Decisions based on uncertain information may benefit from an accumulation of information over time. We asked whether such an accumulation process may underlie decisions about the direction of motion in a random dot kinetogram. To address this question we developed a computational model of the decision process using ensembles of neurons whose spiking activity mimics neurons recorded in the extrastriate visual cortex (area MT or V5) and a sensorimotor association area of the parietal lobe (area LIP). The model instantiates the hypothesis that neurons in sensorimotor association areas compute the time integral of sensory signals from the visual cortex, construed as evidence for or against a proposition, and that the decision is made when the integrated evidence reaches a threshold. The model explains a variety of behavioral and physiological measurements obtained from monkeys.
Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (i) decisions that linger tend to arise from less reliable evidence, and (ii) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal cortex (LIP) of rhesus monkeys performing this task.
The stereotyped delivery of sequences of vocalizations by singing zebra finches is thought to be mediated by a “central motor program.” We hypothesized that electrically stimulating, and thus perturbing, the neural components of this motor program during singing should alter the subsequent singing pattern. In contrast, perturbing the activity of other neurons in the song motor pathway that do not participate directly in generating the song temporal pattern should not affect the singing pattern. We found that unilaterally stimulating the forebrain area RA of singing birds with chronically implanted electrodes distorted ongoing syllables without changing the order or timing of ensuing syllables. However, stimulating forebrain area HVc, which projects directly to RA, altered both ongoing syllables and the ensuing song pattern. These findings indicate that syllable sequencing during singing is organized in forebrain areas above RA (including HVc) and that the resulting pattern is imposed on lower structures of the motor pathway. Furthermore, the observation that unilateral forebrain perturbation was sufficient to alter the pattern of this bilaterally organized behavior suggests that (non-auditory) feedback pathways to the forebrain exist to coordinate the two hemispheres during singing. We suggest that the study of the motor control system for birdsong has provided the most direct evidence to date for localizing the programming of a skilled motor sequence to the telencephalon.
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