Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task

By J. Roitman, Michael N. Shadlen. Journal of Neuroscience, 2002

1,626 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/c5a82fbb837a2157828cf52b22f1e7959e8353c1

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In Cellular and Molecular Neuroscience

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Citations in the corpus

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework (2016, background): “To control the speed-accuracy tradeoff, the target outputs during training did not require the network to commit to a decision immediately but instead after a short delay [62]; the delay determines the cost incurred for answering early but incorrectly versus correctly but at a later time.”
Probabilistic population codes for Bayesian decision making (2008, methodology): “(C) Same as in (A) but for actual LIP neurons (n = 45) in the two-choice experiment (dotted line, data from Roitman and Shadlen, 2002; solid line, data from Churchland et al., 2008).”
The neural systems that mediate human perceptual decision making (2008, methodology): “The human neuroimaging studies we have reviewed so far used single-unit-recording findings as a constraint to predict decision-related changes in fMRI signal”
One-dimensional dynamics of attention and decision making in LIP. (2008, methodology): “Given that similar classes of neurons were involved, we decided to test whether the framework of slow one-dimensional dynamics in LIP applies to the Roitman and Shadlen (2002) experiments.”
A Recurrent Network Mechanism of Time Integration in Perceptual Decisions (2006, methodology): “The value of ␴ noise is chosen such that the psychometric and chronometric functions are close to that of Roitman and Shadlen (2002).”
The effect of stimulus strength on the speed and accuracy of a perceptual decision. (2005, background): “Data are from Roitman and Shadlen (2002). tion of the dots moved coherently in one of two possible directions while the others were randomly repositioned.”
Changing your mind: a computational mechanism of vacillation (2009, neutral): “It is precluded when an action is ballistic, for instance when a subject makes an eye movement to a choice target9,15.”
Integration of Visuospatial and Effector Information during Symbolically Cued Limb Movements in Monkey Lateral Intraparietal Area (2006, result): “This finding is consistent with parallel processing models in which information about visuospatial, perceptual, and motor variables accumulates in parallel during the reaction time (Roitman and Shadlen, 2002).”
Probabilistic decision making by slow reverberation in cortical circuits. (2002, positive): “It was sug- not shown). gested that the discrepancy can be explained if at zero or low coherence reaction time is often longer than 1 s, Dependence on Time Integration of Long Stimulus Signaland hence the network has more time to form a decision in the reaction-time task (Roitman and Shadlen, 2002).”
Reward-based training of recurrent neural networks for cognitive and value-based tasks (2016, methodology): “…the signed coherence (the strength of the evidence, with negative values indicating evidence for L and positive for R) also reveals coherence-dependent ramping activity (Figure 1D) as observed in neural recordings from numerous perceptual decision-making experiments, e.g., Roitman & Shadlen (2002).”
Attention, Intention, and Priority in the Parietal Lobe (2010, background): “…process in estimating time (Janssen & Shadlen 2005, Leon & Shadlen 2003, Maimon & Assad 2006), the direction of motion of a noisy stimulus (Churchland et al. 2008, Roitman & Shadlen 2002, Shadlen & Newsome 2001), confidence (Kiani & Shadlen 2009), and probabilistic reasoning (Yang & Shadlen 2007).”
Neural mechanisms for interacting with a world full of action choices. (2010, background): “For example, Romo and colleagues (Hernandez et al. 2002, Romo et al. 2002, Romo et al. 2004) found that during tasks in which a nominally tactile perceptual decision is reported by an arm movement, correlates of all of the putative sensory encoding, memory, discrimination, and decision-making…”
Artificial Neural Networks for Neuroscientists: A Primer (2020, methodology): “…| · | constrains signs of the connection weights, e.g, After training an ANN to perform the classical random dot motion direction discrimination task [Roitman and Shadlen, 2002], one can “open the box" and examine the resulting “wiring diagram" of recurrent network connectivity pattern (Figure 10).”
Decision-making with multiple alternatives (2008, background): “Decisions between two choices in a perceptual-motion tas”