Evolutionary psychology and the selectionist theories of neural development are usually regarded as two unrelated theories addressing two logically distinct questions. The focus of evolutionary psychology is the phylogeny of the human mind, whereas the selectionist theories of neural development analyse the ontogeny of the mind. This paper will endeavour to combine these two approaches in the explanation of the human mind. Doing so might help in overcoming some of the criticisms of both theories. The first part of (...) the paper mentions three standard objections to evolutionary psychology and then outlines three philosophical problems evolutionary psychology has to offer a solution to. The second part will try to show that an approach combining evolutionary psychology and the selectionist theory of neural development might overcome some of these objections. (shrink)

How do minds emerge from developing brains? According to the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: minimizes the need for prespecification in accordance with (...) recent neurobiological evidence that the developing cerebral cortex is largely free of domain-specific structure. Instead, the representational properties of cortex are built by the nature of the problem domain confronting it. This uniquely powerful and general learning strategy undermines the central assumption of classical learnability theory, that the learning properties of a system can be deduced from a fixed computational architecture. Neural constructivism suggests that the evolutionary emergence of neocortex in mammals is a progression toward more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in innate, specialized circuits. Human cortical postnatal development is also more extensive and protracted than generally supposed, suggesting that cortex has evolved so as to maximize the capacity of environmental structure to shape its structure and function through constructive learning. (shrink)

Neurocostructivism aims to illustrate and explain cognitive development in relation to the underlying neural structures, with the help of computational models. This enterprise should be grounded both in the evolutionary and in the developmental perspectives. In both, selection plays a fundamental role in the construction of neural and cognitive structures.

Both the target article and the precommentary demonstrate that relatively simple biobehavioral processes have the cumulative effect of fostering behavioral outcomes characteristic of attention-deficit/hyperactivity disorder (ADHD). As such, the articles illustrate a central theme of Darwinian thinking – basic processes acting over time can produce complex and diverse outcomes. In this commentary, we indicate that tracing the action of processes over time can be facilitated by quantitative methods such as artificial neural networks.

Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the ‘dynamic core’). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely (...) recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well. (shrink)

Human knowledge is a phenomenon whose roots extend from the cultural, through the neural and the biological and finally all the way down into the Precambrian “primordial soup.” The present paper reports an attempt at understanding this Greater System of Knowledge (GSK) as a hierarchical nested set of selection processes acting concurrently on several different scales of time and space. To this end, a general selection theory extending mainly from the work of Hull and Campbell is introduced. The perhaps (...) most drastic change from previous similar theories is that replication is revealed as a composite function consisting of what is referred to as memory and synthesis. This move is argued to drastically improve the fit between theory and human-related knowledge systems. The introduced theory is then used to interpret the subsystems of the GSK and their interrelations. This is done to the end of demonstrating some of the new perspectives offered by this view. (shrink)

Increased complexity of representations in development probably results from the differentiation of distributed neural circuits. Axonal differentiation plays a crucial role in this process. Axonal differentiation appears to be achieved in stages, each involving combinations of constructive and regressive events controlled by cell intrinsic and cell extrinsic information.

Since its formal definition over sixty years ago, category theory has been increasingly recognized as having a foundational role in mathematics. It provides the conceptual lens to isolate and characterize the structures with importance and universality in mathematics. The notion of an adjunction (a pair of adjoint functors) has moved to center-stage as the principal lens. The central feature of an adjunction is what might be called “determination through universals” based on universal mapping properties. A recently developed “heteromorphic” theory about (...) adjoints suggests a conceptual structure, albeit abstract and atemporal, for how new relatively autonomous behavior can emerge within a system obeying certain laws. The focus here is on applications in the life sciences (e.g., selectionist mechanisms) and human sciences (e.g., the generative grammar view of language). (shrink)

As the commentaries reveal, cognitive neuroscience's first steps toward a theory of development are marked by vigorous debate, ranging from basic points of definition to the fine details of mechanism. In this Response, we present the neural constructivist position on this broad spectrum of issues, from basic questions such as what sets constructivism apart from other theories (particularly selectionism) to its relation to behavioral theories and to its underlying mechanisms. We conclude that the real value of global theories (...) at this stage of cognitive neuroscience is not just their answers but the new set of research questions they pose. (shrink)

The distinction between receptive field and conceptual field is appealing and heuristically useful. Conceptually, it is more satisfactory to distinguish between information from the environment and from the brain. We emphasize here a selectionist view that considers information transmission within the brain as modulated by a stimulus, rather than information transmission from a stimulus as modulated by the context.

There is evidence for increase, followed by decline, in synaptic numbers during development. Dendrites do not function in isolation. A constructive neuronal process may underpin a selectionist cognitive process. The environment shapes both ontogeny and phylogeny. Phylogenetic natural selection and neural selection are compatible. Natural selection can yield both constructivist and selectionist solution to adaptuive problems.

Quartz & Sejnowski's target article concentrates on the development of a number of neural parameters, especially neuronal processes, in the mammalian brain. Data on learning-related changes in spines and synapses in the developing avian brain are consistent with a constructivist interpretation. The issue of an integration of selectionist and constructivist views is discussed.

Much of our work with enriched experience and training in animals supports the Quartz & Sejnowski (Q&S) thesis that environmental information can interact with pre-existing neural structures to produce new synapses and neural structure. However, substantial data as well as an evolutionary perspective indicate that multiple information-capture systems exist: some are constructivist, some are selectionist, and some may be tightly constrained.

The neural structures of the brain exist to construct information. They do this by creating concepts that relate internal, personal need to external, environmental reality. Meaning is formed in the brain by neural network patterns that traverse these two structures of experience: the visceral nervous system and the somatic nervous system. How exactly does the brain get from constructing information to creating meaning, and what can this process tell us about the nature of experience? This book addresses both (...) of these questions, making an important contribution to both neuroscience and philosophy. (shrink)

Indeterminate art invokes a perceptual dilemma in which apparently detailed and vivid images resist identification. We used event-related fMRI to study visual perception of representational, indeterminate and abstract paintings. We hypothesized increased activation along a gradient of posterior-to-anterior ventral visual areas with increased object resolution, and postulated that object resolution would be associated with visual imagery. Behaviorally, subjects were faster to recognize familiar objects in representational than in both indeterminate and abstract paintings. We found activation within a distributed cortical network (...) that includes visual, parietal, limbic and prefrontal regions. Representational paintings, which depict scenes cluttered with familiar objects, evoked stronger activation than indeterminate and abstract paintings in higher-tier visual areas. Perception of scrambled paintings was associated with imagery-related activation in the precuneus and prefrontal cortex. Finally, representational paintings evoked stronger activation than indeterminate paintings in the temporoparietal junction. Our results suggest that perception of familiar content in art works is mediated by object recognition, memory recall and mental imagery, cognitive processes that evoke activation within a distributed cortical network. (shrink)

Fodor claims that the modularity of mind helps undermine relativism in various forms. I shall show first, that the modular vision of mind provides insufficient support for the rejection of relativism, and second, that an alternative model may, in fact, provide a better empirical response to the relativist challenge.

The neural realization of number in abstract form is implausible, but from this it doesn't follow that numbers are not abstract. Clear definitions of abstraction are needed so they can be applied homogenously to numerical and non-numerical cognition. To achieve a better understanding of the neural substrate of abstraction, productive cognition must be investigated.

Recent decades have witnessed the rapid evolution of robotic applications and their expansion into a variety of spheres with remarkable achievements. This article researches a crucial technique of robot manipulators referred to as visual servoing, which relies on the visual feedback to respond to the external information. In this regard, the visual servoing issue is tactfully transformed into a quadratic programming problem with equality and inequality constraints. Differing from the traditional methods, a gradient-based recurrent neural network for solving the (...) visual servoing issue is newly proposed in this article in the light of the gradient descent method. Then, the stability proof is presented in theory with the pixel error convergent exponentially to zero. Specifically speaking, the proposed method is able to impel the manipulator to approach the desired static point while maintaining physical constraints considered. After that, the feasibility and superiority of the proposed GRNN are verified by simulative experiments. Significantly, the proposed visual servo method can be leveraged to medical robots and rehabilitation robots to further assist doctors in treating patients remotely. (shrink)

Convolutional neural networks, which automatically learn features from raw data to approximate functions, are being increasingly applied to the end-to-end analysis of electroencephalographic signals, especially for decoding brain states in brain-computer interfaces. Nevertheless, CNNs introduce a large number of trainable parameters, may require long training times, and lack in interpretability of learned features. The aim of this study is to propose a CNN design for P300 decoding with emphasis on its lightweight design while guaranteeing high performance, on the effects (...) of different training strategies, and on the use of post-hoc techniques to explain network decisions. The proposed design, named MS-EEGNet, learned temporal features in two different timescales in an efficient and optimized way, and was validated on three P300 datasets. The CNN was trained using different strategies and was compared with several state-of-the-art algorithms. Furthermore, variants of the baseline MS-EEGNet were analyzed to evaluate the impact of different hyper-parameters on performance. Lastly, saliency maps were used to derive representations of the relevant spatio-temporal features that drove CNN decisions. MS-EEGNet was the lightest CNN compared with the tested SOA CNNs, despite its multiple timescales, and significantly outperformed the SOA algorithms. Post-hoc hyper-parameter analysis confirmed the benefits of the innovative aspects of MS-EEGNet. Furthermore, MS-EEGNet did benefit from transfer learning, especially using a low number of training examples, suggesting that the proposed approach could be used in BCIs to accurately decode the P300 event while reducing calibration times. Representations derived from the saliency maps matched the P300 spatio-temporal distribution, further validating the proposed decoding approach. This study, by specifically addressing the aspects of lightweight design, transfer learning, and interpretability, can contribute to advance the development of deep learning algorithms for P300-based BCIs. (shrink)

Behaviorally assessing residual consciousness of acutely comatose patients involves a high rate of false-negatives. That is, long-term behavioral assessment shows that 41% of vegetative state patients in fact have residual consciousness. Nonetheless, surrogates need to remove ventilation before the acute-phase passes away if they want to induce medico-legal death due to pragmatic factors, such as financial costs. So, surrogate decision-making regarding behaviorally nonresponsive acutely comatose patients involves a moral dilemma: should we ignore the chance that patients have residual consciousness for (...) the sake of pragmatic factors? This paper examines whether neural methods can resolve the moral dilemma. Neural methods are used to assess residual consciousness of behaviorally nonresponsive postcomatose patients. For instance, by instructing a vegetative state patient to imagine wiggling all of her toes, conscious- ness is ascribed if brain activities are localized in the supplementary motor area. Since the most extensive application of neural methods has been in chronic population, it is unclear whether such methods can resolve the moral dilemma. I argue that neural methods also involve a high rate of false-negatives because current tasks of neural methods are structurally misguided. Given the argument, there is no significant difference between behavioral and neural methods regarding the moral dilemma. (shrink)

The current study examined whether Callous-Unemotional (CU) traits, a core component of psychopathy, modulate neural responses of participants engaged in a social exchange game. In this task, participants were offered an allocation of money and then given the chance to punish the offerer. Twenty youth participated and responses to both offers and the participant’s punishment (or not) of these offers were examined. Increasingly unfair offers were associated with increased dorsal anterior cingulate cortex (dACC) activity but this responsiveness was not (...) modulated by CU traits. Increasing punishment of unfair offers was associated with increased dACC and anterior insula activity and this activity was modulated by CU traits. Higher CU trait participants showed a weaker association between activity and punishment level. These data suggest that CU traits are associated with appropriate expectations of other individual’s normative behavior but weaker representations of such information when guiding behavior of the self. (shrink)

Do perceptual experiences always inherit the content of their neural correlates? Most scientists and philosophers working on perception say ‘yes’. They hold the view that an experience’s content just is (i.e. is identical to) the content of its neural correlate. This paper presses back against this view, while trying to retain as much of its spirit as possible. The paper argues that type-2 blindsight experiences are plausible cases of experiences which lack the content of their neural correlates. (...) They are not experiences of the stimuli or stimulus properties prompting them, but their neural correlates represent these stimulus properties. The argument doesn’t depend on any special view of what it is for an experience to be of a stimulus or stimulus property. The upshot is that, even assuming there is a deep relationship between experiential content and neural content, that relationship is more complex than simple identity. (shrink)

One problem of interpreting research on subconscious processing is the possibility that participants are weakly conscious of the stimuli. Here, we compared the fMRI BOLD response in healthy adults to clearly visible single letters with the response to letters presented in the absence of any behavioural evidence of visibility . No letter catch trials served as a control condition. Forced-choice responses did not differ from chance when letter-to-background contrast was low, whereas they were almost 100% correct when contrast was high. (...) A comparison of fMRI BOLD signals for supraliminal and subliminal letters with the control trials revealed a signal increase in left BA 37 . Comparison of supraliminal with subliminal letters showed a significant increase in the right inferior frontal gyrus . Finally, a comparison of subliminal with supraliminal letters showed increases in the left middle temporal gyrus and the right extrastriate cortex. (shrink)

This commentary focuses on how the large-scale cortical dynamics described in Nunez's target article are related to various phenomena at different scales, both spatial and temporal, in particular, how the brain dynamics measured with EEG could relate to (i) experience and mental state, (ii) neuromodulatory effects, and (iii) spontaneous firing and autogenerated electromagnetic effects.