Biology subjects

Greenspon, C.

Publications and source records attributed to Greenspon, C..

5 recordsLinked to original sources

bioRxiv2026

Real-time intracortical decoding from human motor cortex reveals a task-independent commitment to act that aligns with conscious intent

Preparatory neural signals that precede movement onset are well established. However, whether they mark a commitment to act, align with conscious intention, or are subject to voluntary control remains under debate. We addressed these questions with a closed-loop experiment: a strategic timing game where a virtual opponent monitored intracortical sensorimotor activity and preempted participants' actions when their intention to move was detected. In three people with tetraplegia and preserved wrist extension, movement onset was reliably predicted from motor cortex 250-400 ms before action. Although participants attempted to act unpredictably, they were preempted on 94% of trials -and movement output generally followed despite the opponent's interruption. Participants reported intending to act on 88% of preemptions. The same decoder accurately predicted participants' actions in a non-competitive task, without retraining. These findings identify a late, task-independent motor-cortical state marking a voluntary commitment to act, which participants report as an intention when interrupted.

neuroscience↗

bioRxiv2025

A Generalist Intracortical Motor Decoder

Mapping the relationship between neural activity and motor behavior is a central aim of sensori-motor neuroscience and neurotechnology. While most progress to this end has relied on restricting complexity, the advent of foundation models instead proposes integrating a breadth of data as an alternate avenue for broadly advancing downstream modeling. We quantify this premise for motor decoding from intracortical microelectrode data, pretraining an autoregressive Transformer on 2000 hours of neural population spiking activity paired with diverse motor covariates from over 30 monkeys and humans. The resulting model is broadly useful, benefiting decoding on 8 downstream decoding tasks and generalizing to a variety of neural distribution shifts. However, we also highlight that scaling autoregressive Transformers seems unlikely to resolve limitations stemming from sensor variability and output stereotypy in neural datasets. Code: https://github.com/joel99/ndt3

neuroscience↗

bioRxiv2024

Neuronal firing rate diversity lowers the dimension of population covariability

Neuronal responses are very diverse, with specific stimuli or behaviors eliciting a range of activity across a neuronal population. These responses also show large and correlated trial-to-trial fluctuations that occupy a low-dimensional region in activity space. We link these two aspects of neuronal response in both feedforward and recurrent circuit models and derive the following relation: the more diverse the firing rates of neurons in a population, the lower the effective dimension of their trial-to-trial covariability. We test our prediction using simultaneously recorded neuronal populations from numerous brain areas in mice, non-human primates, and in the motor cortex of human participants. Finally, we show how diverse neural codes lead to better stimulus discrimination, and that when the brain is in a heightened state of processing responses are more diverse and have lower-dimensional fluctuations. In sum, we present an organizing principle of population response that is widely observed across the nervous system and acts to synergistically improve population representation.

neuroscience↗

bioRxiv2022

The coarse mental map of the breast is anchored on the nipple

AO_SCPLOWBSTRACTC_SCPLOWTouch plays a key role in our perception of our body and shapes our interactions with the world, from the objects we manipulate to the people we touch. While the tactile sensibility of the hand has been extensively characterized, much less is known about touch on other parts of the body. Despite the important role of the breast in lactation as well as in affective and sexual touch, relatively little is known about its sensory properties. To fill this gap, we investigated the ability of women to locate touches on the breast and compared it to that of the hand and back, body regions that span the range of tactile discriminative capabilities. First, we found that the tactile precision of the breast was even lower than that of the back, heretofore the paragon of poor precision. Second, precision was lower for breasts that had undergone greater expansion, consistent with the hypothesis that innervation capacity does not scale with body size. Third, touches to different regions of the nipple were largely indistinguishable, suggesting sparse innervation density. Fourth, localization errors were systematically biased toward the nipple. SO_SCPLOWIGNIFICANCEC_SCPLOWOur basic understanding of the tactile capabilities of the breast remains poorly understood in comparison to the hand or face despite the fact that the breast plays a major role in the lives of those with breasts. This paper establishes common methods for studying breast tactile sensation and presents the breast and nipple as two fundamentally discrete tactile units from the torso.

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↗