Motor selection dynamics in FEF explain the reaction time variance of saccades to single targets

Abstract

In studies of voluntary movement, a most elemental quantity is the reaction time (RT) between the onset of a visual stimulus and a saccade toward it. However, this RT demonstrates extremely high variability, which in spite of extensive research remains unexplained. It is well established that, when a visual target appears, oculomotor activity gradually builds up until a critical level is reached, at which point a saccade is triggered. Here, we further characterize the dynamics of this rise-to-threshold process based on computational work and single-neuron recordings from the frontal eye field (FEF) of behaving monkeys. We find that the baseline activity, build-up rate, and threshold level show strong, nonlinear co-dependencies that explain the distinct RT distributions observed experimentally. The results indicate that intrinsic randomness contributes little to saccade variance, which results mainly from an intricate, fundamentally deterministic mechanism of motor conflict resolution that has subtle yet highly characteristic manifestations.

Population temporal structure supplements the rate code during sensorimotor transformations

“…Current knowledge points to a role by the OPNs in defining the threshold and controlling saccade initiation (6,38). However, thresholds vary across behavioral paradigms (8,39), raising the question of how the threshold is set in a particular condition. Furthermore, evidence that the threshold changes during the course of a trial purely based on OPN activity is limited; OPN activity increases transiently during the visual burst but only by an additional spike or two and only in a small subset of neurons (38).…”

Discarding optimality: Throwing out the baby with the bathwater?

“…The effects are huge. For example, in our own data (Hauser et al 2018), we found that the reaction time (RT) went from about 150 ± 25 ms (mean ± standard deviation) to about 250 ± 80 ms, with the error rate changing from virtually zero (99.7% right) to about 10% of incorrect saccades. The extraordinary sensitivity of the monkeys to reward asymmetry also manifests in other, low-level behavioral metrics, such as the peak saccade velocity, as well as in the swiftness with which the animals respond to changes in the asymmetry over time.…”

“…When the rewarded location changes, which happens without warning, it takes a single trial for the spatial bias to switch accordingly (when only two locations are used). This rich phenomenology is highly consistent between animals, laboratories, and task variants, and it remains stable for months, even after many thousands of trials of practice (Hauser et al 2018;Hikosaka et al 2006;Takikawa et al 2002;Watanabe et al 2001).…”

How did that individual make that perceptual decision?

“…The 1DR task is deceptively simple (Hauser et al 2018;Hikosaka et al 2006;Lauwereyns et al 2002). The subject (a monkey, in this case) is instructed to perform an elementary action: to look at a lone, clearly visible stimulus.…”

“…In this context, justifying the animals' behavior on the basis of an optimality principle or ideal observer model seems rather unnecessary. Furthermore, in our own laboratory, we recently developed a mechanistic model that replicates the monkeys' RT distributions as well as single-neuron activity in the frontal eye field (FEF) during performance of the 1DR task (Hauser et al 2018). This model explains the observed behavior in great quantitative detail based on dynamical interactions found in FEF.…”