Artificial life and higher level cognition

The influence of Generalized Anxiety Disorder on Executive Functions in children with ADHD

The present study was aimed at verifying whether the presence of generalized anxiety disorder (GAD) affects executive functions in children with attention-deficit hyperactivity disorder (ADHD). Two groups of children with ADHD were selected for the study according to the presence or absence of GAD. The first group of 28 children with ADHD with GAD (mean age: 9 ± 1.2; males/females: 24/4) was matched for gender, age, IQ, psychiatric comorbidity with a second group of 29 children with ADHD without GAD (mean age: 8.8 ± 0.7; males/females: 26/3). The two groups with ADHD were compared to 28 typically developing children (mean age: 8.3 ± 1.3; males/females: 23/5) on different measures involving processes especially important in inhibitory control such as rule maintenance, stimulus detection, action selection and action execution. Our results indicated that, differently from children with ADHD with GAD, only the group with ADHD without GAD showed a deficit in inhibitory control. Comorbid subgroups should be differentiated, especially, to develop specific and efficient therapeutic interventions in ADHD.

Cyclic Incrementality in Competitive Coevolution: Evolvability through Pseudo-Baldwinian Switching-Genes

Coevolving systems are notoriously difficult to understand. This is largely due to the Red Queen effect that dictates heterospecific fitness interdependence. In simulation studies of coevolving systems, master tournaments are often used to obtain more informed fitness measures by testing evolved individuals against past and future opponents. However, such tournaments still contain certain ambiguities. We introduce the use of a phenotypic cluster analysis to examine the distribution of opponent categories throughout an evolutionary sequence. This analysis, adopted from widespread usage in the bioinformatics community, can be applied to master tournament data. This allows us to construct behavior-based category trees, obtaining a hierarchical classification of phenotypes that are suspected to interleave during cyclic evolution. We use the cluster data to establish the existence of switching-genes that control opponent specialization, suggesting the retention of dormant genetic adaptations, that is, genetic memory. Our overarching goal is to reiterate how computer simulations may have importance to the broader understanding of evolutionary dynamics in general. We emphasize a further shift from a component-driven to an interaction-driven perspective in understanding coevolving systems. As yet, it is unclear how the sudden development of switching-genes relates to the gradual emergence of genetic adaptability. Likely, context genes gradually provide the appropriate genetic environment wherein the switching-gene effect can be exploited.

Mechanisms underpinning inattention and hyperactivity: neurocognitive support for ADHD dimensionality

BACKGROUND

Taxometric and behavioral genetic studies suggest that attention deficit hyperactivity disorder (ADHD) is best modeled as a dimension rather than a category. We extended these analyses by testing for the existence of putative ADHD-related deficits in basic information processing (BIP) and inhibitory-based executive function (IB-EF) in individuals in the subclinical and full clinical ranges. Consistent with the dimensional model, we predicted that ADHD-related deficits would be expressed across the full spectrum, with the degree of deficit linearly related to the severity of the clinical presentation.

METHOD

A total of 1547 children (aged 6-12 years) participated in the study. The Development and Well-Being Assessment (DAWBA) was used to classify children into groups according to levels of inattention and hyperactivity independently: (1) asymptomatic, (2) subthreshold minimal, (3) subthreshold moderate and (4) clinical ADHD. Neurocognitive performance was evaluated using a two-choice reaction time task (2C-RT) and a conflict control task (CCT). BIP and IB-EF measures were derived using a diffusion model (DM) for decomposition of reaction time (RT) and error data.

RESULTS

Deficient BIP was found in subjects with minimal, moderate and full ADHD defined in terms of inattention (in both tasks) and hyperactivity/impulsivity dimensions (in the 2C-RT). The size of the deficit increased in a linear manner across increasingly severe presentations of ADHD. IB-EF was unrelated to ADHD.

CONCLUSIONS

Deficits in BIP operate at subclinical and clinical levels of ADHD. The linear nature of this relationship provides support for a dimensional model of ADHD in which diagnostic thresholds are defined in terms of clinical and societal burden rather than representing discrete pathophysiological states.

Specificity of basic information processing and inhibitory control in attention deficit hyperactivity disorder

BACKGROUND

Both inhibitory-based executive functioning (IB-EF) and basic information processing (BIP) deficits are found in clinic-referred attention deficit hyperactivity disorder (ADHD) samples. However, it remains to be determined whether: (1) such deficits occur in non-referred samples of ADHD; (2) they are specific to ADHD; (3) the co-morbidity between ADHD and oppositional defiant disorder/conduct disorder (ODD/CD) has additive or interactive effects; and (4) IB-EF deficits are primary in ADHD or are due to BIP deficits.

METHOD

We assessed 704 subjects (age 6-12 years) from a non-referred sample using the Development and Well-Being Assessment (DAWBA) and classified them into five groups: typical developing controls (TDC; n = 378), Fear disorders (n = 90), Distress disorders (n = 57), ADHD (n = 100), ODD/CD (n = 40) and ADHD+ODD/CD (n = 39). We evaluated neurocognitive performance with a Two-Choice Reaction Time Task (2C-RT), a Conflict Control Task (CCT) and a Go/No-Go (GNG) task. We used a diffusion model (DM) to decompose BIP into processing efficiency, speed-accuracy trade-off and encoding/motor function along with variability parameters.

RESULTS

Poorer processing efficiency was found to be specific to ADHD. Faster encoding/motor function differentiated ADHD from TDC and from fear/distress whereas a more cautious (not impulsive) response style differentiated ADHD from both TDC and ODD/CD. The co-morbidity between ADHD and ODD/CD reflected only additive effects. All ADHD-related IB-EF classical effects were fully moderated by deficits in BIP.

CONCLUSIONS

Our findings challenge the IB-EF hypothesis for ADHD and underscore the importance of processing efficiency as the key specific mechanism for ADHD pathophysiology.

Evolution of cartesian genetic programs for development of learning neural architecture

Although artificial neural networks have taken their inspiration from natural neurological systems, they have largely ignored the genetic basis of neural functions. Indeed, evolutionary approaches have mainly assumed that neural learning is associated with the adjustment of synaptic weights. The goal of this paper is to use evolutionary approaches to find suitable computational functions that are analogous to natural sub-components of biological neurons and demonstrate that intelligent behavior can be produced as a result of this additional biological plausibility. Our model allows neurons, dendrites, and axon branches to grow or die so that synaptic morphology can change and affect information processing while solving a computational problem. The compartmental model of a neuron consists of a collection of seven chromosomes encoding distinct computational functions inside the neuron. Since the equivalent computational functions of neural components are very complex and in some cases unknown, we have used a form of genetic programming known as Cartesian genetic programming (CGP) to obtain these functions. We start with a small random network of soma, dendrites, and neurites that develops during problem solving by repeatedly executing the seven chromosomal programs that have been found by evolution. We have evaluated the learning potential of this system in the context of a well-known single agent learning problem, known as Wumpus World. We also examined the harder problem of learning in a competitive environment for two antagonistic agents, in which both agents are controlled by independent CGP computational networks (CGPCN). Our results show that the agents exhibit interesting learning capabilities.

Are Motor Inhibition and Cognitive Flexibility Dead Ends in ADHD?

Executive dysfunction has been postulated as the core deficit in ADHD, although many deficits in lower order cognitive processes have also been identified. By obtaining an appropriate baseline of lower order cognitive functioning light may be shed on as to whether executive deficits result from problems in lower order and/or higher order cognitive processes. We examined motor inhibition and cognitive flexibility in relation to a baseline measure in 816 children from ADHD and control families. Multiple children in a family were tested in order to examine the familiality of the measures. No evidence was found for deficits in motor inhibition or cognitive flexibility in children with ADHD or their nonaffected siblings: Compared to their baseline speed and accuracy of responding, children with ADHD and their (non)affected siblings were not disproportionally slower or inaccurate when demands for motor inhibition or cognitive flexibility were added to the task. However, children with ADHD and their (non)affected siblings were overall less accurate than controls, which could not be attributed to differences in response speed. This suggests that inaccuracy of responding is characteristic of children having (a familial risk for) ADHD. Motor inhibition and cognitive flexibility as operationalized with mean reaction time were found to be familial. It is concluded that poorer performance on executive tasks in children with ADHD and their (non)affected siblings may result from deficiencies in lower order cognitive processes and not (only) from higher order cognitive processes/executive functions.

Dynamical approaches to cognitive science

Dynamical ideas are beginning to have a major impact on cognitive science, from foundational debates to daily practice. In this article, I review three contrasting examples of work in this area that address the lexical and grammatical structure of language, Piaget's classic 'A-not-B' error, and active categorical perception in an embodied, situated agent. From these three examples, I then attempt to articulate the major differences between dynamical approaches and more traditional symbolic and connectionist approaches. Although the three models reviewed here vary considerably in their details, they share a focus on the unfolding trajectory of a system's state and the internal and external forces that shape this trajectory, rather than the representational content of its constituent states or the underlying physical mechanisms that instantiate the dynamics. In some work, this dynamical viewpoint is augmented with a situated and embodied perspective on cognition, forming a promising unified theoretical framework for cognitive science broadly construed.

The evolutionary language game

We explore how evolutionary game dynamics have to be modified to accomodate a mathematical framework for the evolution of language. In particular, we are interested in the evolution of vocabulary, that is associations between signals and objects. We assume that successful communication contributes to biological fitness: individuals who communicate well leave more offspring. Children inherit from their parents a strategy for language learning (a language acquisition device). We consider three mechanisms whereby language is passed from one generation to the next: (i) parental learning: children learn the language of their parents; (ii) role model learning: children learn the language of individuals with a high payoff; and (iii) random learning: children learn the language of randomly chosen individuals. We show that parental and role model learning outperform random learning. Then we introduce mistakes in language learning and study how this process changes language over time. Mistakes increase the overall efficacy of parental and role model learning: in a world with errors evolutionary adaptation is more efficient. Our model also provides a simple explanation why homonomy is common while synonymy is rare.

The evolution of language

The emergence of language was a defining moment in the evolution of modern humans. It was an innovation that changed radically the character of human society. Here, we provide an approach to language evolution based on evolutionary game theory. We explore the ways in which protolanguages can evolve in a nonlinguistic society and how specific signals can become associated with specific objects. We assume that early in the evolution of language, errors in signaling and perception would be common. We model the probability of misunderstanding a signal and show that this limits the number of objects that can be described by a protolanguage. This "error limit" is not overcome by employing more sounds but by combining a small set of more easily distinguishable sounds into words. The process of "word formation" enables a language to encode an essentially unlimited number of objects. Next, we analyze how words can be combined into sentences and specify the conditions for the evolution of very simple grammatical rules. We argue that grammar originated as a simplified rule system that evolved by natural selection to reduce mistakes in communication. Our theory provides a systematic approach for thinking about the origin and evolution of human language.

Cognition and life: the autonomy of cognition

In this paper we propose a philosophical distinction between biological and cognitive domains based on two conditions that are postulated to obtain a useful characterization of cognition: biological grounding and explanatory sufficiency. According to this, we argue that the origin of cognition in natural systems (cognition as we know it) is the result of the appearance of an autonomous system embedded into another more generic one: the whole organism. This basic idea is complemented by another one: the formation and development of this system, in the course of evolution, cannot be understood but as the outcome of a continuous process of interaction between organisms and environment, between different organisms, and, specially, between the very cognitive organisms. Finally, we address the problem of the generalization of a theory of cognition (cognition as it could be) and conclude that this work would imply a grounding work on the problem of the origins developed in the frame of a confluence between both Artificial Life and an embodied Artificial Intelligence.