Kohitij Kar

3.5k total citations
49 papers, 1.3k citations indexed

About

Kohitij Kar is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Kohitij Kar has authored 49 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Cognitive Neuroscience, 7 papers in Cellular and Molecular Neuroscience and 7 papers in Artificial Intelligence. Recurrent topics in Kohitij Kar's work include Neural dynamics and brain function (20 papers), Face Recognition and Perception (10 papers) and Transcranial Magnetic Stimulation Studies (7 papers). Kohitij Kar is often cited by papers focused on Neural dynamics and brain function (20 papers), Face Recognition and Perception (10 papers) and Transcranial Magnetic Stimulation Studies (7 papers). Kohitij Kar collaborates with scholars based in United States, Canada and Belgium. Kohitij Kar's co-authors include James J. DiCarlo, Pouya Bashivan, Bart Krekelberg, Kailyn Schmidt, Elias B. Issa, Jonas Kubilius, Rishi Rajalingham, Jacob Duijnhouwer, B. N. Mehrotra and D. S. BHAKUNI and has published in prestigious journals such as Science, Nature Communications and Neuron.

In The Last Decade

Kohitij Kar

43 papers receiving 1.2k citations

Peers

Kohitij Kar

CVPR

CMN

NEURO

Laurent Perrinet France

Hedva Spitzer Israel

Okito Yamashita Japan

Shinji Nishimoto Japan

Grace W. Lindsay United States

Diego Sona Italy

Pietro Berkes United States

Mihail Bota United States

Hossein Esteky Iran

Guangyu Robert Yang United States

Laurent Perrinet France

Kohitij Kar

992 ×1.1

195 ×1.0

CVPR

252 ×1.4

CMN

102 ×0.7

39 ×0.3

NEURO

Citations per year, relative to Kohitij Kar Kohitij Kar (= 1×) peers Laurent Perrinet

Countries citing papers authored by Kohitij Kar

Since Specialization

Citations

This map shows the geographic impact of Kohitij Kar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kohitij Kar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kohitij Kar more than expected).

Fields of papers citing papers by Kohitij Kar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kohitij Kar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kohitij Kar. The network helps show where Kohitij Kar may publish in the future.

Co-authorship network of co-authors of Kohitij Kar

This figure shows the co-authorship network connecting the top 25 collaborators of Kohitij Kar. A scholar is included among the top collaborators of Kohitij Kar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kohitij Kar. Kohitij Kar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ramezanpour, Hamidreza, et al.. (2024). Low-cost, portable, easy-to-use kiosks to facilitate home-cage testing of nonhuman primates during vision-based behavioral tasks. Journal of Neurophysiology. 132(3). 666–677. 1 indexed citations

Kar, Kohitij & James J. DiCarlo. (2024). The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates. Annual Review of Vision Science. 10(1). 91–121. 3 indexed citations

Yu, Hongbo, et al.. (2023). Multimodal investigations of emotional face processing and social trait judgment of faces. Annals of the New York Academy of Sciences. 1531(1). 29–48. 6 indexed citations

Kar, Kohitij, Nancy Kanwisher, & Katharina Dobs. (2023). Deep neural networks optimized for both face detection and face discrimination most accurately predict face-selective neurons in macaque inferior temporal cortex. 1 indexed citations

Kar, Kohitij, Simon Kornblith, & Evelina Fedorenko. (2022). Interpretability of artificial neural network models in artificial intelligence versus neuroscience. Nature Machine Intelligence. 4(12). 1065–1067. 23 indexed citations

Kar, Kohitij. (2022). A Computational Probe into the Behavioral and Neural Markers of Atypical Facial Emotion Processing in Autism. Journal of Neuroscience. 42(25). 5115–5126. 5 indexed citations

Kar, Kohitij, Martin Schrimpf, Kailyn Schmidt, & James J. DiCarlo. (2021). Chemogenetic suppression of macaque V4 neurons produces retinotopically specific deficits in downstream IT neural activity patterns and core object recognition behavior. Journal of Vision. 21(9). 2489–2489. 1 indexed citations

Kar, Kohitij & James J. DiCarlo. (2020). Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition. Neuron. 109(1). 164–176.e5. 72 indexed citations

Bashivan, Pouya, Kohitij Kar, & James J. DiCarlo. (2019). Neural population control via deep image synthesis. Science. 364(6439). 206 indexed citations

10.

Kar, Kohitij, Takuya Ito, Michael W. Cole, & Bart Krekelberg. (2019). Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity. Journal of Neurophysiology. 123(1). 428–438. 25 indexed citations

11.

Nayebi, Aran, Daniel M. Bear, Jonas Kubilius, et al.. (2018). Task-driven convolutional recurrent models of the visual system. Lirias (KU Leuven). 31. 5290–5301. 16 indexed citations

12.

Rajalingham, Rishi, Elias B. Issa, Pouya Bashivan, et al.. (2018). Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks. Journal of Neuroscience. 38(33). 7255–7269. 190 indexed citations

13.

Kar, Kohitij, Jacob Duijnhouwer, & Bart Krekelberg. (2017). Transcranial Alternating Current Stimulation Attenuates Neuronal Adaptation. Journal of Neuroscience. 37(9). 2325–2335. 38 indexed citations

14.

Kar, Kohitij & Bart Krekelberg. (2016). Testing the assumptions underlying fMRI adaptation using intracortical recordings in area MT. Cortex. 80. 21–34. 22 indexed citations

15.

Kar, Kohitij. (2015). Commentary: On the possible role of stimulation duration for after-effects of transcranial alternating current stimulation. Frontiers in Systems Neuroscience. 9. 148–148. 6 indexed citations

16.

Sip, Kamila E., David V. Smith, Anthony J. Porcelli, Kohitij Kar, & Mauricio R. Delgado. (2014). Social closeness and feedback modulate susceptibility to the framing effect. Social Neuroscience. 10(1). 35–45. 26 indexed citations

17.

Kar, Kohitij & Bart Krekelberg. (2014). Transcranial Alternating Current Stimulation Attenuates Visual Motion Adaptation. Journal of Neuroscience. 34(21). 7334–7340. 46 indexed citations

18.

Kar, Kohitij, Jacob Duijnhouwer, & Bart Krekelberg. (2013). Transcranial electrical stimulation affects adaptation of MT/V5 neurons in awake behaving macaques. Journal of Vision. 13(9). 357–357.

19.

Kar, Kohitij & Bart Krekelberg. (2012). Effects of transcranial electrical stimulation on human motion detection. Journal of Vision. 12(9). 756–756. 2 indexed citations

20.

Kar, Kohitij & Bart Krekelberg. (2011). Retinal and cortical effects of transcranial electric stimulation. Journal of Vision. 11(11). 764–764.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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