Force oscillations underlying precision grip in humans with lesioned corticospinal tracts

Abstract

Stability of precision grip depends on the ability to regulate forces applied by the digits. Increased frequency composition and temporal irregularity of oscillations in the force signal are associated with enhanced force stability, which is thought to result from increased voluntary drive along the corticospinal tract (CST). There is limited knowledge of how these oscillations in force output are regulated in the context of dexterous hand movements like precision grip, which are often impaired by CST damage due to stroke. The extent of residual CST volume descending from primary motor cortex may help explain the ability to modulate force oscillations at higher frequencies. Here, stroke survivors with longstanding hand impairment (n = 17) and neurologically-intact controls (n = 14) performed a precision grip task requiring dynamic and isometric muscle contractions to scale and stabilize forces exerted on a sensor by the index finger and thumb. Diffusion spectrum imaging was used to quantify total white matter volume within the residual and intact CSTs of stroke survivors (n = 12) and CSTs of controls (n = 14). White matter volumes within the infarct region and an analogous portion of overlap with the CST, mirrored onto the intact side, were also quantified in stroke survivors. We found reduced ability to stabilize force and more restricted frequency ranges in force oscillations of stroke survivors relative to controls; though, more broadband, irregular output was strongly related to force-stabilizing ability in both groups. The frequency composition and temporal irregularity of force oscillations observed in stroke survivors did not correlate with maximal precision grip force, suggesting that it is not directly related to impaired force-generating capacity. The ratio of residual to intact CST volumes contained within infarct and mirrored compartments was associated with more broadband, irregular force oscillations in stroke survivors. Our findings provide insight into granular aspects of dexterity altered by corticospinal damage and supply preliminary evidence to support that the ability to modulate force oscillations at higher frequencies is explained, at least in part, by residual CST volume in stroke survivors.

Keywords: Corticospinal tract; Motor control; Precision grip; Stroke; White matter.

Fig. 1

A) Experimental set up and representative force traces from a B) control and C) stroke subject. The solid red line represents the real-time force trace and blue rectangles reflect targets at each target force level. Note that only the targets and red circular cursor (black arrow in A) representing the current force output were visible to the subject. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 2

A) Independent raters manually segmented fibers in DSI Studio. M1 and CST Templates were used as separate regions of interest. Fibers were segmented after seeding in each region of interest, resulting in four segmentations for a given subject per rater. The resulting fibers tracts from Rater 1 and Rater 2 were merged to generate a final tract from which white matter volumes were quantified. B) Representative CSTs from three stroke survivors (subject IDs 4, 14, and 16 from Table 1) and three control subjects. Note the differential loss of white matter among stroke survivors.

Fig. 3

Force stability, as measured by CV, as a function of A) target force level and B) group. Force stability, as measured by RMSE, as a function of C) target force level and D) group. Error bars reflect standard error of the mean (*p < 0.05).

Fig. 4

Relative spectral density as a function of force level for A) control and B) stroke groups. Each line represents the relative power at each force level averaged over all 36 target crossings (2 per force per trial, for 18 trials) across all subjects. Note the elevated relative power at the lower frequency peak (black arrows) in stroke survivors and second peak (black arrows) in controls.

Fig. 5

Force output in frequency (Slope and F95) and time (FuzMEn) domains. Slope as a function of A) force level and B) group is shown in the top panel. F95 as a function of C) force level and D) group is shown in the middle panel. FuzMEn as a function of E) force level and F) group is shown in the bottom panel. Error bars reflect standard error of the mean. (*p < 0.05).

Fig. 6

Scatter plots illustrating results of mixed effects models: force stability (CV, RMSE) vs force output in frequency and time domains (Slope, F95, FuzMEn). The left column contains fitted models for log-CV vs A) Slope, B) log-F95 and C) log-FuzMEn. The right column contains fitted models for log-RMSE vs D) Slope, E) log-F95 and F) log-FuzMEn. Red (control) and blue (stroke) data points correspond to individual target crossings (108 per subject). Red and blue lines reflect the predicted group averaged values for control and stroke groups, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 7

Coronal posterior view of CSTs in representative A) control and B) stroke subjects. The dominant CST is contained within the left hemisphere of the control subject, and the residual CST is contained within the right hemisphere of the stroke survivor (infarct compartment shown in yellow). Bar plots illustrating C) total volume by group (control vs stroke) and CST (dominant vs non-dominant vs residual vs intact); D) compartment volume (left vertical axis) and proportional volume (right vertical axis). (*p < 0.05). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 8

Scatterplots illustrating relation between proportional volume asymmetry and FuzMEn at A) 7%, B) 14% and C) 21% target force levels in stroke survivors.