Neural Control of Voluntary Movement Initiation

Abstract

When humans respond to sensory stimulation, their reaction times tend to be long and variable relative to neural transduction and transmission times. The neural processes responsible for the duration and variability of reaction times are not understood. Single-cell recordings in a motor area of the cerebral cortex in behaving rhesus monkeys (Macaca mulatta) were used to evaluate two alternative mathematical models of the processes that underlie reaction times. Movements were initiated if and only if the neural activity reached a specific and constant threshold activation level. Stochastic variability in the rate at which neural activity grew toward that threshold resulted in the distribution of reaction times. This finding elucidates a specific link between motor behavior and activation of neurons in the cerebral cortex.

Saccadic latency distributions in Parkinson’s disease and the effects of l-dopa

“…For example, there are cells within the frontal eye fields of the monkey whose firing rate exhibits rise-tothreshold behaviour in advance of a saccade, and whose rate of rise corresponds closely with saccadic latency (Hanes and Schall 1996).…”

“…The ultimate brain region influenced by L-dopa in this instance is not known, but an appealing candidate is the frontal eye fields, where the firing rate of single neurons in the monkey show rise-to-threshold behaviour in advance of a saccade that correspond closely with LATER's decision signal (Hanes and Schall 1996). Furthermore, in primates, D2 receptor activation can modulate the activity of prefrontal neurons to memory-guided saccades (Wang et al 2004).…”

Two-stage dynamic signal detection: A theory of choice, decision time, and confidence.

“…Provocative results from this area suggest that sequential sampling models like diffusion models are a good representation of the neural mechanisms underlying sensory decisions (Gold & Shadlen, 2007), which appear to be embedded in the sensory-motor circuitry in the brain (Hanes & Schall, 1996;Kim & Shadlen, 1999;Romo, Hernandez, Zainos, Lemus, & Brody, 2002;Shadlen & Newsome, 2001). These results have led to the hypothesis that these sensorymotor areas are the mediating mechanisms for other types of abstract and value-based decisions (Busemeyer, Jessup, Johnson, & Townsend, 2006;Shadlen, Kiani, Hanks, & Churchland, 2008).…”

Neural Models of Bayesian Belief Propagation

“…Figure 11.7E shows the activity of a neuron in the frontal eye fields (FEF) for fast, medium, and slow responses to a visual target [39,40]. Schall and collaborators have shown that the distribution of monkey response times can be reproduced using the time taken by neural activity in FEF to reach a fixed threshold [15]. A similar rise-to-threshold model by Carpenter and colleagues has received strong support in human psychophysical experiments that manipulate the prior probabilities of targets [3] and the urgency of the task [35].…”

“…The posterior probabilities of the unknown variables C, L, and F given the input image I, are calculated by combining the messages at each node as follows: 15) where α, β, and γ are normalization constants that make each of the above probabilities sum to 1. Note how the prior P (L) multiplicatively modulates the posterior probability of a feature in equation 11.15 via equation 11.12.…”