S
Seyed-Mahdi Khaligh-Razavi
Researcher at Massachusetts Institute of Technology
Publications - 36
Citations - 1900
Seyed-Mahdi Khaligh-Razavi is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Visual processing & Cognitive neuroscience of visual object recognition. The author has an hindex of 14, co-authored 36 publications receiving 1509 citations. Previous affiliations of Seyed-Mahdi Khaligh-Razavi include Macquarie University & Royan Institute.
Papers
More filters
Journal ArticleDOI
Deep supervised, but not unsupervised, models may explain IT cortical representation.
TL;DR: The results suggest that explaining IT requires computational features trained through supervised learning to emphasize the behaviorally important categorical divisions prominently reflected in IT.
Journal ArticleDOI
Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG
Susan G. Wardle,Nikolaus Kriegeskorte,Tijl Grootswagers,Seyed-Mahdi Khaligh-Razavi,Thomas A. Carlson,Thomas A. Carlson +5 more
TL;DR: It is shown that large-scale brain activation patterns contain a neural signature for the perceptual Gestalt of composite visual features, and a strong correspondence between perception and complex patterns of brain activity is demonstrated.
Journal ArticleDOI
Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models
TL;DR: The results demonstrate the benefits of testing both the specific representational hypothesis expressed by a model’s original feature space and the hypothesis space generated by linear transformations of that feature space.
Journal ArticleDOI
Visual representations are dominated by intrinsic fluctuations correlated between areas
Linda Henriksson,Linda Henriksson,Seyed-Mahdi Khaligh-Razavi,Kendrick Kay,Nikolaus Kriegeskorte +4 more
TL;DR: It is reported that intrinsic cortical dynamics strongly affect the representational geometry of a brain region, as reflected in response-pattern dissimilarities, and exaggerate the similarity of representations between brain regions.
Journal ArticleDOI
Beyond core object recognition: Recurrent processes account for object recognition under occlusion.
Karim Rajaei,Yalda Mohsenzadeh,Reza Ebrahimpour,Seyed-Mahdi Khaligh-Razavi,Seyed-Mahdi Khaligh-Razavi +4 more
TL;DR: Evidence is provided from multivariate analysis of MEG data, behavioral data, and computational modelling, demonstrating an essential role for recurrent processes in object recognition under occlusion and suggesting a mechanistic explanation of how the human brain might be solving this problem.