Terrence J. Sejnowski
Affiliations: | Computational Neurobiology Laboratory | Salk Institute for Biological Studies, La Jolla, CA, United States | |
| Neurosciences | University of California, San Diego, La Jolla, CA |
Area:
Computation & TheoryWebsite:
http://www.cnl.salk.edu/Google:
"Terrence J. Sejnowski"Bio:
http://www.nasonline.org/member-directory/members/20002157.html
Mean distance: 10.45 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentor| John Archibald Wheeler | research assistant | 1970 | Princeton (Physics Tree) | |
| (M. A.) | ||||
| John J. Hopfield | grad student | 1978 | Princeton | |
| (A stochastic model of nonlinearly interacting neurons) | ||||
| Alan Gelperin | post-doc | 1978-1979 | Princeton | |
| Stephen W. Kuffler | post-doc | 1979-1982 | Harvard Medical School | |
Children
Sign in to add traineeCollaborators
Sign in to add collaborator| April A Benasich | collaborator | Salk Institute for Biological Studies, and University of California, San Diego | |
| Christopher Bowd | collaborator | ||
| Patricia Churchland | collaborator | UCSD | |
| Gerald M Pao | collaborator | Salk Institute for Biological Studies, and University of California, San Diego | |
| Xin Yu | collaborator | 2015- | |
| Mircea Steriade | collaborator | 1990-2006 | Salk Institute |
| Jason S. Sherfey | collaborator | 2009-2010 | The Salk Institute for Biological Studies & UCSD |
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Publications
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| Bartol TM, Ordyan M, Sejnowski TJ, et al. (2024) A spatial model of autophosphorylation of CaMKII in a glutamatergic spine suggests a network-driven kinetic mechanism for bistable changes in synaptic strength. Biorxiv : the Preprint Server For Biology |
| Samavat M, Bartol TM, Bromer C, et al. (2024) Long-Term Potentiation Produces a Sustained Expansion of Synaptic Information Storage Capacity in Adult Rat Hippocampus. Biorxiv : the Preprint Server For Biology |
| Sameni S, Bartol TM, Corey-Bloom J, et al. (2023) Computer simulations predict the impact of neuronal atrophy on the calcium dynamics in Huntington's disease. Pnas Nexus. 3: pgad443 |
| Tsuda B, Richmond BJ, Sejnowski TJ. (2023) Exploring strategy differences between humans and monkeys with recurrent neural networks. Plos Computational Biology. 19: e1011618 |
| Garcia GC, Gupta K, Bartol TM, et al. (2023) Mitochondrial morphology governs ATP production rate. The Journal of General Physiology. 155 |
| Zador A, Escola S, Richards B, et al. (2023) Catalyzing next-generation Artificial Intelligence through NeuroAI. Nature Communications. 14: 1597 |
| Rungratsameetaweemana N, Lainscsek C, Cash SS, et al. (2022) Brain network dynamics codify heterogeneity in seizure evolution. Brain Communications. 4: fcac234 |
| Chen Y, Bukhari Q, Lin TW, et al. (2022) Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times. Network Neuroscience (Cambridge, Mass.). 6: 614-633 |
| Bermperidis T, Schafer S, Gage FH, et al. (2022) Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Psychiatric Disorders. Frontiers in Neuroscience. 16: 884707 |
| Grün S, Li J, McNaughton B, et al. (2022) Emerging principles of spacetime in brains: Meeting report on spatial neurodynamics. Neuron. 110: 1894-1898 |