Catalyzing next-generation artificial intelligence through neuroai A Zador, S Escola, B Richards, B Ölveczky, Y Bengio, K Boahen, ... Nature communications 14 (1), 1597, 2023 | 195 | 2023 |
full-FORCE: A target-based method for training recurrent networks B DePasquale, CJ Cueva, K Rajan, GS Escola, LF Abbott PloS one 13 (2), e0191527, 2018 | 172 | 2018 |
Learning multiple variable-speed sequences in striatum via cortical tutoring JM Murray, GS Escola Elife 6, e26084, 2017 | 105 | 2017 |
Thalamic control of cortical dynamics in a model of flexible motor sequencing L Logiaco, LF Abbott, S Escola Cell reports 35 (9), 2021 | 95 | 2021 |
Hidden Markov models for the stimulus-response relationships of multistate neural systems S Escola, A Fontanini, D Katz, L Paninski Neural computation 23 (5), 1071-1132, 2011 | 87 | 2011 |
Toward next-generation artificial intelligence: Catalyzing the neuroai revolution A Zador, S Escola, B Richards, B Ölveczky, Y Bengio, K Boahen, ... arXiv preprint arXiv:2210.08340, 2022 | 68 | 2022 |
Reconstruction of Metabolic Networks from High‐Throughput Metabolite Profiling Data: In Silico Analysis of Red Blood Cell Metabolism I Nemenman, GS Escola, WS Hlavacek, PJ Unkefer, CJ Unkefer, ME Wall Annals of the New York Academy of Sciences 1115 (1), 102-115, 2007 | 36 | 2007 |
Neuromatch Academy: Teaching computational neuroscience with global accessibility T van Viegen, A Akrami, K Bonnen, E DeWitt, A Hyafil, H Ledmyr, ... Trends in cognitive sciences 25 (7), 535-538, 2021 | 33 | 2021 |
Remembrance of things practiced with fast and slow learning in cortical and subcortical pathways JM Murray, GS Escola Nature Communications 11 (1), 6441, 2020 | 31 | 2020 |
Dissociating the contributions of sensorimotor striatum to automatic and visually guided motor sequences KGC Mizes, J Lindsey, GS Escola, BP Ölveczky Nature neuroscience 26 (10), 1791-1804, 2023 | 26 | 2023 |
& Tsao, D.(2023). Catalyzing nextgeneration artificial intelligence through neuroai A Zador, S Escola, B Richards, B Ölveczky, Y Bengio, K Boahen Nature communications 14 (1), 1597, 0 | 17 | |
A model of flexible motor sequencing through thalamic control of cortical dynamics L Logiaco, LF Abbott, S Escola Biorxiv, 2019.12. 17.880153, 2019 | 15 | 2019 |
Maximally reliable Markov chains under energy constraints S Escola, M Eisele, K Miller, L Paninski Neural computation 21 (7), 1863-1912, 2009 | 11 | 2009 |
Optimization and scaling of patient-derived brain organoids uncovers deep phenotypes of disease K Shah, R Bedi, A Rogozhnikov, P Ramkumar, Z Tong, B Rash, M Stanton, ... bioRxiv, 2020.08. 26.251611, 2020 | 10 | 2020 |
Specific connectivity optimizes learning in thalamocortical loops KJ Lakshminarasimhan, M Xie, JD Cohen, BA Sauerbrei, AW Hantman, ... Cell reports 43 (4), 2024 | 9 | 2024 |
Hidden Markov models applied toward the inference of neural states and the improved estimation of linear receptive fields S Escola, L Paninski COSYNE07, 2007 | 8 | 2007 |
Motor cortex is required for flexible but not automatic motor sequences KGC Mizes, J Lindsey, GS Escola, BP Ölveczky bioRxiv, 2023 | 7 | 2023 |
Thalamocortical motor circuit insights for more robust hierarchical control of complex sequences L Logiaco, GS Escola arXiv preprint arXiv:2006.13332, 2020 | 6 | 2020 |
Catalyzing next-generation artificial intelligence through NeuroAI. Nat Commun 14: 1597 A Zador, S Escola, B Richards, B Ölveczky, Y Bengio, K Boahen, ... | 5 | 2023 |
Neuromatch Academy: a 3-week, online summer school in computational neuroscience BM t Hart, T Achakulvisut, A Adeyemi, A Akrami, B Alicea, ... Technological University Dublin, 2022 | 5 | 2022 |