Dataset Information

Motor cortical activity changes during neuroprosthetic-controlled object interaction.

ABSTRACT: Brain-computer interface (BCI) controlled prosthetic arms are being developed to restore function to people with upper-limb paralysis. This work provides an opportunity to analyze human cortical activity during complex tasks. Previously we observed that BCI control became more difficult during interactions with objects, although we did not quantify the neural origins of this phenomena. Here, we investigated how motor cortical activity changed in the presence of an object independently of the kinematics that were being generated using intracortical recordings from two people with tetraplegia. After identifying a population-wide increase in neural firing rates that corresponded with the hand being near an object, we developed an online scaling feature in the BCI system that operated without knowledge of the task. Online scaling increased the ability of two subjects to control the robotic arm when reaching to grasp and transport objects. This work suggests that neural representations of the environment, in this case the presence of an object, are strongly and consistently represented in motor cortex but can be accounted for to improve BCI performance.

SUBMITTER: Downey JE

PROVIDER: S-EPMC5717217 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Motor cortical activity changes during neuroprosthetic-controlled object interaction.

Downey John E JE Brane Lucas L Gaunt Robert A RA Tyler-Kabara Elizabeth C EC Boninger Michael L ML Collinger Jennifer L JL

Scientific reports 20171205 1

Brain-computer interface (BCI) controlled prosthetic arms are being developed to restore function to people with upper-limb paralysis. This work provides an opportunity to analyze human cortical activity during complex tasks. Previously we observed that BCI control became more difficult during interactions with objects, although we did not quantify the neural origins of this phenomena. Here, we investigated how motor cortical activity changed in the presence of an object independently of the kin ...[more]

PMID: 29209023

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Project description:Interactions between the ventral premotor (PMv) and the primary motor cortex (M1) are crucial for transforming an object's geometrical properties, such as its size and shape, into a motor command suitable for grasp of the object. Recently, we showed that PMv interacts with M1 in a specific fashion, depending on the hand posture. However, the functional connectivity between PMv and M1 during the preparation of an actual grasp is still unknown. To address this issue, PMv-M1 interactions were tested while subjects were preparing to grasp different visible objects requiring either a precision grip or a whole hand grasp. A conditioning-test transcranial magnetic stimulation (TMS) paradigm was used: a test stimulus was applied over M1 either in isolation or after a conditioning stimulus delivered, at different delays, over the ipsilateral PMv. Motor evoked potentials (MEPs) were recorded in the first dorsal interosseus and abductor digiti minimi muscles, which show highly differentiated activity according to grasp. While subjects prepared to grasp, delivering a conditioning PMv pulse 6 or 8msec before a test pulse over M1 strikingly facilitated MEPs in the specific muscles that were used in the upcoming grasp. This degree of facilitation correlated with the amount of muscle activity used later in the trial to grasp the objects. The present results demonstrate that, during grasp preparation, the PMv-M1 interactions are muscle-specific. PMv appears to process the object geometrical properties relevant for the upcoming grasp, and transmits this information to M1, which in turn generates a motor command appropriate for the grasp. We also reveal that the grasp-specific facilitation resulting from PMv-M1 interactions is differently related to the upcoming grasp muscle activity than is that from paired-pulse stimulation over M1, suggesting that these two TMS paradigms assess the excitability of cortico-cortical pathways devoted to the control of grasp at two different levels.

Project description:The task of parceling perceived visual motion into self- and object motion components is critical to safe and accurate visually guided navigation. In this paper, we used functional magnetic resonance imaging to determine the cortical areas functionally active in this task and the pattern connectivity among them to investigate the cortical regions of interest and networks that allow subjects to detect object motion separately from induced self-motion. Subjects were presented with nine textured objects during simulated forward self-motion and were asked to identify the target object, which had an additional, independent motion component toward or away from the observer. Cortical activation was distributed among occipital, intra-parietal and fronto-parietal areas. We performed a network analysis of connectivity data derived from partial correlation and multivariate Granger causality analyses among functionally active areas. This revealed four coarsely separated network clusters: bilateral V1 and V2; visually responsive occipito-temporal areas, including bilateral LO, V3A, KO (V3B) and hMT; bilateral VIP, DIPSM and right precuneus; and a cluster of higher, primarily left hemispheric regions, including the central sulcus, post-, pre- and sub-central sulci, pre-central gyrus, and FEF. We suggest that the visually responsive networks are involved in forming the representation of the visual stimulus, while the higher, left hemisphere cluster is involved in mediating the interpretation of the stimulus for action. Our main focus was on the relationships of activations during our task among the visually responsive areas. To determine the properties of the mechanism corresponding to the visual processing networks, we compared subjects' psychophysical performance to a model of object motion detection based solely on relative motion among objects and found that it was inconsistent with observer performance. Our results support the use of scene context (e.g., eccentricity, depth) in the detection of object motion. We suggest that the cortical activation and visually responsive networks provide a potential substrate for this computation.

Dataset Information

Motor cortical activity changes during neuroprosthetic-controlled object interaction.

Publications

Motor cortical activity changes during neuroprosthetic-controlled object interaction.

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