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)

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)

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)

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)

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.

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.

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)

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.

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.

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)

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.

Brain activity determines which relations between objects in the environment are perceived as differences and similarities in colour, smell, sound, etc. According to selectionism, brain activity does not create those relations; it only selects which of them are perceptually available to the subject on a given occasion. In effect, selectionism entails that perceptual experience is diaphanous, i.e. that sameness and difference in the phenomenal character of experience is exhausted by sameness and difference in the perceived items. It has (...) been argued that diaphaneity is undermined by phenomenological considerations and empirical evidence. This paper considers five prominent arguments of this sort and shows that none of them succeeds. (shrink)

I argue that van Fraassen’s selectionist explanation for the success of science is superior to the realists’ explanation. Whereas realists argue that our current theories are successful because they accurately reflect the structure of the world, the selectionist claims that our current theories are successful because unsuccessful theories have been eliminated. I argue that, unlike the explanation proposed by the realist, the selectionist explanation can also account for the failures of once successful theories and the fact that sometimes two competing (...) theories are both equally successful. (shrink)

In his recent 2018 book, Resisting Scientific Realism, K. Brad Wray provides a detailed, full-fledged defense of anti-realism about science. In this paper, I argue against the two main claims that constitute Wray’s positive and novel argument for his position, viz., his suggested Darwinian-selectionist explanation of the success of science and his skepticism about unobservables based on radical theory change. My goal is not wholly negative though. Instead, I aim to identify the type of work that an anti-realist like Wray (...) would need to undertake in order to further substantiate their position, viz., taking a stance on inductive inference and support, and the type of realist and anti-realist positions that seem viable. (shrink)

The dominant view today on evolutionary progress is that it has been thoroughly debunked. Even value-neutral progress concepts are seen to lack important theoretical underpinnings: natural selection provides no rationale for progress, and natural selection need not even be invoked to explain large-scale evolutionary trends. In this paper I challenge this view by analysing how natural selection acts in heterogeneous environments. This not only undermines key debunking arguments, but also provides a selectionist rationale for a pattern of “evolutionary unfolding”, where (...) life radiates across an increased range of exploitation of environmental heterogeneity. (shrink)

Selectionism addresses the process of transition or change. In its evolution, Homo Sapiens has demonstrated such transitions to more hierarchically complex stages of performance at the individual, organizational, cultural, and biological levels. Traditionally, changes in biological, cultural, organizational, and individual behavior have been studied separately, with very little overlap. The current theory integrates selectionism across these realms, while noting that in each, selectionism operates through somewhat different mechanisms. Selectionism is comprised of complex processes in which tasks (...) of greater hierarchical complexity may be selected. Increased stages of performance underlie evolution's dynamics of increased complexity. (shrink)

According to realists, theories are successful because they are true, but according to selectionists, theories are successful because they have gone through a rigorous selection process. Wray claims that the realist and selectionist explanations are rivals to each other. Lee objects that they are instead complementary to each other. In my view, Lee’s objection presupposes that the realist explanation is true, and thus it begs the question against selectionists. By contrast, the selectionist explanation invokes a scientific theory, and thus it (...) is not clear whether it is a realist explanation or an antirealist explanation. Finally, the six new arguments for scientific realism in the literature truly complement the no-miracles argument. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...) 97.50 % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

Evolutionary linguistics is methodologically inspired by evolutionary psychology and the neo-Darwinian, selectionist approach. Language is claimed to have evolved by means of natural selection. The focus therefore lies not on how language evolved, but on finding out why language evolved. This latter question is answered by identifying the functional benefits and adaptive status that language provides, from which in turn selective pressures are deduced. This article analyses five of the most commonly given pressures or reasons why presumably language evolved. I (...) demonstrate that these reasons depend on functional definitions of what language is. To undo this bias, I suggest that scholars move away from the ?why? and ?what for? questions of language evolution, and focus on how language actually evolved. The latter project inquires into the distinct evolutionary mechanisms enabling the evolution of the anatomical and sociocultural traits underlying linguistic behaviour. (shrink)

Human neural organoid research is advancing rapidly. As Greely notes in the target article, this progress presents an “onrushing ethical dilemma.” We can’t rule out the possibility that suff...

An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role (...) of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design. (shrink)

The search for neural correlates of consciousness (or NCCs) is arguably the cornerstone in the recent resurgence of the science of consciousness. The search poses many difficult empirical problems, but it seems to be tractable in principle, and some ingenious studies in recent years have led to considerable progress. A number of proposals have been put forward concerning the nature and location of neural correlates of consciousness. A few of these include.

I identify two versions of the scientific anti-realist’s selectionist explanation for the success of science: Bas van Fraassen’s original and K. Brad Wray’s newer interpretation. In Wray’s version, psycho-social factors internal to the scientific community – viz. scientists’ interests, goals, and preferences – explain the theory-selection practices that explain theory-success. I argue that, if Wray’s version were correct, then science should resemble art. In art, the artwork-selection practices that explain artwork-success appear faddish. They are prone to radical change over time. (...) Theory-selection practices that explain theory-success in science are however not faddish. They are mostly stable; that is, long-lived and consistent over time. This is because scientists (explicitly or implicitly) subscribe to what I will call the testability norm: scientific theories must make falsifiable claims about the external physical world. The testability norm and not psycho-sociology explains the theory-selection practices that explain theory-success in science. Contra Wray, scientific anti-realists can then maintain that the external physical world (as expressed in the testability norm) explains theory-success. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...) is suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

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)

This article explores the domain of legal analysis and its methodologies, emphasising the significance of generalisation in legal systems. It discusses the process of generalisation in relation to legal concepts and the development of ideal concepts that form the foundation of law. The article examines the role of logical induction and its similarities with semantic generalisation, highlighting their importance in legal decision-making. It also critiques the formal-deductive approach in legal practice and advocates for more adaptable models, incorporating fuzzy logic, non-monotonic (...) defeasible reasoning, and artificial intelligence. The potential application of neural networks, specifically deep learning algorithms, in legal theory is also discussed. The article discusses how neural networks encode legal knowledge in their synaptic connections, while the syllogistic model condenses legal information into axioms. The article also highlights how neural networks assimilate novel experiences and exhibit evolutionary progression, unlike the deductive model of law. Additionally, the article examines the historical and theoretical foundations of jurisprudence that align with the basic principles of neural networks. It delves into the statistical analysis of legal phenomena and theories that view legal development as an evolutionary process. The article then explores Friedrich Hayek’s theory of law as an autonomous self-organising system and its compatibility with neural network models. It concludes by discussing the implications of Hayek’s theory on the role of a lawyer and the precision of neural networks. (shrink)

While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example (...) involving research on the information-processing mechanisms mammals employ in navigating their environments. This research was galvanized by the discovery in the 1970s of place cells in the hippocampus. This discovery prompted research in what the activity of these cells represents and how place representations figure in navigation. It also led to the discovery of a host of other types of neurons—grid cells, head-direction cells, boundary cells—that carry other types of spatial information and interact with place cells in the mechanism underlying spatial navigation. As I will try to make clear, the research is explicitly devoted to identifying representations and determining how they are constructed and used in an information processing mechanism. Construals of neural activity as representations are not mere glosses but are characterizations to which neuroscientists are committed in the development of their explanatory accounts. (shrink)

The nature and diversity of moral codes can be understood in terms of a few basic propensities honed by diachronic dialectics between what people do and what they are supposed to do in the culture in question. Many of the moral heuristics presented by Sunstein can be seen as by-products of these processes.

Neural decoding studies seem to show that the “private” experiences of others are more accessible than philosophers have traditionally believed. While these studies have many limitations, they do demonstrate that by capturing patterns in brain activity, we can discover a great deal about what a subject is experiencing. We present a thought experiment about a super-decoder — the Atlantis machine — and argue that given plausible assumptions, an Atlantis machine could one day be built. On the basis of this (...) argument, we then argue for the rejection of robust notions of consciousness, which have generated numerous puzzles, including puzzles about the possibility of philosophical zombies. In light of the Atlantis machine, it can be seen that robust notions of consciousness do not earn their explanatory or descriptive keep. More modest concepts of consciousness are sufficient to account for all phenomena — in both senses of the term. This kind of antirobustness about consciousness is a deflationary approach to conscious experience that differs in important ways from illusionist approaches. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog (...) computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)

A general feature of our moral psychology is that we feel that some moral demands are motivated externally. Stanford explains this feature with an evolutionary account, such that moral externalism was selected for its ability to facilitate prosocial interactions. Alternatively, I argue that a cognitive, non-selectionist account of moral externalism is a more parsimonious explanation.

This book brings together an international group of neuroscientists and philosophers who are investigating how the content of subjective experience is...

Colombo’s (Phenomenology and the Cognitive Sciences, 2013) plea for neural representationalism is the focus of a recent contribution to Phenomenology and Cognitive Science by Daniel D. Hutto and Erik Myin. In that paper, Hutto and Myin have tried to show that my arguments fail badly. Here, I want to respond to their critique clarifying the type of neural representationalism put forward in my (Phenomenology and the Cognitive Sciences, 2013) piece, and to take the opportunity to make a few (...) remarks of general interest concerning what Hutto and Myin have dubbed “the Hard Problem of Content.”. (shrink)

and apply it to various examples of neural plasticity in which input is rerouted intermodally or intramodally to nonstandard cortical targets. In some cases but not others, cortical activity ‘defers’ to the nonstandard sources of input. We ask why, consider some possible explanations, and propose a dynamic sensorimotor hypothesis. We believe that this distinction is important and worthy of further study, both philosophical and empirical, whether or not our hypothesis turns out to be correct. In particular, the question of (...) how the distinction should be explained is linked to explanatory gap issues for consciousness. Comparative and absolute explanatory gaps should be distinguished: why does neural activity in a particular area of cortex have this qualitative expression rather than that, and why does it have any qualitative expression at all? We use the dominance/deference distinction to address the comparative gaps, both intermodal and intramodal. We do so not by inward scrutiny but rather by expanding our gaze to include relations between brain, body and environment. (shrink)

In this paper, I analyze the disruptive impact of Darwinian selectionism for the century-long tradition in which the environment had a direct causative role in shaping an organism’s traits. In the case of humans, the surrounding environment often determined not only the physical, but also the mental and moral features of individuals and whole populations. With its apparatus of indirect effects, random variations, and a much less harmonious view of nature and adaptation, Darwinian selectionism severed the deep imbrication (...) of organism and milieu posited by these traditional environmentalist models. This move had radical implications well beyond strictly biological debates. In my essay, I discuss the problematization of the moral idiom of environmentalism by William James and August Weismann who adopted a selectionist view of the development of mental faculties. These debates show the complex moral discourse associated with the environmentalist-selectionist dilemma. They also well illustrate how the moral reverberations of selectionism went well beyond the stereotyped associations with biological fatalism or passivity of the organism. Rereading them today may be helpful as a genealogical guide to the complex ethical quandaries unfolding in the current postgenomic scenario in which a revival of new environmentalist themes is taking place. (shrink)

Neural reuse theories suggest that, in the course of evolution, a brain structure may acquire or lose a number of cognitive uses while maintaining its cognitive workings (or low-level operations) fixed. This, in turn, suggests that homologous structures may have very different cognitive uses, while sharing the same workings. And this, essentially, is homology thinking applied to brain function.

Despite the ubiquity of knowledge attribution in human social cognition, its associated neural and cognitive mechanisms are poorly documented. A wealth of converging evidence in cognitive neuroscience has identified independent perspective-taking and inhibitory processes for belief attribution, but the extent to which these processes are shared by knowledge attribution isn't presently understood. Here, we present the findings of an EEG study designed to directly address this shortcoming. These findings suggest that belief attribution is not a component process in knowledge (...) attribution, contra a standard attitude taken by philosophers. Instead, observed differences in P3b amplitude indicate that knowledge attribution doesn't recruit the strong self-perspective inhibition characteristic of belief attribution. However, both belief and knowledge attribution were observed to display a late slow wave widely associated with mental state attribution, indicating that knowledge attribution also shares in more general processing of others' mental states. These results provide a new perspective both on how we think about knowledge attribution, as well as Theory of Mind processes generally. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.