Seyed-Mahdi Khaligh-Razavi

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Nikolaus KriegeskorteProfessor of Psychology and Neuroscience, Columbia UniversityVerified email at columbia.edu
Reza EbrahimpourProf. of Cognitive Neuroscience, Shahid Rajaee University (SRU) & School of Cognitive Sciences, IPMVerified email at sru.ac.ir
Kendrick KayAssistant Professor, University of MinnesotaVerified email at post.harvard.edu
Dimitrios PantazisMcGovern Institute for Brain Research, MITVerified email at mit.edu
Linda HenrikssonSenior University Lecturer at Aalto UniversityVerified email at aalto.fi
Haniyeh MarefatSchool of Cognitive Sciences, Institute for Research in Fundamental SciencesVerified email at ipm.ir
Thomas A CarlsonAssociate Professor, University of SydneyVerified email at sydney.edu.au
Susan G. WardleNational Institutes of Health (NIH), Laboratory of Brain and CognitionVerified email at nih.gov
Maryam SadeghiUniversity of Kansas Medical Center (KUMC)Verified email at kumc.edu
Amirhossein FarzmahdiAlbert Einstein College of MedicineVerified email at einsteinmed.org
Radoslaw Martin CichyFreie Universität BerlinVerified email at zedat.fu-berlin.de
Hadi ModarresUniversity of CambridgeVerified email at cam.ac.uk
Tijl GrootswagersMARCS Institute for Brain, Behaviour & Development, Western Sydney UniversityVerified email at westernsydney.edu.au
Yalda MohsenzadehAssistant Professor, Department of Computer Science & Brain and Mind Institute, Western UniversityVerified email at uwo.ca
Aude OlivaMIT College Director Strategic Industry Engagement; MIT Director MIT-IBM Lab; Senior ResearchVerified email at mit.edu
Hamed KarimiBoston CollegeVerified email at bc.edu
zahra vahabiTehran University of medical scienceVerified email at sina.tums.ac.ir
Sajjad ZabbahPost-Doctoral Fellow, Institute for Research in Fundamental Sciences (IPM), School of CognitiveVerified email at ipm.ir
Dr. Amin MirzaeiInstitute of Neuroscience and Medicine (INM-6), Research Centre JülichVerified email at fz-juelich.de
Sidney LehkySalk InstituteVerified email at salk.edu

Seyed-Mahdi Khaligh-Razavi

Cognetivity Neurosciences

Verified email at Cognetivity.com - Homepage

Computational Vision Computational Neuroscience Dementia Deep learning


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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	893	2014
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	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	70*	2016
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	59	2019
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	51	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	50	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	44	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	37	2014
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), 1-17, 2016	22*	2016
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), 1-11, 2019	19	2019
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	19	2018
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	19	2013
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	19	2012
System for assessing a mental health disorder SM KHALIGH-RAZAVI, S HABIBI GB Patent WO2015067945 A1, 2015	17*	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	17	2014
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	13	2020
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	10	2020
Object-vision models that better explain IT also categorize better, but all models fail at both SM Khaligh-Razavi, N Kriegeskorte Cosyne Abstracts, Salt Lake City USA, 2013	8	2013
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	7	2016
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	7	2014

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