The neural separation and integration of object and background scene information in natural images C Mullin, SM Khaligh-Razavi, D Pantazis, A Oliva Journal of Vision 17 (10), 1089-1089 2017 Combining human MEG and fMRI data reveals the spatio-temporal dynamics of animacy and real-world object size SM Khaligh-Razavi, R Cichy, D Pantazis, A Oliva Journal of Vision 17 (10), 574-574 2017 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 Tracking the spatiotemporal neural dynamics of object properties in the human brain SM Khaligh-Razavi, RM Cichy, D Pantazis, A Oliva Cognitive Computational Neuroscience 2017 Content-Dependent Fusion: Combining Human MEG and FMRI Data to Reveal Spatiotemporal Dynamics of Animacy and Real-world Object Size SM Khaligh-Razavi, RM Cichy, D Pantazis, A Oliva AAAI Publications 2017 Sudden emergence of categoricality at the lateral-occipital stage of ventral visual processing A Walther, J Diedrichsen, M Mur, SM Khaligh-Razavi, N Kriegeskorte Journal of Vision 16 (12), 407-407 2016 Temporal Dynamics of Memorability: An Intrinsic Brain Signal Distinct from Memory SM Khaligh-Razavi, WA Bainbridge, D Pantazis, A Oliva Journal of Vision 16 (12), 38-38 2016 Mixing deep neural network features to explain brain representations SM Khaligh-Razavi, L Henriksson, K Kay, N Kriegeskorte Journal of Vision 16 (12), 369-369 2016 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 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, 25025 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 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 The effects of recurrent dynamics on ventral-stream representational geometry SM Khaligh-Razavi, J Carlin, RM Cichy, N Kriegeskorte Journal of vision 15 (12), 1089-1089 2015 Visual representations are dominated by intrinsic fluctuations correlated between areas L Henriksson, SM Khaligh-Razavi, K Kay, N Kriegeskorte NeuroImage 114, 275-286 2015 Perceptual similarity of visual patterns predicts the similarity of their dynamic neural activation patterns measured with MEG SG Wardle, N Kriegeskorte, T Grootswagers, SM Khaligh-Razavi, … arXiv preprint arXiv:1506.02208 2015 Representational geometries of object vision in man and machine SM Khaligh-Razavi University of Cambridge 2015 System for assessing a mental health disorder SM KHALIGH-RAZAVI, S HABIBI GB Patent WO2015067945 A1 2015 Deep supervised, but not unsupervised, models may explain IT cortical representation SM Khaligh-Razavi, N Kriegeskorte PLoS computational biology 10 (11), e1003915 2014 What is the nature of the decodable neuromagnetic signal? MEG, Models, and Perception. T Carlson, S Khaligh-Razavi, N Kriegeskorte Journal of Vision 14 (10), 585-585 2014 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 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 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 Explaining the hierarchy of visual representational geometries by remixing of features from many computational vision models SM Khaligh-Razavi, L Henriksson, K Kay, N Kriegeskorte bioRxiv, 009936 2014 Intrinsic cortical dynamics dominate population responses to natural images across human visual cortex L Henriksson, SM Khaligh-Razavi, K Kay, N Kriegeskorte bioRxiv, 008961 2014 Population-code representations of natural images across human visual areas L Henriksson, SM Khaligh-Razavi, N Kriegeskorte Journal of Vision 13 (9), 1035-1035 2013 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 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 A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization K Rajaei, SM Khaligh-Razavi, M Ghodrati, R Ebrahimpour, MESA Abadi PloS one 7 (6), e38478 2012 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