Multimodal Interactions between Proprioceptive and Cutaneous Signals in Primary Somatosensory Cortex

Primary somatosensory cortex organization for engineering artificial somatosensation

Somatosensory deficits from stroke, spinal cord injury, or other neurologic damage can lead to a significant degree of functional impairment. The primary (SI) and secondary (SII) somatosensory cortices encode information in a medial to lateral organization. SI is generally organized topographically, with more discrete cortical representations of specific body regions. SII regions corresponding to anatomical areas are less discrete and may represent a more functional rather than topographic organization. Human somatosensory research continues to map cortical areas of sensory processing with efforts primarily focused on hand and upper extremity information in SI. However, research into SII and other body regions is lacking. In this review, we synthesize the current state of knowledge regarding the cortical organization of human somatosensation and discuss potential applications for brain computer interface. In addition to accurate individualized mapping of cortical somatosensation, further research is required to uncover the neurophysiological mechanisms of how somatosensory information is encoded in the cortex.

Biases in hand perception are driven by somatosensory computations, not a distorted hand model

To sense and interact with objects in the environment, we effortlessly configure our fingertips at desired locations. It is therefore reasonable to assume that the underlying control mechanisms rely on accurate knowledge about the structure and spatial dimensions of our hand and fingers. This intuition, however, is challenged by years of research showing drastic biases in the perception of finger geometry.1,2,3,4,5 This perceptual bias has been taken as evidence that the brain's internal representation of the body's geometry is distorted,6 leading to an apparent paradox regarding the skillfulness of our actions.7 Here, we propose an alternative explanation of the biases in hand perception-they are the result of the Bayesian integration of noisy, but unbiased, somatosensory signals about finger geometry and posture. To address this hypothesis, we combined Bayesian reverse engineering with behavioral experimentation on joint and fingertip localization of the index finger. We modeled the Bayesian integration either in sensory or in space-based coordinates, showing that the latter model variant led to biases in finger perception despite accurate representation of finger length. Behavioral measures of joint and fingertip localization responses showed similar biases, which were well fitted by the space-based, but not the sensory-based, model variant. The space-based model variant also outperformed a distorted hand model with built-in geometric biases. In total, our results suggest that perceptual distortions of finger geometry do not reflect a distorted hand model but originate from near-optimal Bayesian inference on somatosensory signals.

Task-driven neural network models predict neural dynamics of proprioception

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.

Irregularity of instantaneous gamma frequency in the motor control network characterize visuomotor and proprioceptive information processing

Objective.The study aims to characterize movements with different sensory goals, by contrasting the neural activity involved in processing proprioceptive and visuo-motor information. To accomplish this, we have developed a new methodology that utilizes the irregularity of the instantaneous gamma frequency parameter for characterization.Approach.In this study, eight essential tremor patients undergoing an awake deep brain stimulation implantation surgery repetitively touched the clinician's finger (forward visually-guided/FV movement) and then one's own chin (backward proprioceptively-guided/BP movement). Neural electrocorticographic recordings from the motor (M1), somatosensory (S1), and posterior parietal cortex (PPC) were obtained and band-pass filtered in the gamma range (30-80 Hz). The irregularity of the inter-event intervals (IEI; inverse of instantaneous gamma frequency) were examined as: (1) auto-information of the IEI time series and (2) correlation between the amplitude and its proceeding IEI. We further explored the network connectivity after segmenting the FV and BP movements by periods of accelerating and decelerating forces, and applying the IEI parameter to transfer entropy methods.Main results.Conceptualizing that the irregularity in IEI reflects active new information processing, we found the highest irregularity in M1 during BP movement, highest in PPC during FV movement, and the lowest during rest at all sites. Also, connectivity was the strongest from S1 to M1 and from S1 to PPC during FV movement with accelerating force and weakest during rest.Significance. We introduce a novel methodology that utilize the instantaneous gamma frequency (i.e. IEI) parameter in characterizing goal-oriented movements with different sensory goals, and demonstrate its use to inform the directional connectivity within the motor cortical network. This method successfully characterizes different movement types, while providing interpretations to the sensory-motor integration processes.

From Multisensory Integration to Multisensory Decision-Making

Organisms live in a dynamic environment in which sensory information from multiple sources is ever changing. A conceptually complex task for the organisms is to accumulate evidence across sensory modalities and over time, a process known as multisensory decision-making. This is a new concept, in terms of that previous researches have been largely conducted in parallel disciplines. That is, much efforts have been put either in sensory integration across modalities using activity summed over a duration of time, or in decision-making with only one sensory modality that evolves over time. Recently, a few studies with neurophysiological measurements emerge to study how different sensory modality information is processed, accumulated, and integrated over time in decision-related areas such as the parietal or frontal lobes in mammals. In this review, we summarize and comment on these studies that combine the long-existed two parallel fields of multisensory integration and decision-making. We show how the new findings provide insight into our understanding about neural mechanisms mediating multisensory information processing in a more complete way.

Beyond sense-specific processing: decoding texture in the brain from touch and sonified movement

Texture, a fundamental object attribute, is perceived through multisensory information including touch and auditory cues. Coherent perceptions may rely on shared texture representations across different senses in the brain. To test this hypothesis, we delivered haptic textures coupled with a sound synthesizer to generate real-time textural sounds. Participants completed roughness estimation tasks with haptic, auditory, or bimodal cues in an MRI scanner. Somatosensory, auditory, and visual cortices were all activated during haptic and auditory exploration, challenging the traditional view that primary sensory cortices are sense-specific. Furthermore, audio-tactile integration was found in secondary somatosensory (S2) and primary auditory cortices. Multivariate analyses revealed shared spatial activity patterns in primary motor and somatosensory cortices, for discriminating texture across both modalities. This study indicates that primary areas and S2 have a versatile representation of multisensory textures, which has significant implications for how the brain processes multisensory cues to interact more efficiently with our environment.

Nonadditive integration of visual information in ensemble processing

Statistically summarizing information from a stimulus array into an ensemble representation (e.g., the mean) improves the efficiency of visual processing. However, little is known about how the brain computes the ensemble statistics. Here, we propose that ensemble processing is realized by nonadditive integration, rather than linear averaging, of individual items. We used a linear regression model approach to extract EEG responses to three levels of information: the individual items, their local interactions, and their global interaction. The local and global interactions, representing nonadditive integration of individual items, elicited rapid and independent neural responses. Critically, only the neural representation of the global interaction predicted the precision of the ensemble perception at the behavioral level. Furthermore, spreading attention over the global pattern to enhance ensemble processing directly promoted rapid neural representation of the global interaction. Taken together, these findings advocate a global, nonadditive mechanism of ensemble processing in the brain.

Mediolateral Postural Control Mechanisms and Proprioception Improve With Kicking Sports Training During Adolescence

Sensorimotor stimulation during the sensitive period is crucial for proper brain development. Kicking sports (KS) training stimulates these sensorimotor functions. The purpose of this study was to investigate if incorporating specific sensorimotor stimulation in mediolateral axis and proprioceptive inputs during KS training will improve the specific sensorimotor performance in adolescents. We assessed stability limits in 13 KS practitioners and 20 control participants. Starting from an upright position, subjects were asked to lean as far as possible (forward, backward, rightward, and leftward). Three sensory conditions were tested: (1) eyes open, (2) eyes closed, and (3) eyes closed while standing on a foam mat. We analyzed the maximal center of pressure excursion and the root means square of the center of pressure displacements. Results showed that KS group had smaller root means square and larger maximal center of pressure excursions than those of control participants in mediolateral axis in all sensory conditions. Furthermore, the results also revealed a significant smaller root means square excursion in KS group under foam mat condition compared to control group ML axis. This study provides evidence that KS training improved the lateral balance control and proprioceptive integration.

Sensory weighting of position and force feedback during pinching

Human hands are complex biomechanical systems that allow for dexterous tasks with many degrees of freedom. Coordination of the fingers is essential for many activities of daily living and involves integrating sensory signals. During this sensory integration, the central nervous system deals with the uncertainty of sensory signals. When handling compliant objects, force and position are related. Interactions with stiff objects result in reduced position changes and increased force changes compared to compliant objects. Literature has shown sensory integration of force and position at the shoulder. Nevertheless, differences in sensory requirements between proximal and distal joints may lead to different proprioceptive representations, hence findings at proximal joints cannot be directly transferred to distal joints, such as the digits. Here, we investigate the sensory integration of force and position during pinching. A haptic manipulator rendered a virtual spring with adjustable stiffness between the index finger and the thumb. Participants had to blindly reproduce a force against the spring. In both visual reference trials and blind reproduction trials, the relation between pinch force and spring compression was constant. However, by covertly changing the spring characteristics in catch trials into an adjusted force-position relation, the participants' weighting of force and position could be revealed. In agreement with previous studies on the shoulder, participants relied more on force sense in trials with higher stiffness. This study demonstrated stiffness-dependent sensory integration of force and position feedback during pinching.

Multi-finger receptive field properties in primary somatosensory cortex: A revised account of the spatiotemporal integration functions of area 3b

The leading view in the somatosensory system indicates that area 3b serves as a cortical relay site that primarily encodes (cutaneous) tactile features limited to individual digits. Our recent work argues against this model by showing that area 3b cells can integrate both cutaneous and proprioceptive information from the hand. Here, we further test the validity of this model by studying multi-digit (MD) integration properties in area 3b. In contrast to the prevailing view, we show that most cells in area 3b have a receptive field (RF) that extends to multiple digits, with the size of the RF (i.e., the number of responsive digits) increasing across time. Further, we show that MD cells' orientation angle preference is highly correlated across digits. Taken together, these data show that area 3b plays a larger role in generating neural representations of tactile objects, as opposed to just being a "feature detector" relay site.

In the back of your mind: Cortical mapping of paraspinal afferent inputs

Topographic organisation is a hallmark of vertebrate cortex architecture, characterised by ordered projections of the body's sensory surfaces onto brain systems. High-resolution functional magnetic resonance imaging (fMRI) has proven itself as a valuable tool to investigate the cortical landscape and its (mal-)adaptive plasticity with respect to various body part representations, in particular extremities such as the hand and fingers. Less is known, however, about the cortical representation of the human back. We therefore validated a novel, MRI-compatible method of mapping cortical representations of sensory afferents of the back, using vibrotactile stimulation at varying frequencies and paraspinal locations, in conjunction with fMRI. We expected high-frequency stimulation to be associated with differential neuronal activity in the primary somatosensory cortex (S1) compared with low-frequency stimulation and that somatosensory representations would differ across the thoracolumbar axis. We found significant differences between neural representations of high-frequency and low-frequency stimulation and between representations of thoracic and lumbar paraspinal locations, in several bilateral S1 sub-regions, and in regions of the primary motor cortex (M1). High-frequency stimulation preferentially activated Brodmann Area (BA) regions BA3a and BA4p, whereas low-frequency stimulation was more encoded in BA3b and BA4a. Moreover, we found clear topographic differences in S1 for representations of the upper and lower back during high-frequency stimulation. We present the first neurobiological validation of a method for establishing detailed cortical maps of the human back, which might serve as a novel tool to evaluate the pathological significance of neuroplastic changes in clinical conditions such as chronic low back pain.

Development of a spontaneous pain indicator based on brain cellular calcium using deep learning

Chronic pain remains an intractable condition in millions of patients worldwide. Spontaneous ongoing pain is a major clinical problem of chronic pain and is extremely challenging to diagnose and treat compared to stimulus-evoked pain. Although extensive efforts have been made in preclinical studies, there still exists a mismatch in pain type between the animal model and humans (i.e., evoked vs. spontaneous), which obstructs the translation of knowledge from preclinical animal models into objective diagnosis and effective new treatments. Here, we developed a deep learning algorithm, designated AI-bRNN (Average training, Individual test-bidirectional Recurrent Neural Network), to detect spontaneous pain information from brain cellular Ca²⁺ activity recorded by two-photon microscopy imaging in awake, head-fixed mice. AI-bRNN robustly determines the intensity and time points of spontaneous pain even in chronic pain models and evaluates the efficacy of analgesics in real time. Furthermore, AI-bRNN can be applied to various cell types (neurons and glia), brain areas (cerebral cortex and cerebellum) and forms of somatosensory input (itch and pain), proving its versatile performance. These results suggest that our approach offers a clinically relevant, quantitative, real-time preclinical evaluation platform for pain medicine, thereby accelerating the development of new methods for diagnosing and treating human patients with chronic pain.

A microscopy technique coupled with an artificial intelligence (AI) platform could help researchers discover new types of pain-relief medicines. A team from South Korea led by Sun Kwang Kim of Kyung Hee University and Sang Jeong Kim of Seoul National University created a machine-learning algorithm that converts calcium signaling data in the brain, as estimated via imaging on genetically engineered mice, into a measurement of pain intensity. The researchers applied the technique to several mouse models of chronic pain and showed that it accurately captured the analgesic effects of known painkillers. They also extended the system to multiple brain regions, cell types and another brain-controlled sensory process, itch. The researchers propose using the AI-based tool to evaluate candidate anti-pain and anti-itch medicines ahead of human trials.

Human muscle spindles are wired to function as controllable signal-processing devices

Muscle spindles are encapsulated sensory organs found in most of our muscles. Prevalent models of sensorimotor control assume the role of spindles is to reliably encode limb posture and movement. Here, I argue that the traditional view of spindles is outdated. Spindle organs can be tuned by spinal γ motor neurons that receive top-down and peripheral input, including from cutaneous afferents. A new model is presented, viewing γ motor activity as an intermediate coordinate transformation that allows multimodal information to converge on spindles, creating flexible coordinate representations at the level of the peripheral nervous system. That is, I propose that spindles play a unique overarching role in the nervous system: that of a peripheral signal-processing device that flexibly facilitates sensorimotor performance, according to task characteristics. This role is compatible with previous findings and supported by recent studies with naturalistically active humans. Such studies have so far shown that spindle tuning enables the independent preparatory control of reflex muscle stiffness, the selective extraction of information during implicit motor adaptation, and for segmental stretch reflexes to operate in joint space. Incorporation of advanced signal-processing at the periphery may well prove a critical step in the evolution of sensorimotor control theories.

Ensemble size perception: Its neural signature and the role of global interaction over individual items

To efficiently process complex visual scenes, the visual system often summarizes statistical information across individual items and represents them as an ensemble. However, due to the lack of techniques to disentangle the representation of the ensemble from that of the individual items constituting the ensemble, whether there exists a specialized neural mechanism for ensemble processing and how ensemble perception is computed in the brain remain unknown. To address these issues, we used a frequency-tagging EEG approach to track brain responses to periodically updated ensemble sizes. Neural responses tracking the ensemble size were detected in parieto-occipital electrodes, revealing a global and specialized neural mechanism of ensemble size perception. We then used the temporal response function to isolate neural responses to the individual sizes and their interactions. Notably, while the individual sizes and their local and global interactions were encoded in the EEG signals, only the global interaction contributed directly to the ensemble size perception. Finally, distributed attention to the global stimulus pattern enhanced the neural signature of the ensemble size, mainly by modulating the neural representation of the global interaction between all individual sizes. These findings advocate a specialized, global neural mechanism of ensemble size perception and suggest that global interaction between individual items contributes to ensemble perception.

Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields

For cortical motor activity, the relationships between different body part representations is unknown. Through reciprocal body part relationships, functionality of cortical motor areas with respect to whole body motor control can be characterized. In the current study, we investigate the relationship between body part representations within individual neuronal populations in motor cortices, following a 7 Tesla fMRI 18-body-part motor experiment in combination with our newly developed non-rigid population Response Field (pRF) model and graph theory. The non-rigid pRF metrics reveal somatotopic structures in all included motor cortices covering frontal, parietal, medial and insular cortices and that neuronal populations in primary sensorimotor cortex respond to fewer body parts than secondary motor cortices. Reciprocal body part relationships are estimated in terms of uniqueness, clique-formation, and influence. We report unique response profiles for the knee, a clique of body parts surrounding the ring finger, and a central role for the shoulder and wrist. These results reveal associations among body parts from the perspective of the central nervous system, while being in agreement with intuitive notions of body part usage.

Neural representation in M1 and S1 cortex of bilateral hand actions during prehension

Bimanual movements that require coordinated actions of the two hands may be coordinated by synchronous bilateral activation of somatosensory and motor cortical areas in both hemispheres, by enhanced activation of individual neurons specialized for bimanual actions, or by both mechanisms. To investigate cortical neural mechanisms that mediate unimanual and bimanual prehension, we compared actions of the left and right hands in a reach to grasp-and-pull instructed-delay task. Spike trains were recorded with multiple electrode arrays placed in the hand area of primary motor (M1) and somatosensory (S1) cortex of the right hemisphere in macaques, allowing us to measure and compare the relative timing, amplitude, and synchronization of cortical activity in these areas as animals grasped and manipulated objects that differed in shape and location. We report that neurons in the right hemisphere show common task-related firing patterns for the two hands but actions of the ipsilateral hand elicited weaker and shorter-duration responses than those of the contralateral hand. We report significant bimanual activation of neurons in M1 but not in S1 cortex when animals have free choice of hand use in prehension tasks. Population ensemble responses in M1 thereby provide an accurate depiction of hand actions during skilled manual tasks. These studies also demonstrate that somatosensory cortical areas serve important cognitive and motor functions in skilled hand actions. Bilateral representation of hand actions may serve an important role in "motor equivalence" when the same movements are performed by either hand and in transfer of skill learning between the hands.NEW & NOTEWORTHY Humans can manipulate small objects with the right or left hand but typically select the dominant hand to handle them. We trained monkeys to grasp and manipulate objects with either hand, while recording neural activity in primary motor (M1) and somatosensory (S1) cortex. Actions of both hands activate M1 neurons, but S1 neurons respond only to the contralateral hand. Bilateral sensitivity in M1 may aid skill transfer between hands after stroke or head injury.

Global surface features contribute to human haptic roughness estimations

Previous studies have paid special attention to the relationship between local features (e.g., raised dots) and human roughness perception. However, the relationship between global features (e.g., curved surface) and haptic roughness perception is still unclear. In the present study, a series of roughness estimation experiments was performed to investigate how global features affect human roughness perception. In each experiment, participants were asked to estimate the roughness of a series of haptic stimuli that combined local features (raised dots) and global features (sinusoidal-like curves). Experiments were designed to reveal whether global features changed their haptic roughness estimation. Furthermore, the present study tested whether the exploration method (direct, indirect, and static) changed haptic roughness estimations and examined the contribution of global features to roughness estimations. The results showed that sinusoidal-like curved surfaces with small periods were perceived to be rougher than those with large periods, while the direction of finger movement and indirect exploration did not change this phenomenon. Furthermore, the influence of global features on roughness was modulated by local features, regardless of whether raised-dot surfaces or smooth surfaces were used. Taken together, these findings suggested that an object’s global features contribute to haptic roughness perceptions, while local features change the weight of the contribution that global features make to haptic roughness perceptions.

Control of Mammalian Locomotion by Somatosensory Feedback

When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. © 2021 American Physiological Society. Compr Physiol 11:1-71, 2021.

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

The interaction between motion and texture in the sense of touch

Besides providing information on elementary properties of objects, like texture, roughness, and softness, the sense of touch is also important in building a representation of object movement and the movement of our hands. Neural and behavioral studies shed light on the mechanisms and limits of our sense of touch in the perception of texture and motion, and of its role in the control of movement of our hands. The interplay between the geometrical and mechanical properties of the touched objects, such as shape and texture, the movement of the hand exploring the object, and the motion felt by touch, will be discussed in this article. Interestingly, the interaction between motion and textures can generate perceptual illusions in touch. For example, the orientation and the spacing of the texture elements on a static surface induces the illusion of surface motion when we move our hand on it or can elicit the perception of a curved trajectory during sliding, straight hand movements. In this work we present a multiperspective view that encompasses both the perceptual and the motor aspects, as well as the response of peripheral and central nerve structures, to analyze and better understand the complex mechanisms underpinning the tactile representation of texture and motion. Such a better understanding of the spatiotemporal features of the tactile stimulus can reveal novel transdisciplinary applications in neuroscience and haptics.

An Emergent Population Code in Primary Auditory Cortex Supports Selective Attention to Spectral and Temporal Sound Features

Textbook descriptions of primary sensory cortex (PSC) revolve around single neurons' representation of low-dimensional sensory features, such as visual object orientation in primary visual cortex (V1), location of somatic touch in primary somatosensory cortex (S1), and sound frequency in primary auditory cortex (A1). Typically, studies of PSC measure neurons' responses along few (one or two) stimulus and/or behavioral dimensions. However, real-world stimuli usually vary along many feature dimensions and behavioral demands change constantly. In order to illuminate how A1 supports flexible perception in rich acoustic environments, we recorded from A1 neurons while rhesus macaques (one male, one female) performed a feature-selective attention task. We presented sounds that varied along spectral and temporal feature dimensions (carrier bandwidth and temporal envelope, respectively). Within a block, subjects attended to one feature of the sound in a selective change detection task. We found that single neurons tend to be high-dimensional, in that they exhibit substantial mixed selectivity for both sound features, as well as task context. We found no overall enhancement of single-neuron coding of the attended feature, as attention could either diminish or enhance this coding. However, a population-level analysis reveals that ensembles of neurons exhibit enhanced encoding of attended sound features, and this population code tracks subjects' performance. Importantly, surrogate neural populations with intact single-neuron tuning but shuffled higher-order correlations among neurons fail to yield attention- related effects observed in the intact data. These results suggest that an emergent population code not measurable at the single-neuron level might constitute the functional unit of sensory representation in PSC.SIGNIFICANCE STATEMENT The ability to adapt to a dynamic sensory environment promotes a range of important natural behaviors. We recorded from single neurons in monkey primary auditory cortex (A1), while subjects attended to either the spectral or temporal features of complex sounds. Surprisingly, we found no average increase in responsiveness to, or encoding of, the attended feature across single neurons. However, when we pooled the activity of the sampled neurons via targeted dimensionality reduction (TDR), we found enhanced population-level representation of the attended feature and suppression of the distractor feature. This dissociation of the effects of attention at the level of single neurons versus the population highlights the synergistic nature of cortical sound encoding and enriches our understanding of sensory cortical function.

Evoking highly focal percepts in the fingertips through targeted stimulation of sulcal regions of the brain for sensory restoration

Background:

Paralysis and neuropathy, affecting millions of people worldwide, can be accompanied by significant loss of somatosensation. With tactile sensation being central to achieving dexterous movement, brain-computer interface (BCI) researchers have used intracortical and cortical surface electrical stimulation to restore somatotopically-relevant sensation to the hand. However, these approaches are restricted to stimulating the gyral areas of the brain. Since representation of distal regions of the hand extends into the sulcal regions of human primary somatosensory cortex (S1), it has been challenging to evoke sensory percepts localized to the fingertips.

Objective/hypothesis:

Targeted stimulation of sulcal regions of S1, using stereoelectroencephalography (SEEG) depth electrodes, can evoke focal sensory percepts in the fingertips.

Methods:

Two participants with intractable epilepsy received cortical stimulation both at the gyri via high-density electrocorticography (HD-ECoG) grids and in the sulci via SEEG depth electrode leads. We characterized the evoked sensory percepts localized to the hand.

Results:

We show that highly focal percepts can be evoked in the fingertips of the hand through sulcal stimulation. fMRI, myelin content, and cortical thickness maps from the Human Connectome Project elucidated specific cortical areas and sub-regions within S1 that evoked these focal percepts. Within-participant comparisons showed that percepts evoked by sulcal stimulation via SEEG electrodes were significantly more focal (80% less area; p = 0.02) and localized to the fingertips more often, than by gyral stimulation via HD-ECoG electrodes. Finally, sulcal locations with consistent modulation of high-frequency neural activity during mechanical tactile stimulation of the fingertips showed the same somatotopic correspondence as cortical stimulation.

Conclusions:

Our findings indicate minimally invasive sulcal stimulation via SEEG electrodes could be a clinically viable approach to restoring sensation.

Distinct patterns of activity in individual cortical neurons and local networks in primary somatosensory cortex of mice evoked by square-wave mechanical limb stimulation

Artificial forms of mechanical limb stimulation are used within multiple fields of study to determine the level of cortical excitability and to map the trajectory of neuronal recovery from cortical damage or disease. Square-wave mechanical or electrical stimuli are often used in these studies, but a characterization of sensory-evoked response properties to square-waves with distinct fundamental frequencies but overlapping harmonics has not been performed. To distinguish between somatic stimuli, the primary somatosensory cortex must be able to represent distinct stimuli with unique patterns of activity, even if they have overlapping features. Thus, mechanical square-wave stimulation was used in conjunction with regional and cellular imaging to examine regional and cellular response properties evoked by different frequencies of stimulation. Flavoprotein autofluorescence imaging was used to map the somatosensory cortex of anaesthetized C57BL/6 mice, and in vivo two-photon Ca2+ imaging was used to define patterns of neuronal activation during mechanical square-wave stimulation of the contralateral forelimb or hindlimb at various frequencies (3, 10, 100, 200, and 300 Hz). The data revealed that neurons within the limb associated somatosensory cortex responding to various frequencies of square-wave stimuli exhibit stimulus-specific patterns of activity. Subsets of neurons were found to have sensory-evoked activity that is either primarily responsive to single stimulus frequencies or broadly responsive to multiple frequencies of limb stimulation. High frequency stimuli were shown to elicit more population activity, with a greater percentage of the population responding and greater percentage of cells with high amplitude responses. Stimulus-evoked cell-cell correlations within these neuronal networks varied as a function of frequency of stimulation, such that each stimulus elicited a distinct pattern that was more consistent across multiple trials of the same stimulus compared to trials at different frequencies of stimulation. The variation in cortical response to different square-wave stimuli can thus be represented by the population pattern of supra-threshold Ca2+ transients, the magnitude and temporal properties of the evoked activity, and the structure of the stimulus-evoked correlation between neurons.

Chemotherapy-induced functional changes of the default mode network in patients with lung cancer

Previous studies have demonstrated that cognitive impairment is associated with neurophysiological changes in lung cancer following chemotherapy. This study aimed to investigate the intrinsic functional connectivity (FC) pattern within the default mode network (DMN) and its associations with cognitive impairment in patients with lung cancer revealed by resting-state functional magnetic resonance imaging (fMRI). Resting-state fMRI scans were acquired from 21 post-chemotherapy and 27 non-chemotherapy lung cancer patients and 30 healthy controls. All groups were age, gender and education-matched. The posterior cingulate cortex (PCC) was chosen as the seed region to detect the FC patterns and then determine whether these changes were related with specific cognitive performance. Compared with non-chemotherapy lung cancer patients, chemotherapy patients revealed decreased FC between the PCC and the right anterior cingulate cortex (ACC), left inferior parietal lobule (IPL), and left medial prefrontal cortex (mPFC), as well as increased FC with the left postcentral gyrus (PoCG). Relative to healthy controls, post-chemotherapy patients exhibited reduced FC between the PCC and the left ACC and left temporal lobe, as well as increased FC with the right PoCG. Moreover, the decreased FC of the PCC to bilateral ACC in post-chemotherapy patients was positively associated with reduced MoCA scores (left: r = 0.529, p = 0.029; right: r = 0.577, p = 0.015). The current study mainly demonstrated reduced resting-state FC pattern within the DMN regions that was linked with impaired cognitive function in lung cancer patients after chemotherapy. These findings illustrated the potential role of the DMN in lung cancer patients that will provide novel insight into the underlying neuropathological mechanisms in chemotherapy-induced cognitive impairment.

Mesoscale hierarchical organization of primary somatosensory cortex captured by resting-state-fMRI in humans

The primary somatosensory cortex (S1) plays a key role in the processing and integration of afferent somatosensory inputs along an anterior-to-posterior axis, contributing towards necessary human function. It is believed that anatomical connectivity can be used to probe hierarchical organization, however direct characterization of this principle in-vivo within humans remains elusive. Here, we use resting-state functional connectivity as a complement to anatomical connectivity to investigate topographical principles of human S1. We employ a novel approach to examine mesoscopic variations of functional connectivity, and demonstrate a topographic organisation spanning the region's hierarchical axis that strongly correlates with underlying microstructure while tracing along architectonic Brodmann areas. Our findings characterize anatomical hierarchy of S1 as a 'continuous spectrum' with evidence supporting a functional boundary between areas 3b and 1. The identification of this topography bridges the gap between structure and connectivity, and may be used to help further current understanding of sensorimotor deficits.

An elasticity-curvature illusion decouples cutaneous and proprioceptive cues in active exploration of soft objects

Our sense of touch helps us encounter the richness of our natural world. Across a myriad of contexts and repetitions, we have learned to deploy certain exploratory movements in order to elicit perceptual cues that are salient and efficient. The task of identifying optimal exploration strategies and somatosensory cues that underlie our softness perception remains relevant and incomplete. Leveraging psychophysical evaluations combined with computational finite element modeling of skin contact mechanics, we investigate an illusion phenomenon in exploring softness; where small-compliant and large-stiff spheres are indiscriminable. By modulating contact interactions at the finger pad, we find this elasticity-curvature illusion is observable in passive touch, when the finger is constrained to be stationary and only cutaneous responses from mechanosensitive afferents are perceptible. However, these spheres become readily discriminable when explored volitionally with musculoskeletal proprioception available. We subsequently exploit this phenomenon to dissociate relative contributions from cutaneous and proprioceptive signals in encoding our percept of material softness. Our findings shed light on how we volitionally explore soft objects, i.e., by controlling surface contact force to optimally elicit and integrate proprioceptive inputs amidst indiscriminable cutaneous contact cues. Moreover, in passive touch, e.g., for touch-enabled displays grounded to the finger, we find those spheres are discriminable when rates of change in cutaneous contact are varied between the stimuli, to supplant proprioceptive feedback.

Different activation signatures in the primary sensorimotor and higher-level regions for haptic three-dimensional curved surface exploration

Haptic object perception begins with continuous exploratory contact, and the human brain needs to accumulate sensory information continuously over time. However, it is still unclear how the primary sensorimotor cortex (PSC) interacts with these higher-level regions during haptic exploration over time. This functional magnetic resonance imaging (fMRI) study investigates time-dependent haptic object processing by examining brain activity during haptic 3D curve and roughness estimations. For this experiment, we designed sixteen haptic stimuli (4 kinds of curves × 4 varieties of roughness) for the haptic curve and roughness estimation tasks. Twenty participants were asked to move their right index and middle fingers along the surface twice and to estimate one of the two features-roughness or curvature-depending on the task instruction. We found that the brain activity in several higher-level regions (e.g., the bilateral posterior parietal cortex) linearly increased as the number of curves increased during the haptic exploration phase. Surprisingly, we found that the contralateral PSC was parametrically modulated by the number of curves only during the late exploration phase but not during the early exploration phase. In contrast, we found no similar parametric modulation activity patterns during the haptic roughness estimation task in either the contralateral PSC or in higher-level regions. Thus, our findings suggest that haptic 3D object perception is processed across the cortical hierarchy, whereas the contralateral PSC interacts with other higher-level regions across time in a manner that is dependent upon the features of the object.

Anisotropic Psychophysical Trends in the Discrimination of Tactile Direction in a Precision Grip

Tactile cues arising from interactions with objects have a sense of directionality which affects grasp. Low latency responses to varied grip perturbations indicate that grasp safety margins are exaggerated in certain directions and conditions. In a grip with the ulnar-radial axis vertical, evidence suggests that distal and downward directions are more sensitive to task parameters and have larger safety margins. This suggests that, for the purpose of applying forces with the fingers, reference frames with respect to the hand and gravity are both in operation. In this experiment, we examined human sensitivities to the direction of tactile movement in the context of precision grip in orientations either orthogonal to or parallel to gravity. Subjects performed a two-alternative-forced-choice task involving a textured cube which moved orthogonal to their grip axis. Subjects' arms were placed in a brace that allowed for finger movement but minimized arm movement. Movement of thumb and index joints were monitored via PhaseSpace motion capture. The subject was presented with a textured cube and instructed to lightly grasp the cube, as if it were slipping. In each trial the object was first translated 1 cm in 0° (proximal), 90° (radial), 180° (distal), or 270° (ulnar) and returned to its origin. This primary stimulus was immediately followed by a 10 mm secondary stimulus at a random 5° interval between -30° and 30° of the primary stimulus. Response from the subject after each pair of stimuli indicated whether the test direction felt the same as or different from the primary stimulus. Traditional bias and sensitivity analyses did not provide conclusive results but suggested that performance is best in the ulnar-radial axis regardless of gravity. Modeling of the response curve generated a detection threshold for each primary stimulus. Lower thresholds, indicating improved detection, persisted in the ulnar-radial axis. Anisotropic thresholds of increased detection appear to coincide with digit displacement and appear to be independent of the grasp orientation.

Abnormal white matter microstructure along the thalamus fiber pathways in women with primary dysmenorrhea

Primary dysmenorrhea (PDM) is a cyclic menstrual pain in the absence of pelvic anomalies, and women with PDM have an increased sensitivity to pain than the internal and external areas associated with menstrual pain. However, the brain abnormality in the ascending pain pathways in dysmenorrhea remains largely unclear. As the thalamus plays a significant role in transmission of nociceptive input, we examined whether white matter microstructure of the thalamus-related fiber tracts obtained by DTI in women with PDM (n = 47) differs from healthy controls. A novel tractography atlas-based analysis method that detects tract integrity and altered microstructural properties along selected fibers was employed. The fiber bundles of interest contained the thalamus- primary somatosensory cortex (SI), thalamus- dorsal anterior cingulate cortex (dACC)/supplementary motor area (SMA), thalamus-insula, and thalamus-ACC. As compared with controls, abnormal white matter microstructures were found along the thalamus-related white matter fiber tracts. Additionally, the intensity of menstrual pain was significantly associated with diffusion measures of thalamus-SI fiber connections. Our study suggested that the thalamus-related pain processing pathways had altered white matter integrity that persisted beyond the time of menstruation, and the white matter microstructure of the thalamus-SI pathways was closely related to menstrual pain in the intensity by women with PDM.

Changes in the Organization of the Secondary Somatosensory Cortex While Processing Lumbar Proprioception and the Relationship With Sensorimotor Control in Low Back Pain

OBJECTIVES

Patients with nonspecific low back pain (NSLBP) rely more on the ankle compared with the lower back proprioception while standing, perform sit-to-stand-to-sit (STSTS) movements slower, and exhibit perceptual impairments at the lower back. However, no studies investigated whether these sensorimotor impairments relate to a reorganization of the primary and secondary somatosensory cortices (S1 and S2) and primary motor cortex (M1) during proprioceptive processing.

MATERIALS AND METHODS

Proprioceptive stimuli were applied at the lower back and ankle muscles during functional magnetic resonance imaging in 15 patients with NSLBP and 13 controls. The location of the activation peaks during the processing of proprioception within S1, S2, and M1 were determined and compared between groups. Proprioceptive use during postural control was evaluated, the duration to perform 5 STSTS movements was recorded, and participants completed the Fremantle Back Awareness Questionnaire (FreBAQ) to assess back-specific body perception.

RESULTS

The activation peak during the processing of lower back proprioception in the right S2 was shifted laterally in the NSLBP group compared with the healthy group (P=0.007). Moreover, patients with NSLSP performed STSTS movements slower (P=0.018), and reported more perceptual impairments at the lower back (P<0.001). Finally, a significant correlation between a more lateral location of the activation peak during back proprioceptive processing and a more disturbed body perception was found across the total group (ρ=0.42, P=0.025).

CONCLUSIONS

The results suggest that patients with NSLBP show a reorganization of the higher-order processing of lower back proprioception, which could negatively affect spinal control and body perception.

Decoding hand kinematics from population responses in sensorimotor cortex during grasping

OBJECTIVE

The hand-a complex effector comprising dozens of degrees of freedom of movement-endows us with the ability to flexibly, precisely, and effortlessly interact with objects. The neural signals associated with dexterous hand movements in primary motor cortex (M1) and somatosensory cortex (SC) have received comparatively less attention than have those associated with proximal upper limb control.

APPROACH

To fill this gap, we trained two monkeys to grasp objects varying in size and shape while tracking their hand postures and recording single-unit activity from M1 and SC. We then decoded their hand kinematics across tens of joints from population activity in these areas.

MAIN RESULTS

We found that we could accurately decode kinematics with a small number of neural signals and that different cortical fields carry different amounts of information about hand kinematics. In particular, neural signals in rostral M1 led to better performance than did signals in caudal M1, whereas Brodmann's area 3a outperformed areas 1 and 2 in SC. Moreover, decoding performance was higher for joint angles than joint angular velocities, in contrast to what has been found with proximal limb decoders.

SIGNIFICANCE

We conclude that cortical signals can be used for dexterous hand control in brain machine interface applications and that postural representations in SC may be exploited via intracortical stimulation to close the sensorimotor loop.

Neural representations of haptic object size in the human brain revealed by multivoxel fMRI patterns

The brain must interpret sensory input from diverse receptor systems to estimate object properties. Much has been learned about the brain mechanisms behind these processes in vision, but our understanding of haptic perception remains less clear. Here we examined haptic judgments of object size, which require integrating multiple cutaneous and proprioceptive afferent signals, as a model problem. To identify candidate human brain regions that support this process, participants (n = 16) in an event-related functional MRI experiment grasped objects to categorize them as one of four sizes. Object sizes were calibrated psychophysically to be equally distinct for each participant. We applied representational similarity logic to whole brain, multivoxel searchlight analyses to identify brain regions that exhibit size-relevant voxelwise activity patterns. Of particular interest was to identify regions for which more similar sizes produce more similar patterns of activity, which constitutes evidence of a metric size code. Regions of the intraparietal sulcus and the lateral prefrontal cortex met this criterion, both within hands and across hands. We suggest that these regions compute representations of haptic size that abstract over the specific peripheral afferent signals generated in a grasp. Results of a matched visual size task, performed by the same participants and analyzed in the same fashion, identified similar regions, indicating that these representations may be partly modality general. We consider these results with respect to perspectives on magnitude estimation in general and to computational views on perceptual signal integration.NEW & NOTEWORTHY Our understanding of the neural basis of haptics (perceiving the world through touch) remains incomplete. We used functional MRI to study human haptic judgments of object size, which require integrating multiple afferent signals. Multivoxel pattern analyses identified intraparietal and prefrontal regions that encode size haptically in a metric and hand-invariant fashion. Effector-independent haptic size estimates are useful on their own and in combination with other sensory estimates for a variety of perceptual and motor tasks.

Time-dependent Cues Encode the Minimum Exploration Time in Discriminating Naturalistic Compliances

Our perception of compliance is informed by multi-dimensional tactile cues. Compared with stationary cues at terminal contact, time-dependent cues may afford optimal efficiency, speed, and fidelity. In this work, we investigate strategies by which temporal cues may encode compliances by modulating our exploration time. Two potential perceptual strategies are considered, inspired by memory representations within and between explorations. For either strategy, we introduce a unique computational approach. First, a curve similarity analysis, of accumulating touch force between sequentially explored compliances, generates a minimum time for discrimination. Second, a Kalman filtering approach derives a recognition time from progressive integration of stiffness estimates over time within a single exploration. Human-subjects experiments are conducted for both single finger touch and pinch grasp. The results indicate that for either strategy, by employing a more natural pinch grasp, time-dependent cues afford greater efficiency by reducing the exploration time, especially for harder objects. Moreover, compared to single finger touch, pinch grasp improves discrimination rates in judging plum ripeness. The time-dependent strategies as defined here appear promising, and may tie with the time-scales over which we make perceptual judgments.

Sensory information from a slipping object elicits a rapid and automatic shoulder response

Humans have the remarkable ability to hold, grasp, and manipulate objects. Previous work has reported rapid and coordinated reactions in hand and shoulder muscles in response to external perturbations to the arm during object manipulation; however, little is known about how somatosensory feedback of an object slipping in the hand influences responses of the arm. We built a handheld device to stimulate the sensation of slipping at all five fingertips. The device was integrated into an exoskeleton robot that supported it against gravity. The setup allowed us to decouple somatosensory stimulation in the fingers from forces applied to the arm, two variables that are highly interdependent in real-world scenarios. Fourteen participants performed three experiments in which we measured their arm feedback responses during slip stimulation. Slip stimulations were applied horizontally in one of two directions, and participants were instructed to either follow the slip direction or move the arm in the opposite direction. Participants showed shoulder muscle responses within ∼67 ms of slip onset when following the direction of slip but significantly slower responses when instructed to move in the opposite direction. Shoulder responses were modulated by the speed but not the distance of the slip. Finally, when slip stimulation was combined with mechanical perturbations to the arm, we found that sensory information from the fingertips significantly modulated the shoulder feedback responses. Overall, the results demonstrate the existence of a rapid feedback system that stabilizes handheld objects.NEW & NOTEWORTHY We tested whether the sensation of an object slipping from the fingers modulates shoulder feedback responses. We found rapid shoulder feedback responses when participants were instructed to follow the slip direction with the arm. Shoulder responses following mechanical joint perturbations were also potentiated when combined with slipping. These results demonstrate the existence of fast and automatic feedback responses in the arm in reaction to sensory input to the fingertips that maintain grip on handheld objects.

Low Back Pain: The Potential Contribution of Supraspinal Motor Control and Proprioception

Motor control, which relies on constant communication between motor and sensory systems, is crucial for spine posture, stability and movement. Adaptions of motor control occur in low back pain (LBP) while different motor adaption strategies exist across individuals, probably to reduce LBP and risk of injury. However, in some individuals with LBP, adapted motor control strategies might have long-term consequences, such as increased spinal loading that has been linked with degeneration of intervertebral discs and other tissues, potentially maintaining recurrent or chronic LBP. Factors contributing to motor control adaptations in LBP have been extensively studied on the motor output side, but less attention has been paid to changes in sensory input, specifically proprioception. Furthermore, motor cortex reorganization has been linked with chronic and recurrent LBP, but underlying factors are poorly understood. Here, we review current research on behavioral and neural effects of motor control adaptions in LBP. We conclude that back pain-induced disrupted or reduced proprioceptive signaling likely plays a pivotal role in driving long-term changes in the top-down control of the motor system via motor and sensory cortical reorganization. In the outlook of this review, we explore whether motor control adaptations are also important for other (musculoskeletal) pain conditions.

The role of BTBD9 in the cerebral cortex and the pathogenesis of restless legs syndrome

Restless legs syndrome (RLS) is a nocturnal neurological disorder affecting up to 10% of the population. It is characterized by an urge to move and uncomfortable sensations in the legs which can be relieved by movements. Mutations in BTBD9 may confer a higher risk of RLS. We developed Btbd9 knockout mice as an animal model. Functional alterations in the cerebral cortex, especially the sensorimotor cortex, have been found in RLS patients in several imaging studies. However, the role of cerebral cortex in the pathogenesis of RLS remains unclear. To explore this, we used in vivo manganese-enhanced MRI and found that the Btbd9 knockout mice had significantly increased neural activities in the primary somatosensory cortex (S1) and the rostral piriform cortex. Morphometry study revealed a decreased thickness in a part of S1 representing the hindlimb (S1HL) and M1. The electrophysiological recording showed Btbd9 knockout mice had enhanced short-term plasticity at the corticostriatal terminals to D1 medium spiny neurons (MSNs). Furthermore, we specifically knocked out Btbd9 in the cerebral cortex of mice (Btbd9 cKO). The Btbd9 cKO mice showed a rest-phase specific motor restlessness, decreased thermal sensation, and a thinner S1HL and M1. Both Btbd9 knockout and Btbd9 cKO exhibited motor deficits. Our results indicate that systematic BTBD9 deficiency leads to both functional and morphometrical changes of the cerebral cortex, and an alteration in the corticostriatal pathway to D1 MSNs. Loss of BTBD9 only in the cerebral cortex is sufficient to cause similar phenotypes as observed in the Btbd9 complete knockout mice.

Somatosensory interactions reveal feature-dependent computations

Our ability to perceive and discriminate textures is based on the processing of high-frequency vibrations generated on the fingertip as it scans across a surface. Although much is known about the processing of vibration amplitude and frequency information when cutaneous stimulation is experienced at a single location on the body, how these stimulus features are processed when touch occurs at multiple locations is poorly understood. We evaluated participants’ ability to discriminate tactile cues (100–300 Hz) on one hand while they ignored distractor cues experienced on their other hand. We manipulated the relative positions of the hands to characterize how limb position influenced cutaneous touch interactions. In separate experiments, participants judged either the frequency or intensity of mechanical vibrations. We found that vibrations experienced on one hand always systematically modulated the perception of vibrations on the other hand. Notably, bimanual interaction patterns and their sensitivity to hand locations differed according to stimulus feature. Somatosensory interactions in intensity perception were only marked by attenuation that was invariant to hand position manipulations. In contrast, interactions in frequency perception consisted of both bias and sensitivity changes that were more pronounced when the hands were held in close proximity. We implemented models to infer the neural computations that mediate somatosensory interactions in the intensity and frequency dimensions. Our findings reveal obligatory and feature-dependent somatosensory interactions that may be supported by both feature-specific and feature-general operations.

NEW & NOTEWORTHY Little is known about the neural computations mediating feature-specific sensory interactions between the hands. We show that vibrations experienced on one hand systematically modulate the perception of vibrations felt on the other hand. Critically, interaction patterns and their dependence on the relative positions of the hands differed depending on whether participants judged vibration intensity or frequency. These results, which we recapitulate with models, imply that somatosensory interactions are mediated by feature-dependent neural computations.

Roles of Force Cues and Proprioceptive Joint Angles in Active Exploration of Compliant Objects

We employ distinct exploratory procedures to improve our perceptual judgments of an object's properties. For instance, with respect to compliance, we exert pressure against a resisting force. The present work investigates ties between strategies for active control of the finger and resultant cues by which compliances may be discriminated. In particular, we employ elastic spheres that co-vary in compliance and radius, as these generate non-differentiable contact areas and are discriminable only in active touch with proprioceptive inputs. During human-subjects psychophysical experiments, we measure touch force, fingertip displacement, and joint kinematics. Two active touch paradigms are used, with and without a force constraint. First, in behaviorally-controlled situations that make force cues non-useful, the results indicate that participants can employ a force-matching strategy between the compliant objects and rely upon displacement-related cues to differentiate them. We show these cues are directly tied to a proprioception mechanism, specifically, the angle of the MCP joint. However, in the fully active paradigm, participants control displacements instead and discriminate via force-related cues. Similar to prior findings in passive touch, we find that force-related cues, likewise, are used in active touch for the optimal and efficient discrimination of compliant objects.

Motor modules account for active perception of force

Despite longstanding evidence suggesting a relation between action and perception, the mechanisms underlying their integration are still unclear. It has been proposed that to simplify the sensorimotor integration processes underlying active perception, the central nervous system (CNS) selects patterns of movements aimed at maximizing sampling of task-related sensory input. While previous studies investigated the action-perception loop focusing on the role of higher-level features of motor behavior (e.g., kinematic invariants, effort), the present study explored and quantified the contribution of lower-level organization of motor control. We tested the hypothesis that the coordinated recruitment of group of muscles (i.e., motor modules) engaged to counteract an external force contributes to participants’ perception of the same force. We found that: 1) a model describing the modulation of a subset of motor modules involved in the motor task accounted for about 70% of participants’ perceptual variance; 2) an alternative model, incompatible with the motor modules hypothesis, accounted for significantly lower variance of participants’ detection performance. Our results provide empirical evidence of the potential role played by muscle activation patterns in active perception of force. They also suggest that a modular organization of motor control may mediate not only coordination of multiple muscles, but also perceptual inference.

Touch as an auxiliary proprioceptive cue for movement control

Recent studies extended the classical view that touch is mainly devoted to the perception of the external world. Perceptual tasks where the hand was stationary demonstrated that cutaneous stimuli from contact with objects provide the illusion of hand displacement. Here, we tested the hypothesis that touch provides auxiliary proprioceptive feedback for guiding actions. We used a well-established perceptual phenomenon to dissociate the estimates of reaching direction from touch and musculoskeletal proprioception. Participants slid their fingertip on a ridged plate to move toward a target without any visual feedback on hand location. Tactile motion estimates were biased by ridge orientation, inducing a systematic deviation in hand trajectories in accordance with our hypothesis. Results are in agreement with an ideal observer model, where motion estimates from different somatosensory cues are optimally integrated for the control of movement. These outcomes shed new light on the interplay between proprioception and touch in active tasks.

Putting the "Sensory" Into Sensorimotor Control: The Role of Sensorimotor Integration in Goal-Directed Hand Movements After Stroke

Integration of sensory and motor information is one-step, among others, that underlies the successful production of goal-directed hand movements necessary for interacting with our environment. Disruption of sensorimotor integration is prevalent in many neurologic disorders, including stroke. In most stroke survivors, persistent paresis of the hand reduces function and overall quality of life. Current rehabilitative methods are based on neuroplastic principles to promote motor learning that focuses on regaining motor function lost due to paresis, but the sensory contributions to motor control and learning are often overlooked and currently understudied. There is a need to evaluate and understand the contribution of both sensory and motor function in the rehabilitation of skilled hand movements after stroke. Here, we will highlight the importance of integration of sensory and motor information to produce skilled hand movements in healthy individuals and individuals after stroke. We will then discuss how compromised sensorimotor integration influences relearning of skilled hand movements after stroke. Finally, we will propose an approach to target sensorimotor integration through manipulation of sensory input and motor output that may have therapeutic implications.

Neural Networks for Modeling Neural Spiking in S1 Cortex

Somatosensation is composed of two distinct modalities: touch, arising from sensors in the skin, and proprioception, resulting primarily from sensors in the muscles, combined with these same cutaneous sensors. In contrast to the wealth of information about touch, we know quite less about the nature of the signals giving rise to proprioception at the cortical level. Likewise, while there is considerable interest in developing encoding models of touch-related neurons for application to brain machine interfaces, much less emphasis has been placed on an analogous proprioceptive interface. Here we investigate the use of Artificial Neural Networks (ANNs) to model the relationship between the firing rates of single neurons in area 2, a largely proprioceptive region of somatosensory cortex (S1) and several types of kinematic variables related to arm movement. To gain a better understanding of how these kinematic variables interact to create the proprioceptive responses recorded in our datasets, we train ANNs under different conditions, each involving a different set of input and output variables. We explore the kinematic variables that provide the best network performance, and find that the addition of information about joint angles and/or muscle lengths significantly improves the prediction of neural firing rates. Our results thus provide new insight regarding the complex representations of the limb motion in S1: that the firing rates of neurons in area 2 may be more closely related to the activity of peripheral sensors than it is to extrinsic hand position. In addition, we conduct numerical experiments to determine the sensitivity of ANN models to various choices of training design and hyper-parameters. Our results provide a baseline and new tools for future research that utilizes machine learning to better describe and understand the activity of neurons in S1.

Linear Integration of Tactile and Non-tactile Inputs Mediates Estimation of Fingertip Relative Position

While skin, joints and muscles receptors alone provide lower level information about individual variables (e.g., exerted limb force and limb displacement), the distance between limb endpoints (i.e., relative position) has to be extracted from high level integration of somatosensory and motor signals. In particular, estimation of fingertip relative position likely involves more complex sensorimotor transformations than those underlying hand or arm position sense: the brain has to estimate where each fingertip is relative to the hand and where fingertips are relative to each other. It has been demonstrated that during grasping, feedback of digit position drives rapid adjustments of fingers force control. However, it has been shown that estimation of fingertips' relative position can be biased by digit forces. These findings raise the question of how the brain combines concurrent tactile (i.e., cutaneous mechanoreceptors afferents induced by skin pressure and stretch) and non-tactile (i.e., both descending motor command and joint/muscle receptors signals associated to muscle contraction) digit force-related inputs for fingertip distance estimation. Here we addressed this question by quantifying the contribution of tactile and non-tactile force-related inputs for the estimation of fingertip relative position. We asked subjects to match fingertip vertical distance relying only on either tactile or non-tactile inputs from the thumb and index fingertip, and compared their performance with the condition where both types of inputs were combined. We found that (a) the bias in the estimation of fingertip distance persisted when tactile inputs and non-tactile force-related signals were presented in isolation; (b) tactile signals contributed the most to the estimation of fingertip distance; (c) linear summation of the matching errors relying only on either tactile or non-tactile inputs was comparable to the matching error when both inputs were simultaneously available. These findings reveal a greater role of tactile signals for sensing fingertip distance and suggest a linear integration mechanism with non-tactile inputs for the estimation of fingertip relative position.

Auditory-induced response in the primary sensory cortex of rodents

The details of auditory response at the subthreshold level in the rodent primary somatosensory cortex, the barrel cortex, have not been studied extensively, although several phenomenological reports have been published. Multisensory features may act as neuronal representations of links between inputs from one sensory modality to other sensory modalities. Here, we examined the basic multisensory postsynaptic responses in the rodent barrel cortex using in vivo whole-cell recordings of neurons. We observed robust responses to acoustic stimuli in most barrel cortex neurons. Acoustically evoked responses were mediated by hearing and reached approximately 60% of the postsynaptic response amplitude elicited by strong somatosensory stimuli. Compared to tactile stimuli, auditory stimuli evoked postsynaptic potentials with a longer latency and longer duration. Specifically, auditory stimuli in barrel cortex neurons appeared to trigger "up states", episodes associated with membrane depolarization and increased synaptic activity. Taken together, our data suggest that barrel cortex neurons have multisensory properties, with distinct synaptic mechanisms underlying tactile and non-tactile responses.

Neural Basis of Touch and Proprioception in Primate Cortex

The sense of proprioception allows us to keep track of our limb posture and movements and the sense of touch provides us with information about objects with which we come into contact. In both senses, mechanoreceptors convert the deformation of tissues-skin, muscles, tendons, ligaments, or joints-into neural signals. Tactile and proprioceptive signals are then relayed by the peripheral nerves to the central nervous system, where they are processed to give rise to percepts of objects and of the state of our body. In this review, we first examine briefly the receptors that mediate touch and proprioception, their associated nerve fibers, and pathways they follow to the cerebral cortex. We then provide an overview of the different cortical areas that process tactile and proprioceptive information. Next, we discuss how various features of objects-their shape, motion, and texture, for example-are encoded in the various cortical fields, and the susceptibility of these neural codes to attention and other forms of higher-order modulation. Finally, we summarize recent efforts to restore the senses of touch and proprioception by electrically stimulating somatosensory cortex. © 2018 American Physiological Society. Compr Physiol 8:1575-1602, 2018.

Context-dependent tactile texture-sensitivity in monkey M1 and S1 cortex

Caudal primary motor cortex (M1, area 4) is sensitive to cutaneous inputs, but the extent to which the physical details of complex stimuli are encoded is not known. We investigated the sensitivity of M1 neurons (4 Macaca mulatta monkeys) to textured stimuli (smooth/rough or rough/rougher) during the performance of a texture discrimination task and, for some cells, during a no-task condition (same surfaces; no response). The recordings were made from the hemisphere contralateral to the stimulated digits; the motor response (sensory decision) was made with the nonstimulated arm. Most M1 cells were modulated during surface scanning in the task (88%), but few of these were texture-related (24%). In contrast, 44% of M1 neurons were texture related in the no-task condition. Recordings from the neighboring primary somatosensory cortex (S1), the potential source of texture-related signals to M1, showed that S1 neurons were significantly more likely to be texture related during the task (57 vs 24%) than M1. No difference was observed in the no-task condition (52 vs. 44%). In these recordings, the details about surface texture were relevant for S1 but not for M1. We suggest that tactile inputs to M1 were selectively suppressed when the animals were engaged in the task. S1 was spared these controls, as the same inputs were task-relevant. Taken together, we suggest that the suppressive effects are most likely exerted directly at the level of M1, possibly through the activation of a top-down gating mechanism specific to motor set/intention. NEW & NOTEWORTHY Sensory feedback is important for motor control, but we have little knowledge of the contribution of sensory inputs to M1 discharge during behavior. We showed that M1 neurons signal changes in tactile texture, but mainly outside the context of a texture discrimination task. Tactile inputs to M1 were selectively suppressed during the task because this input was not relevant for the recorded hemisphere, which played no role in generating the discrimination response.

Vibrotactile information improves proprioceptive reaching target localization

When pointing to parts of our own body (e.g., the opposite index finger), the position of the target is derived from proprioceptive signals. Consistent with the principles of multisensory integration, it has been found that participants better matched the position of their index finger when they also had visual cues about its location. Unlike vision, touch may not provide additional information about finger position in space, since fingertip tactile information theoretically remains the same irrespective of the postural configuration of the upper limb. However, since tactile and proprioceptive information are ultimately coded within the same population of posterior parietal neurons within high-level spatial representations, we nevertheless hypothesized that additional tactile information could benefit the processing of proprioceptive signals. To investigate the influence of tactile information on proprioceptive localization, we asked 19 participants to reach with the right hand towards the opposite unseen index finger (proprioceptive target). Vibrotactile stimuli were applied to the target index finger prior to movement execution. We found that participants made smaller errors and more consistent reaches following tactile stimulation. These results demonstrate that transient touch provided at the proprioceptive target improves subsequent reaching precision and accuracy. Such improvement was not observed when tactile stimulation was delivered to a distinct body part (the shoulder). This suggests a specific spatial integration of touch and proprioception at the level of high-level cortical body representations, resulting in touch improving position sense.