Vikaas S. Sohal

13.0k total citations · 4 hit papers
88 papers, 8.7k citations indexed

About

Vikaas S. Sohal is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Vikaas S. Sohal has authored 88 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Cognitive Neuroscience, 59 papers in Cellular and Molecular Neuroscience and 24 papers in Molecular Biology. Recurrent topics in Vikaas S. Sohal's work include Neural dynamics and brain function (45 papers), Neuroscience and Neuropharmacology Research (43 papers) and Photoreceptor and optogenetics research (22 papers). Vikaas S. Sohal is often cited by papers focused on Neural dynamics and brain function (45 papers), Neuroscience and Neuropharmacology Research (43 papers) and Photoreceptor and optogenetics research (22 papers). Vikaas S. Sohal collaborates with scholars based in United States, Russia and Switzerland. Vikaas S. Sohal's co-authors include Karl Deisseroth, Ofer Yizhar, Feng Zhang, John L.R. Rubenstein, John R. Huguenard, Peter Hegemann, Anthony T. Lee, Daniel Vogt, Tosha Patel and Thomas J. Davidson and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Vikaas S. Sohal

85 papers receiving 8.7k citations

Hit Papers

Parvalbumin neurons and gamma rhythms enhance cortical ci... 2009 2026 2014 2020 2009 2011 2019 2010 500 1000 1.5k

Peers

Vikaas S. Sohal
Peyman Golshani United States
Joshua A. Gordon United States
Lief E. Fenno United States
Henry H. Yin United States
Michela Fagiolini United States
Anatol C. Kreitzer United States
Ole Paulsen United Kingdom
Peyman Golshani United States
Vikaas S. Sohal
Citations per year, relative to Vikaas S. Sohal Vikaas S. Sohal (= 1×) peers Peyman Golshani

Countries citing papers authored by Vikaas S. Sohal

Since Specialization
Citations

This map shows the geographic impact of Vikaas S. Sohal'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 Vikaas S. Sohal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikaas S. Sohal more than expected).

Fields of papers citing papers by Vikaas S. Sohal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikaas S. Sohal. 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 Vikaas S. Sohal. The network helps show where Vikaas S. Sohal may publish in the future.

Co-authorship network of co-authors of Vikaas S. Sohal

This figure shows the co-authorship network connecting the top 25 collaborators of Vikaas S. Sohal. A scholar is included among the top collaborators of Vikaas S. Sohal 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 Vikaas S. Sohal. Vikaas S. Sohal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cho, Kathleen K.A., et al.. (2023). Long-range inhibition synchronizes and updates prefrontal task activity. Nature. 617(7961). 548–554. 16 indexed citations
2.
Allen, Denise E., Kevin C. Donohue, Cathryn R. Cadwell, et al.. (2022). Fate mapping of neural stem cell niches reveals distinct origins of human cortical astrocytes. Science. 376(6600). 1441–1446. 37 indexed citations
3.
Frost, Nicholas A., et al.. (2021). Dynamic patterns of correlated activity in the prefrontal cortex encode information about social behavior. PLoS Biology. 19(5). e3001235–e3001235. 21 indexed citations
4.
Malik, Ruchi, Thomas A. Lanz, Mark L. Weber, et al.. (2020). GluN2D-mediated excitatory drive onto medial prefrontal cortical PV+ fast-spiking inhibitory interneurons. PLoS ONE. 15(6). e0233895–e0233895. 24 indexed citations
5.
Darbandi, Siavash Fazel, Emily Ling-Lin Pai, Amanda Everitt, et al.. (2020). Enhancing WNT Signaling Restores Cortical Neuronal Spine Maturation and Synaptogenesis in Tbr1 Mutants. Cell Reports. 31(2). 107495–107495. 33 indexed citations
6.
Krukowski, Karen, Amber Nolan, Elma S. Frias, et al.. (2019). Integrated Stress Response Inhibitor Reverses Sex-Dependent Behavioral and Cell-Specific Deficits after Mild Repetitive Head Trauma. Journal of Neurotrauma. 37(11). 1370–1380. 23 indexed citations
7.
Malik, Ruchi, Emily Ling-Lin Pai, Anna Noren Rubin, et al.. (2019). Tsc1 represses parvalbumin expression and fast-spiking properties in somatostatin lineage cortical interneurons. Nature Communications. 10(1). 4994–4994. 33 indexed citations
8.
Sohal, Vikaas S. & John L.R. Rubenstein. (2019). Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders. Molecular Psychiatry. 24(9). 1248–1257. 598 indexed citations breakdown →
9.
Marton, Tobias F., Helia Seifikar, Francisco Luongo, Anthony T. Lee, & Vikaas S. Sohal. (2018). Roles of Prefrontal Cortex and Mediodorsal Thalamus in Task Engagement and Behavioral Flexibility. Journal of Neuroscience. 38(10). 2569–2578. 60 indexed citations
10.
Vu, Mai-Anh, Tülay Adalı, Demba Ba, et al.. (2018). A Shared Vision for Machine Learning in Neuroscience. Journal of Neuroscience. 38(7). 1601–1607. 105 indexed citations
11.
Nolan, Amber, Edel Hennessy, Karen Krukowski, et al.. (2018). Repeated Mild Head Injury Leads to Wide-Ranging Deficits in Higher-Order Cognitive Functions Associated with the Prefrontal Cortex. Journal of Neurotrauma. 35(20). 2425–2434. 36 indexed citations
12.
Chamanzar, Maysamreza, David J. Garfield, Jillian Iafrati, et al.. (2018). Upconverting nanoparticle micro-lightbulbs designed for deep tissue optical stimulation and imaging. Biomedical Optics Express. 9(9). 4359–4359. 15 indexed citations
13.
Kirkby, Lowry A., Francisco Luongo, Morgan B. Lee, et al.. (2018). An Amygdala-Hippocampus Subnetwork that Encodes Variation in Human Mood. Cell. 175(6). 1688–1700.e14. 115 indexed citations
14.
Ullman, Julie C., Jing Yang, Michael L. Sullivan, et al.. (2018). A mouse model of autism implicates endosome pH in the regulation of presynaptic calcium entry. Nature Communications. 9(1). 330–330. 28 indexed citations
15.
Nahum, Mor, Thomas Van Vleet, Vikaas S. Sohal, et al.. (2017). Immediate Mood Scaler: Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale. JMIR mhealth and uhealth. 5(4). e44–e44. 57 indexed citations
16.
Gee, Steven M., et al.. (2017). D3 Receptors Regulate Excitability in a Unique Class of Prefrontal Pyramidal Cells. Journal of Neuroscience. 37(24). 5846–5860. 64 indexed citations
17.
Khoshkhoo, Sattar, Daniel Vogt, & Vikaas S. Sohal. (2016). Dynamic, Cell-Type-Specific Roles for GABAergic Interneurons in a Mouse Model of Optogenetically Inducible Seizures. Neuron. 93(2). 291–298. 118 indexed citations
18.
Lee, Anthony T., Steven M. Gee, Daniel Vogt, et al.. (2013). Pyramidal Neurons in Prefrontal Cortex Receive Subtype-Specific Forms of Excitation and Inhibition. Neuron. 81(1). 61–68. 152 indexed citations
19.
Gee, Steven M., et al.. (2012). Synaptic Activity Unmasks Dopamine D2 Receptor Modulation of a Specific Class of Layer V Pyramidal Neurons in Prefrontal Cortex. Journal of Neuroscience. 32(14). 4959–4971. 170 indexed citations
20.
Gunaydin, Lisa A., Ofer Yizhar, A. Berndt, et al.. (2010). Ultrafast optogenetic control. Nature Neuroscience. 13(3). 387–392. 555 indexed citations breakdown →

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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