Rats and Humans Can Optimally Accumulate Evidence for Decision-Making

By Bingni W. Brunton, Matthew Botvinick, Carlos D. Brody. Science, 2013

609 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Sensory Systems

View Paper: https://www.semanticscholar.org/paper/3b5e38e806b0ff3a689dcc64ee33e4e6f63d8081

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Citations in the corpus

A category-free neural population supports evolving demands during decision-making (2014, methodology): “We assembled as many pseudo-trials as possible by randomly sampling trials from each neuron without replacement; because the number of trials from each neuron was balanced across conditions when training the classifiers, the process was limited by the neuron with the fewest trials in any one conditi”
Economic irrationality is optimal during noisy decision making (2016, methodology): “, sensory samples of a noisy stimulus, or attributes values for an economic prospect) are accumulated in parallel for two or more alternatives, corrupted by noise that could arise either during encoding or during information integration (28).”
The speed-accuracy tradeoff: history, physiology, methodology, and behavior (2014, background): “Moreover, the slope of the accuracy-latency relationship was altered by task difficulty: when odors were highly similar, the rate of gain of accuracy with RT was much lower than for highly dissimilar, and therefore easier, discriminations (see also Brunton et al., 2013).”
Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification (2015, methodology): “…parameter estimates ˆ θ semi obtained by means of MCPL are essentially in between the corresponding supervised and the optimal estimates: In itself, this result might not seem all too helpful as we can easily come up with a semi-supervised parameter estimate for which these…”
Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework (2016, background): “However, the two sources of noise can be biologically and conceptually quite different [47], and for this reason it is helpful to separate the two types of noise in our formulation.”
Recurrent Network Models of Sequence Generation and Memory. (2016, background): “…activity (Harvey et al., 2012), DPA tasks are useful for exploring the different neural correlates of short-term memory (Gold and Shadlen, 2007; Brunton et al., 2013; Hanks et al., 2015; Amit, 1995; Amit and Brunel, 1995; Hansel and Mato, 2001; Hopﬁeld and Tank, 1985; Shadlen and Newsome,…”
Diffusion Decision Model: Current Issues and History (2016, background): “For example, one study [52] reported that the sole source of variability in decision making by human and animal subjects was external noise in the stimulus; they found no effect of internal noise, or leakage, that is, decay of the memory representation of the stimulus sequence with the passage of ti”
Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task (2015, background): “Further, the huge wealth of tasks involving integration of noisy sensory evidence such as random dot motion discrimination and the Poisson clicks auditory discrimination task [44,46].”