Specifying the self for cognitive neuroscience

Cognitive neuroscience investigations of self-experience have mainly focused on the mental attribution of features to the self (self-related processing). In this paper, we highlight another fundamental, yet neglected, aspect of self-experience, that of being an agent. We propose that this aspect of self-experience depends on self-specifying processes, ones that implicitly specify the self by implementing a functional self/non-self distinction in perception, action, cognition and emotion. We describe two paradigmatic cases - sensorimotor integration and homeostatic regulation - and use the principles from these cases to show how cognitive control, including emotion regulation, is also self-specifying. We argue that externally directed, attention-demanding tasks, rather than suppressing self-experience, give rise to the self-experience of being a cognitive-affective agent. We conclude with directions for experimental work based on our framework.     

Intentional concepts in cognitive neuroscience

In this article, I develop an account of the use of intentional predicates in cognitive neuroscience explanations. As pointed out by Maxwell Bennett and Peter Hacker, intentional language abounds in neuroscience theories. According to Bennett and Hacker, the subpersonal use of intentional predicates results in conceptual confusion. I argue against this overly strong conclusion by evaluating the contested language use in light of its explanatory function. By employing conceptual resources from the contemporary philosophy of science, I show that although the use of intentional predicates in mechanistic explanations sometimes leads to explanatorily inert claims, intentional predicates can also successfully feature in mechanistic explanations as tools for the functional analysis of the explanandum phenomenon. Despite the similarities between my account and Daniel Dennett's intentional-stance approach, I argue that intentional stance should not be understood as a theory of subpersonal causal explanation, and therefore cannot be used to assess the explanatory role of intentional predicates in neuroscience. Finally, I outline a general strategy for answering the question of what kind of language can be employed in mechanistic explanations.     

Developmental cognitive neuroscience: progress and potential

Developmental cognitive neuroscience is an evolving field that investigates the relations between neural and cognitive development. Lying at the intersection of diverse disciplines, work in this area promises to shed light on classic developmental questions, mechanisms subserving developmental change, diagnosis and treatment of developmental disorders, and cognitive and neuroscientific topics traditionally considered outside the domain of development. Fundamental questions include: What are the interrelations between developmental changes in the brain (e.g. in connectivity, chemistry, morphology) and developmental changes in children's behavior and cognitive abilities (e.g. representational complexity, ability to sustain selective attention, speed of processing)? Why, and how, is learning enhanced during certain periods in development? How is our knowledge organized, and how does this change with development? We discuss preliminary investigations of such questions and directions for future work.     

Doing cognitive neuroscience: a third way

The “top-down” and “bottom-up” approaches have been thought to exhaust the possibilities for doing cognitive neuroscience. We argue that neither approach is likely to succeed in providing a theory that enables us to understand how cognition is achieved in biological creatures like ourselves. We consider a promising third way of doing cognitive neuroscience, what might be called the “neural dynamic systems” approach, that construes cognitive neuroscience as an autonomous explanatory endeavor, aiming to characterize in its own terms the states and processes responsible for brain-based cognition. We sketch the basic motivation for the approach, describe a particular version of the approach, so-called ‘Dynamic Causal Modeling’ (DCM), and consider a concrete example of DCM. This third way, we argue, has the potential to avoid the problems that afflict the other two approaches.     

Understanding implicit memory. A cognitive neuroscience approach.

Dissociations between implicit and explicit memory have attracted considerable attention in recent memory research. A central issue concerns whether such dissociations require the postulation of separate memory systems or are best understood in terms of different processes operating within a single system. This article presents a cognitive neuroscience approach to implicit memory in general and the systems-processes debate in particular, which draws on evidence from research with brain-damaged patients, neuroimaging techniques, and nonhuman primates. The article illustrates how a cognitive neuroscience orientation can help to supply a basis for postulating memory systems, can provide useful constraints for processing views, and can encourage the use of research strategies that the author refers to as cross-domain hypothesis testing and cross-domain hypothesis generation, respectively. The cognitive neuroscience orientation suggests a complementary role for multiple systems and processing approaches.     

The cognitive neuroscience of creativity

This article outlines a framework of creativity based on functional neuroanatomy. Recent advances in the field of cognitive neuroscience have identified distinct brain circuits that are involved in specific higher brain functions. To date, these findings have not been applied to research on creativity. It is proposed that there are four basic types of creative insights, each mediated by a distinctive neural circuit. By definition, creative insights occur in consciousness. Given the view that the working memory buffer of the prefrontal cortex holds the content of consciousness, each of the four distinctive neural loops terminates there. When creativity is the result of deliberate control, as opposed to spontaneous generation, the prefrontal cortex also instigates the creative process. Both processing modes, deliberate and spontaneous, can guide neural computation in structures that contribute emotional content and in structures that provide cognitive analysis, yielding the four basic types of creativity. Supportive evidence from psychological, cognitive, and neuroscientific studies is presented and integrated in this article. The new theoretical framework systematizes the interaction between knowledge and creative thinking, and how the nature of this relationship changes as a function of domain and age. Implications for the arts and sciences are briefly discussed.     

Discrimination of structure: I. Implications for connectionist theories of discrimination learning

In each of 4 experiments animals were given a structural discrimination task that involved visual patterns composed of identical features, but the spatial relations among the features were different for reinforced and nonreinforced trials. In Experiment 1 the stimuli were pairs of colored circles, and pigeons were required to discriminate between patterns that were the mirror image of each other. A related task was given to rats in Experiment 2. Subjects solved these discriminations. For Experiment 3, some pigeons were given a discrimination similar to that used in Experiment 1, which they solved, whereas others received a comparable task but with 3 colored circles present on every trial, which they failed to solve. The findings from Experiment 3 were replicated in Experiment 4 using different patterns. The results are difficult to explain by certain connectionist theories of discrimination learning, unless they are modified to take account of the way in which compound stimuli are structured.     

Similarity-based cognition: radical enactivism meets cognitive neuroscience

Similarity-based cognition is commonplace. It occurs whenever an agent or system exploits the similarities that hold between two or more items—e.g., events, processes, objects, and so on—in order to perform some cognitive task. This kind of cognition is of special interest to cognitive neuroscientists. This paper explicates how similarity-based cognition can be understood through the lens of radical enactivism and why doing so has advantages over its representationalist rival, which posits the existence of structural representations or S-representations. Specifically, it is argued that there are problems both with accounting for the content of S-representations and with understanding how neurally-based structural similarities can work as representations (even if contentless) in guiding intelligent behavior. Finally, with these clarifications in place, it is revealed how radical enactivism can commit to an account of similarity-based cognition in its understanding of neurodynamics.

     

Constructive Metatheory: II. Implications for Psychotherapy

Abstract

The implications of constructive metatheory for the conceptualization and practice of psychotherapy are briefly outlined. It is argued that the constructivist therapist construes the client as an active and developing process, and that psychological problems are approached not as piecemeal flaws or deficiencies, but as expressions of current discrepancies between an individual's adaptive capacities and the challenges she or he faces. Likewise, the process of psychotherapy is portrayed as one of trial-and-error experimentation with different (novel) ways of “being in the world.” Ideally, the client and therapist create an intimate and emotionally charged alliance in and from which the client can explore and experiment with self and world relationships. These practical features dovetail with many assertions of the major me-tatheories of psychotherapy, and it is argued that constructive metatheory may be uniauely suited to facilitating attempts at conceptual integration     

Human recognition memory: a cognitive neuroscience perspective

For many years the cognitive processes underlying recognition memory have been the subject of considerable interest in experimental psychology. To account for a broad range of behavioral findings, psychologists have put forward a variety of 'dual-process' models, all of which propose that recognition memory is supported by two forms of memory - familiarity and recollection - that differ in their speed of operation and the specificity of the retrieved information. More recently, the dual-process framework has been extended to encompass findings from studies investigating the neural basis of recognition memory. Results from neuropsychological, ERP and functional neuroimaging studies can be accommodated within the framework, and suggest that familiarity and recollection are supported by distinct neural mechanisms.     

Cognitive neuroscience: the biology of the mind and findings and current opinion in cognitive neuroscience

Cognitive Neuroscience: The Biology of the Mind by Michael Gazzaniga, Richard Ivry and George Mangun, W.W. Norton, 1998. ￡24.95 (xv+587 pages) ISBN 0 393 97219 4 Findings and Current Opinion in Cognitive Neuroscience by Larry Squire and Stephen Kosslyn, MIT Press, 1998. $35.00 (vii+381 pages) ISBN 0 262 69204 X.     

Executive functions in preschool children born preterm: application of cognitive neuroscience paradigms.

Although children born preterm are at risk for neuropsychological impairments at school age and adolescence, including difficulties with visual motor integration, spatial/constructional skills, attention, arithmetic, and nonverbal executive functions, specific neuropsychological outcome has not been investigated adequately in preschoolers. Application of cognitive neuroscience tasks offers the opportunity to characterize early executive functions in young children born preterm. In a preliminary sample of 29 preschool children born preterm (M birth gestational age = 32.4 weeks), executive function outcome was compared to that of fullterm controls by contrasting performance on two prototypic delayed-response-type paradigms, Delayed Alternation and Spatial Reversal. Preschoolers born preterm correctly retrieved the reward on fewer trials on Delayed Alternation than did matched controls. Furthermore, preschool children born preterm used problem-solving strategies that included more perseverative errors than controls. These preliminary findings highlight the utility of cognitive neuroscience paradigms to understand neuropsychological outcome in preschool children born preterm and suggest areas of developmental vulnerability that may include dorsolateral prefrontal circuits.     

Facial expressions of emotion: a cognitive neuroscience perspective

Facial expressions are one example of emotional behavior that illustrate the importance of emotions to both basic survival and social interaction. Basic facial responses to stimuli such as sweet and bitter taste are important for species fitness and governed by simple rules. Even at this basic level, facial responses have communicative value to other species members. During evolution simple facial responses were extended for use in more complex nonverbal communications; the responses are labile. The perception and production of facial expressions are cognitive processes and numerous subcortical and cortical areas contribute to these operations. We suggest that no specific emotion center exists over and above cognitive systems in the brain, and that emotion should not be divorced from cognition.     

Computational analyses in cognitive neuroscience: in defense of biological implausibility

Because cognitive neuroscience researchers attempt to understand the human mind by bridging behavior and brain, they expect computational analyses to be biologically plausible. In this paper, biologicallyimplausible computational analyses are shown to have critical and essential roles in the various stages and domains of cognitive neuroscience research. Specifically, biologically implausible computational analyses can contribute to (1) understanding and characterizing the problem that is being studied, (2) examining the availability of information and its representation, and (3) evaluating and understanding the neuronal solution. In the context of the distinct types of contributions made by certain computational analyses, the biological plausibility of those analyses is altogether irrelevant. These biologically implausible models are nevertheless relevant and important for biologically driven research.     

The cognitive neuroscience of auditory distraction

We are often aware of the content of distracting sound, although typically remain unaware of the processes by which that sound is disruptive. Disruption can occur even when the sound is ignored and unrelated to the task being performed. In a recent major development, Gisselg?rd et al. have used positron emission tomography to reveal how distracting sounds recruit the involvement of dorsolateral prefrontal cortex.