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Parallel developments in neuroscience and deep learning have led to mutually productive exchanges, pushing our understanding of real and artificial neural networks in sensory and cognitive systems.
Speed, stride frequency and energy cost per stride: how do they change with body size and gait?
Norman C Heglund and C Richard Taylor · 1988
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Temporal hierarchical control of singing in birds
C Yu Albert and Daniel Margoliash · 1996
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The basal ganglia: focused selection and inhibition of competing motor programs
Jonathan W Mink · 1996
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The brain has a body: adaptive behavior emerges from interactions of nervous system, body and environment
Hillel J Chiel and Randall D Beer · 1997
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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An ultra-sparse code underliesthe generation of neural sequences in a songbird
Richard HR Hahnloser, Alexay A Kozhevnikov, and Michale S Fee · 2002
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Can a biologist fix a radio? Or, what I learned while studying apoptosis
Yuri Lazebnik · 2002
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The organization of behavioral repertoire in motor cortex
Michael Graziano · 2006
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Modeling a vertebrate motor system: pattern generation, steering and control of body orientation
Sten Grillner, Alexander Kozlov, Paolo Dario, Cesare Stefanini, Arianna Menciassi, Anders Lansner, and Jeanette Hellgren Kotaleski · 2007
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From swimming to walking with a salamander robot driven by a spinal cord model
Auke Jan Ijspeert, Alessandro Crespi, Dimitri Ryczko, and Jean-Marie Cabelguen · 2007
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Representational similarity analysis-connecting the branches of systems neuroscience
Nikolaus Kriegeskorte, Marieke Mur, and Peter A Bandettini · 2008
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Dimensionality and dynamics in the behavior of c. elegans
Greg J Stephens, Bethany Johnson-Kerner, William Bialek, and William S Ryu · 2008
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Striatal versus hippocampal representations during win-stay maze performance
Joshua D Berke, Jason T Breck, and Howard Eichenbaum · 2009
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From intention to action: motor cortex and the control of reaching movements
John F Kalaska · 2009
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Stimulus onset quenches neural variability: a widespread cortical phenomenon
Mark M Churchland, M Yu Byron, John P Cunningham, Leo P Sugrue, Marlene R Cohen, Greg S Corrado, William T Newsome, Andrew M Clark, Paymon Hosseini, Benjamin B Scott, et al · 2010
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Neural population dynamics during reaching
Mark M Churchland, John P Cunningham, Matthew T Kaufman, Justin D Foster, Paul Nuyujukian, Stephen I Ryu, and Krishna V Shenoy · 2012
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MuJoCo: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
Cited alongside, same era.
Preference distributions of primary motor cortex neurons reflect control solutions optimized for limb biomechanics
Timothy P Lillicrap and Stephen H Scott · 2013
Cited alongside, same era.
Mapping the stereotyped behaviour of freely moving fruit flies
Gordon J Berman, Daniel M Choi, William Bialek, and Joshua W Shaevitz · 2014
Cited alongside, same era.
Deep supervised, but not unsupervised, models may explain it cortical representation
Seyed-Mahdi Khaligh-Razavi and Nikolaus Kriegeskorte · 2014
Cited alongside, same era.
Variability in neural activity and behavior
Alfonso Renart and Christian K Machens · 2014
Cited alongside, same era.
Performance-optimized hierarchical models predict neural responses in higher visual cortex
Toward goal-driven neural network models for the rodent whisker-trigeminal system
Chengxu Zhuang, Jonas Kubilius, Mitra JZ Hartmann, and Daniel L Yamins · 2017
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Maximum a posteriori policy optimisation
Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Remi Munos, Nicolas Heess, and Martin Riedmiller · 2018
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Vector-based navigation using grid-like representations in artificial agents
Andrea Banino, Caswell Barry, Benigno Uria, Charles Blundell, Timothy Lillicrap, Piotr Mirowski, Alexander Pritzel, Martin J Chadwick, Thomas Degris, Joseph Modayil, et al · 2018
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Christopher J Cueva and Xue-Xin Wei · 2018
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IMPALA: Scalable distributed deep-rl with importance weighted actor-learner architectures
Lasse Espeholt, Hubert Soyer, Remi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, et al · 2018
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Daniel LK Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, and James J DiCarlo · 2014
Cited alongside, same era.
Motor cortex is required for learning but not for executing a motor skill
Risa Kawai, Timothy Markman, Rajesh Poddar, Raymond Ko, Antoniu L Fantana, Ashesh K Dhawale, Adam R Kampff, and Bence P Ölveczky · 2015
Cited alongside, same era.
The striatum multiplexes contextual and kinematic information to constrain motor habits execution
Pavel E Rueda-Orozco and David Robbe · 2015
Cited alongside, same era.
A neural network that finds a naturalistic solution for the production of muscle activity
David Sussillo, Mark M Churchland, Matthew T Kaufman, and Krishna V Shenoy · 2015
Cited alongside, same era.
Dissociated sequential activity and stimulus encoding in the dorsomedial striatum during spatial working memory
Hessameddin Akhlaghpour, Joost Wiskerke, Jung Yoon Choi, Joshua P Taliaferro, Jennifer Au, and Ilana B Witten · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Terrain-adaptive locomotion skills using deep reinforcement learning
Xue Bin Peng, Glen Berseth, and Michiel Van de Panne · 2016
Cited alongside, same era.
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A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy
Alexander JE Kell, Daniel LK Yamins, Erica N Shook, Sam V Norman-Haignere, and Josh H McDermott · 2018
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Kickstarting deep reinforcement learning
Simon Schmitt, Jonathan J Hudson, Augustin Zidek, Simon Osindero, Carl Doersch, Wojciech M Czarnecki, Joel Z Leibo, Heinrich Kuttler, Andrew Zisserman, Karen Simonyan, et al · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy Lillicrap, and Martin Riedmiller · 2018
Later among the works it cites.
The basal ganglia can control learned motor sequences independently of motor cortex
Ashesh K Dhawale, Steffen BE Wolff, Raymond Ko, and Bence P Ölveczky · 2019
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Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior
Kohitij Kar, Jonas Kubilius, Kailyn Schmidt, Elias B Issa, and James J DiCarlo · 2019
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Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey E. Hinton · 2019
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Peeling the onion of brain representations
Nikolaus Kriegeskorte and Jörn Diedrichsen · 2019
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A neural network model of flexible grasp movement generation
Jonathan A Michaels, Stefan Schaffelhofer, Andres Agudelo-Toro, and Hansjörg Scherberger · 2019
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Reverse-engineering the locomotion of a stem amniote
John A Nyakatura, Kamilo Melo, Tomislav Horvat, Kostas Karakasiliotis, Vivian R Allen, Amir Andikfar, Emanuel Andrada, Patrick Arnold, Jonas Lauströer, John R Hutchinson, et al · 2019
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V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
H Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, et al · 2019
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Task representations in neural networks trained to perform many cognitive tasks
Guangyu Robert Yang, Madhura R Joglekar, H Francis Song, William T Newsome, and Xiao-Jing Wang · 2019
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