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Szymanik, Jakub; Kochari, Arnold; Bremnes, Heming Strømholt – Cognitive Science, 2023
One approach to understanding how the human cognitive system stores and operates with quantifiers such as "some," "many," and "all" is to investigate their interaction with the cognitive mechanisms for estimating and comparing quantities from perceptual input (i.e., nonsymbolic quantities). While a potential link…
Descriptors: Cognitive Processes, Symbols (Mathematics), Numbers, Mathematical Concepts
Thomas, Michael S. C.; Coecke, Selma – Cognitive Science, 2023
Differences in socioeconomic status (SES) correlate both with differences in cognitive development and in brain structure. Associations between SES and brain measures such as cortical surface area and cortical thickness mediate differences in cognitive skills such as executive function and language. However, causal accounts that link SES, brain,…
Descriptors: Socioeconomic Status, Cognitive Processes, Brain, Cognitive Development
Wang, Wentao; Vong, Wai Keen; Kim, Najoung; Lake, Brenden M. – Cognitive Science, 2023
Neural network models have recently made striking progress in natural language processing, but they are typically trained on orders of magnitude more language input than children receive. What can these neural networks, which are primarily distributional learners, learn from a naturalistic subset of a single child's experience? We examine this…
Descriptors: Brain Hemisphere Functions, Linguistic Input, Longitudinal Studies, Self Concept
Morse, Anthony F.; Cangelosi, Angelo – Cognitive Science, 2017
Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between…
Descriptors: Vocabulary Development, Language Acquisition, Language Processing, Learning Theories
Cleeremans, Axel – Cognitive Science, 2014
Consciousness remains a mystery--"a phenomenon that people do not know how to think about--yet" (Dennett, D. C., 1991, p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing…
Descriptors: Cognitive Processes, Computation, Brain, Metacognition
Botvinick, Matthew M.; Cohen, Jonathan D. – Cognitive Science, 2014
Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on…
Descriptors: Cognitive Ability, Guidelines, Models, Cognitive Processes
McClelland, James L.; Mirman, Daniel; Bolger, Donald J.; Khaitan, Pranav – Cognitive Science, 2014
In a seminal 1977 article, Rumelhart argued that perception required the simultaneous use of multiple sources of information, allowing perceivers to optimally interpret sensory information at many levels of representation in real time as information arrives. Building on Rumelhart's arguments, we present the Interactive Activation…
Descriptors: Perception, Comprehension, Cognitive Processes, Alphabets
Ringach, Dario; Shapley, Robert – Cognitive Science, 2004
This article presents a review of reverse correlation in neurophysiology. We discuss the basis of reverse correlation in linear transducers and in spiking neurons. The application of reverse correlation to measure the receptive fields of visual neurons using white noise and m-sequences, and classical findings about spatial and color processing in…
Descriptors: Correlation, Neurology, Physiology, Brain
Li, Ping; Zhao, Xiaowei; Whinney, Brian Mac – Cognitive Science, 2007
In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition,…
Descriptors: Word Frequency, Short Term Memory, Vocabulary Development, Self Management