Biology subjects

Callier, T.

Publications and source records attributed to Callier, T..

6 recordsLinked to original sources

bioRxiv2026

Functional ultrasound imaging through a human cranial window for mesoscopic mapping of motor effector encoding within the sensorimotor cortex

Understanding movement encoding within human cortical circuits has been essential for advancing brain computer interfaces (BCIs). However, there are limited minimally invasive, high resolution neurorecording methods sensitive enough to detect single-trial movement-correlated neural activity. Functional ultrasound imaging (fUSI) provides submillimeter spatial resolution of deep cortical tissue with high sensitivity and, when paired with acoustically transparent skull implants, enables transcutaneous recording of human neurovascular changes. Prior studies have used fUSI in participants with acoustically transparent skull implants for on-off task mapping and decoding. Here, we demonstrate fUSIs ability to reliably resolve multi-body-part and single digit movement encoding within the primary sensorimotor cortex in a participant with an acoustically transparent skull implant. We obtained fine-grained mappings of individual effector representation that were consistent with classic somatotopy for both multi-body-part and single digit movement. We were able to resolve single-trial event-related activity, enabling single-trial decoding of both conditions. Analysis of voxels important for decoding suggested differential encoding of single digit movement information across the different Brodmann areas. Finally, we show that these patterns can be approximated across different sessions, allowing for cross session decoding. These results establish that fUSI can reliably delineate somatotopically organized motor representations at submillimeter resolution, bridging a critical gap between invasive electrophysiology and noninvasive hemodynamic imaging in a human subject.

neuroscience↗

bioRxiv2025

VARS-fUSI: Variable Sampling for Fast and Efficient Functional Ultrasound Imaging using Neural Operators

Functional ultrasound imaging (fUSI) is a promising neuroimaging method that infers neural activity by detecting cerebral blood volume changes. It offers high sensitivity and spatial resolution relative to fMRI and is an epidural alternative to electrophysiology for medical and neuroscience applications, including brain-computer interfaces. However, current fUSI methods require hundreds of compounded images and ultrasound pulse emissions, leading to high computational costs, memory demands, and potential probe heating. We propose VARiable Sampling fUSI (VARS-fUSI), the first deep learning fUSI method to allow for different sampling durations and rates during training and inference by using neural operators. VARS-fUSI reconstructs high-quality fUSI images using 10 - 15% of the time or sampling rate needed per image while preserving decodable behavior-correlated signals. Additionally, VARS-fUSI offers efficient finetuning for generalization to new animals and humans. Demonstrated across mouse, monkey, and human data, VARS-fUSI achieves state-of-the-art performance, enhancing imaging efficiency by significantly reducing storage and processing needs.

bioengineering↗

bioRxiv2023

Tessellation Of Artificial Touch Via Microstimulation Of Human Somatosensory Cortex

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

neuroscience↗

bioRxiv2023

Biomimetic multi-channel microstimulation of somatosensory cortex conveys high resolution force feedback for bionic hands

AO_SCPLOWBSTRACTC_SCPLOWManual interactions with objects are supported by tactile signals from the hand. This tactile feedback can be restored in brain-controlled bionic hands via intracortical microstimulation (ICMS) of somatosensory cortex (S1). In ICMS-based tactile feedback, contact force can be signaled by modulating the stimulation intensity based on the output of force sensors on the bionic hand, which in turn modulates the perceived magnitude of the sensation. In the present study, we gauged the dynamic range and precision of ICMS-based force feedback in three human participants implanted with arrays of microelectrodes in S1. To this end, we measured the increases in sensation magnitude resulting from increases in ICMS amplitude and participants ability to distinguish between different intensity levels. We then assessed whether we could improve the fidelity of this feedback by implementing "biomimetic" ICMS-trains, designed to evoke patterns of neuronal activity that more closely mimic those in natural touch, and by delivering ICMS through multiple channels at once. We found that multi-channel biomimetic ICMS gives rise to stronger and more distinguishable sensations than does its single-channel counterpart. Finally, we implemented biomimetic multi-channel feedback in a bionic hand and had the participant perform a compliance discrimination task. We found that biomimetic multi-channel tactile feedback yielded improved discrimination over its single-channel linear counterpart. We conclude that multi-channel biomimetic ICMS conveys finely graded force feedback that more closely approximates the sensitivity conferred by natural touch.

neuroscience↗

bioRxiv2022

Disentangling temporal and rate codes in primate somatosensory cortex

AO_SCPLOWBSTRACTC_SCPLOWMillisecond-scale temporal spiking patterns encode sensory information in the periphery, but their role in cortex remains controversial. The sense of touch provides a window into temporal coding because tactile neurons often exhibit precise, repeatable, and informative temporal spiking patterns. In somatosensory cortex (S1), for example, responses to skin vibrations exhibit phase-locking that faithfully carries information about vibratory frequency. However, the respective roles of spike timing and rate in frequency coding are confounded because vibratory frequency shapes both the timing and rates of S1 responses. To disentangle the contributions of these two neural features, we measured S1 responses as animals performed a frequency discrimination task, in which differences in frequency were accompanied by behaviorally irrelevant variations in amplitude. We then assessed the degree to which the strength and timing of S1 responses could account for the animals performance on the task. First, we showed that animals can discriminate frequency, but their performance is biased by amplitude. Second, rate-based representations of frequency are susceptible to changes in amplitude, but in ways that are inconsistent with the animals behavior, calling into question a rate-based code for frequency. In contrast, timing-based representations are impervious to changes in amplitude, also inconsistent with the animals behavior. We account for the animals behavior with a model wherein frequency coding relies on a temporal code, but frequency judgments are biased by perceived magnitude. Our results constitute further evidence for the role of millisecond-scale spike timing in cortex. SO_SCPLOWIGNIFICANCEC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSTATEMENTC_SCPLOWWhile neurons in the cerebral cortex are known to produce temporally patterned responses with single-digit millisecond precision, the role of this patterning remains controversial. The alternative hypothesis is that the critical feature of neuronal responses is the rate at which spikes are emitted, and the distribution of the spikes in time only matters at much slower time scales (tens or hundreds of milliseconds). To disentangle these two putative neural codes, we trained animals to discriminate the frequency of skin vibrations while recording from somatosensory cortex. We show that only a timing-based representation of frequency can account for the performance of the animals, though overall population firing rate biases their frequency judgments.

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↗