Experimental and theoretical study of velocity fluctuations during slow movements in humans

Abstract

Moving smoothly is generally considered as a higher-order goal of motor control and moving jerkily as a witness of clumsiness or pathology, yet many common and well-controlled movements (e.g., tracking movements) have irregular velocity profiles with widespread fluctuations. The origin and nature of these fluctuations have been associated with the operation of an intermittent process but in fact remain poorly understood. Here we studied velocity fluctuations during slow movements, using combined experimental and theoretical tools. We recorded arm movement trajectories in a group of healthy participants performing back-and-forth movements at different speeds, and we analyzed velocity profiles in terms of series of segments (portions of velocity between 2 minima). We found that most of the segments were smooth (i.e., corresponding to a biphasic acceleration) and had constant duration irrespective of movement speed and linearly increasing amplitude with movement speed. We accounted for these observations with an optimal feedback control model driven by a staircase goal position signal in the presence of sensory noise. Our study suggests that one and the same control process can explain the production of fast and slow movements, i.e., fast movements emerge from the immediate tracking of a global goal position and slow movements from the successive tracking of intermittently updated intermediate goal positions. NEW & NOTEWORTHY We show in experiments and modeling that slow movements could result from the brain tracking a sequence of via points regularly distributed in time and space. Accordingly, slow movements would differ from fast movement by the nature of the guidance and not by the nature of control. This result could help in understanding the origin and nature of slow and segmented movements frequently observed in brain disorders.

Modulation of ellipses drawing by sonification

“…Taken together, these experiments suggested that, firstly, performing movements at a low speed induces particular constraints on motor control (Guigon et al 2019) and that, secondly, there is a lower limit for the regulation of the frequency of rhythmic movements. Consistent with these findings, Levy-Tzedek also found "that specific combinations of required movement frequency and amplitude give rise to two distinct types of movements: one of a more rhythmic nature, and the other of a more discrete nature" (Levy-Tzedek et al 2010).…”

“…It is now understood that discrete and rhythmic movements are on the same continuum and that the transition from one to the other is speed dependant (Hogan and Sternad 2007). A recent study showed that slow movements, whether discrete (Guigon et al 2019) or rhythmic (Park et al 2017;van der Wel et al 2010) are less regular and involve different control mechanisms. Levy-Tzedek studied how movement amplitude and frequency were modulated together in the voluntary control of movement speed during a rhythmic task (Levy-Tzedek et al 2011;Levy-Tzedek et al 2010).…”

Time-to-Target Simplifies Optimal Control of Visuomotor Feedback Responses

“…In order to better understand this modulation we built four normative models using OFC: a classical finite-horizon OFC (Liu and Todorov (2007)), a finite-horizon time-to-target adjusted OFC, a receding-horizon OFC (Guigon et al (2019)) and an infinite-horizon OFC (Qian et al (2013)). While the classical, receding and infinite horizon models failed to predict the experimental visuomotor feedback response intensities, the time-to-target model qualitatively replicated the visuomotor feedback intensity profile of our participants.…”

“…In addition to our finite horizon control we also implemented a receding horizon controller (Guigon et al (2019)).…”

For Motion Assistance Humans Prefer to Rely on a Robot Rather Than on an Unpredictable Human

“…2C shows that the correlation of signed deviation between TG and HP over all subjects drastically decreases with increasing stiffness. In contrast, the correlation between RP and HP only slightly decreases probably due to the oscillations of force in HPs [19]. The high correlation between the HPs and the RP indicates that the user deviates in the same way when interacting with either of these partner conditions.…”