Decision making in recurrent neuronal circuits.

By Xiao-Jing Wang. Neuron, 2008

648 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b1845b04420d64b283e65b67457df04ceb93dd6e

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In Cognitive Neuroscience

Citations in the corpus

Cortical Information Flow During Flexible Sensorimotor Decisions (2015, background): “Similar dynamics in PFC and LIP could indicate that accumulation of sensory evidence depends on their recurrent interactions (24, 25).”
The speed-accuracy tradeoff: history, physiology, methodology, and behavior (2014, background): “Wald’s procedure, which became known as the sequential probability ratio test (Wald, 1947), allows one to approach a known (acceptable) error rate with a potentially enormous savings in time and resources.”
Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks (2013, result): “This is in contrast to network models that are explicitly constructed to implement a specific known mechanism (see Wang, 2008; Hopfield, 1982).”
Intention, action planning, and decision making in parietal-frontal circuits. (2009, background): “For instance, it is believed that the apparent stability of the world during eye movements, which sweep the visual scene across the retinas, is achieved by a forward model that makes use of feedback of eye movement commands (VonHolst and Mittelstaedt, 1950; von Helmoltz, 1866; Haarmeier et al., 2001”
The effect of acute physical exercise on cognitive function during development (2010, background): “It is also considered as a general indicator of functional integrity of the central nervous system (Wang, 2008).”
Neural basis of reinforcement learning and decision making. (2012, background): “Converging evidence from a number of recent studies suggests that many of these computations are carried out in multiple interconnected regions in the frontal cortex and basal ganglia.”
Neuronal Reward and Decision Signals: From Theories to Data. (2015, methodology): “[From Wang (623), with permission from Elsevier.”
The Neurobiology of Decision: Consensus and Controversy (2009, neutral): “Wang and colleagues (Lo and Wang, 2006; Wang, 2008; Wong and Wang, 2006) have recently shown that a single collicular or parietal circuit can be designed that performs both winner-take-all and thresholding operations in a stochastic fashion that depends on the inhibitory tone of the network.”
Cognitive computational neuroscience (2018, background): “However, recurrent neural networks, which reprocess the outputs of their units and generate complex dynamics, have brought additional engineering advances(106) and better capture the recurrent signaling in brains.(107,108,48,109) Whereas feedforward networks are universal function approximators, rec”
Selection of cortical dynamics for motor behaviour by the basal ganglia (2015, background): “A channel can release from inhibition a distinct cortical pattern (among others Wickens et al. 1994; Graybiel 1998; Ponzi and Wickens 2010).”
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition (2010, background): “Third, NMDA receptor-mediated excitatory reverberation may be critical for slow time integration of information underlying decision making computations (1032, 1034, 1071).”
The Noisy Brain: Stochastic Dynamics as a Principle of Brain Function (2010, neutral): “Complementary theoretical neuroscience models are approaching the problem by design - ing biologically realistic neural circuits that can perform the comparison of two signals ( Wang 2002 , Brody , Romo and Kepecs 2003b , Machens , Romo and Brody 2005 , Wang 2008 ) .”
Reward-based training of recurrent neural networks for cognitive and value-based tasks (2016, background): “We consider this sampling as an abstract representation of the downstream action selection mechanisms present in the brain, including the role of noise in implicitly realizing stochastic choices with deterministic outputs ( Wang, 2002 , 2008 ).”