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Ila R Fiete

Showing results (11-20 of 31) with videos related to

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Hippocampus|November 21, 2008
Grid cells: the position code, neural network models of activity, and the problem of learningPeter E Welinder, Yoram Burak, Ila R Fiete
Elife|July 10, 2018
Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cellsJohn Widloski, Michael P Marder, Ila R Fiete
Journal of Neurophysiology|July 27, 2007
Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductancesIla R Fiete, Michale S Fee, H Sebastian Seung
Neural Computation|September 19, 2023
Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNsMikail Khona, Sarthak Chandra, Joy J Ma, et al.
Elife|May 24, 2021
Place-cell capacity and volatility with grid-like inputsMan Yi Yim, Lorenzo A Sadun, Ila R Fiete, et al.
Elife|September 8, 2017
Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activityOnur Ozan Koyluoglu, Yoni Pertzov, Sanjay Manohar, et al.
Neuron|March 2, 2010
Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activityIla R Fiete, Walter Senn, Claude Z H Wang, et al.
Neuron|February 23, 2016
Grid Cell Responses in 1D Environments Assessed as Slices through a 2D LatticeKiJung Yoon, Sam Lewallen, Amina A Kinkhabwala, et al.
Current Biology : CB|June 16, 2015
Bias in Human Path Integration Is Predicted by Properties of Grid CellsXiaoli Chen, Qiliang He, Jonathan W Kelly, et al.
Journal of Neurophysiology|April 9, 2004
Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsongIla R Fiete, Richard H R Hahnloser, Michale S Fee, et al.
Pageof 4

Showing results (11-20 of 31) with videos related to

Sort By:
Pageof 4
Hippocampus|November 21, 2008
Grid cells: the position code, neural network models of activity, and the problem of learningPeter E Welinder, Yoram Burak, Ila R Fiete
Elife|July 10, 2018
Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cellsJohn Widloski, Michael P Marder, Ila R Fiete
Journal of Neurophysiology|July 27, 2007
Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductancesIla R Fiete, Michale S Fee, H Sebastian Seung
Neural Computation|September 19, 2023
Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNsMikail Khona, Sarthak Chandra, Joy J Ma, et al.
Elife|May 24, 2021
Place-cell capacity and volatility with grid-like inputsMan Yi Yim, Lorenzo A Sadun, Ila R Fiete, et al.
Elife|September 8, 2017
Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activityOnur Ozan Koyluoglu, Yoni Pertzov, Sanjay Manohar, et al.
Neuron|March 2, 2010
Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activityIla R Fiete, Walter Senn, Claude Z H Wang, et al.
Neuron|February 23, 2016
Grid Cell Responses in 1D Environments Assessed as Slices through a 2D LatticeKiJung Yoon, Sam Lewallen, Amina A Kinkhabwala, et al.
Current Biology : CB|June 16, 2015
Bias in Human Path Integration Is Predicted by Properties of Grid CellsXiaoli Chen, Qiliang He, Jonathan W Kelly, et al.
Journal of Neurophysiology|April 9, 2004
Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsongIla R Fiete, Richard H R Hahnloser, Michale S Fee, et al.
Pageof 4