| Large-scale, high-resolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks R Rajalingham, EB Issa, P Bashivan, K Kar, K Schmidt, JJ DiCarlo Journal of Neuroscience 38 (33), 7255-7269, 2018 | 150 | 2018 |
| Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior K Kar, J Kubilius, K Schmidt, EB Issa, JJ DiCarlo Nature neuroscience 22 (6), 974-983, 2019 | 111 | 2019 |
| Neural population control via deep image synthesis P Bashivan*, K Kar*, JJ DiCarlo Science 364 (6439), eaav9436, 2019 | 102 | 2019 |
| Transcranial electrical stimulation over visual cortex evokes phosphenes with a retinal origin K Kar, B Krekelberg Journal of Neurophysiology, 2012 | 80 | 2012 |
| Brain-score: Which artificial neural network for object recognition is most brain-like? M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ... BioRxiv, 407007, 2018 | 74 | 2018 |
| Task-driven convolutional recurrent models of the visual system A Nayebi, D Bear, J Kubilius, K Kar, S Ganguli, D Sussillo, JJ DiCarlo, ... Advances in Neural Information Processing Systems, 5290-5301, 2018 | 64 | 2018 |
| Transcranial alternating current stimulation attenuates visual motion adaptation K Kar, B Krekelberg Journal of Neuroscience 34 (21), 7334-7340, 2014 | 40 | 2014 |
| Transcranial alternating current stimulation attenuates neuronal adaptation K Kar, J Duijnhouwer, B Krekelberg Journal of Neuroscience 37 (9), 2325-2335, 2017 | 29 | 2017 |
| Brain-like object recognition with high-performing shallow recurrent anns J Kubilius, M Schrimpf, K Kar, H Hong, N Majaj, R Rajalingham, E Issa, ... Advances in Neural Information Processing Systems, 12785-12796, 2019 | 26 | 2019 |
| Testing the assumptions underlying fMRI adaptation using intracortical recordings in area MT K Kar, B Krekelberg Cortex 80, 21-34, 2016 | 26 | 2016 |
| Social closeness and feedback modulate susceptibility to the framing effect KE Sip, DV Smith, AJ Porcelli, K Kar, MR Delgado Social neuroscience 10 (1), 35-45, 2015 | 21 | 2015 |
| Probing the mechanisms underlying the mitigation of cognitive aging with anodal transcranial direct current stimulation K Kar, J Wright Journal of Neurophysiology, 2013 | 15 | 2013 |
| Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results L Arend, Y Han, M Schrimpf, P Bashivan, K Kar, T Poggio, JJ DiCarlo, ... Center for Brains, Minds and Machines (CBMM), 2018 | 5 | 2018 |
| Commentary: on the possible role of stimulation duration for after-effects of transcranial alternating current stimulation K Kar Frontiers in systems neuroscience 9, 148, 2015 | 5 | 2015 |
| Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity K Kar, T Ito, MW Cole, B Krekelberg Journal of Neurophysiology 123 (1), 428-438, 2020 | 4 | 2020 |
| Can Deep Neural Networks Rival Human Ability to Generalize in Core Object Recognition? J Kubilius*, K Kar*, K Schmidt, JJ DiCarlo 2018 Conference on Cognitive Computational Neuroscience, Date: 2018/09/05 …, 2018 | 3 | 2018 |
| Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition K Kar, JJ DiCarlo Neuron, 2020 | 2* | 2020 |
| An Open Resource for Non-human Primate Optogenetics S Tremblay, L Acker, A Afraz, DL Albaugh, H Amita, AR Andrei, ... Neuron, 2020 | 2 | 2020 |
| The inferior temporal cortex is a potential cortical precursor of orthographic processing in untrained monkeys R Rajalingham, K Kar, S Sanghavi, S Dehaene, JJ DiCarlo Nature communications 11 (1), 1-13, 2020 | 2* | 2020 |
| Using brain-score to evaluate and build neural networks for brain-like object recognition M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, C Ziemba, ... Cosyne 19, Date: 2019/02/28-2019/03/03, Location: Lisbon, Portugal, 2019 | 2 | 2019 |
James J DiCarloMassachusetts Institute of TechnologyBestätigte E-Mail-Adresse bei mit.edu
