Ipsilateral finger representations in the sensorimotor cortex are driven by active movement processes, not passive sensory input

Abstract

Hand and finger movements are mostly controlled through crossed corticospinal projections from the contralateral hemisphere. During unimanual movements, activity in the contralateral hemisphere is increased while the ipsilateral hemisphere is suppressed below resting baseline. Despite this suppression, unimanual movements can be decoded from ipsilateral activity alone. This indicates that ipsilateral activity patterns represent parameters of ongoing movement, but the origin and functional relevance of these representations is unclear. In this study, we asked whether ipsilateral representations are caused by active movement or whether they are driven by sensory input. Participants alternated between performing single finger presses and having fingers passively stimulated while we recorded brain activity using high-field (7T) functional imaging. We contrasted active and passive finger representations in sensorimotor areas of ipsilateral and contralateral hemispheres. Finger representations in the contralateral hemisphere were equally strong under passive and active conditions, highlighting the importance of sensory information in feedback control. In contrast, ipsilateral finger representations in the sensorimotor cortex were stronger during active presses. Furthermore, the spatial distribution of finger representations differed between hemispheres: the contralateral hemisphere showed the strongest finger representations in Brodmann areas 3a and 3b, whereas the ipsilateral hemisphere exhibited stronger representations in premotor and parietal areas. Altogether, our results suggest that finger representations in the two hemispheres have different origins: contralateral representations are driven by both active movement and sensory stimulation, whereas ipsilateral representations are mainly engaged during active movement. NEW & NOTEWORTHY Movements of the human body are mostly controlled by contralateral cortical regions. The function of ipsilateral activity during movements remains elusive. Using high-field neuroimaging, we investigated how human contralateral and ipsilateral hemispheres represent active and passive finger presses. We found that representations in contralateral sensorimotor cortex are equally strong during both conditions. Ipsilateral representations were mostly present during active movement, suggesting that sensorimotor areas do not receive direct sensory input from the ipsilateral hand.

Keywords: fMRI; finger movements; ipsilateral; motor; sensory.

Fig. 1.

Apparatus and experimental design. A: keyboard used in the task. The left hand was positioned on a mirror-symmetric keyboard. B: an adjustable foam pillow was sitting on the top of each finger, preventing any overt finger motion. In the active condition, participants pressed one of the keys and the force applied was recorded through the force transducer. In the passive condition, the force was applied to the finger via a pneumatic piston. C: each trial started with a cue denoting which condition and finger are implicated in the trial. This was followed by a warning press to the finger, after which each participant either received 5 finger presses (passive condition) or pressed the key 5 times (active condition). Each trial lasted for a total of 8.2 s. Both active and passive conditions involved only the right hand.

Fig. 2.

Average contralateral evoked activation and distances between finger patterns during active and passive tasks across subfields of sensorimotor cortex. A: evoked activity for the active (red) and passive (blue) conditions on the flattened contralateral cortical surface. The two conditions activated similar cortical areas, with the overlap indicated by purple areas. Regions of interest (ROIs) were defined on the basis of a probabilistic cytoarchitectonic atlas (Fischl et al. 2008), with each node assigned the area of the highest probability. Borders between regions are indicated with white dotted lines. B: percent signal change for active and passive tasks was sampled in a cross section from anterior (BA6) to posterior (BA2), along a rectangular strip with a width of 26 mm. Horizontal red and blue bars indicate significant activation during the active and passive tasks, respectively. *P < 0.0071, significant differences between the activation for active and passive tasks (Bonferroni correction). C: average distance between finger patterns for the active (red) and passive (blue) tasks on the flattened contralateral cortical surface. The two conditions evoked similar distances, which is indicated by the purple overlap. D: distances in the contralateral hemisphere were significantly higher than 0 for both tasks, as indicated by the red and blue bars. There was no difference in distances between the two conditions in any ROI. Shaded areas in B and D reflect the standard error of the group mean (N = 7).

Fig. 3.

Average ipsilateral evoked activation and distances between finger patterns during active and passive tasks across subfields of sensorimotor cortex. A: evoked activity above resting baseline for the two conditions on the flattened ipsilateral hemisphere. B: ipsilateral hemisphere showed suppression of activity below resting baseline around the central sulcus for both conditions, indicated with gray background. BA6 displayed more activation for the active than passive condition, but all other areas responded similarly for the two conditions. C: average passive and active distances in the ipsilateral hemisphere. The active condition elicited higher distances than the passive condition, which is reflected in the predominately red areas, especially in the depth of the central sulcus. D: ipsilateral hemisphere displayed higher distances for the active than the passive task. This difference was significant in areas BA4a, 4p, 3a, and 3b (*P < 0.0071). Shaded areas in B and D reflects the standard error of the group mean (N = 7).

Fig. 4.

Representational dissimilarity matrix for distances between patterns of digit pairs in contralateral and ipsilateral M1 (BA4a and BA4p combined) for passive and active conditions. The distances are averaged across 7 participants. The structure of dissimilarity matrix (see Ejaz et al. 2015) is preserved across hemispheres and conditions.

Fig. 5.

Correlation between finger-specific activity patterns in the active and passive conditions. A: correlation coefficients estimated using pattern component modeling (PCM) for contralateral (solid line) and ipsilateral (dashed line) hemispheres. Note that for ipsilateral area 3b, there was not enough evidence for a finger-specific representation in the passive condition to reliably estimate a correlation coefficient. B: performance of the model with correlation between active and passive patterns unconstrained (flexible correlation model) and the model where the correlation is constrained to be 1 (perfect correlation model); both are expressed relative to a null model (no correlation between active and passive patterns). Although a log-Bayes factor of 1 is considered positive evidence and a log-Bayes factor of 3 as strong model evidence (Kass and Raftery 1995), our log-Bayes factors are likely inflated due to residual dependence between voxels after prewhitening. Therefore, the critical test is whether the group log-Bayes factors are significantly different from 0 in a frequentist (t) test. ns, Not significant. C: percent signal change in active (red) and passive (blue) conditions for contralateral (solid) and ipsilateral (dashed) hemispheres. Error bars are standard error of the group mean (N = 7).