Quartz & Sejnowski find flaws in standard theories of neural selection, which they propose to repair by introducing Lamarckian mechanisms for anatomical refinement that are analogous to directed mutation in evolution. The reversal of cause and effect that these mechanisms require is no more plausible in an explanation of cognition than it is in an explanation of evolution.

Page proposes a simple, localist, lateral inhibitory network for implementing a selection process that approximately conforms to the Luce choice rule. I describe another localist neural mechanism for selection in accordance with the Luce choice rule. The mechanism implements an independent race model. It consists of parallel, independent nerve fibers connected to a winner-take-all cluster, which records the winner of the race.

In this chapter, we discuss a selection of current views of the neural correlates of consciousness (NCC). We focus on the different predictions they make, in particular with respect to the role of prefrontal cortex (PFC) during visual experiences, which is an area of critical interest and some source of contention. Our discussion of these views focuses on the level of functional anatomy, rather than at the neuronal circuitry level. We take this approach because we currently understand more (...) about experimental evidence at this coarse level and because these results are appropriate for arbitrating between current theoretical frameworks. We discuss the Two-Visual-Systems Hypothesis (Milner & Goodale 1995; 2006), Local Recurrency (Lamme 2010; Lamme 2006), Higher Order (Lau 2008; Lau & Rosenthal 2011) and Global Workspace theories (Baars 1997; Baars 2005; Dehaene & Naccache 2001; Dehaene 2014). Despite the apparent stark differences between conscious and unconscious perceptual processing, available evidence suggests that their neural substrates must be largely shared. This indicates that the difference in neural activity between conscious and unconscious perceptual processing is likely to be subtle and highly specialized. We argue that current experimental evidence about the involvement of specific activity in prefrontal cortex supports the higher order neural theory of consciousness. In consequence, imaging techniques that focus only on marked differences between conscious and unconscious level of activity are likely to be insensitive to the relevant neural activity patterns that underlie conscious experiences. Finally, it follows from the evidence we discuss that the functional advantages of conscious over unconscious perceptual processing may be more limited than commonly thought. (shrink)

In their account of learning and behavior, the authors define an interactor as emitted behavior that operates on the environment, which excludes Pavlovian learning. A unified neural-network account of the operant-Pavlovian dichotomy favors interpreting neurons as interactors and synaptic efficacies as replicators. The latter interpretation implies that single-synapse change is inherently Lamarckian.

Activity anorexia illustrates selection of behavior at the biological, behavioral, and neural levels. Based on evolutionary history, food depletion increases the reinforcement value of physical activity that, in turn, decreases the reinforcement effectiveness of eating – resulting in activity anorexia. Neural opiates participate in the selection of physical activity during periods of food depletion.

Mainstream teleosemantics is the view that mental representation should be understood in terms of biological functions, which, in turn, should be understood in terms of selection processes. One of the traditional criticisms of teleosemantics is the problem of novel contents: how can teleosemantics explain our ability to represent properties that are evolutionarily novel? In response, some have argued that by generalizing the notion of a selection process to include phenomena such as operant conditioning, and the neural (...) class='Hi'>selection that underlies it, we can resolve this problem. Here, we do four things: we develop this suggestion in a rigorous way through a simple example, we draw on recent neurobiological research to support its empirical plausibility, we defend the move from a host of objections in the literature, and we sketch how the picture can be extended to help us think about more complex “conceptual” representations and not just perceptual ones. (shrink)

In their account of learning and behavior, the authors define an interactor as emitted behavior that operates on the environment, which excludes Pavlovian learning. A unified neural-network account of the operant-Pavlovian dichotomy favors interpreting neurons as interactors and synaptic efficacies as replicators. The latter interpretation implies that single-synapse change is inherently Lamarckian.

A common misunderstanding of the selected effects theory of function is that natural selection operating over an evolutionary time scale is the only functionbestowing process in the natural world. This construal of the selected effects theory conflicts with the existence and ubiquity of neurobiological functions that are evolutionary novel, such as structures underlying reading ability. This conflict has suggested to some that, while the selected effects theory may be relevant to some areas of evolutionary biology, its relevance to neuroscience (...) is marginal. This line of reasoning, however, neglects the fact that synapses, entire neurons, and potentially groups of neurons can undergo a type of selection analogous to natural selection operating over an evolutionary time scale. In the following, I argue that neural selection should be construed, by the selected effect theorist, as a distinct type of function-bestowing process in addition to natural selection. After explicating a generalized selected effects theory of function and distinguishing it from similar attempts to extend the selected effects theory, I do four things. First, I show how it allows one to identify neural selection as a distinct function-bestowing process, in contrast to other forms of neural structure formation such as neural construction. Second, I defend the view from one major criticism, and in so doing I clarify the content of the view. Third, I examine drug addiction to show the potential relevance of neural selection to neuroscientific and psychological research. Finally, I endorse a modest pluralism of function concepts within biology. (shrink)

In the present work, an artificial neural network (ANN) will be developed to estimate the relative rotation and translation of the autonomous mobile robot (AMR). The ANN will work as an iterative closed point, which is commonly used with the singular value decomposition algorithm. This development will provide better resolution for a relative positioning technique that is essential for the AMR localization. The ANN requires a specific architecture, although in the current work a neural architecture search will be (...) adapted to select the best ANN for estimating the relative motion. At the end, these ANNs will be compared with conventional algorithms to check the good performance of adopting an intelligent method for relative positioning estimation. (shrink)

Activity anorexia illustrates selection of behavior at the biological, behavioral, and neural levels. Based on evolutionary history, food depletion increases the reinforcement value of physical activity that, in turn, decreases the reinforcement effectiveness of eating – resulting in activity anorexia. Neural opiates participate in the selection of physical activity during periods of food depletion.

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)

Despite the voluminous literature on biological functions produced over the last 40 years, few philosophers have studied the concept of function as it is used in neuroscience. Recently, Craver (forthcoming; also see Craver 2001) defended the causal role theory against the selected effects theory as the most appropriate theory of function for neuroscience. The following argues that though neuroscientists do study causal role functions, the scope of that theory is not as universal as claimed. Despite the strong prima facie superiority (...) of the causal role theory, the selected effects theory (when properly developed) can handle many cases from neuroscience with equal facility. It argues this by presenting a new theory of function that generalizes the notion of a ‘selection process’ to include processes such as neural selection, antibody selection, and some forms of learning—that is, to include structures that have been differentially retained as well as those that have been differentially reproduced. This view, called the generalized selected effects theory of function, will be defended from criticism and distinguished from similar views in the literature. (shrink)

This article sketches an idealized strategy for the identification of neural correlates of consciousness. The proposed strategy is based on a state space approach originating from the analysis of dynamical systems. The article then focuses on one constituent of consciousness, phenomenal awareness. Several rudimentary requirements for the identification of neural correlates of phenomenal awareness are suggested. These requirements are related to empirical data on selective attention, on completely intrinsic selection and on globally unconscious states. As an example, (...) neuroscientific findings on synchronized γ activity are categorized according to these requirements. (shrink)

Infertility is a global problem affecting 48 to 186 million couples of reproductive age. In Poland, it concerns approx. 1.5 million couples, which amounts to 20% of the population capable of reproducing. One of the factors influencing the incidence of fertility disorders may be lifestyle, understood as a multi-disciplinary accumulation of everyday behaviours and habits. In the study, a group of 201 young adults, students of medical and related faculties, were surveyed in order to check the actual level of knowledge (...) about the impact of lifestyle on reproductive health. The Kohonen network, which is an example of a self-learning neural network, was used to find non-obvious connections between the data. The trained Kohonen neural network formed 4 clusters with different characteristics. Based on analyses of the structure of each cluster, it was found that 2nd year students of Medicine are internally divided into 3 fractions. The first fraction declared a high level of knowledge, but did not have real knowledge. The second fraction was aware of their ignorance, as confirmed by the knowledge test. The last fraction was characterized by a high level of self-confidence regarding their knowledge about reproductive health and obtained a high result in the knowledge test. It was confirmed that people studying at the Medical faculty know more than students of the same year at faculties other than Medicine. Interesting results were obtained for a group of 3rd year students of first-cycle studies in Dietetics. They did not obtain a significantly better result in the knowledge test concerning the influence of diet and lifestyle on reproductive health. It would seem that one could expect at least a few highly knowledgeable students in a group of 3rd year students, but this was not confirmed by the study. In view of the obtained results, it was concluded that the Kohonen neural network is applicable to the analysis of data on the actual state of knowledge about the impact of lifestyle on reproductive health. (shrink)

Theories of binding have recently come into the focus of the consciousness debate. In this review, we discuss the potential relevance of temporal binding mechanisms for sensory awareness. Specifically, we suggest that neural synchrony with a precision in the millisecond range may be crucial for conscious processing, and may be involved in arousal, perceptual integration, attentional selection and working memory. Recent evidence from both animal and human studies demonstrates that specific changes in neuronal synchrony occur during all of (...) these processes and that they are distinguished by the emergence of fast oscillations with frequencies in the gamma-range. (shrink)

This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network and multiple linear regression. The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses (...) were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to develop the model of multiple linear regression with the stepwise regression technique in the SPSS v25 software. The results indicate that the model of trip generation is related to family size and composition, gender, students’ number in the family, workers’ number in the family, and car ownership. The ANN prediction model is more accurate than the MLR predicted model: the average accuracy was 83.72% in the ANN model but only 72.46% in the MLR model. (shrink)

How does the human brain link relational concepts to perceptual experience? For example, a speaker may say “the cup to the left of the computer” to direct the listener's attention to one of two cups on a desk. We provide a neural dynamic account for both perceptual grounding, in which relational concepts enable the attentional selection of objects in the visual array, and for the generation of descriptions of the visual array using relational concepts. In the model, activation (...) in neural populations evolves dynamically under the influence of both inputs and strong interaction as formalized in dynamic field theory. Relational concepts are modeled as patterns of connectivity to perceptual representations. These generalize across the visual array through active coordinate transforms that center the representation of target objects in potential reference objects. How the model perceptually grounds or generates relational descriptions is probed in 104 simulations that systematically vary the spatial and movement relations employed, the number of feature dimensions used, and the number of matching and nonmatching objects. We explain how sequences of decisions emerge from the time‐ and state‐continuous neural dynamics, how relational hypotheses are generated and either accepted or rejected, followed by the selection of new objects or the generation of new relational hypotheses. Its neural realism distinguishes the model from information processing accounts, its capacity to autonomously generate sequences of processing steps distinguishes it from deep neural network accounts. The model points toward a neural dynamic theory of higher cognition. (shrink)

We explored the neural mechanisms allowing humans to report the subjective onset times of conscious events. Magnetoencephalographic recordings of neural oscillations were obtained while human subjects introspected the timing of sensory, intentional, and motor events during a forced choice task. Brain activity was reconstructed with high spatio-temporal resolution. Event-time introspection was associated with specific neural activity at the time of subjective event onset which was spatially distinct from activity induced by the event itself. Different brain regions were (...) selectively recruited for introspection of different event types, e.g., the bilateral angular gyrus for introspection of intention. Our results suggest that event-time introspection engages specific neural networks to assess the contents of consciousness. Subjective event times should therefore be interpreted as the result of complex interactions between introspection and experience networks, rather than as direct reproduction of the individual’s conscious state or as a mere post hoc interpretation. (shrink)

Our model integrates the nativist assumption of prespecified neural structures underpinning basic emotions with the constructionist view that emotions are assembled from psychological constituents. From a dynamic systems perspective, the nervous system self-organizes in different ways at different time scales, in relation to functions served by emotions. At the evolutionary scale, brain parts and their connections are specified by selective pressures. At the scale of development, connectivity is revised through synaptic shaping. At the scale of real time, temporary networks (...) of synchronized activity mediate responses to situations. To the degree that humans share common emotional functions, neural structuration is similar across scales, giving rise to “basic” emotions. However, unique developmental and situational factors select for neural configurations mediating emotional variants. (shrink)

The ontology of social objects and facts remains a field of continued controversy. This situation complicates the life of social scientists who seek to make predictive models of social phenomena. For the purposes of modelling a social phenomenon, we would like to avoid having to make any controversial ontological commitments. The overwhelming majority of models in the social sciences, including statistical models, are built upon ontological assumptions that can be questioned. Recently, however, artificial neural networks have made their way (...) into the social sciences, raising the question whether they can avoid controversial ontological assumptions. ANNs are largely distinguished from other statistical and machine learning techniques by being a representation-learning technique. That is, researchers can let the neural networks select which features of the data to use for internal representation instead of imposing their preconceptions. On this basis, I argue that neural networks can avoid ontological assumptions to a greater degree than common statistical models in the social sciences. I then go on, however, to establish that ANNs are not ontologically innocent either. The use of ANNs in the social sciences introduces ontological assumptions typically in at least two ways, via the input and via the architecture. (shrink)

Violent extremism is often explicitly motivated by commitment to abstract ideals such as the nation or divine law – so-called “sacred” values that are relatively insensitive to material incentives and define our primary reference groups. Moreover, extreme pro-group behavior seems to intensify after social exclusion. This fMRI study explores underlying neural and behavioral relationships between sacred values, violent extremism, and social exclusion. Ethnographic fieldwork and psychological surveys were carried out among young men from a European Muslim community in neighborhoods (...) in and around Barcelona, Spain. Candidates for an fMRI experiment were selected from those who expressed willingness to engage in or facilitate, violence associated with jihadist causes. In the scanner, participants were assessed for their willingness to fight and die for in-group sacred values before and after an experimental manipulation using Cyberball, a toss ball game known to yield strong feelings of social exclusion. Results indicate that neural activity associated with sacred value processing in a sample vulnerable to recruitment into violent extremism shows marked activity in the left inferior frontal gyrus, a region previously associated with sacred values and rule retrieval. Participants also behaviorally expressed greater willingness to fight and die for sacred versus non-sacred values, consistent with previous studies of combatants and noncombatants. The social exclusion manipulation specifically affected non-sacred values, increasing their similarities with sacred values in terms of heightened left inferior frontal activity and greater expressed willingness to fight and die. These findings suggest that sacralization of values interacts with willingness to engage in extreme behavior in populations vulnerable to radicalization. In addition, social exclusion may be a relevant factor motivating violent extremism and consolidation of sacred values. If so, counteracting social exclusion and sacralization of values should figure into policies to prevent radicalization. (shrink)

Recent studies on neural pathways in a broad spectrum of vertebrates suggest that, in addition to migration and an increase in the number of certain select neurons, a significant aspect of neural evolution is a “parcellation” (segregation-isolation) process that involves the loss of selected connections by the new aggregates. A similar process occurs during ontogenetic development. These findings suggest that in many neuronal systems axons do not invade unknown territories during evolutionary or ontogenetic development but follow in their (...) ancestors' paths to their ancestral targets; if the connection is later lost, it reflects the specialization of the circuitry.The pattern of interspecific variability suggests (1) that overlap of circuits is a more common feature in primitive (generalized) than in specialized brain organizations and (2) that most projections, such as the retinal, thalamotelencephalic, corticotectal, and tectal efferent ones, were bilateral in the primitive condition. Specialization of these systems in some vertebrate groups has involved the selective loss of connections, resulting in greater isolation of functions. The parcellation process may also play an important role in cell diversification.The parcellation process as described here is thought to be one of several underlying mechanisms of evolutionary and ontogenetic differentiation. (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)

We propose a neural model of multiattribute-decision processes, based on an attractor neural network with dynamic thresholds. The model may be viewed as a generalization of the elimination by aspects model, whereby simultaneous selection of several aspects is allowed. Depending on the amount of synaptic inhibition, various kinds of scanning strategies may be performed, leading in some cases to vacillations among the alternatives. The model predicts that decisions of a longer time duration exhibit a lower violation of (...) the simple scalability law, as opposed to shorter decisions. Furthermore, the model is suggested as a general attribute-based decision module. Accordingly, various decision strategies are manifested depending on the module's parameters. (shrink)

Over many centuries, the homing pigeon has been selectively bred for returning home from a distant location. As a result of this strong selective pressure, homing pigeons have developed an excellent spatial navigation system. This system passes through the hippocampal formation, which shares many striking similarities to the mammalian hippocampus; there are a host of shared neuropeptides, interconnections, and its role in the storage and manipulation of spatial maps. There are some notable differences as well: there are unique connectivity patterns (...) and spatial encoding strategies. This review summarizes the comparisons between the avian and mammalian hippocampal systems, and the responses of single neurons in several general categories: location and place cells responding in specific areas, path and goal cells responding between goal locations, context-dependent cells that respond before or during a task, and pattern, grid, and boundary cells that increase firing at stable intervals. Head-direction cells, responding to a specific compass direction, are found in mammals and other birds but not to date in pigeons. By studying an animal that evolved under significant adaptive pressure to quickly develop a complex and efficient spatial memory system, we may better understand the comparative neurology of neurospatial systems, and plot new and potentially fruitful avenues of comparative research in the future. (shrink)

O Darwinismo Neural explica o funcionamento do sistema nervosocentral com base em um processo de seleção populacional de gruposneuronais. Três características são compartilhadas entre DN e a teoria daseleção natural: repertórios variados de elementos, cuja fonte de variaçãonão está causalmente relacionada a eventos subseqüentes; interaçãocom o ambiente, permitindo a seleção de variantes favorecidas; e reprodução diferencial e herança de características das variantes.Interpretado como uma forma de epistemologia evolucionista, DN podeser incluído no programa da epistemologia evolucionista de mecanismos, como entendido (...) por Bradie. Este autor caracteriza este programapor enfocar o entendimento da dinâmica das estruturas cognitivas de umaperspectiva evolutiva. Neste artigo, discutimos como o DN foi construídoa partir de uma extensão metafórica da teoria da seleção natural. Osmecanismos propostos por aquela teoria para explicar o desenvolvimentoda dinâmica do SNC também são discutidos.Neural Darwinism explains the functioning of the central nervoussystem on the grounds of a process of populational selection ofneuronal groups. ND and the theory of natural selection share threecharacteristics: varied repertoires of elements, with variation source notbeing causally related to subsequent events; interaction with the environment, allowing for the selection of favored variants; and differential reproduction and heredity of characteristics of the variants. Ifinterpreted as a form of evolutionary epistemology, DN can be included inthe program of the evolutionary epistemology of mechanisms ,according to Bradie. He describes this program as focusing on theunderstanding of the dynamics of cognitive structures from an evolutionaryperspective. In this paper, we address how ND was built from a metaphoricalextension of the theory of natural selection. We also discuss the mechanismsproposed by that theory to explain the development of CNS dynamics. (shrink)

The human brain is the first computer to which all others are compared. Yet we know painfully little about how a brain accomplishes its peculiar computations. In particular, consciousness is at once familiar and mysterious, and needs to be understood both for science and for medicine. Boldly, but gently this book introduces a reader to the neural circuitry that achieves consciousness. This amazing interconnection enables consciousness to flow like a stream, intimately relevant to the outside world; and for this (...) to happen, fundamental cues emerge from mental images to bring forth associated recalls. Alas cues can be inconsistent, causing memory failure; fortunately a subliminal cue editor encourages remembering forgotten items. Furthermore, cues generally address several memories, forcing the brain to make a selection. This necessitates another special circuit whose purpose is subliminal editing. The simplified explanations provided in this book make it clear that neurons do far more than ordinary devices, since a single neuron is capable of remarkably dense combinational and sequential logic. Beginning with their interesting and unexpected logical behavior, the reader will genuinely enjoy Dr. Burger's synthesis of a system for biological consciousness, a system that may someday result in credible artificial consciousness. (shrink)

Activity-dependent processes play an active role in shaping the structure of neuronal circuitry and therefore contribute to neural and cognitive development. Neural constructivism claims to be able to account for increases in the complexity of cognitive representations in terms of directed growth of neurons. This claim is overstated, rests on biased nterpretations of the evidence, and is based on serious misapprehensions of the nature of somatic variation and selection.