Tessellation of artificial touch via microstimulation of human somatosensory cortex

Abstract

When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin. To provide intuitive location information, tactile sensors on the robotic hand drive ICMS through electrodes that evoke sensations at skin locations matching sensor locations. This approach requires that ICMS-evoked sensations be focal, stable, and distributed over the hand. To systematically investigate the localization of ICMS-evoked sensations, we analyzed the projected fields (PFs) of ICMS-evoked sensations - their location and spatial extent - from reports obtained over multiple years from three participants implanted with microelectrode arrays in S1. First, we found that PFs vary widely in their size across electrodes, are highly stable within electrode, are distributed over large swaths of each participant's hand, and increase in size as the amplitude or frequency of ICMS increases. Second, while PF locations match the locations of the receptive fields (RFs) of the neurons near the stimulating electrode, PFs tend to be subsumed by the corresponding RFs. Third, multi-channel stimulation gives rise to a PF that reflects the conjunction of the PFs of the component channels. By stimulating through electrodes with largely overlapping PFs, then, we can evoke a sensation that is experienced primarily at the intersection of the component PFs. To assess the functional consequence of this phenomenon, we implemented multichannel ICMS-based feedback in a bionic hand and demonstrated that the resulting sensations are more localizable than are those evoked via single-channel ICMS.

Figure 1.. Array implant locations and sensation maps for all participants.

Left column: Anatomical MRI with (subsequently implanted) arrays superimposed whose location is based on intra-operative photos. M1 and S1 denote primary motor cortex and somatosensory cortex (Brodmann’s area 1), respectively. The central sulcus is indicated by the dashed line. Middle and right columns: The hand region on which ICMS-sensations are experienced along with the electrodes that evoked those sensations. Each row shows data from one participant.

Figure 2.. Projected field locations systematically vary in size and location across electrodes and participants.

A| Example projected fields from one session from each participant. Crosses denote the respective centroids. B| The same projected fields as in panel A but across all sessions. C| The density function computed for the same electrodes across all sessions. D| Hand regions over which each participant reported a sensation across all electrodes. The lighter shade indicates pixels selected on <33% of sessions while the darker shade indicates pixels selected on >33% of sessions. E| The area of the hand over which a sensation was evoked (union of PFs across electrodes, after thresholding) for each participant. F| The distribution of individual PF sizes (after thresholding) for each participant.

Figure 3.. Projected field locations are stable over time.

A| Distance between the centroid of the single-day PF and the aggregate centroid for each electrode, averaged across electrodes. The line denotes the mean and the shaded area the standard deviation. B| Mean distance between single day PF centroid and aggregate PF centroid for each electrode. Mean distance increases with the size of the PF. Dashed line denotes best fit. C| Mean centroid distance when reports were collected within a single day compared to that computed across years for a subset of electrodes. Dashed line denotes unity.

Figure 4.. PFs progress systematically across electrodes.

A| Classification performance vs. the angle of the projection axis, expressed relative to the local curvature of S1. The ability to infer digit or palmar segment identity based on position along a single axis depends on the angle of that axis. B| Optimal digit/palmar segment discrimination axis (perpendicular to the projection axis), superimposed on each S1 array (dotted line). The dashed line denotes the local curvature of S1, which, for C1, deviates from the curvature of the central sulcus. C| Within digit, the distance between two PF centroids is significantly correlated with the distance between the electrodes (n = 5892 pairs, r = 0.69, p < 0.01) and this relationship is observed for each array individually (r > 0.4, p < 0.01).

Figure 5.. The projected field of an electrode is smaller than and circumscribed by its receptive field.

A| Aggregate PF (red) and RF (blue) for two example electrodes from participant C1 (left) and P3 (right), respectively. The hue of each denotes the proportion of times a pixel was included in the PF or RF. B| Size of the RF vs. size of the PF for electrodes from which both were obtained in participants C1 and P3. Receptive fields were larger for both participants (paired t-test, p < 0.01 for both). Dashed line shows unity. C| Proportion of the PF that fell within the RF for all tested electrodes. The median proportion was 1 for both with 25^th percentiles of 0.83 and 0.72 for C1 and P3, respectively, suggesting that PFs tended to be completely subsumed by the RF. D| Number of regions (digits and palm) encapsulated by each electrode’s RF minus the number of regions encapsulated by its PF for 3 participants (N = 62, 25, 21 for participants C1, P3, and R1, respectively). Multiple electrodes are shown for each participant. RFs spanned more hand regions than PFs in all 3 participants (Wilcoxon rank sum test, p < 0.01, Holm-Bonferroni corrected).

Figure 6.. PF size and sensory magnitude increase with ICMS amplitude and frequency.

A| Normalized ratings of sensory magnitude and PF size vs. ICMS amplitude (with frequency fixed at 100 Hz). The size of the PF for each electrode and condition was normalized by the mean PF across conditions. B| Normalized ratings of sensory magnitude and PF size vs. ICMS frequency (with amplitude fixed at 60 μA). Both frequency and amplitude significantly impact perceived size and intensity (2-way ANOVA, p< 0.01 for all). C| The effect of ICMS amplitude and frequency on PF size can be accounted for by the latter’s impact on sensory magnitude (r = 0.77, p < 0.01). Data from participant C1.

Figure 7.. Projected fields with multi-channel stimulation are additive.

A, B| Two example projected fields predicted from the union of two individual channels versus the reported field when the two channels were stimulated simultaneously. C| Correlation between the additive model and observed projected field versus a null model where two random channels were chosen. The additive model significantly outperformed the null model (2-sample Kolmogorov-Smirnov test, D = 0.86, p < 0.01). Data from participant C1.

Figure 8. Multi-channel ICMS evokes more localizable sensations than does single-electrode ICMS.

A| Task setup for robotic digit localization task. The participant was blindfolded while an experimenter randomly squeezed individual prosthetic digits or pairs of digits. B| Consolidated performance of robotic and open loop localization tasks. Multi-electrode stimulation evokes more localizable sensations (2-sample t-test, t(236) = 21.6, p < 0.01) Note that trials where the participant failed to detect stimulation are excluded here to reduce confounding localization performance with detectability. Data from participant C1.