Psychophysics

Humans’ outstanding ability to interact with the environment, e.g., transporting an object, throwing a ball, typing on a keyboard – depends on accurate and fast integration of motor commands with sensory inputs elicited by physical interactions. Such a combination of signals occurs at different levels of the Central Nervous System, from the spinal cord up to the neocortex. We employ neurophysiological and behavioral methods to gain insights on how sensory cues are merged for motor learning and motor decision making. Furthermore, we use psychophysical approaches to investigate how the combination of motor and sensory signals drives motor control and perception of our body and the world. Below are some examples of our research in this area.

Interaction between visual feedback of object motion and grip force modulation

To prevent objects from slipping, digit grip force is adjusted in synchrony to the load changes induced by hand motion. Due to unavoidable delays in detecting load force modulation by the fingertips, the timing of grip force adjustments need to be planned in an anticipatory fashion by predicting when load peak will occur. This prediction depends on sensorimotor memory (internal models) built through previously-experienced hand-object interactions.

Digit Forces and Perception of Digit Distance

Motivated by our findings on the interplay between sensory cues of digit position and digit force control, we have been investigating whether and how inputs associated with force production elicited at the fingertip drive the estimation of inter-digit distance. This work revealed that, in context of manipulation, digit distance estimation is influenced by the hand used to sense (and reproduce) finger configuration as well as by the distance between the digits in contact with the grasped object.

Muscle activity and Force Perception

Nonlinearity and redundancy of the musculoskeletal system, as well as noise and delays of sensory inputs, challenge sensorimotor integration processes. However, humans have a remarkable ability to produce efficient goal-directed movements and make precise perceptual inference. It has been proposed that to simplify these processes during perceptual decision making, the central nervous system (CNS) select patterns of movements aimed to maximize the sampling of task-related sensory input, i.e., active sensing.