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Within-category representational stability through the lens of manipulable objects
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Neural Signal to Violations of Abstract Rules Using Speech-Like Stimuli. ...
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Neural Signal to Violations of Abstract Rules Using Speech-Like Stimuli.
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Understanding facial impressions between and within identities.
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The relationship between parental mental-state language and 2.5-year-olds' performance on a nontraditional false-belief task.
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Eye movements provide insight into individual differences in children's analogical reasoning strategies.
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What causes the greater perceived similarity of consonant-transposed nonwords? ...
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What causes the greater perceived similarity of consonant-transposed nonwords?
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Smiles in face matching: Idiosyncratic information revealed through a smile improves unfamiliar face matching performance.
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Categorical Perception Beyond the Basic Level: The Case of Warm and Cool Colors.
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In: Cognitive science, vol 41, iss 4 (2017)
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The center of attention: Metamers, sensitivity, and bias in the emergent perception of gaze.
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In: Vision research, vol 131 (2017)
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A common neural hub resolves syntactic and non-syntactic conflict through cooperation with task-specific networks.
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Spatiotemporal dynamics of word retrieval in speech production revealed by cortical high-frequency band activity. ...
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Spatiotemporal dynamics of word retrieval in speech production revealed by cortical high-frequency band activity.
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Increased discriminability of authenticity from multimodal laughter is driven by auditory information.
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The effect of semantic transparency on the processing of morphologically derived words: Evidence from decision latencies and event-related potentials.
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In: Brain and Mind Institute Researchers' Publications (2017)
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The ERP signature of the contextual diversity effect in visual word recognition
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Fragile associations coexist with robust memories for precise details in long-term memory.
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In: Journal of experimental psychology. Learning, memory, and cognition, vol 42, iss 3 (2016)
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Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration.
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In: Journal of cognitive neuroscience, vol 28, iss 4 (2016)
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Abstract:
Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I., McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v, that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing ["The Model", TM, Cottrell, G. W., & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception. Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a "spreading transform" for faces (separating them in representational space) that generalizes to objects that must be individuated. Interestingly, when the task of the network is basic level categorization, no increase in the correlation between domains is observed. Hence, our model predicts that it is the type of experience that matters and that the source of the correlation is in the fusiform face area, rather than in cortical areas that subserve basic level categorization. This result is consistent with our previous modeling elucidating why the FFA is recruited for novel domains of expertise [Tong, M. H., Joyce, C. A., & Cottrell, G. W. Why is the fusiform face area recruited for novel categories of expertise? A neurocomputational investigation. Brain Research, 1202, 14-24, 2008].
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Keyword:
Brain Mapping; Cognitive Sciences; Computer Simulation; cs.CV; Experimental Psychology; Face; Humans; Models; Neurological; Neurosciences; Pattern Recognition; Photic Stimulation; Principal Component Analysis; Psychology; q-bio.NC; Recognition (Psychology); Statistics as Topic; Visual
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URL: https://escholarship.org/uc/item/9hg7194z
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The effect of word position on eye-movements in sentence and paragraph reading
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