The critical stability task: quantifying sensory-motor control during ongoing movement in nonhuman primates

Abstract

Everyday behaviors require that we interact with the environment, using sensory information in an ongoing manner to guide our actions. Yet, by design, many of the tasks used in primate neurophysiology laboratories can be performed with limited sensory guidance. As a consequence, our knowledge about the neural mechanisms of motor control is largely limited to the feedforward aspects of the motor command. To study the feedback aspects of volitional motor control, we adapted the Critical Stability Task (CST) from the human performance literature (Jex et al. 1966). In the CST, our monkey subjects interact with an inherently unstable (i.e., divergent) virtual system and must generate sensory-guided actions to stabilize it about an equilibrium point. The difficulty of the CST is determined by a single parameter, which allows us to quantitatively establish the limits of performance in the task for different sensory feedback conditions. Two monkeys learned to perform the CST with visual or vibrotactile feedback. Performance was better under visual feedback, as expected, but both monkeys were able to utilize vibrotactile feedback to successfully perform the CST. We also observed changes in behavioral strategy as the task became more challenging. The CST will have value for basic science investigations of the neural basis of sensory-motor integration during ongoing actions, and it may also provide value for the design and testing of bidirectional brain computer interface systems.

Inferring control objectives in a virtual balancing task in humans and monkeys

“…The hand's displacements were recorded by 3D motion capture (Qualisys, Gothenburg), with a reflective marker attached to the hand. The cursor dynamics were generated by a linear first-order dynamical system, relating hand and cursor kinematics as described in Quick et al, 2018: where 𝑥 and 𝑥 are the horizontal cursor position and cursor velocity on the screen, 𝑝 is the horizontal hand position, and 𝜆 is a positive constant fixed at the beginning of each trial. The parameter 𝜆 sets the gain of the system.…”

“…A critical step for bridging insights between human and monkey behavior is through the computational approach that could explain behavior equally well in both human and monkey performance (Badre et al, 2015;Rajalingham et al, 2022). In an earlier attempt of modeling CST, a simple PD controller with delay in sensory feedback was proposed to explain the recorded behavior (Quick et al, 2018). However, the model was limited in its ability to capture most features observed in the data, such as success rate, or correlation between hand and cursor movements.…”

“…The order of difficulty was pseudo-randomly selected for each subject. For this study, we only analyzed the CST data from Block 2 (stepwise increase in λ) as it matched the procedure used in the monkey experiment (Quick et al, 2018). Subjects repeated the same experimental procedure on Day 2 and 3.…”

“…After representing the performance of each subject in the RMS space, the classifier was used to determine what control objective was used in each trial. Figure 8 illustrates the classification results for human subjects who received no instructions (Experiment 1) as well as two monkeys (Monkey I and J from Quick et. al.…”

“…We used an experimental paradigm, the Critical Stability Task (CST), that can be performed by both humans and monkeys (Quick et al, 2018). The CST requires the subject to balance an unstable virtual system governed by a very simple dynamical equation (see Met hods).…”