symbol system with a determinate functional architecture provides a compelling conception of the relation of cognitive inquiry to neuroscience inquiry: cognitive inquiry explores the activity within the symbol system while neuroscience explains how the symbol system is realized in the brain. However, the view the the mind is a physical symbol system is being challenged today by researchers in artificial intelligence who propose that the mind is a connectionist system and (...) not simply a rule processing system. I describe this challenge and offer evidence that indicates the challenge may be well motivated. I then turn to the question of how such changes in the conception of the activity of the mind will affect our understanding of the relation of neuroscience to cognitive inquiry and sketch a framework in which the cognitive system consists of several levels and in which both neuroscience and cognitive science can make contributions at several of these levels. (shrink)

While some philosophers have assumed that there are only two options for characterizing the ontological status of mental models in cognitive information processing psychology--treating them as nearly autonomous from theories of brain activity (Putnam 1975 and Fodor 1974) or eliminating them in favor of neuroscience accounts (Churchland 1979)-- cognitive scientists have often tacitly assumed a third option. This involves treating the mental models as systems of rules and representations that are instantiated in the nervous system much in the way (...) computer programs are instantiated in computers. While this seems to be the position of those endorsing the autonomy of psychology, it, in fact is consistent with a much weaker interpretation if one recognizes that the vehicle in which mental processes or computer programs are instantiated may limit and constrain what kinds of mental processes or computer programs can be instantiated. (shrink)

In discussions regarding models of cognition, the very mention of “computationalism” often incites reactions against the insufficiency of the Turing machine model, its abstractness, determinism, the lack of naturalist foundations, triviality and the absence of clarity. None of those objections, however, concerns models based on natural computation or computing nature, where the model of computation is broader than symbol manipulation or conventional models of computation. Computing nature consists of physical structures that form layered computational architecture, with computation processes ranging (...) from quantum to chemical, biological/cognitive and social-level computation. It is argued that, on the lower levels of information processing in the brain, finite automata or Turing machines may still be adequate models, while, on the higher levels of whole-brain information processing, natural computing models are necessary. A layered computational architecture of the mind based on the intrinsic computing of physical systems avoids objections against early versions of computationalism in the form of abstract symbols manipulation. (shrink)

b>: In this article I outline, apply, and defend a theory of natural representation. The main consequences of this theory are: i) representational status is a matter of how physical entities are used, and specifically is not a matter of causation, nomic relations with the intentional object, or information; ii) there are genuine (brain-)internal representations; iii) such representations are really representations, and not just farcical pseudo-representations, such as attractors, principal components, state-space partitions, or what-have-you;and iv) the theory allows us (...) to sharply distinguish those complex behaviors which are genuinely cognitive from those which are merely complex and adaptive. (shrink)

"Cognitive Architecture" asks how evolving modalities--from bio-politics to "noo-politics"--can be mapped upon the city under contemporary conditions of urbanization and globalization. Noo-politics, most broadly understood as the power exerted over the life of the mind, reconfigures perception, memory and attention, and also implicates potential ways and means by which neurobiological architecture is undergoing reconfiguration. This volume, motivated by theories such as 'cognitive capitalism' and concepts such as 'neural plasticity, ' shows how architecture and urban processes and products (...) commingle to form complex systems that produce novel forms of networks that empower the imagination and constitute the cultural landscape. This volume rethinks the relations between form and forms of communication, calling for a new logic of representation; it examines the manner in which information, with its non-hierarchical and distributed format is contributing both to the sculpting of brain and production of mind. "Cognitive Architecture" brings together renowned specialists in the areas of political and aesthetic philosophy, neuroscience, socio-cultural and architecture theory, visual and spatial theorists and practitioners. (shrink)

The posterior cortex, hippocampus, and prefrontal cortex in the Leabra architecture are specialized in terms of various neural parameters, and thus are predilections for learning and processing, but domain-general in terms of cognitive functions such as face recognition. Also, these areas are not encapsulated and violate Fodorian criteria for modularity. Anderson's terminology obscures these important points, but we applaud his overall message.

This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with the (...) environment, is mediated by affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot. (shrink)

Thomas & Karmiloff- Smith raise the excellent and, in retrospect, obvious point that in a dynamic learning environment where feedback is possible, we should expect networks to adapt to damage by altering details of their behavior. We should therefore not expect that developmental disorders should result in “normal” modules. The implications of this point go much further, since interprocess dependency in the brain does not rely only on learned neural connections. This argues strongly against behavioral and process-related definitions, as (...) opposed to structural and architecture-related definitions, of mental modularity. (shrink)

Compositionality has been a central concept in linguistics and philosophy for decades, and it is increasingly prominent in many other areas of cognitive science. Its status, however, remains contentious. Here, I reassess the nature and scope of the principle of compositionality (Partee, 1995) from the perspective of psycholinguistics and cognitive neuroscience. First, I review classic arguments for compositionality and conclude that they fail to establish compositionality as a property of human language. Next, I state a new competence argument, acknowledging the (...) fact that any competent user of a language L can assign to most expressions in L at least one meaning which is a functiononlyof the meanings of the expression's parts and of its syntactic structure. I then discuss selected results from cognitive neuroscience, indicating that the human brain possesses the processing capacities presupposed by the competence argument. Finally, I outline a language processing architecture consistent with the neuroscience results, where semantic representations may be generated by a syntax‐driven streamandby an “asyntactic” processing stream, jointly or independently. Compositionality is viewed as a constraint on computation in the former stream only. (shrink)

The criterion of computational universality for an architecture should be replaced by the notion of compliancy, where a model built within an architecture is compliant to the extent that the model allows the architecture to determine the processing. The test should be that the architecture does easily – that is, enables a compliant model to do – what people do easily.

Fodor and Pylyshyn (1988) argue that any successful model of cognition must use classical architecture; it must depend upon rule-based processing sensitive to constituent structure. This claim is central to their defense of classical AI against the recent enthusiasm for connectionism. Connectionist nets, they contend, may serve as theories of the implementation of cognition, but never as proper theories of psychology. Connectionist models are doomed to describing the brain at the wrong level, leaving the classical view to account (...) for the mind.This paper considers whether recent results in connectionist research weigh against Fodor and Pylyshyn's thesis. The investigation will force us to develop criteria for determining exactly when a net is capable of systematic processing. Fodor and Pylyshyn clearly intend their thesis to affect the course of research in psychology. I will argue that when systematicity is defined in a way that makes the thesis relevant in this way, the thesis is challenged by recent progress in connectionism. (shrink)

The human brain shows neuroplastic adaptations induced by motor skill training. However, the description of the plastic architecture of the whole-brain network in resting-state is still limited. In the present study, we aimed to detect how motor training affected the density distribution of whole-brain resting-state functional connectivity (FC) brain in fast-ball student-athletes using resting-state functional magnetic resonance imaging (fMRI) data of student-athletes (SA), and non-athlete healthy controls (NC). The voxel-wise data-driven graph theory approach, namely global (...) functional connectivity density (gFCD) mapping was applied. The results showed that the SA group exhibited significantly decreased gFCD in brain regions centered at left triangular part of inferior frontal gyrus (IFG), extending to opercular part of left IFG and middle frontal gyrus (MFG) compared with NC group. The findings supported the idea of an increased neural efficiency of athletes’ brain in the brain regions associated with attentional-motor modulation and executive control. Furthermore, the behavioral results demonstrated that in the SA group, faster executive control reaction time was associated with smaller gFCD values in left IFG. The findings implied that the motor skill training would decrease the numbers of FC in IFG to accelerate the execution control with high attentional demands, and focus the attention to the target detection the athletes are interested in. (shrink)

Cognitive architectures (i.e., theorized blueprints on the structure of the mind) can be used to make predictions about the effect of multiregion brain activity on the systems level. Recent work has connected one high-level cognitive architecture, known as the “Common Model of Cognition,” to task-based functional MRI data with great success. That approach, however, was limited in that it was intrinsically top-down, and could thus only be compared with alternate architectures that the experimenter could contrive. In this paper, (...) we propose a bottom-up method to infer a cognitive architecture directly from brain imaging data itself, overcoming this limitation. Specifically, Granger causality modeling was applied to the same task-based fMRI data to infer a network of causal connections between brain regions based on their functional connectivity. The resulting network shares many connections with those proposed by the Common Model of Cognition but also suggests important additions likely related to the role of episodic memory. This combined top-down and bottom-up modeling approach can be used to help formalize the computational instantiation of cognitive architectures and further refine a comprehensive theory of cognition. (shrink)

The model of parallel architecture for language presented by Jackendoff is a kind of stratificational model in the spirit of Sydney Lamb. It differs from the more usual stratificationalism most importantly in its clear commitment to nativism, though the variety of nativism is greatly modified from what is more usual among Chomskyans. The revised model presents a potential for fruitful discussion with proponents of stratificationalism, and the potential for enrichment via a relational implementation.

Cognitive architectures, like programming languages, make commitments only at the implementation level and have limited explanatory power. Their universality implies that it is hard, if not impossible, to justify them in detail from finite quantities of data. It is more fruitful to focus on particular tasks such as language understanding and propose testable theories at the computational and algorithmic levels.

According to Darwinian thinking, organisms are designed by natural selection, and so are integrated collections of adaptations, where an adaptation is a phenotypic trait that is a specialized response to a particular selection pressure. For animals that make their living in the Arctic, one adaptive problem is how to maintain body temperature above a certain minimum level necessary for survival. Polar bears' thick coats are a response to that selection pressure . A thick coat makes a positive difference to a (...) polar bear's fitness, since polar bears with very thin coats left fewer offspring than those with thicker coats. The foundational idea of evolutionary psychology is that brains are no different from any other organ with an evolutionary function, insofar as brains too are systems shaped by natural selection to solve adaptive problems. Thus brains have a particular functional organization because their behavioural effects tend, or once tended, to help maintain or increase the fitness of organisms with those brains. Prominent evolutionary psychologists have endorsed the view that the last time any significant modifications were made by natural selection to the human brain's functional architecture, we were hunter-gatherers, inhabiting a world quite different from that which we now inhabit. That world was the Pleistocene epoch, between about 2 million years ago and 10 thousand years ago. On this view, then, the Pleistocene constitutes what evolutionary psychologists often call our environment of evolutionary adaptedness , and the information- processing structure and organization of our present-day cognitive architecture is no different from that of our recent huntergatherer ancestors. (shrink)

Human cognition is unique in the way in which it relies on combinatorial (or compositional) structures. Language provides ample evidence for the existence of combinatorial structures, but they can also be found in visual cognition. To understand the neural basis of human cognition, it is therefore essential to understand how combinatorial structures can be instantiated in neural terms. In his recent book on the foundations of language, Jackendoff described four fundamental problems for a neural instantiation of combinatorial structures: the massiveness (...) of the binding problem, the problem of 2, the problem of variables, and the transformation of combinatorial structures from working memory to long-term memory. This paper aims to show that these problems can be solved by means of neural “blackboard” architectures. For this purpose, a neural blackboard architecture for sentence structure is presented. In this architecture, neural structures that encode for words are temporarily bound in a manner that preserves the structure of the sentence. It is shown that the architecture solves the four problems presented by Jackendoff. The ability of the architecture to instantiate sentence structures is illustrated with examples of sentence complexity observed in human language performance. Similarities exist between the architecture for sentence structure and blackboard architectures for combinatorial structures in visual cognition, derived from the structure of the visual cortex. These architectures are briefly discussed, together with an example of a combinatorial structure in which the blackboard architectures for language and vision are combined. In this way, the architecture for language is grounded in perception. Perspectives and potential developments of the architectures are discussed. Key Words: binding; blackboard architectures; combinatorial structure; compositionality; language; dynamic system; neurocognition; sentence complexity; sentence structure; working memory; variables; vision. (shrink)

The article of Finlay et al. is an excellent example of identifying constraints in the development of the brain, and their implications on brain architecture in evolution. Here we further illustrate the importance of constraints by presenting a few examples of how a small number of biophysical mechanisms or even a single life history parameter can have an enormous impact on brain evolution.

_Figure 1. Dendrites and cell bodies of schematic neurons connected by dendritic-dendritic gap junctions form a laterally connected input_ _layer (“dendritic web”) within a neurocomputational architecture. Dendritic web dynamics are temporally coupled to gamma synchrony_ _EEG, and correspond with integration phases of “integrate and fire” cycles. Axonal firings provide input to, and output from, integration_ _phases (only one input, and three output axons are shown). Cell bodies/soma contain nuclei shown as black circles; microtubule networks_ _pervade the cytoplasm. According to (...) the Orch OR theory, gamma EEG-synchronized integration phases include quantum computations in_ _microtubule networks which culminate with conscious moments. Insert closeup shows a gap junction through which microtubule quantum_ _states entangle among different neurons, enabling macroscopic quantum states in dendritic webs extending throughout cortex and other_ _brain regions._. (shrink)

Despite its computational elegancy, Jackendoff's proposal to reconcile competing approaches by postulating a parallel architecture for phonological, syntactic, and semantic modules is disappointing. We argue that it is a pragmatic version of the leading module which Jackendoff would probably prefer, but which he does not explicitly acknowledge. This internal conflict leads to several shortcomings and even distortions of information presented in the book.

Theories of intelligence can be of use to neuroscientists if they: 1. Provide illuminating suggestions about the functional architecture of neural systems; 2. Suggest specific models of processing that neural circuits might implement. The objective of our session was to stand back and consider the prospects for this interdisciplinary exchange.

Quantum probability (QP) theory provides an alternative account of empirical phenomena in decision making that classical probability (CP) theory cannot explain. Cognitive architectures combine probabilistic mechanisms with symbolic knowledge-based representations (e.g., heuristics) to address effects that motivate QP. They provide simple and natural explanations of these phenomena based on general cognitive processes such as memory retrieval, similarity-based partial matching, and associative learning.

We (Patterson & Plaut, 2009) argued that cognitive neuropsychology has had a limited impact on cognitive science due to a nearly exclusive reliance on (a) single‐case studies, (b) dissociations in cognitive performance, and (c) shallow, box‐and‐arrow theorizing, and we advocated adopting a case‐series methodology, considering associations as well as dissociations, and employing explicit computational modeling in studying “how the brain does its cognitive business.” In reply, Coltheart (2010) claims that our concern is misplaced because cognitive neuropsychology is concerned only (...) with studying the mind, in terms of its “functional architecture,” without regard to how this is implemented in the brain. In this response, we do not dispute his characterization of cognitive neuropsychology as it has typically been practiced over the last 40 years, but we suggest that our understanding of brain structure and function has advanced to the point where studying the mind without regard to the brain is unwise and perpetuates the field’s isolation. (shrink)

Recent years have seen a gradual convergence of seemingly distant research fields over a single goal: understanding and replicating biological intelligence in artifacts. This work presents a general overview on the origin, the state-of-the-art, scientific challenges and the future of Biologically Inspired Cognitive Architecture (BICA) research. Our perspective decomposes the field into the four principal semantic components associated with the BICA challenge that together call for an integration of efforts of researchers across disciplines. Areas and directions of study where (...) new integrated efforts will be primarily needed are summarized. (shrink)

Already hailed as a masterpiece, Foundations of Language offers a brilliant overhaul of the last thirty-five years of research in generative linguistics and related fields. "Few books really deserve the cliché 'this should be read by every researcher in the field'," writes Steven Pinker, author of The Language Instinct, "but Ray Jackendoff's Foundations of Language does." Foundations of Language offers a radically new understanding of how language, the brain, and perception intermesh. The book renews the promise of early generative (...) linguistics: that language can be a valuable entrée into understanding the human mind and brain. The approach is remarkably interdisciplinary. Behind its innovations is Jackendoff's fundamental proposal that the creativity of language derives from multiple parallel generative systems linked by interface components. This shift in basic architecture makes possible a radical reconception of mental grammar and how it is learned. As a consequence, Jackendoff is able to reintegrate linguistics with philosophy of mind, cognitive and developmental psychology, evolutionary biology, neuroscience, and computational linguistics. Among the major topics treated are language processing, the relation of language to perception, the innateness of language, and the evolution of the language capacity, as well as more standard issues in linguistic theory such as the roles of syntax and the lexicon. In addition, Jackendoff offers a sophisticated theory of semantics that incorporates insights from philosophy of language, logic and formal semantics, lexical semantics of various stripes, cognitive grammar, psycholinguistic and neurolinguistic approaches, and the author's own conceptual semantics. (shrink)

• These ... have now been joined by ... dynamical systems theory which is being used to interpret brain dynamics on the one hand and language and cognition on the other.