Probabilistic decision making by slow reverberation in cortical circuits.

By Xiao-Jing Wang. 2002

1,005 citations recorded by the source corpus.

How researchers see this paper

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In Cognitive Neuroscience

Citations in the corpus

Normalization as a canonical neural computation (2011, neutral): “Exponentiation, a form of thresholding, operates at the level of neurons and of network”
The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks (2008, neutral): “Besides these developments, there have been theoretical advances that attempt to produce models based on populations of spiking neurons, modeling the physiological behavior of neurons, synapses, and neurotransmitters (e.g., Lo & Wang, 2006; Wang, 2002; Wong & Wang, 2006).”
Probabilistic population codes for Bayesian decision making (2008, neutral): “…ﬁrst glance, it might appear that our model does not differ much from previous neural models of decision making (Machens et al., 2005; Mazurek et al., 2003; Ratcliff and Rouder, 1998; Reddi and Carpenter, 2000; Smith and Ratcliff, 2004; Usher and McClelland, 2001; Wang, 2002; Wong and Wang, 2006).”
Attractor and integrator networks in the brain (2021, positive): “Subsequently, many canonical brain circuits for motor control, sensory amplification and memory, motion integration, evidence integration, decision making, and spatial navigation have been modeled using the same general principle – that a set of states stabilized through collective positive feedback”
The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain (2010, neutral): “In sensory and routing areas these homogeneous populations were grouped into larger groups, forming local modules as used in previous studies [36,37].”
The neural basis of decision making. (2007, neutral): “In general, it is not clear why core principles perceptual tasks should be abandoned to account these”
A neural circuit model of flexible sensorimotor mapping: learning and forgetting on multiple timescales. (2007, positive): “The architecture and all the parameters of the network of 2000 integrate-and-fire neurons (1600 excitatory and 400 inhibitory) are identical to the one proposed in previous work (Wang, 2002; Brunel and Wang, 2001).”
Artificial Neural Networks for Neuroscientists: A Primer (2020, positive): “…law, the connectivity emerging from training is a heterogeneous version of that of a biologically-based structured network model of decision-making [Wang, 2002], demonstrating that machine learning brought closer to brain’s hardware can indeed be used to shed insights into biological neural…”
Integrated Neural Processes for Defining Potential Actions and Deciding between Them: A Computational Model (2006, positive): “In this sense, the present model is more like those of Wang (2002) and Machens et al. (2005), which propose that the decision-making process occurs between mutually competing cells and which also demonstrate the functional value of mixed representations.”
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition (2010, neutral): “Third, NMDA receptor-mediated excitatory reverberation may be critical for slow time integration of information underlying decision making computations (1032, 1034, 1071).”
The orbitofrontal cortex and beyond: from affect to decision-making. (2008, positive): “This population that wins the competition suppresses the other populations via the inhibitory neurons, so that we end up with a binary outcome that represents the choice made (Deco and Rolls, 2006; Rolls, 2008e; Wang, 2002).”