Neural Mechanisms of Speed-Accuracy Tradeoff
Intelligent agents balance speed of responding with accuracy of deciding. Stochastic accumulator models commonly explain this speed-accuracy tradeoff by strategic adjustment of response threshold. Several laboratories identify specific neurons in prefrontal and parietal cortex with this accumulation...
Gespeichert in:
Veröffentlicht in: | Neuron (Cambridge, Mass.) Mass.), 2012-11, Vol.76 (3), p.616-628 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Intelligent agents balance speed of responding with accuracy of deciding. Stochastic accumulator models commonly explain this speed-accuracy tradeoff by strategic adjustment of response threshold. Several laboratories identify specific neurons in prefrontal and parietal cortex with this accumulation process, yet no neurophysiological correlates of speed-accuracy tradeoff have been described. We trained macaque monkeys to trade speed for accuracy on cue during visual search and recorded the activity of neurons in the frontal eye field. Unpredicted by any model, we discovered that speed-accuracy tradeoff is accomplished through several distinct adjustments. Visually responsive neurons modulated baseline firing rate, sensory gain, and the duration of perceptual processing. Movement neurons triggered responses with activity modulated in a direction opposite of model predictions. Thus, current stochastic accumulator models provide an incomplete description of the neural processes accomplishing speed-accuracy tradeoffs. The diversity of neural mechanisms was reconciled with the accumulator framework through an integrated accumulator model constrained by requirements of the motor system.
► Monkeys immediately adjusted speed-accuracy tradeoff (SAT) based on a symbolic cue ► SAT was accomplished by proactive, perceptual, and response changes in distinct neurons ► Results appear to disagree with stochastic accumulator models ► Including an invariant motor threshold reconciles neural activity with accumulator model
Trading speed for accuracy is common in decision making, but the neuronal mechanisms have not been investigated. Heitz and Schall demonstrate proactive, sensory, and motor neurophysiological adjustments in prefrontal cortex. They also show how the findings can be reconciled with computational decision models. |
---|---|
ISSN: | 0896-6273 1097-4199 |
DOI: | 10.1016/j.neuron.2012.08.030 |