
Bria Lorelle Long
Postdoctoral Research Fellow, Psychology
Professional Education
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Master of Science, Ecole Normale Superieure (2011)
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Doctor of Philosophy, Harvard University (2017)
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Bachelor of Arts, Stanford University, HUMBI-BAH (2009)
All Publications
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Mid-level visual features underlie the high-level categorical organization of the ventral stream
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2018; 115 (38): E9015–E9024
Abstract
Human object-selective cortex shows a large-scale organization characterized by the high-level properties of both animacy and object size. To what extent are these neural responses explained by primitive perceptual features that distinguish animals from objects and big objects from small objects? To address this question, we used a texture synthesis algorithm to create a class of stimuli-texforms-which preserve some mid-level texture and form information from objects while rendering them unrecognizable. We found that unrecognizable texforms were sufficient to elicit the large-scale organizations of object-selective cortex along the entire ventral pathway. Further, the structure in the neural patterns elicited by texforms was well predicted by curvature features and by intermediate layers of a deep convolutional neural network, supporting the mid-level nature of the representations. These results provide clear evidence that a substantial portion of ventral stream organization can be accounted for by coarse texture and form information without requiring explicit recognition of intact objects.
View details for PubMedID 30171168
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Data availability, reusability, and analytic reproducibility: evaluating the impact of a mandatory open data policy at the journal Cognition
ROYAL SOCIETY OPEN SCIENCE
2018; 5 (8)
View details for DOI 10.1098/rsos.180448
View details for Web of Science ID 000443443000059
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Constructing agency: the role of language
FRONTIERS IN PSYCHOLOGY
2010; 1
View details for DOI 10.3389/fpsyg.2010.00162
View details for Web of Science ID 000208849100059