Representations in the brain are encoded as patterns of activity of large populations of neurons. The science of population encoded representations, also known as parallel distributed processing (PDP), achieves neurological verisimilitude and has been able to account for a large number of cognitive phenomena in normal people, including reaction times (and reading latencies), stimulus recognition, the effect of stimulus salience on attention, perceptual invariance, simultaneous egocentric and allocentric visual processing, top-down/bottom-up processing, language errors, the effect of statistical regularities of experience, frequency, and age of acquisition, instantiation of rules and symbols, content addressable memory and the capacity for pattern completion, preservation of function in the face of noisy or distorted input, inference, parallel constraint satisfaction, the binding problem and gamma coherence, principles of hippocampal function, the location of knowledge in the brain, limitations in the scope and depth of knowledge acquired through experience, and Piagetian stages of cognitive development. PDP studies have been able to provide a coherent account for impairment in a variety of language functions resulting from stroke or dementia in a large number of languages and the phenomenon of graceful degradation observed in such studies. They have also made important contributions to our understanding of attention (including hemispatial neglect), emotional function, executive function, motor planning, visual processing, decision making, and neuroeconomics. The relationship of neural network population dynamics to electroencephalographic rhythms is starting to emerge. Nevertheless, PDP approaches have scarcely penetrated major areas of study of cognition, including neuropsychology and cognitive neuropsychology, as well as much of cognitive psychology. This article attempts to provide an overview of PDP principles and applications that addresses a broader audience.
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http://dx.doi.org/10.3389/fnhum.2020.00050 | DOI Listing |
J Biochem
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Division of Cancer and Senescence Biology, Cancer Research Institute, Kanazawa University, Kanazawa, Ishikawa, Japan.
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View Article and Find Full Text PDFPsychol Rev
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Department of Psychology, State University of New York at Albany.
Cognitive scientists and neuroscientists are increasingly deploying computational models to develop testable theories of psychological functions and make quantitative predictions about cognition, brain activity, and behavior. Computational models are used to explain target phenomena such as experimental effects, individual, and/or population differences. They do so by relating these phenomena to the underlying components of the model that map onto distinct cognitive mechanisms.
View Article and Find Full Text PDFACS Nano
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Mechanobiology Institute, National University of Singapore, Singapore 117411, Singapore.
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Department of Chemistry - Ångström Laboratory, Uppsala University, SE-75120 Uppsala, Sweden.
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Department of Biology, University of Florence, Via Madonna del Piano 6, Sesto Fiorentino, 50019, Italy.
Resistance, tolerance, and persistence to antibiotics have mainly been studied at the level of a single microbial isolate. However, in recent years it has become evident that microbial interactions play a role in determining the success of antibiotic treatments, in particular by influencing the occurrence of persistence and tolerance within a population. Additionally, the challenge of resuscitation (the capability of a population to revive after antibiotic exposure) and pathogen clearance are strongly linked to the small size of the surviving population and to the presence of fluctuations in cell counts.
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