Rishi Rajalingham
Affiliations: | 2010-2012 | McGill University, Montreal, QC, Canada | |
2013- | Massachusetts Institute of Technology, Cambridge, MA, United States |
Area:
vision, motor-planning, brain-machine interfacesGoogle:
"Rishi Rajalingham"Mean distance: 14.27 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentorSam Musallam | grad student | 2010-2012 | McGill |
James J. DiCarlo | grad student | 2013-2018 | MIT |
Mehrdad Jazayeri | post-doc | 2019- | MIT |
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Publications
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Rajalingham R, Sohn H, Jazayeri M. (2025) Dynamic tracking of objects in the macaque dorsomedial frontal cortex. Nature Communications. 16: 346 |
Nayebi A, Rajalingham R, Jazayeri M, et al. (2023) Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes. Arxiv |
Rajalingham R, Piccato A, Jazayeri M. (2022) Recurrent neural networks with explicit representation of dynamic latent variables can mimic behavioral patterns in a physical inference task. Nature Communications. 13: 5865 |
Rajalingham R, Sorenson M, Azadi R, et al. (2021) Chronically implantable LED arrays for behavioral optogenetics in primates. Nature Methods |
Sohn H, Meirhaeghe N, Rajalingham R, et al. (2020) A Network Perspective on Sensorimotor Learning. Trends in Neurosciences |
Tremblay S, Acker L, Afraz A, et al. (2020) An Open Resource for Non-human Primate Optogenetics. Neuron |
Rajalingham R, Kar K, Sanghavi S, et al. (2020) The inferior temporal cortex is a potential cortical precursor of orthographic processing in untrained monkeys. Nature Communications. 11: 3886 |
Rajalingham R, DiCarlo JJ. (2019) Reversible Inactivation of Different Millimeter-Scale Regions of Primate IT Results in Different Patterns of Core Object Recognition Deficits. Neuron |
Rajalingham R, Kar K, Sanghavi S, et al. (2019) A precursor of reading: Neural responses to letters strings in the untrained primate inferior temporal cortex predict word recognition behavior Journal of Vision. 19: 172b |
Rajalingham R, Issa EB, Bashivan P, 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. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience |