The proposed P01 project is designed to advance our understanding of the developmental, neural, evolutionary, and cognitive mechanisms of categorization. The proposed research will be guided by a set of general hypotheses. First, categorization is mediated by multiple interacting systems. Second, these systems may become fully functional at different points of development. And third, the degree of involvement of each system is determined by: (a) its functional maturity, (b) the structure of the stimulus input, and (c) the way training is administered. The P01 as a whole has 4 specific aims: (1) to elucidate the ontogenetic and phylogenetic changes in categorization; (2) to link brain development with the development of categorization in humans; (3) to develop and test animal models of category learning; and (4) to use animal models for examining the neurobiology of categorization.
These aims will be addressed three individual projects: (1) Individual Project 1 aims at elucidating the development of categorization and at linking it to the developing brain, (2) Individual Project 2 aims at developing, testing, and using animal models examining the neurobiology of categorization, and (3) Individual Project 3 aims at developing computational models of interacting systems of category learning and to empirically test these models. Although methodological details may and will differ across species (i.e., pigeons, rats, and humans) and across human populations (i.e., infants, children, and adults), individual projects will use the same set of tasks and the same set of secondary dependent variables (e.g., learning curves, costs, savings, etc.) that will enable direct comparisons among the different subject populations. Therefore, each individual project will contribute to the same goal: better understanding of the developmental, neural, evolutionary and cognitive mechanisms of a critically important human intellectual ability. There will be two Core Units. The Administrative Core Unit will enable seamless communication across the individual sites and the overall integrative activities. The Data Core Unit will enable data sharing, statistical analyses, and model selection services across the individual projects.
The project will elucidate relationships between the developing brain and developing cognition and will advance our understanding of categorization -- a critical component of cognitive development. In addition to contributing to our understanding of typical cognitive development, these answers may also contribute to the early diagnostics and treatment of atypical development, such as autism and Williams's syndrome.
| O'Leary, Allison P; Sloutsky, Vladimir M (2018) Components of metacognition can function independently across development. Dev Psychol : |
| Darby, Kevin P; Castro, Leyre; Wasserman, Edward A et al. (2018) Cognitive flexibility and memory in pigeons, human children, and adults. Cognition 177:30-40 |
| Ahlheim, Christiane; Love, Bradley C (2018) Estimating the functional dimensionality of neural representations. Neuroimage 179:51-62 |
| Castro, Leyre; Wasserman, Edward A; Lauffer, Marisol (2018) Unsupervised learning of complex associations in an animal model. Cognition 173:28-33 |
| Kim, Jangjin; Castro, Leyre; Wasserman, Edward A et al. (2018) Dorsal hippocampus is necessary for visual categorization in rats. Hippocampus 28:392-405 |
| Bobadilla-Suarez, Sebastian; Love, Bradley C (2018) Fast or frugal, but not both: Decision heuristics under time pressure. J Exp Psychol Learn Mem Cogn 44:24-33 |
| Mack, Michael L; Love, Bradley C; Preston, Alison R (2018) Building concepts one episode at a time: The hippocampus and concept formation. Neurosci Lett 680:31-38 |
| Guest, Olivia; Love, Bradley C (2017) What the success of brain imaging implies about the neural code. Elife 6: |
| Sloutsky, Vladimir M; Yim, Hyungwook; Yao, Xin et al. (2017) An associative account of the development of word learning. Cogn Psychol 97:1-30 |
| Palmeri, Thomas J; Love, Bradley C; Turner, Brandon M (2017) Model-based cognitive neuroscience. J Math Psychol 76:59-64 |
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