Premotor cortex encoding of dynamic hand force and motor output observation underlying hand-object interaction

We studied encoding of hand force and its relations with observation-related activity in macaques trained in an isometric hand-force application and recalibration task, that required to move a visual cursor on a screen toward eight peripheral targets by exerting a force on an isometric joystick, in absence or presence of an opposing force field. Monkeys also observed the result of their action in play-back, as motion of a visual cursor on the screen. This approach combined in a single experiment isometric action performance and force adjustment with observation of its consequences in the external world, also allowing to determine whether PMd neuronal populations reflected an inverse model that specified the force necessary to move in different directions a visual object, or a forward computation encoding its desired trajectory in visual space. We found that a population of PMd cells encoded the direction of dynamic force and its recalibration when the force condition changed but did not retain memory of such change, probably reflecting an adaptation rather than a learning process. Cells with observation-related activity also modulated by change in hand force were not modulated when the force conditions changed, suggesting that their activity reflected the motion of the visual cursor on the screen, therefore the consequences of force application in the visual space. These results also allow a direct comparison of the relative contribute of different populations of PMd cells with that of cells with similar activity profile in the encoding of hand force and its consequences in the parieto-frontal system

A multi-stage recurrent neural network better describes decision-related activity in dorsal premotor cortex

We studied how a network of recurrently connected artificial units solve a visual perceptual decision-making task. The goal of this task is to discriminate the dominant color of a central static checkerboard and report the decision with an arm movement. This task has been used to study neural activity in the dorsal premotor (PMd) cortex. When a single recurrent neural network (RNN) was trained to perform the task, the activity of artificial units in the RNN differed from neural recordings in PMd, suggesting that inputs to PMd differed from inputs to the RNN. We expanded our architecture and examined how a multi-stage RNN performed the task. In the multi-stage RNN, the last stage exhibited similarities with PMd by representing direction information but not color information. We then investigated how the representation of color and direction information evolve across RNN stages. Together, our results are a demonstration of the importance of incorporating architectural constraints into RNN models. These constraints can improve the ability of RNNs to model neural activity in association areas.https://doi.org/10.32470/CCN.2019.1123-0Accepted manuscrip

The neural correlates of speech motor sequence learning

Speech is perhaps the most sophisticated example of a species-wide movement capability in the animal kingdom, requiring split-second sequencing of approximately 100 muscles in the respiratory, laryngeal, and oral movement systems. Despite the unique role speech plays in human interaction and the debilitating impact of its disruption, little is known about the neural mechanisms underlying speech motor learning. Here, we studied the behavioral and neural correlates of learning new speech motor sequences. Participants repeatedly produced novel, meaningless syllables comprising illegal consonant clusters (e.g., GVAZF) over 2 days of practice. Following practice, participants produced the sequences with fewer errors and shorter durations, indicative of motor learning. Using fMRI, we compared brain activity during production of the learned illegal sequences and novel illegal sequences. Greater activity was noted during production of novel sequences in brain regions linked to non-speech motor sequence learning, including the BG and pre-SMA. Activity during novel sequence production was also greater in brain regions associated with learning and maintaining speech motor programs, including lateral premotor cortex, frontal operculum, and posterior superior temporal cortex. Measures of learning success correlated positively with activity in left frontal operculum and white matter integrity under left posterior superior temporal sulcus. These findings indicate speech motor sequence learning relies not only on brain areas involved generally in motor sequencing learning but also those associated with feedback-based speech motor learning. Furthermore, learning success is modulated by the integrity of structural connectivity between these motor and sensory brain regions.R01 DC007683 - NIDCD NIH HHS; R01DC007683 - NIDCD NIH HH

Visual feedback alters force control and functional activity in the visuomotor network after stroke.

Modulating visual feedback may be a viable option to improve motor function after stroke, but the neurophysiological basis for this improvement is not clear. Visual gain can be manipulated by increasing or decreasing the spatial amplitude of an error signal. Here, we combined a unilateral visually guided grip force task with functional MRI to understand how changes in the gain of visual feedback alter brain activity in the chronic phase after stroke. Analyses focused on brain activation when force was produced by the most impaired hand of the stroke group as compared to the non-dominant hand of the control group. Our experiment produced three novel results. First, gain-related improvements in force control were associated with an increase in activity in many regions within the visuomotor network in both the stroke and control groups. These regions include the extrastriate visual cortex, inferior parietal lobule, ventral premotor cortex, cerebellum, and supplementary motor area. Second, the stroke group showed gain-related increases in activity in additional regions of lobules VI and VIIb of the ipsilateral cerebellum. Third, relative to the control group, the stroke group showed increased activity in the ipsilateral primary motor cortex, and activity in this region did not vary as a function of visual feedback gain. The visuomotor network, cerebellum, and ipsilateral primary motor cortex have each been targeted in rehabilitation interventions after stroke. Our observations provide new insight into the role these regions play in processing visual gain during a precisely controlled visuomotor task in the chronic phase after stroke

Slowed response to peripheral visual stimuli during strenuous exercise

Recently, we proposed that strenuous exercise impairs peripheral visual perception because visual responses to peripheral visual stimuli were slowed during strenuous exercise. However, this proposal was challenged because strenuous exercise is also likely to affect the brain network underlying motor responses. The purpose of the current study was to resolve this issue. Fourteen participants performed a visual reaction-time (RT) task at rest and while exercising at 50% (moderate) and 75% (strenuous) peak oxygen uptake. Visual stimuli were randomly presented at different distances from fixation in two task conditions: the Central condition (2° or 5° from fixation) and the Peripheral condition (30° or 50° from fixation). We defined premotor time as the time between stimulus onset and the motor response, as determined using electromyographic recordings. In the Central condition, premotor time did not change during moderate (167 ± 19 ms) and strenuous (168 ± 24 ms) exercise from that at rest (164 ± 17 ms). In the Peripheral condition, premotor time significantly increased during moderate (181 ± 18 ms, P < 0.05) and strenuous exercise (189 ± 23 ms, P < 0.001) from that at rest (173 ± 17 ms). These results suggest that increases in Premotor Time to the peripheral visual stimuli did not result from an impaired motor-response network, but rather from impaired peripheral visual perception. We conclude that slowed response to peripheral visual stimuli during strenuous exercise primarily results from impaired visual perception of the periphery

Drawing cartoon faces - a functional imaging study of the cognitive neuroscience of drawing

We report a functional imaging study of drawing cartoon faces. Normal, untrained participants were scanned while viewing simple black and white cartoon line-drawings of human faces, retaining them for a short memory interval, and then drawing them without vision of their hand or the paper. Specific encoding and retention of information about the faces was tested for by contrasting these two stages (with display of cartoon faces) against the exploration and retention of random dot stimuli. Drawing was contrasted between conditions in which only memory of a previously viewed face was available versus a condition in which both memory and simultaneous viewing of the cartoon was possible, and versus drawing of a new, previously unseen, face. We show that the encoding of cartoon faces powerfully activates the face sensitive areas of the lateral occipital cortex and the fusiform gyrus, but there is no significant activation in these areas during the retention interval. Activity in both areas was also high when drawing the displayed cartoons. Drawing from memory activates areas in posterior parietal cortex and frontal areas. This activity is consistent with the encoding and retention of the spatial information about the face to be drawn as a visuo-motor action plan, either representing a series of targets for ocular fixation or as spatial targets for the drawing actio

Point-light biological motion perception activates human premotor cortex

Motion cues can be surprisingly powerful in defining objects and events. Specifically, a handful of point-lights attached to the joints of a human actor will evoke a vivid percept of action when the body is in motion. The perception of point-light biological motion activates posterior cortical areas of the brain. On the other hand, observation of others' actions is known to also evoke activity in motor and premotor areas in frontal cortex. In the present study, we investigated whether point-light biological motion animations would lead to activity in frontal cortex as well. We performed a human functional magnetic resonance imaging study on a high-field-strength magnet and used a number of methods to increase signal, as well as cortical surface-based analysis methods. Areas that responded selectively to point-light biological motion were found in lateral and inferior temporal cortex and in inferior frontal cortex. The robust responses we observed in frontal areas indicate that these stimuli can also recruit action observation networks, although they are very simplified and characterize actions by motion cues alone. The finding that even point-light animations evoke activity in frontal regions suggests that the motor system of the observer may be recruited to "fill in" these simplified displays

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke