Brain and cognitive evolution: forms of modularity and functions of mind

Cognitive-Cultural Looping Mechanism of Urban Space Conceptualization

A crucial point for urban design is the acknowledgement that urban material structures are not only constituting a set of cognitive-cultural affordances that shapes people's behavior and experiential world, but likewise that the design process itself is an expression of cultural conceptualizations possibly evoked by ongoing cultural practices and perceptions, thus forming a dynamic loop. In this paper, we outline a framework for the study of material, cultural and social mechanisms interacting with human cognition, behavior and emotions. We attempt a conceptual model that integrates dynamic interactions between cognitive-cultural affordances and our conceptualization of the environment and provides a few illustrative case examples. The model proposes a set of dynamic relations between cognitive and cultural processes at shorter time scales modifying conceptualizations and environmental affordances on longer timescales, while these - in turn - come to guide and constrain processes at the shorter timescales. The model has important implications for our understanding of the role of environmental design, especially urban design, as bridging between aspects of human situated experience, behavior, social and cultural norms and material culture.

Runaway Social Selection in Human Evolution

Darwin posited that social competition among conspecifics could be a powerful selective pressure. Alexander proposed a model of human evolution involving a runaway process of social competition based on Darwin’s insight. Here we briefly review Alexander’s logic, and then expand upon his model by elucidating six core arenas of social selection that involve runaway, positive-feedback processes, and that were likely involved in the evolution of the remarkable combination of adaptations in humans. We discuss how these ideas fit with the hypothesis that a key life history innovation that opened the door to runaway social selection, and cumulative culture, during hominin evolution was increased cooperation among individuals in small fission-fusion groups.

The Creative Neurons

Creativity generates novel solutions to tasks by processing information. Imagination and mental representations are part of the creative process; we can mull over ideas of our own making, and construct algorithms or scenarios from them. Social scenario-building can be viewed as a human cognitive "super-power" that involves abstraction, meta-representation, time-travel, and directed imaginative thought. We humans have a "theater in our minds" to play out a near-infinite array of social strategies and contingencies. Here we propose an integrative model for why and how humans evolved extraordinary creative abilities. We posit that a key aspect of hominin evolution involved relatively open and fluid social relationships among communities, enabled by a unique extended family structure similar to that of contemporary hunter-gatherer band societies. Intercommunity relationships facilitated the rapid flow of information-"Culture"-that underpinned arms-races in information processing, language, imagination, and creativity that distinguishes humans from other species.

Super-natural fears

Supernatural fears, although common, are not as well-understood as natural fears and phobias (e.g., social, blood, and animal phobias) which are prepared by evolution, such that they are easily acquired through direct experience and relatively immune to cognitive mediation. In contrast, supernatural fears do not involve direct experience but seem to be related to sensory or cognitive biases in the interpretation of stimuli as well as culturally driven cognitions and beliefs. In this multidisciplinary synthesis and collaborative review, we claim that supernatural beliefs are "super natural." That is, they occur spontaneously and are easy to acquire, possibly because such beliefs rest on intuitive concepts such as mind-body dualism and animism, and may inspire fear in believers as well as non-believers. As suggested by psychological and neuroscientific evidence, they tap into an evolutionarily prepared fear of potential impending dangers or unknown objects and have their roots in "prepared fears" as well as "cognitively prepared beliefs," making fear of supernatural agents a fruitful research avenue for social, anthropological, and psychological inquires.

The hierarchically mechanistic mind: an evolutionary systems theory of the human brain, cognition, and behavior

The purpose of this review was to integrate leading paradigms in psychology and neuroscience with a theory of the embodied, situated human brain, called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that functions to minimize the entropy of our sensory and physical states via action-perception cycles generated by hierarchical neural dynamics. First, we review the extant literature on the hierarchical structure of the brain. Next, we derive the HMM from a broader evolutionary systems theory that explains neural structure and function in terms of dynamic interactions across four nested levels of biological causation (i.e., adaptation, phylogeny, ontogeny, and mechanism). We then describe how the HMM aligns with a global brain theory in neuroscience called the free-energy principle, leveraging this theory to mathematically formulate neural dynamics across hierarchical spatiotemporal scales. We conclude by exploring the implications of the HMM for psychological inquiry.

The hierarchically mechanistic mind: A free-energy formulation of the human psyche

This article presents a unifying theory of the embodied, situated human brain called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that actively minimises the decay of our sensory and physical states by producing self-fulfilling action-perception cycles via dynamical interactions between hierarchically organised neurocognitive mechanisms. This theory synthesises the free-energy principle (FEP) in neuroscience with an evolutionary systems theory of psychology that explains our brains, minds, and behaviour by appealing to Tinbergen's four questions: adaptation, phylogeny, ontogeny, and mechanism. After leveraging the FEP to formally define the HMM across different spatiotemporal scales, we conclude by exploring its implications for theorising and research in the sciences of the mind and behaviour.

What Do Evolutionary Models Teach Us About Sensitive Periods in Psychological Development?

Abstract. Sensitive periods in development are widespread in nature. Many psychologists and biologists regard sensitive periods as byproducts of developmental processes. Although this view may be correct in some cases, it is unlikely to be the whole story. There is large variation in sensitive periods (a) between species in the same trait ( Beecher & Brenowitz, 2005 ), (b) between individuals of the same species ( Frankenhuis, Panchanathan, & Belsky, 2016 ), and (c) between different traits within a single individual ( Zeanah, Gunnar, McCall, Kreppner, & Fox, 2011 ). In this article, we discuss recent insights provided by formal models of the evolution of sensitive periods. These models help to identify the conditions in which sensitive periods are likely to evolve, and make predictions about the factors that affect their development. We conclude by discussing future directions for empirical research.

The evolution of general intelligence

The presence of general intelligence poses a major evolutionary puzzle, which has led to increased interest in its presence in nonhuman animals. The aim of this review is to critically evaluate this question and to explore the implications for current theories about the evolution of cognition. We first review domain-general and domain-specific accounts of human cognition in order to situate attempts to identify general intelligence in nonhuman animals. Recent studies are consistent with the presence of general intelligence in mammals (rodents and primates). However, the interpretation of a psychometric g factor as general intelligence needs to be validated, in particular in primates, and we propose a range of such tests. We then evaluate the implications of general intelligence in nonhuman animals for current theories about its evolution and find support for the cultural intelligence approach, which stresses the critical importance of social inputs during the ontogenetic construction of survival-relevant skills. The presence of general intelligence in nonhumans implies that modular abilities can arise in two ways, primarily through automatic development with fixed content and secondarily through learning and automatization with more variable content. The currently best-supported model, for humans and nonhuman vertebrates alike, thus construes the mind as a mix of skills based on primary and secondary modules. The relative importance of these two components is expected to vary widely among species, and we formulate tests to quantify their strength.

Cognitive and brain systems underlying early mathematical development

We review current debate regarding the core competencies that support early mathematics learning, focusing on the contributions of the inherent system for representing approximate magnitudes, and domain-general systems that facilitate learning across academic domains. The latter include the executive control system that enables explicit processing of quantitative symbols, such as Arabic numerals, and the logical problem-solving abilities (intelligence) that facilitate learning the relations among numerals. The neural systems that underlie these abilities, as related to mathematical learning, are also discussed, albeit briefly. We place the contributions of inherent quantitative abilities and domain-general mechanisms in an evolutionary context and provide some discussion as to how they interact during the learning of evolutionarily novel mathematics.

Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials

Creative thinking is arguably the pinnacle of cerebral functionality. Like no other mental faculty, it has been omnipotent in transforming human civilizations. Probing the neural basis of this most extraordinary capacity, however, has been doggedly frustrated. Despite a flurry of activity in cognitive neuroscience, recent reviews have shown that there is no coherent picture emerging from the neuroimaging work. Based on this, we take a different route and apply two well established paradigms to the problem. First is the evolutionary framework that, despite being part and parcel of creativity research, has no informed experimental work in cognitive neuroscience. Second is the emerging prediction framework that recognizes predictive representations as an integrating principle of all cognition. We show here how the prediction imperative revealingly synthesizes a host of new insights into the way brains process variation-selection thought trials and present a new neural mechanism for the partial sightedness in human creativity. Our ability to run offline simulations of expected future environments and action outcomes can account for some of the characteristic properties of cultural evolutionary algorithms running in brains, such as degrees of sightedness, the formation of scaffolds to jump over unviable intermediate forms, or how fitness criteria are set for a selection process that is necessarily hypothetical. Prospective processing in the brain also sheds light on how human creating and designing - as opposed to biological creativity - can be accompanied by intentions and foresight. This paper raises questions about the nature of creative thought that, as far as we know, have never been asked before.

Concept learning set-size functions for Clark's nutcrackers

Same/Different abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana) was tested with novel stimuli following learning of training set expansion (8, 16, 32, 64, 128, 256, 512, and 1024 picture items). The resulting set-size function was compared to those from rhesus monkeys (Macaca mulatta), capuchin monkeys (Cebus apella), and pigeons (Columba livia). Nutcrackers showed partial concept learning following initial eight-item set learning, unlike the other species (Magnotti, Katz, Wright, & Kelly, 2015). The mean function for the nutcrackers' novel-stimulus transfer increased linearly as a function of the logarithm of training set size, which intersected its baseline function at the 128-item set size. Thus, nutcrackers on average achieved full concept learning (i.e., transfer statistically equivalent to baseline performance) somewhere between set sizes of 64 to 128 items, similar to full concept learning by monkeys. Pigeons required a somewhat larger training set (256 items) for full concept learning, but results from other experiments (initial training and transfer with 32- and 64-item set sizes) suggested carryover effects with smaller set sizes may have artificially prolonged the pigeon's full concept learning. We find it remarkable that these diverse species with very different neural architectures can fully learn this same/different abstract concept, and (at least under some conditions) do so with roughly similar sets sizes (64-128 items) and numbers of training exemplars, despite initial concept learning advantages (nutcrackers), learning disadvantages (pigeons), or increasing baselines (monkeys).

Use of a modified version of the switching verbal fluency test for the assessment of cognitive flexibility

Objective

Verbal fluency tests are widely used for the assessment of executive functions. However, traditional versions of the test depend on several cognitive factors beyond these components. The aim of this study was to evaluate the associations of a modified version of the verbal fluency with specific measures of executive functions.

Methods

Sixty adults were evaluated using traditional versions of verbal fluency (animals/fruits) and a modified condition where subjects must switch between animals and fruits. Processing speed, semantic abilities, psychiatric symptoms and executive functions were also assessed.

Results

Partial correlations between the verbal fluency tests and measures of executive functions, controlled for demographic, cognitive and psychiatric symptoms, suggest that cognitive flexibility has 9% shared variance with the verbal fluency test – category animals, 2 % with category fruits, 8% with total words in switching condition, and 20% with total correct word-pairs produced in switching condition. The other aspects of executive functions during the task had shared variance of between 1% and 7% with the verbal fluency tasks.

Conclusion

The results suggest that correct word-pairs produced in switching verbal fluency may be a more specific measure for evaluating cognitive flexibility compared to other versions of verbal fluency.

Superior pattern processing is the essence of the evolved human brain

Humans have long pondered the nature of their mind/brain and, particularly why its capacities for reasoning, communication and abstract thought are far superior to other species, including closely related anthropoids. This article considers superior pattern processing (SPP) as the fundamental basis of most, if not all, unique features of the human brain including intelligence, language, imagination, invention, and the belief in imaginary entities such as ghosts and gods. SPP involves the electrochemical, neuronal network-based, encoding, integration, and transfer to other individuals of perceived or mentally-fabricated patterns. During human evolution, pattern processing capabilities became increasingly sophisticated as the result of expansion of the cerebral cortex, particularly the prefrontal cortex and regions involved in processing of images. Specific patterns, real or imagined, are reinforced by emotional experiences, indoctrination and even psychedelic drugs. Impaired or dysregulated SPP is fundamental to cognitive and psychiatric disorders. A broader understanding of SPP mechanisms, and their roles in normal and abnormal function of the human brain, may enable the development of interventions that reduce irrational decisions and destructive behaviors.

The evolution of self-control

Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.

The nature of thinking, shallow and deep

Because the criteria for success differ across various domains of life, no single normative standard will ever work for all types of thinking. One method for dealing with this apparent dilemma is to propose that the mind is made up of a large number of specialized modules. This review describes how this multi-modular framework for the mind overcomes several critical conceptual and theoretical challenges to our understanding of human thinking, and hopefully clarifies what are (and are not) some of the implications based on this framework. In particular, an evolutionarily informed "deep rationality" conception of human thinking can guide psychological research out of clusters of ad hoc models which currently occupy some fields. First, the idea of deep rationality helps theoretical frameworks in terms of orienting themselves with regard to time scale references, which can alter the nature of rationality assessments. Second, the functional domains of deep rationality can be hypothesized (non-exhaustively) to include the areas of self-protection, status, affiliation, mate acquisition, mate retention, kin care, and disease avoidance. Thus, although there is no single normative standard of rationality across all of human cognition, there are sensible and objective standards by which we can evaluate multiple, fundamental, domain-specific motives underlying human cognition and behavior. This review concludes with two examples to illustrate the implications of this framework. The first example, decisions about having a child, illustrates how competing models can be understood by realizing that different fundamental motives guiding people's thinking can sometimes be in conflict. The second example is that of personifications within modern financial markets (e.g., in the form of corporations), which are entities specifically constructed to have just one fundamental motive. This single focus is the source of both the strengths and flaws in how such entities behave.

Understanding the emergence of modularity in neural systems

Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when, and how they emerge. It is a natural assumption that modularity offers some form of computational advantage, and hence evolution by natural selection has translated those advantages into the kind of modular neural structures familiar to cognitive scientists. However, simulations of the evolution of simplified neural systems have shown that, in many cases, it is actually non-modular architectures that are most efficient. In this paper, the relevant issues are discussed and a series of simulations are presented that reveal crucial dependencies on the details of the learning algorithms and tasks that are being modelled, and the importance of taking into account known physical brain constraints, such as the degree of neural connectivity. A pattern is established which provides one explanation of why modularity should emerge reliably across a range of neural processing tasks.

Evolutionary Systems Theory: A Unifying Meta-Theory of Psychological Science

Psychology is a theoretically heterogeneous discipline seeking a single, cohesive framework to unite the subdisciplines. To address this issue, I propose a hierarchical metatheory of psychological science that synthesizes neo-Darwinian selectionist thinking and dynamic systems theory by organizing evolutionary psychology, evolutionary developmental biology, developmental psychobiology, and the subdisciplines of psychology around four specific, interrelated levels of analysis: functional explanations for evolved, species-typical characteristics; explanations for between-groups differences arising from phylogenetic mechanisms; explanations for individual differences resulting from ontogenetic processes; and mechanistic explanations for real-time phenomena, respectively. Informational exchange between these levels advances their integration and facilitates important innovations, and the nonsubstantive metatheories of general selection and self-organization interpenetrate all four levels to promote consilience. I conclude by discussing the implications of this model for theory and research.

MODELLING ROBOTIC COGNITIVE MECHANISMS BY HIERARCHICAL COOPERATIVE COEVOLUTION

Recently, many brain modelling efforts attempt to support cognitive abilities of artificial organisms. The present work introduces a computational framework to address brain modelling, emphasizing on the integrative performance of substructures. Specifically, we present an agent-based representation of brain areas, together with a hierarchical cooperative coevolutionary scheme, which is able to highlight both the speciality of brain areas and their cooperative performance. The inherent ability of coevolutionary methods to design cooperative partial structures supports the design of partial brain models and, at the same time, provides a consistent method to achieve their integration. As a result, the proposed approach proceeds in either an incremental or a compound mode. Furthermore, the performance of the model in lesion conditions is considered during the design process to enforce the reliability of the result. Implemented models are embedded in a robotic platform to support its behavioral capabilities.

Disgust as an adaptive system for disease avoidance behaviour

Disgust is an evolved psychological system for protecting organisms from infection through disease avoidant behaviour. This ‘behavioural immune system’, present in a diverse array of species, exhibits universal features that orchestrate hygienic behaviour in response to cues of risk of contact with pathogens. However, disgust is also a dynamic adaptive system. Individuals show variation in pathogen avoidance associated with psychological traits like having a neurotic personality, as well as a consequence of being in certain physiological states such as pregnancy or infancy. Three specialized learning mechanisms modify the disgust response: the Garcia effect, evaluative conditioning and the law of contagion. Hygiene behaviour is influenced at the group level through social learning heuristics such as ‘copy the frequent’. Finally, group hygiene is extended symbolically to cultural rules about purity and pollution, which create social separations and are enforced as manners. Cooperative hygiene endeavours such as sanitation also reduce pathogen prevalence. Our model allows us to integrate perspectives from psychology, ecology and cultural evolution with those of epidemiology and anthropology. Understanding the nature of disease avoidance psychology at all levels of human organization can inform the design of programmes to improve public health.

Evolutionary functions of early social modulation of hypothalamic-pituitary-adrenal axis development in humans

The hypothalamic-pituitary-adrenal axis (HPAA) is highly responsive to social challenges. Because stress hormones can have negative developmental and health consequences, this presents an evolutionary paradox: Why would natural selection have favored mechanisms that elevate stress hormone levels in response to psychosocial stimuli? Here we review the hypothesis that large brains, an extended childhood and intensive family care in humans are adaptations resulting from selective forces exerted by the increasingly complex and dynamic social and cultural environment that co-evolved with these traits. Variations in the modulation of stress responses mediated by specific HPAA characteristics (e.g., baseline cortisol levels, and changes in cortisol levels in response to challenges) are viewed as phenotypically plastic, ontogenetic responses to specific environmental signals. From this perspective, we discuss relations between physiological stress responses and life history trajectories, particularly the development of social competencies. We present brief summaries of data on hormones, indicators of morbidity and social environments from our long-term, naturalistic studies in both Guatemala and Dominica. Results indicate that difficult family environments and traumatic social events are associated with temporal elevations of cortisol, suppressed reproductive functioning and elevated morbidity. The long-term effects of traumatic early experiences on cortisol profiles are complex and indicate domain-specific effects, with normal recovery from physical stressors, but some heightened response to negative-affect social challenges. We consider these results to be consistent with the hypothesis that developmental programming of the HPAA and other neuroendocrine systems associated with stress responses may facilitate cognitive targeting of salient social challenges in specific environments.

Domain Specific vs Domain General: Implications for Dynamic Assessment

The article responds to the need for evidence-based dynamic assessment. The article is divided into two sections: In Part 1 we examine the scientific answer to the question of how far human mental activities and capabilities are domain general (DG) I domain specific (DS). A highly complex answer emerges from the literature review of domains such as intelligence, traits, emotions and working memory. Thus, for each domain we must base ourselves on the research findings in order to decide how far a domain can be generalized. In Part 2, the conclusions of Part 1 are applied to the field of dynamic assessment (DA). The main conclusion is that assessors tend to over-generalize and generate incorrect rules having relied on the premise that DG is the rule, even though the research literature shows the relationship to be complex. Several solutions to over-generalization are proposed: (A) Replace the concept of “domain” with “task”, (B) Establish a relationship between tasks and concepts as part of a theory of mind, (C) Preserve the principle that the burden of proof of generalizibility of dynamic assessment findings rests with the assessor in fact, (D). Make the dynamic assessor the case manager, (E) Base selection and construction of assessment tasks on four principles: (1) Theory-based tasks, (2) Tasks excelled in by the child assessed, (3) Tasks using standardized instruments, (4) Curriculum-based tasks which the assessed child failed the assessment. Although the solutions demand substantial change from dynamic assessors, the moral and ethical implications of flawed dynamic assessment mean that we must try to change them.

Evolution, Psychology, and a Conflict Theory of Culture

This article develops an evolutionary theory of conflict over the construction of culture that is informed by current knowledge of psychological mechanisms. Psychological mechanisms important for the production of culture include (1) general intelligence (including the ability to engender hypothetical scenarios and means-end reasoning necessary for constructing tools and other exemplars of technology); (2) explicit processing mechanisms (e.g., symbolic representations of the world). Explicit processing allows humans to regulate modular mechanisms in accordance with culturally constructed norms and culturally constructed cost/benefit payoff schedules. It also enables active attempts to construct culture in accordance with explicit perceptions of possible costs and benefits. Because people have different construals of the costs and benefits of particular forms of culture, there is conflict over the construction of culture. Social controls and ideologies are introduced as general cultural categories that are enabled by explicit processing and which are able to regulate and motivate behavior within particular historical contexts, at times in ways that conflict with evolved predispositions. Ideologies are often intimately intertwined with various social controls but are logically and psychologically independent from social controls. Ideologies typically rationalize extant social controls but they also benefit from the power of social controls to enforce ideological conformity in schools or in religious institutions. Because of the control of explicit processing over behavior, this theory predicts that conflicts over culture will often be intense. Discussion deals with the implications of this model for group selection, cultural transmission, gene-culture co-evolution, and the various types of conflicts of interest apparent in conflicts over the construction of culture.

Modern modularity and the road towards a modular psychiatry

We propose to use modules representing functional subunits of the brain as the substrates of pathogenetic factors in mental disorders. This approach is based on scientific evidence from neurophysiology and cognitive psychology regarding the organisation of the human brain in functionally discernible, not necessarily temporally or spatially stable subunits, which are interconnected in complex, often multilayered networks of neuronal circuits. Such a definition would reconcile modern network theories of brain function with localizationist models. Module-based diagnosis and therapy of mental disorders will be the goal of a modular psychiatry, which has the advantage that it is founded in neuroscientific evidence and does not rely on arbitrary definitions of mental disorders based mainly on clinical empiricism.

Sex differences in child-onset, life-course-persistent conduct disorder. A review of biological influences

Sex is widely acknowledged to be an important factor in understanding many aspects of behavior, not the least of which is antisocial behavior. When antisocial behavior manifests itself in the domain of juvenile psychopathology, it often takes the form of a type of conduct disorder (CD) that begins in childhood and is life-course-persistent. There is an overwhelming consensus that there is a massive male preponderance in this type of CD and that biological variables are major influences on this difference. This review built on this consensual scaffolding in an attempt to provide some useful leads for identifying the biological contributions to the predominantly male complexion of life-course-persistent CD by linking it to three different levels of biological mechanisms.

The parent-infant dyad and the construction of the subjective self

Developmental psychology and psychopathology has in the past been more concerned with the quality of self-representation than with the development of the subjective agency which underpins our experience of feeling, thought and action, a key function of mentalisation. This review begins by contrasting a Cartesian view of pre-wired introspective subjectivity with a constructionist model based on the assumption of an innate contingency detector which orients the infant towards aspects of the social world that react congruently and in a specifically cued informative manner that expresses and facilitates the assimilation of cultural knowledge. Research on the neural mechanisms associated with mentalisation and social influences on its development are reviewed. It is suggested that the infant focuses on the attachment figure as a source of reliable information about the world. The construction of the sense of a subjective self is then an aspect of acquiring knowledge about the world through the caregiver's pedagogical communicative displays which in this context focuses on the child's thoughts and feelings. We argue that a number of possible mechanisms, including complementary activation of attachment and mentalisation, the disruptive effect of maltreatment on parent-child communication, the biobehavioural overlap of cues for learning and cues for attachment, may have a role in ensuring that the quality of relationship with the caregiver influences the development of the child's experience of thoughts and feelings.

An evolutionary perspective on learning disability in mathematics

A distinction between potentially evolved, or biologically-primary forms of cognition, and the culturally-specific, or biologically-secondary forms of cognition that are built from primary systems is used to explore mathematical learning disability (MLD). Using this model, MLD could result from deficits in the brain and cognitive systems that support biologically-primary mathematical competencies, or from the brain and cognitive systems that support the modification of primary systems for the creation of secondary knowledge and secondary cognitive competencies. The former include visuospatial long-term and working memory and the intraparietal sulcus, whereas the latter include the central executive component of working memory and the anterior cingulate cortex and lateral prefrontal cortex. Different forms of MLD are discussed as related to each of the cognitive and brain systems.

Theories and measures of consciousness: an extended framework

A recent theoretical emphasis on complex interactions within neural systems underlying consciousness has been accompanied by proposals for the quantitative characterization of these interactions. In this article, we distinguish key aspects of consciousness that are amenable to quantitative measurement from those that are not. We carry out a formal analysis of the strengths and limitations of three quantitative measures of dynamical complexity in the neural systems underlying consciousness: neural complexity, information integration, and causal density. We find that no single measure fully captures the multidimensional complexity of these systems, and all of these measures have practical limitations. Our analysis suggests guidelines for the specification of alternative measures which, in combination, may improve the quantitative characterization of conscious neural systems. Given that some aspects of consciousness are likely to resist quantification altogether, we conclude that a satisfactory theory is likely to be one that combines both qualitative and quantitative elements.

Mechanisms of same/different concept learning in primates and avians

Mechanisms of same/different concept learning by rhesus monkeys, capuchin monkeys, and pigeons were studied in terms of how these species learned the task (e.g., item-specific learning versus relational learning) and how rapidly they learned the abstract concept, as the training set size was doubled. They had similar displays, training stimuli, test stimuli, and contingencies. The monkey species learned the abstract concept at similar rates and more rapidly than pigeons, thus showing a quantitative difference across species. All species eventually showed full concept learning (novel-stimulus transfer equivalent to baseline: 128-item set size for monkeys; 256-item set for pigeons), thus showing a qualitative similarity across species. Issues of stimulus regularity/symmetry, generalization from item pairs, and familiarity processing were not considered to be major factors in the final performances, converging on the conclusion that these species were increasingly controlled by the sample-test relationship (i.e., relational processing) leading to full abstract-concept learning.

Variation and homogeneity in affective responses to physical activity of varying intensities: an alternative perspective on dose-response based on evolutionary considerations

A model for systematic changes in patterns of inter-individual variation in affective responses to physical activity of varying intensities is presented, as a conceptual alternative to the search for a global dose-response curve. It is theorized that trends towards universality will emerge in response to activities that are either generally adaptive, such as moderate walking, or generally maladaptive, such as strenuous running that requires anaerobic metabolism and precludes the maintenance of a physiological steady state. At the former intensity the dominant response will be pleasure, whereas at the latter intensity the dominant response will be displeasure. In contrast, affective responses will be highly variable, involving pleasure or displeasure, when the intensity of physical activity approximates the transition from aerobic to anaerobic metabolism, since activity performed at this intensity entails a trade-off between benefits and risks. Preliminary evidence in support of this model is presented, based on a reanalysis of data from a series of studies.

Modelling brain emergent behaviours through coevolution of neural agents

Recently, many research efforts focus on modelling partial brain areas with the long-term goal to support cognitive abilities of artificial organisms. Existing models usually suffer from heterogeneity, which constitutes their integration very difficult. The present work introduces a computational framework to address brain modelling tasks, emphasizing on the integrative performance of substructures. Moreover, implemented models are embedded in a robotic platform to support its behavioural capabilities. We follow an agent-based approach in the design of substructures to support the autonomy of partial brain structures. Agents are formulated to allow the emergence of a desired behaviour after a certain amount of interaction with the environment. An appropriate collaborative coevolutionary algorithm, able to emphasize both the speciality of brain areas and their cooperative performance, is employed to support design specification of agent structures. The effectiveness of the proposed approach is illustrated through the implementation of computational models for motor cortex and hippocampus, which are successfully tested on a simulated mobile robot.

A much needed macro level view: a commentary on Henriques' "psychology defined"

To develop greater coherence, psychology must develop its macro and integrative approaches to the mind. In this illuminating paper, Henriques (this issue) outlines the kind of thinking that is needed. He skillfully illuminates the levels of emergence of mind from the material world and argues that the recursive self-regulative abilities of self-awareness set us apart from other animals. The interaction between an evolved mind, adapted to pursue strategic goals, while also being phenotypically shaped by both environment and our recently evolved cognitive competencies, is a core focus of psychology.

The Evolution of Domain-General Mechanisms in Intelligence and Learning

For both humans and animals, domain-general mechanisms are fallible but powerful tools for attaining evolutionary goals (e.g., resources) in uncertain, novel environments that were not recurrent features of the environment of evolutionary adaptedness. Domain-general mechanisms interact in complex ways with domain-specific, information-encapsulated modules, most importantly by manipulating information obtained from various modules in attempting to solve novel problems. Mechanisms of general intelligence, particularly the executive functions of working memory, underlie analogical reasoning as well as the decontextualization processes that are central to human thought. Although there is a variety of evolved, special purpose learning devices, learning is also characterized by domain-general mechanisms that are able to achieve evolutionary goals by making novel and serendipitous associations with environmental cues.

Evolutionary psychology and developmental dynamics: comment on Lickliter and Honeycutt (2003)

Evolutionary psychology provides a cogent metatheory for psychological science. It has furnished compelling theories of major domains of human functioning, including mating, parenting, kinship, morality, cooperation, conflict, aggression, and aesthetics. It has produced hundreds of empirical discoveries missed entirely by prior psychologists. Developmental dynamics, properly conceived, can add to the theoretical foundation of evolutionary psychology. But it has not provided alternative theories capable of explaining the many detailed empirical discoveries made by evolutionary' psychologists. Nor has it generated a comparable bounty of new empirical discoveries. By critical scientific standards--theoretical cogency, predictive accuracy, interdisciplinary consistency, and empirical harvest--modern evolutionary psychology fares well compared with alternatives.

General Intelligence as a Domain-Specific Adaptation

General intelligence (g) poses a problem for evolutionary psychology's modular view of the human brain. The author advances a new evolutionary psychological theory of the evolution of general intelligence and argues that general intelligence evolved as a domain-specific adaptation for the originally limited sphere of evolutionary novelty in the ancestral environment. It has accidentally become universally important merely because we now live in an evolutionarily novel world. The available data seem to support the author's contention that intelligent people can solve problems better than less intelligent people only if the problems are evolutionarily novel, and they have no advantage in solving evolutionarily familiar problems. This perspective can also solve some empirical anomalies, such as the "central theoretical problem of human sociobiology" (D. R. Vining, 1986, p. 167) and the geographic distribution of general intelligence throughout the world.

The motivation to control and the origin of mind: Exploring the life–mind joint point in the Tree of Knowledge System

The evolved function of brain, cognitive, affective, conscious-psychological, and behavioral systems is to enable animals to attempt to gain control of the social (e.g., mates), biological (e.g., prey), and physical (e.g., nesting spots) resources that have tended to covary with survival and reproductive outcomes during the species' evolutionary history. These resources generate information patterns that range from invariant to variant. Invariant information is consistent across generations and within lifetimes (e.g., the prototypical shape of a human face) and is associated with modular brain and cognitive systems that coalesce around the domains of folk psychology, folk biology, and folk physics. The processing of information in these domains is implicit and results in automatic bottom-up behavioral responses. Variant information varies across generations and within lifetimes (e.g., as in social dynamics) and is associated with plastic brain and cognitive systems and explicit, consciously driven top-down behavioral responses. The fundamentals of this motivation-to-control model are outlined and links are made to Henriques' (2004) Tree of Knowledge System and Behavioral Investment Theory.

Autism and pervasive developmental disorders

The quantity and quality of research into autism and related conditions have increased dramatically in recent years. Consequently we selectively review key accomplishments and highlight directions for future research. More consistent approaches to diagnosis and more rigorous assessment methods have significantly advanced research, although the boundaries of the 'broader phenotype' remain to be defined and the validity of Asperger's disorder as a discrete syndrome remains controversial. Recent epidemiological studies have shown that Autism Spectrum Disorders are common, but there continues to be debate about the causes of the increase in the frequency with which autism is diagnosed. Psychological research has helped to develop new developmental models for the disorder and there have also been significant advances in the molecular genetics of autism and understanding of the underlying neurobiological processes. Areas important for future research include the study of autism as it first develops, i.e., in infants and very young children, and of specific processes (psychological and neurobiological) which underlie the disorder. Significant challenges lie ahead in evaluating the growing number of treatments for autism and in integrating the results of research into treatment and educational settings.

Peeling the onion: NMDA dysfunction as a unifying model in schizophrenia

N-methyl-d-aspartate receptor (NMDAR) dysfunction plays a crucial role in schizophrenia, leading to impairments in cognitive coordination. NMDAR agonists (e.g., glycine) ameliorate negative and cognitive symptoms, consistent with NMDAR models. However, not all types of cognitive coordination use NMDAR. Further, not all aspects of cognitive coordination are impaired in schizophrenia, suggesting the need for specificity in applying the cognitive coordination construct.

High-frequency synchronisation in schizophrenia: Too much or too little?

Phillips & Silverstein's focus on schizophrenia as a failure of “cognitive coordination” is welcome. They note that a simple hypothesis of reduced Gamma synchronisation subserving impaired coordination does not fully account for recent observations. We suggest that schizophrenia reflects a dynamic compensation to a core deficit of coordination, expressed either as hyper- or hyposynchronisation, with neurotransmitter systems and arousal as modulatory mechanisms.

No blind schizophrenics: Are NMDA-receptor dynamics involved?

Numerous searches have failed to identify a single co-occurrence of total blindness and schizophrenia. Evidence that blindness causes loss of certain NMDA-receptor functions is balanced by reports of compensatory gains. Connections between visual and anterior cingulate NMDA-receptor systems may help to explain how blindness could protect against schizophrenia.