Biology subjects

Bensmaia, S. J.

Publications and source records attributed to Bensmaia, S. J..

28 records · Page 2Linked to original sources

bioRxiv2021

Sensory computations in the cuneate nucleus of macaques

AO_SCPLOWBSTRACTC_SCPLOWTactile nerve fibers fall into a few classes that can be readily distinguished based on their spatiotemporal response properties. Because nerve fibers reflect local skin deformations, they individually carry ambiguous signals about object features. In contrast, cortical neurons exhibit heterogeneous response properties that reflect computations applied to convergent input from multiple classes of afferents, which confer to them a selectivity for behaviorally relevant features of objects. The conventional view is that these complex response properties arise within the cortex itself, implying that sensory signals are not processed to any significant extent in the two intervening structures - the cuneate nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in CN to a battery of stimuli that have been extensively used to characterize tactile coding in both the periphery and cortex, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their cortical counterparts than they are to their inputs: CN neurons receive input from multiple classes of nerve fibers, they have spatially complex receptive fields, and they exhibit selectivity for object features. Contrary to consensus, then, CN plays a key role in processing tactile information. SO_SCPLOWIGNIFICANCEC_SCPLOWPerception is the outcome of the sequential processing of sensory signals at multiple stages along the neuraxis. The conventional view is that tactile signals are processed predominantly in the cerebral cortex. We tested this view by investigating the response properties of neurons in the cuneate nucleus (CN), the first potential stage of processing along the primary touch neuraxis. We found that CN responses more nearly resemble those of cortical neurons than they do those of nerve fibers: CN neurons have spatially complex receptive fields reflecting convergent input from multiple classes of nerve fibers and exhibit a selectivity for object features, absent in the nerve. We conclude that CN plays a key, early role in the processing of tactile information.

neuroscience↗

bioRxiv2021

Texture is encoded in precise temporal spiking patterns in primate somatosensory cortex

AO_SCPLOWBSTRACTC_SCPLOWWe are exquisitely sensitive to the microstructure and material properties of surfaces. In the peripheral nerves, two separate mechanisms convey texture information: coarse textural features are encoded in spatial patterns of activation that reflect their spatial layout and fine features are encoded in highly repeatable, texture specific temporal spiking patterns evoked as the skin moves across the surface. In the present study, we examined whether this temporal code is preserved in the responses of neurons in somatosensory cortex. To this end, we scanned a diverse set of everyday textures across the fingertip of awake macaques while recording the responses evoked in individual cortical neurons. We found that temporal spiking patterns are highly repeatable across multiple presentations of the same texture, with millisecond precision. As a result, texture identity can be reliably decoded from the temporal patterns themselves, even after information carried in the spike rates is eliminated. However, the combination of rate and timing does is more informative than either code in isolation. The temporal precision of the texture response is heterogenous across cortical neurons and depends on the submodality composition of their input and on their location along the somatosensory neuraxis. Furthermore, temporal spiking patterns in cortex dilate and contract with decreases and increases in scanning speed and this systematic relationship between speed and patterning may contribute to the observed perceptual invariance to speed. Finally, we find that the quality of a texture percept can be better predicted when these temporal patterns are taken into consideration. We conclude that high-precision spike timing complements rate-based signals to encode texture in somatosensory cortex.

neuroscience↗

bioRxiv2021

ENCODING OF LIMB STATE BY SINGLE NEURONS IN THE CUNEATE NUCLEUS OF AWAKE MONKEYS

The cuneate nucleus (CN) is among the first sites along the neuraxis where proprioceptive signals can be integrated, transformed, and modulated. The objective of the study was to characterize the proprioceptive representations in CN. To this end, we recorded from single CN neurons in three monkeys during active reaching and passive limb perturbation. We found that many neurons exhibited responses that were tuned approximately sinusoidally to limb movement direction, as has been found for other sensorimotor neurons. The distribution of their preferred directions (PDs) was highly non-uniform and resembled that of muscle spindles within individual muscles, suggesting that CN neurons typically receive inputs from only a single muscle. We also found that the responses of proprioceptive CN neurons tended to be modestly amplified during active reaching movements compared to passive limb perturbations, in contrast to cutaneous CN neurons whose responses were not systematically different in the active and passive conditions. Somatosensory signals thus seem to be subject to a "spotlighting" of relevant sensory information rather than uniform suppression as has been suggested previously.

neuroscience↗

bioRxiv2020

Frequency shapes the quality of tactile percepts evoked through electrical stimulation of the nerves

AO_SCPLOWBSTRACTC_SCPLOWTouch is critical for our ability to manipulate objects, as evidenced by the deficits incurred when touch is absent. To restore the sense of touch via electrical stimulation of the peripheral nerves requires that we understand how the parameters of stimulation shape the evoked sensation. To this end, we investigated the sensory consequences of changing the frequency of pulse trains (PF) delivered to the peripheral nerves of humans chronically implanted with multi-channel nerve cuff electrodes. We found that increases in PF led to systematic increases in perceived frequency, up to about 50 Hz, at which point further changes in PF had little to no impact on sensory quality. Above this transition frequency, ratings of perceived frequency levelled off, the ability to discriminate changes in PF was abolished, and verbal descriptors selected to characterize the sensation changed abruptly. We conclude that the quality of electrically evoked tactile sensations can be shaped by imposing temporal patterns on a fixed neural population, but this temporal patterning can only be resolved up to about 50 Hz. These findings highlight the importance of spike timing in shaping the quality of a sensation and will contribute to the development of encoding strategies for conveying touch feedback through bionic hands and feet.

bioengineering↗

bioRxiv2019

Unexpected Complexity Of Everyday Manual Behaviors

AO_SCPLOWBSTRACTC_SCPLOWHow does the brain control an effector as complex and versatile as the hand? One possibility is that the neural control of the hand is simplified by limiting the space of achievable hand postures. Indeed, hand kinematics can be largely accounted for within a small subspace of postures. This oft replicated finding has been interpreted as evidence that hand postures are confined to this subspace, and that leaving it volitionally is impossible. A prediction from this hypothesis is that measured hand movements that fall outside of this subspace reflect motor or measurement noise. To address this question, we track hand postures of human participants as they perform two distinct tasks - grasping and signing in American Sign Language. We then apply a standard dimensionality reduction technique - principal components analysis - and replicate the finding that hand movements can be largely described within a reduced subspace. However, we show that postural dimensions that fall outside of this subspace are highly structured and task dependent, suggesting that they too are under volitional control. We conclude that hand control occupies a higher dimensional space than previously considered, and propose that controlling the complexity of hand movements is well within the scope of the brains computational power.

neuroscience↗

bioRxiv2019

Texture-Elicited Vibrations Stretch Or Contract Systematically Depending On Scanning Speed

To sense the texture of a surface, we run our fingers across it, which leads to the elicitation of skin vibrations that depend both on the surface and on exploratory parameters, particularly scanning speed. The transduction and processing of these vibrations mediates the ability to discern fine surface features. In the present study, we seek to characterize the effect of changes in scanning speed on texture-elicited vibrations to better understand how the exploratory strategy shapes the neuronal representation of texture. To this end, we scanned a variety of textures across the fingertip of human participants at a variety of speeds (10 - 160 mm/s) while measuring the resulting vibrations using a laser Doppler vibrometer. We found that increases in speed led to systematic increases in vibratory intensity and to a systematic upward multiplicative shift in the frequency composition of the vibrations. Furthermore, we showed that the upward shift in frequency composition accounts for the increase in intensity. The enhancement of higher frequency components accounts for the observed increase in the firing rates of nerve fibers, particularly Pacinian corpuscle-associated fibers, which are most sensitive at the high frequencies.

neuroscience↗

bioRxiv2019

NEURAL POPULATION DYNAMICS IN MOTOR CORTEX ARE DIFFERENT FOR REACH AND GRASP

AO_SCPLOWBSTRACTC_SCPLOWRotational dynamics are observed in neuronal population activity in primary motor cortex (M1) when monkeys make reaching movements. This population-level behavior is consistent with a role for M1 as an autonomous pattern generator that drives muscles to produce movement. Here, we show that M1 does not exhibit smooth dynamics during grasping movements, suggesting a more input-driven circuit.

neuroscience↗

bioRxiv2019

THE FREQUENCY OF CORTICAL MICROSTIMULATION SHAPES ARTIFICIAL TOUCH

AO_SCPLOWBSTRACTC_SCPLOWIntracortical microstimulation (ICMS) of somatosensory cortex evokes vivid tactile sensations and can be used to convey sensory feedback in brain-controlled bionic hands. Changes in ICMS frequency result in discriminable percepts, but the effects of frequency have only been investigated over a narrow range of low frequencies, spanning only a small fraction of that relevant for neuroprosthetics. Furthermore, the sensory correlates of changes in ICMS frequency remain to be elucidated. To fill these gaps, we trained monkeys to discriminate the frequency of ICMS pulse trains over a wide range of frequencies (from 10 to 400 Hz). ICMS amplitude also varied across stimuli to reduce the animals reliance on magnitude in making frequency judgments. We found that animals could discriminate ICMS frequency up to about 200 Hz but that the sensory correlates of frequency were highly electrode dependent. We discuss the implications of our findings for neural coding and brain-machine interfaces.

neuroscience↗

bioRxiv2019

Postural representations of the hand in primate sensorimotor cortex

Dexterous hand control requires not only a sophisticated motor system but also a sensory system to provide tactile and proprioceptive feedback. To date, the study of the neural basis of proprioception in cortex has focused primarily on reaching movements, at the expense of hand-specific behaviors such as grasp. To fill this gap, we record both the time-varying hand kinematics and the neural activity evoked in somatosensory and motor cortices as monkeys grasp a variety of different objects. We find that neurons in somatosensory cortex, as well as in motor cortex, preferentially track postures of multi-joint combinations spanning the entire hand. This contrasts with neural responses during reaching movements, which preferentially track movement kinematics of the arm rather than its postural configuration. These results suggest different representations of arm and hand movements likely adapted to suit the different functional roles of these two effectors.

neuroscience↗

bioRxiv2018

Rapid Geometric Feature Signaling In The Spiking Activity Of A Complete Population Of Tactile Nerve Fibers

Tactile feature extraction is essential to guide the dexterous manipulation of objects. The longstanding theory is that geometric features at each location of contact between hand and object are extracted from the spatial layout of the response of populations of tactile nerve fibers. However, recent evidence suggests that some features (edge orientation, e.g.) are extracted very rapidly (<200ms), casting doubt that this information relies on a spatial code, which ostensibly requires integrating responses over time. An alternative hypothesis is that orientation is conveyed in precise temporal spiking patterns. Here, we simulate, using a recently developed and validated model, the responses of tactile fibers from the entire human fingertip ([~]800 afferents) to edges indented into the skin. We show that edge orientation can be quickly (<50 ms) and accurately (<3{degrees}) decoded from the spatial pattern of activation across the afferent population, starting with the very first spike. Next, we implement a biomimetic decoder of edge orientation, consisting of a bank of oriented Gabor filters, designed to mimic the documented responses of cortical neurons. We find that the biomimetic approach leads to orientation decoding performance that approaches the limit set by optimal decoders and is actually more robust to changes in other stimulus features. Finally, we show that orientation signals, measured from single units in non-human primate cortex (2 macaque monkeys, 1 female), follow a time course consistent with that of their counterparts in the nerve. We conclude that a spatial code is fast and accurate enough to support object manipulation.

neuroscience↗