Value-based gain control: divisive normalization in parietal cortex

By Kenway Louie, Lauren E Grattan, Paul Glimcher. 2011

281 citations recorded by the source corpus.

The representation of value is a critical component of decision making. Rational choice theory assumes that options are assigned absolute values, independent of the value or existence of other alternatives. However, context-dependent choice behavior in both animals and humans violates this assumption, suggesting that biological decision processes rely on comparative evaluation. Here we show that neurons in the monkey lateral intraparietal cortex encode a relative form of saccadic value, explicitly dependent on the values of the other available alternatives. Analogous to extra-classical receptive field effects in visual cortex, this relative representation incorporates target values outside the response field and is observed in both stimulus-driven activity and baseline firing rates. This context-dependent modulation is precisely described by divisive normalization, indicating that this standard form of sensory gain control may be a general mechanism of cortical computation. Such normalization in decision circuits effectively implements an adaptive gain control for value coding and provides a possible mechanistic basis for behavioral context-dependent violations of rationality.

Subfields: Cognitive Neuroscience

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Citations in the corpus

Attention, learning and the value of information (2012, result): “Similar results are obtained in tasks that manipulate the desirability of a target using different methods, for example by controlling the relative magnitude, probability or delay of its expected reward (Bernacchia et al., 2011; Louie et al., 2011; Sugrue et al., 2004; Yang and Shadlen, 2007).”
Neuronal Reward and Decision Signals: From Theories to Data. (2015, background): “Divisive normalization from sensory physiology describes well the adaptations to changes in individual values of choice options in reward neurons of parietal cortex (332).”
Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback (2014, background): “, 2011), attention mechanisms (Reynolds & Heeger, 2009; Treue, 2001), and decision making (Louie et al., 2011; Louie & Glimcher, 2012).”
The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value (2013, unknown): “We have assumed for simplicity that zero corresponds to no outcome at all, but there is evidence that decision makers actually evaluate outcomes relative to a reference point based either on predictions (Montague et al., 1996) or concurrent context (Louie et al., 2011).”