962 resultados para cognitive processes
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Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.
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In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes.
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Decades of research attest that memory processes suffer under conditions of auditory distraction. What is however less well understood is whether people are able to modify how their memory processes are deployed in order to compensate for disruptive effects of distraction. The metacognitive approach to memory describes a variety of ways people can exert control over their cognitive processes to optimize performance. Here we describe our recent investigations into how these control processes change under conditions of auditory distraction. We specifically looked at control of encoding in the form of decisions about how long to study a word when it is presented and control of memory reporting in the form of decisions whether to volunteer or withhold retrieved details. Regarding control of encoding, we expected that people would compensate for disruptive effects of distraction by extending study time under noise. Our results revealed, however, that when exposed to irrelevant speech, people curtail rather than extend study. Regarding control of memory reporting, we expected that people would compensate for the loss of access to memory records by volunteering responses held with lower confidence. Our results revealed, however, that people’s reporting strategies do not differ when memory task is performed in silence or under auditory distraction, although distraction seriously undermines people’s confidence in their own responses. Together, our studies reveal novel avenues for investigating the psychological effects of auditory distraction within a metacognitive framework.
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In this article, the authors aim to present a critical review of recent MRI studies addressing white matter (WM) abnormalities in Alzheimer's disease (AD) and mild cognitive impairment (MCI), by searching PubMed and reviewing MRI studies evaluating subjects with AD or MCI using WM volumetric methods, diffusion tensor imaging and assessment of WM hyperintensities. Studies have found that, compared with healthy controls, AD and MCI samples display WM volumetric reductions and diffusion tensor imaging findings suggestive of reduced WM integrity. These changes affect complex networks relevant to episodic memory and other cognitive processes, including fiber connections that directly link medial temporal structures and the corpus callosum. Abnormalities in cortico-cortical and cortico-subcortical WM interconnections are associated with an increased risk of progression from MCI to dementia. It can be concluded that WM abnormalities are detectable in early stages of AD and MCI. Degeneration of WM networks causes disconnection among neural cells and the degree of such changes is related to cognitive decline. © 2013 2013 Expert Reviews Ltd.
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The research activity characterizing the present thesis was mainly centered on the design, development and validation of methodologies for the estimation of stationary and time-varying connectivity between different regions of the human brain during specific complex cognitive tasks. Such activity involved two main aspects: i) the development of a stable, consistent and reproducible procedure for functional connectivity estimation with a high impact on neuroscience field and ii) its application to real data from healthy volunteers eliciting specific cognitive processes (attention and memory). In particular the methodological issues addressed in the present thesis consisted in finding out an approach to be applied in neuroscience field able to: i) include all the cerebral sources in connectivity estimation process; ii) to accurately describe the temporal evolution of connectivity networks; iii) to assess the significance of connectivity patterns; iv) to consistently describe relevant properties of brain networks. The advancement provided in this thesis allowed finding out quantifiable descriptors of cognitive processes during a high resolution EEG experiment involving subjects performing complex cognitive tasks.
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Primates as a taxonomic Order have the largest brains corrected for body size in the animal kingdom. These large brains have allowed primates to evolve the capacity to demonstrate advanced cognitive processes across a wide array of abilities. Nonhuman primates are particularly adept at social learning, defined as the modification of behavior by observing the actions of others. Additionally, primates often exploit resources differently depending on their social context. In this study, capuchin monkeys (Cebus apella) were tested on a cognitive task in three social contexts to determine if social context influenced their performance on the task. The three social contexts included: alone, having a dominant individual in an adjacent compartment, and having a subordinate individual in the adjacent compartment. The benefits to this design were thatthe social context was the only variable influencing performance, whereas in previous studies investigating audience effects other animals could physically and directly influence a subject's performance in an open testing situation. Based on past studies, Ipredicted that the presence of a dominant individual would reduce cognitive task performance compared to the other conditions. The cognitive test used was a match-tosample discrimination task in which animals matched combinations of eight geometric shapes. Animals were trained on this task in an isolated context until they reached a baseline level of proficiency and were then tested in the three social contexts in a random order multiple times. Two subjects (Mt and Dv) have successfully completed trials under all conditions. Results indicated that there were no significant difference in taskperformance across the three conditions (Dv x^2 (1) = 0.42, p=0.58; Mt x^2 (1) = 0.02, p=0.88). In all conditions, subjects performed significantly above chance (i.e., 39/60 trials determined by a binomial distribution). Results are contrary to previous studies thatreport low status monkeys 'play dumb' when testing in a mixed social context, possibly because other studies did not account for aggressive interference by dominants while testing. Results of this study suggest that the mere presence of a dominant individualdoes not necessarily affect performance on a cognitive task, but rather the imminence of physical aggression is the most important factor influencing testing in a social context.
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The IDA model of cognition is a fully integrated artificial cognitive system reaching across the full spectrum of cognition, from low-level perception/action to high-level reasoning. Extensively based on empirical data, it accurately reflects the full range of cognitive processes found in natural cognitive systems. As a source of plausible explanations for very many cognitive processes, the IDA model provides an ideal tool to think with about how minds work. This online tutorial offers a reasonably full account of the IDA conceptual model, including background material. It also provides a high-level account of the underlying computational “mechanisms of mind” that constitute the IDA computational model.
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PDP++ is a freely available, open source software package designed to support the development, simulation, and analysis of research-grade connectionist models of cognitive processes. It supports most popular parallel distributed processing paradigms and artificial neural network architectures, and it also provides an implementation of the LEABRA computational cognitive neuroscience framework. Models are typically constructed and examined using the PDP++ graphical user interface, but the system may also be extended through the incorporation of user-written C++ code. This article briefly reviews the features of PDP++, focusing on its utility for teaching cognitive modeling concepts and skills to university undergraduate and graduate students. An informal evaluation of the software as a pedagogical tool is provided, based on the author’s classroom experiences at three research universities and several conference-hosted tutorials.
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By means of fixed-links modeling the present study assessed processes involved in visual short-term memory functioning and investigates how these processes are related to intelligence. Using a color change detection task, short-term memory demands increased across three experimental conditions as a function of number of presented stimuli. We measured amount of information retained in visual short-term memory by hit rate as well as speed of visual short-term memory scanning by reaction time. For both measures, fixed-links modeling revealed a constant process reflecting processes irrespective of task manipulation as well as two increasing processes reflecting the increasing short-term memory demands. For visual short-term memory scanning, a negative association between intelligence and the constant process was found but no relationship between intelligence and the increasing processes. Thus, basic processing speed, rather than speed influenced by visual short-term memory demands, differentiates between high- and low-intelligent individuals. Intelligence was positively related to the experimental processes of shortterm memory retention but not to the constant process. In sum, significant associations with intelligence were only obtained when the specific processes of short-term memory were decomposed emphasizing the importance of a thorough assessment of cognitive processes when investigating their relation to intelligence.
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Many studies obtained reliable individual differences in speed of information processing (SIP) as measured by elementary cognitive tasks (ECTs). ECTs usually employ response times (RT) as measure of SIP, but different ECTs target different cognitive processes (e.g., simple or choice reaction, inhibition). Here we used modified versions of the Hick and the Eriksen Flanker task to examine whether these tasks assess dissociable or common aspects of SIP. In both tasks, task complexity was systematically varied across three levels. RT data were collected from 135 participants. Applying fixed-links modeling, RT variance increasing with task complexity was separated from RT variance unchanging across conditions. For each task, these aspects of variance were represented by two independent latent variables. The two latent variables representing RT variance not varying with complexity of the two tasks were virtually identical (r = .83). The latent variables representing increasing complexity in the two tasks were also highly correlated (r = .72) but clearly dissociable. Thus, RT measures contain both task-unspecific, person-related aspects of SIP as well as task-specific aspects indicating the cognitive processes manipulated with the respective task. Separating these aspects of SIP facilitates the interpretation of individual differences in RT.
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Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique's resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.
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Culture consists of shared cognitive representations in the minds of individuals. This paper investigates the extent to which English speakers share the "same" semantic structure of English kinship terms. The semantic structure is defined as the arrangement of the terms relative to each other as represented in a metric space in which items judged more similar are placed closer to each other than items judged as less similar. The cognitive representation of the semantic structure, residing in the mind of an individual, is measured by judged similarity tasks involving comparisons among terms. Using six independent measurements, from each of 122 individuals, correspondence analysis represents the data in a common multidimensional spatial representation. Judged by a variety of statistical procedures, the individuals in our sample share virtually identical cognitive representations of the semantic structure of kinship terms. This model of culture accounts for 70-90% of the total variability in these data. We argue that our findings on kinship should generalize to all semantic domains--e.g., animals, emotions, etc. The investigation of semantic domains is important because they may reside in localized functional units in the brain, because they relate to a variety of cognitive processes, and because they have the potential to provide methods for diagnosing individual breakdowns in the structure of cognitive representations typical of such ailments as Alzheimer disease.
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Although androgens are commonly seen as male sex hormones, it has been established over the years that in both sexes, androgens also respond to social challenges. To explain the socially driven changes in androgens, two theoretical models have been proposed: the biosocial model and the challenge hypothesis. These models are typically seen as partly overlapping; however, they generate different predictions that are clarified here. In humans, sports competition and nonmetabolic competitive tasks have been used in the laboratory setting, as a proxy for agonistic interactions in animals. The results reviewed here show that the testosterone (T) response to competition in humans is highly variable – the studies present postcompetition T levels and changes in T that depend on the contest outcome and that cannot be predicted by the current theoretical models. These conflicting results bring to the foreground the importance of considering cognitive factors that could moderate the androgen response to competition. Among these variables, we elect cognitive appraisal and its components as a key candidate modulating factor. It is known that T also modulates the cognitive processes that are relevant to performance in competition. In this article, we reviewed the evidence arising from studies investigating the effect of administering exogenous T and compare those results with the findings from studies that measured endogenous T levels. Finally, we summarized the importance of also considering the interaction between androgens and other hormones, such as cortisol, when investigating the social modulation of T, as proposed by the dual-hormone hypothesis.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Cognitive modelling of phenomena in clinical practice allows the operationalisation of otherwise diffuse descriptive terms such as craving or flashbacks. This supports the empirical investigation of the clinical phenomena and the development of targeted treatment interventions. This paper focuses on the cognitive processes underpinning craving, which is recognised as a motivating experience in substance dependence. We use a high-level cognitive architecture, Interacting Cognitive Subsystems (ICS), to compare two theories of craving: Tiffany's theory, centred on the control of automated action schemata, and our own Elaborated Intrusion theory of craving. Data from a questionnaire study of the subjective aspects of everyday desires experienced by a large non-clinical population are presented. Both the data and the high-level modelling support the central claim of the Elaborated Intrusion theory that imagery is a key element of craving, providing the subjective experience and mediating much of the associated disruption of concurrent cognition.