Seyed-Mahdi Khaligh-Razavi
Seyed-Mahdi Khaligh-Razavi
Cognetivity Neurosciences
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Deep supervised, but not unsupervised, models may explain IT cortical representation
SM Khaligh-Razavi, N Kriegeskorte
PLoS computational biology 10 (11), e1003915, 2014
Beyond core object recognition: Recurrent processes account for object recognition under occlusion
K Rajaei, Y Mohsenzadeh, R Ebrahimpour, SM Khaligh-Razavi
PLoS computational biology 15 (5), e1007001, 2019
Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG
SG Wardle, N Kriegeskorte, T Grootswagers, SM Khaligh-Razavi, ...
Neuroimage 132, 59-70, 2016
Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models
SM Khaligh-Razavi, L Henriksson, K Kay, N Kriegeskorte
Journal of Mathematical Psychology, 2016
Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role
M Ghodrati, SM Khaligh-Razavi, SR Lehky
Progress in Neurobiology 156, 214-255, 2017
Visual representations are dominated by intrinsic fluctuations correlated between areas
L Henriksson, SM Khaligh-Razavi, K Kay, N Kriegeskorte
NeuroImage 114, 275-286, 2015
How can selection of biologically inspired features improve the performance of a robust object recognition model?
M Ghodrati, SM Khaligh-Razavi, R Ebrahimpour, K Rajaei, M Pooyan
PloS one 7 (2), e32357, 2012
Feedforward object-vision models only tolerate small image variations compared to human
M Ghodrati, A Farzmahdi, K Rajaei, R Ebrahimpour, SM Khaligh-Razavi
Frontiers in computational neuroscience 8, 74, 2014
Tracking the spatiotemporal neural dynamics of real-world object size and animacy in the human brain
SM Khaligh-Razavi, RM Cichy, D Pantazis, A Oliva
Journal of cognitive neuroscience 30 (11), 1559-1576, 2018
Integrated cognitive assessment: Speed and accuracy of visual processing as a reliable proxy to cognitive performance
SM Khaligh-Razavi, S Habibi, M Sadeghi, H Marefat, M Khanbagi, ...
Scientific Reports 9 (1), 1102, 2019
A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans
A Farzmahdi, K Rajaei, M Ghodrati, R Ebrahimpour, SM Khaligh-Razavi
Scientific reports 6 (1), 25025, 2016
Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia
C Kalafatis, MH Modarres, P Apostolou, H Marefat, M Khanbagi, H Karimi, ...
Frontiers in Psychiatry, 1155, 2021
Predicting the Human Reaction Time Based On Natural Image Statistics in a Rapid Categorization Task
A Mirzaei, SM Khaligh-Razavi, M Ghodrati, S Zabbah, R Ebrahimpour
Vision Research, 2013
System for assessing a mental health disorder
GB Patent WO2015067945 A1, 2015
The impact of the lateral geniculate nucleus and corticogeniculate interactions on efficient coding and higher-order visual object processing
S Zabbah, K Rajaei, A Mirzaei, R Ebrahimpour, SM Khaligh-Razavi
Vision research 101, 82-93, 2014
A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization
K Rajaei, SM Khaligh-Razavi, M Ghodrati, R Ebrahimpour, ...
PLOS one 7 (6), e38478, 2012
A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)
SM Khaligh-Razavi, M Sadeghi, M Khanbagi, C Kalafatis, SM Nabavi
BMC neurology 20 (1), 1-13, 2020
Noise ceiling on the crossvalidated performance of reweighted models of representational dissimilarity: Addendum to Khaligh-Razavi & Kriegeskorte (2014)
KR Storrs, SM Khaligh-Razavi, N Kriegeskorte
BioRxiv, 2020.03. 23.003046, 2020
What you need to know about the state-of-the-art computational models of object-vision: A tour through the models
SM Khaligh-Razavi
arXiv preprint arXiv:1407.2776, 2014
From what we perceive to what we remember: Characterizing representational dynamics of visual memorability
SM Khaligh-Razavi, WA Bainbridge, D Pantazis, A Oliva
BioRxiv, 049700, 2016
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