Ila Fiete

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Mikail KhonaResearch Scientist, NVIDIAEmail yang diverifikasi di nvidia.com
Yoram BurakHebrew UniversityEmail yang diverifikasi di elsc.huji.ac.il
Rishidev ChaudhuriAssistant Professor, University of California, DavisEmail yang diverifikasi di ucdavis.edu
H Sebastian SeungProfessor, Princeton Neuroscience Institute and Computer Science Dept.Email yang diverifikasi di princeton.edu
Rylan SchaefferStanford UniversityEmail yang diverifikasi di stanford.edu
Sarthak ChandraMassachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Akhilan BoopathyMassachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Kijung YoonHanyang UniversityEmail yang diverifikasi di hanyang.ac.kr
Ingmar KanitscheiderOpenAIEmail yang diverifikasi di openai.com
David W. TankPrinceton UniversityEmail yang diverifikasi di princeton.edu
Richard HahnloserInstitute of Neuroinformatics, ETH Zurich and University of ZurichEmail yang diverifikasi di ini.ethz.ch
Sugandha SharmaBrain and Cognitive Sciences, MITEmail yang diverifikasi di mit.edu
Michale S FeeProfessor of Neuroscience, Massachusetts Institute of Technology (MIT)Email yang diverifikasi di mit.edu
John Widloskipostdoc, UC BerkeleyEmail yang diverifikasi di berkeley.edu
Adrien PeyracheAssociate Professor, Montreal Neurological Institute, McGill UniversityEmail yang diverifikasi di mcgill.ca
Berk GerçekGraduate Student, University of GenevaEmail yang diverifikasi di unige.ch
Biraj Pandeygraduate student, University of WashingtonEmail yang diverifikasi di uw.edu
Caswell BarryCDB, UCLEmail yang diverifikasi di ucl.ac.uk
Neil BurgessProfessor of Cognitive Neuroscience, University College LondonEmail yang diverifikasi di ucl.ac.uk
L F AbbottBrandeis University, CERN, Boston University, Columbia University, Stanford Linear AcceleratorEmail yang diverifikasi di columbia.edu

Ikuti

Ila Fiete

Professor of Brain and Cognitive Sciences, MIT

Email yang diverifikasi di mit.edu

Theoretical neuroscience Machine Learning Theory Memory Cognitive Maps


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Accurate path integration in continuous attractor network models of grid cells Y Burak, IR Fiete PLoS computational biology 5 (2), e1000291, 2009	818	2009
The intrinsic attractor manifold and population dynamics of a canonical cognitive circuit across waking and sleep R Chaudhuri, B Gerçek, B Pandey, A Peyrache, I Fiete Nature neuroscience 22 (9), 1512-1520, 2019	354	2019
What grid cells convey about rat location IR Fiete, Y Burak, T Brookings Journal of Neuroscience 28 (27), 6858-6871, 2008	334	2008
Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity IR Fiete, W Senn, CZH Wang, RHR Hahnloser Neuron 65 (4), 563-576, 2010	321	2010
Specific evidence of low-dimensional continuous attractor dynamics in grid cells KJ Yoon, MA Buice, C Barry, R Hayman, N Burgess, IR Fiete Nature neuroscience 16 (8), 1077-1084, 2013	316	2013
Computational principles of memory. R Chaudhuri, IR Fiete Nature Neuroscience, 2016	268	2016
Grid cells generate an analog error-correcting code for singularly precise neural computation S Sreenivasan, I Fiete Nature neuroscience 14 (10), 1330-1337, 2011	251	2011
Attractor and integrator networks in the brain M Khona, IR Fiete Nature Reviews Neuroscience 23 (12), 744-766, 2022	232	2022
Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances IR Fiete, MS Fee, HS Seung Journal of neurophysiology 98 (4), 2038-2057, 2007	218	2007
Testing odor response stereotypy in the Drosophila mushroom body M Murthy, I Fiete, G Laurent Neuron 59 (6), 1009-1023, 2008	197	2008
The mind of a mouse LF Abbott, DD Bock, EM Callaway, W Denk, C Dulac, AL Fairhall, I Fiete, ... Cell 182 (6), 1372-1376, 2020	175	2020
Gradient learning in spiking neural networks by dynamic perturbation of conductances IR Fiete, HS Seung Physical review letters 97 (4), 048104, 2006	163	2006
Fundamental limits on persistent activity in networks of noisy neurons Y Burak, IR Fiete Proceedings of the National Academy of Sciences 109 (43), 17645-17650, 2012	139	2012
Cortical ensembles orchestrate social competition through hypothalamic outputs N Padilla-Coreano, K Batra, M Patarino, Z Chen, RR Rock, R Zhang, ... Nature 603 (7902), 667-671, 2022	117	2022
Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong IR Fiete, RHR Hahnloser, MS Fee, HS Seung Journal of neurophysiology 92 (4), 2274-2282, 2004	114	2004
A Model of Grid Cell Development through Spatial Exploration and Spike Time-Dependent Plasticity J Widloski, IR Fiete Neuron 83 (2), 481-495, 2014	110	2014
A map-like micro-organization of grid cells in the medial entorhinal cortex Y Gu, S Lewallen, AA Kinkhabwala, C Domnisoru, K Yoon, JL Gauthier, ... Cell 175 (3), 736-750. e30, 2018	107	2018
Grid cell co-activity patterns during sleep reflect spatial overlap of grid fields during active behaviors SG Trettel, JB Trimper, E Hwaun, IR Fiete, LL Colgin Nature neuroscience 22 (4), 609-617, 2019	102	2019
Grid cells: the position code, neural network models of activity, and the problem of learning PE Welinder, Y Burak, IR Fiete Hippocampus 18 (12), 1283-1300, 2008	96	2008
Systematic errors in connectivity inferred from activity in strongly recurrent networks A Das, IR Fiete Nature Neuroscience 23 (10), 1286-1296, 2020	92	2020

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