Sliman J. Bensmaia

A bstract: We are constantly exploring the world around us through touch. Active touch depends on coordination of movement and force, yet the forces used during natural exploration and their relationship with perception is largely unexplored. Here we measured exploration forces together with fingertip motion while 17 participants explored 14 textures and rated their perceived hardness, slipperiness, or roughness. Exploration strategies differed systematically across tasks: hardness judgments involved relatively stationary pressing with larger and more variable normal forces, whereas slipperiness and roughness judgments relied more on sweeping movements. Within tasks, interaction forces covaried with perceptual ratings: harder textures elicited larger maximum tangential forces, consistent with diagonal pressing, while more slippery textures were explored with faster fingertip motion and lower forces. Estimated dynamic friction was negatively correlated with perceived slipperiness but not roughness. At the same time perceived roughness was strongly related to vibrations in the force, indicating distinct physical bases for these perceptual dimensions. These results show that humans actively tailor contact mechanics to perceptual goals during active exploration, supporting a sensorimotor account of texture perception. S ignificance statement: Touch is usually studied as if the skin passively receives information, but in everyday life we actively move and press against objects to recognize them and learn what they feel like. This study measured both fingertip motion and contact forces while people freely explored textures and judged hardness, slipperiness, and roughness – the three of the most salient dimensions of tactile experience. The results show that people adjust how they move and press depending on what they want to perceive, and that different physical signals – friction and vibration – support different texture judgments. This work helps explain touch as an active sensorimotor process, with implications for neuroscience, haptics, robotics, and neuroprosthetics.

Touch plays a key role in our perception of our body and shapes our interactions with the world, from the objects we manipulate to the people we touch. While the tactile sensibility of the hand has been extensively characterized, much less is known about touch on other parts of the body. Despite the important role of the breast in lactation, as well as in affective and sexual touch, relatively little is known about its sensory properties. To fill this gap, we investigated the ability of women to locate touches on the breast and compared it to that of the hand and back, body regions that span the range of tactile discriminative capabilities. First, we found that the tactile precision of the breast was even lower than that of the back, heretofore the paragon of poor precision. Second, precision was lower for breasts that had undergone greater expansion, consistent with the hypothesis that innervation capacity does not scale with body size. Third, touches to different regions of the nipple were largely indistinguishable, suggesting sparse innervation density. Fourth, localization errors were systematically biased toward the nipple.

Touch plays a key role in our perception of our body and shapes our interactions with the world, from the objects we manipulate to the people we touch. While the tactile sensibility of the hand has been extensively characterized, much less is known about touch on other parts of the body. Despite the important role of the breast in lactation as well as in affective and sexual touch, relatively little is known about its sensory properties. To fill this gap, we investigated the ability of women to locate touches on the breast and compared it to that of the hand and back, body regions that span the range of tactile discriminative capabilities. First, we found that the tactile precision of the breast was even lower than that of the back, heretofore the paragon of poor precision. Second, precision was lower for breasts that had undergone greater expansion, consistent with the hypothesis that innervation capacity does not scale with body size. Third, touches to different regions of the nipple were largely indistinguishable, suggesting sparse innervation density. Fourth, localization errors were systematically biased toward the nipple.

A hallmark of primate behavior is the exceptional ability to dexterously grasp and manipulate objects, yet the investigation of the neural mechanisms that support manual dexterity has been hindered by technical challenges. Optical hand tracking is complicated by frequent occlusions, and contact forces are hard to measure with sufficient precision. Furthermore, while monitoring the kinematics during reaching phase, and the contact forces during object manipulation phase is difficult, joint torques are impossible to measure directly. While challenging, the ability to estimate joint torques in the complex primate hand could provide an invaluable continuous mechanical description spanning both phases. With this in mind, we have developed an experimental apparatus and data processing pipeline for quantifying these variables describing prehension. The apparatus presented objects of various sizes and orientations throughout the workspace, evoking different grasping strategies. Object surfaces were instrumented with thousands of pressure-sensitive elements, enabling high-resolution measurement of distributed contact forces. Simultaneously, eight high-speed cameras were used to reconstruct hand and arm movements with markerless tracking, triangulating 3D landmarks, and mapping them onto a musculoskeletal model, enabling estimation of time-varying joint angles. This posture quantification allowed contact forces to be automatically assigned to specific hand segments, in close agreement with manual human annotations. We used the reconstructed movements and contact forces with the musculoskeletal model of the hand to compute inverse dynamics, yielding joint torques throughout behavior, unifying the hand kinematics and grasp forces into a single physical description. Throughout the processing, we identified individual neurons in the motor cortex of monkeys that were related to grasp force, kinematics, and torques. Together, this framework enabled a comprehensive and precise physical characterization of primate manual behavior, providing a foundation for investigating the neural mechanisms of manual dexterity.

Dexterous hand function underlies many essential human activities, from tool use to expression through gestures. Coordinated digit movements are enabled by the intricate musculature of the hand and forearm, which also imposes mechanical coupling between the digits and wrist, constraining their independent control. It remains unclear whether motor cortex inherits these constraints in its activity or encodes digit and wrist independently. To address this problem, we asked individuals with intracortical microelectrode arrays implanted in motor cortex to attempt flexion and extension of individual digits, either in isolation or in combination with attempted wrist movements. We could accurately decode which digit was moving based on cortical recordings, and channels selective for digit identity were arranged somatotopically across the recording arrays. Nevertheless, the activity during flexion or extension overlapped between digits, and movement direction of a given digit could be reliably inferred by a decoder trained on movements of other digits. This directional signal was largely invariant to the digit’s initial posture. The population axis describing digit movement direction was aligned with the axes associated with wrist flexion-extension or pronation-supination. This alignment persisted during simultaneous wrist and digit movements, which complicated efforts to control them individually. However, by decoding wrist and digit motion from activity orthogonal to the shared direction axis, a participant was able to achieve continuous control of virtual hand movements with improved speed and reduced unintended movements. Together, the results identify both a code for digit identity and a low-dimensional flexion-extension signal which is shared across the digits and wrist. This arrangement is consistent with muscle-like biomechanical constraints on motor cortical activity, which must be accounted for to improve coordinated BCI control.

Objective. Intracortical microstimulation (ICMS) of human somatosensory cortex evokes tactile percepts that people describe as originating from their own body, but are not always described as feeling natural. It remains unclear whether stimulation parameters such as amplitude, frequency, and spatiotemporal patterns across electrodes can be chosen to increase the naturalness of these artificial tactile percepts. Approach. In this study, we investigated whether biomimetic stimulation patterns—ICMS patterns that reproduce essential features of natural neural activity—increased the perceived naturalness of ICMS-evoked sensations compared to a non-biomimetic pattern in three people with cervical spinal cord injuries. All participants had electrode arrays implanted in their somatosensory cortices. Rather than qualitatively asking which pattern felt more natural, participants directly compared natural residual percepts, delivered by mechanical indentation on a sensate region of their hand, to artificial percepts evoked by ICMS and were asked whether linear non-biomimetic or biomimetic stimulation felt most like the mechanical indentation. Main results. We show that simple biomimetic ICMS, which modulated the stimulation amplitude on a single electrode, was perceived as being more like a mechanical indentation reference on 32% of the electrodes. We also tested an advanced biomimetic stimulation scheme that captured more of the spatiotemporal dynamics of cortical activity using co-modulated stimulation amplitudes and frequencies across four electrodes. Here, ICMS felt more like the mechanical reference for 75% of the electrode groups. Finally, biomimetic stimulus trains required less charge than their non-biomimetic counterparts to create an intensity-matched sensation. Significance. We conclude that ICMS encoding schemes that mimic naturally occurring neural spatiotemporal activation patterns in the somatosensory cortex feel more like an actual touch than non-biomimetic encoding schemes. This also suggests that using key elements of neuronal activity can be a useful conceptual guide to constrain the large stimulus parameter space when designing future stimulation strategies. This work is a part of Clinical Trial NCT01894802.

Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain–computer interface (BCI) to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays. In five participants with cervical spinal cord injury, across two study locations, this procedure successfully enabled ICMS‐evoked sensations localized to at least the first four digits of the hand. The imaging and planning procedures developed through this clinical trial provide a roadmap for other BCI studies to ensure the successful placement of stimulation electrodes.

Tactile feedback from brain-controlled bionic hands can be partially restored via intracortical microstimulation (ICMS) of the primary somatosensory cortex. In ICMS, the location of percepts depends on the electrode’s location and the percept intensity depends on the stimulation frequency and amplitude. Sensors on a bionic hand can thus be linked to somatotopically appropriate electrodes, and the contact force of each sensor can be used to determine the amplitude of a stimulus. Here we report a systematic investigation of the localization and intensity of ICMS-evoked percepts in three participants with cervical spinal cord injury. A retrospective analysis of projected fields showed that they were typically composed of a focal hotspot with diffuse borders, arrayed somatotopically in keeping with their underlying receptive fields and stable throughout the duration of the study. When testing the participants’ ability to rapidly localize a single ICMS presentation, individual electrodes typically evoked only weak sensations, making object localization and discrimination difficult. However, overlapping projected fields from multiple electrodes produced more localizable and intense sensations and allowed for a more precise use of a bionic hand.

The transition from hand opening to grasping a coffee cup happens smoothly, yet the neural systems underlying this behavior undergo a significant state change at the onset of grasp. At this moment, the motor system begins to control contact forces and the somatosensory system receives a barrage of cutaneous signals that convey information about contact forces and the object’s local features (e.g., edges, texture, and curvature). These cutaneous signals supplement the ongoing flow of proprioceptive input that encodes hand posture as well as muscle forces. How object identity is represented in sensorimotor cortex across this transition remains unknown. In the present study, we sought to quantify the object-specific neural signals in individual neurons of the primary motor cortex (M1) and Brodmann areas 3a, 3b/1, and 2 of the somatosensory cortex in macaque monkeys. Before contact, object-specific information was carried mainly by M1 and proprioceptive area 3a, but this information did not generalize between the periods before and after contact. This observation is consistent with the abruptly changing force signals at contact affecting the assumed postural representation of the object, rather than each modality maintaining an invariant identity. After contact, despite a general decrease in firing rates, information about object identity increased and was encoded with high efficiency across sensorimotor cortex. Cutaneous areas 3b and 1, largely uninformative before contact, became highly informative once objects were grasped. Area 2, which receives both cutaneous and musculotendinous inputs, conveyed little object-specific information before contact, when it too became strongly informative, consistent with its integrative role. Thus, M1 and 3a serve as the main carriers of object information before contact, while cutaneous and integrative somatosensory circuits dominate after contact. This shift highlights the profound change in the coding of object identify in the sensorimotor cortex during contact.

Summary: Understanding how the body is represented in motor cortex is key to understanding how the brain controls movement. The precentral gyrus (PCG) has long been thought to contain largely distinct regions for the arm, leg and face (represented by the “motor homunculus”). However, mounting evidence has begun to reveal a more intermixed, interrelated and broadly tuned motor map. Here, we revisit the motor homunculus using microelectrode array recordings from 20 arrays that broadly sample PCG across 8 individuals, creating a comprehensive map of human motor cortex at single neuron resolution. We found whole-body representations throughout all sampled points of PCG, contradicting traditional leg/arm/face boundaries. We also found two speech-preferential areas with a broadly tuned, orofacial-dominant area in between them, previously unaccounted for by the homunculus. Throughout PCG, movement representations of the four limbs were interlinked, with homologous movements of different limbs (e.g., toe curl and hand close) having correlated representations. Our findings indicate that, while the classic homunculus aligns with each area’s preferred body region at a coarse level, at a finer scale, PCG may be better described as a mosaic of functional zones, each with its own whole-body representation.