Biology subjects

Chase, S. M.

Publications and source records attributed to Chase, S. M..

16 recordsLinked to original sources

bioRxiv2026

Eyes on the prize: a neural basis of perceptual choking under pressure

Even professional athletes sometimes fail to perform when it matters most. This phenomenon, known as choking under pressure, has been observed in a variety of motor and cognitive tasks. Can inordinately large rewards influence even sensory processing, and if so, what might be its neural basis? To probe this, we studied rhesus monkeys performing a challenging color change detection task and recorded from populations of neurons in visual area V4. We found that monkeys underperformed when offered rare "jackpot" rewards and uncovered associated detrimental alterations in V4 population activity. These findings were consistent with misallocated spatial attention, providing a potential neural basis for perceptual choking under pressure.

neuroscience↗

bioRxiv2026

Intracortical BCI Performance is Robust to Changes in Attentional Load During Dual-Tasking

High performance intracortical brain-computer interface (iBCI) control has been demonstrated in research settings, but performance can still vary within and between sessions. One potential source of this variability is the change in attentional load that comes from processing naturally occurring distractors such as thoughts, sounds, fatigue, or pain. To improve the consistency of iBCI performance in real-world environments where this sort of multi-tasking is inevitable, we must understand how shifts in attention can impact performance. Here we examined the effect of attentional load on iBCI performance and movement-related neural activity using a 2D cursor translation + click iBCI task paired with an N-Back working memory task to increase attentional load during dual-task performance. Two participants (P2 and P4) with tetraplegia completed the study while enrolled in a long-term clinical trial of an iBCI device (NCT1894802). Common neural correlates of attention (theta and alpha band power) were measured with simultaneously recorded scalp electroencephalography (EEG). While the EEG recordings and difficulty ratings suggested increased attentional load during dual tasking, iBCI performance was quite robust across the various dual tasking conditions. One participant, P2, experienced a small but significant increase in trial completion time and normalized path length during the mild attentional load condition. Signal quality differences between the two participants may have impacted the results, as P2 had lower signal quality and was therefore likely more vulnerable to attentional load. P4s higher signal quality likely allowed him to accommodate increased attentional load without a drop in performance. Overall, iBCI performance appears to be robust to attentional load, but the complex trends observed here reflect a need for continued investigation of BCI use under different cognitive states to elucidate potential challenges and compensatory mechanisms across participants.

bioengineering↗

bioRxiv2026

Distinct neural modes carry information about grasp force and phase in the sensorimotor cortex

Humans perform a variety of complex hand movements to manipulate objects, requiring precise control of changing forces. Understanding the role of sensorimotor cortex and the cortical dynamics underlying these actions is crucial for developing interventions that restore dexterous hand function after injury or disease. In this study, two individuals with tetraplegia resulting from cervical spinal cord injury attempted a series of isometric grasps. Neural activity was recorded from the motor and somatosensory cortices using intracortical microelectrode arrays while participants attempted to exert a static force or to ramp force up and down. Despite their inability to execute movement, and with limited afferent input, the spiking activity in motor and somatosensory cortex was modulated with the task. Within the neural response we identified independent neural modes - distinct patterns of population-level neural activity - that were informative about both the timing and magnitude of the force. Moreover, distinct neural modes were observed during static and dynamic grasping conditions, suggesting independent control schemes for maintaining and changing forces. These modes were related to phases of the task, including the onset, offset, holding periods, as well as phases of increasing and decreasing force. These results will inform the design of intracortical brain-computer interface (iBCI) systems that can leverage these naturally occurring patterns of grasp and force control to restore dexterous hand function. Significance StatementRestoring dexterous hand function after injury remains a major challenge, partly due to an incomplete understanding of the cortical dynamics underlying grasping and force control. In this study, we investigated neural activity within the motor and somatosensory cortices of individuals with tetraplegia attempting to perform grasps to different target forces with varying temporal profiles. We identified distinct neural modes modulated during specific phases of grasp that encode force information throughout the task. These findings suggest that brain-computer interfaces could leverage these native neural modes to restore grasping and force modulation.

neuroscience↗

bioRxiv2025

Reward influences movement vigor through multiple motor cortical mechanisms

The prospect of greater rewards often invigorates movements. What neural mechanisms support this increase of movement vigor for greater rewards? We had three rhesus monkeys perform reaching movements to targets worth different magnitudes of reward. We recorded neural population activity from primary motor and dorsal premotor cortex, brain areas at the output of cortical processing for voluntary movements, and asked how neural activity mediated the translation of reward into increased vigor. We identified features of neural activity during movement preparation, initiation, and execution that were both correlated with vigor and modulated by reward. We also found that the neural metrics that correlate with different aspects of movement vigor exhibit only limited correlation with one another, suggesting that there are multiple mechanisms through which reward modulates vigor. Finally, we note that the majority of rewards modulation of motor cortical activity cannot be accounted for by reward-mediated vigor differences in behavior, indicating that reward modulations within motor cortex may serve roles in addition to affecting vigor. Overall, our results provide insight into the neural mechanisms that link reward-driven motivation to the modulation of the details of movement.

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

A posture subspace in primary motor cortex

To generate movements, the brain must combine information about movement goal and body posture. Motor cortex (M1) is a key node for the convergence of these information streams. How are posture and goal information organized within M1s activity to permit the flexible generation of movement commands? To answer this question, we recorded M1 activity while monkeys performed a variety of tasks with the forearm in a range of postures. We found that posture- and goal-related components of neural population activity were separable and resided in nearly orthogonal subspaces. The posture subspace was stable across tasks. Within each task, neural trajectories for each goal had similar shapes across postures. Our results reveal a simpler organization of posture information in M1 than previously recognized. The compartmentalization of posture and goal information might allow the two to be flexibly combined in the service of our broad repertoire of actions.

neuroscience↗

bioRxiv2024

A theory of brain-computer interface learning via low-dimensional control

A remarkable demonstration of the flexibility of mammalian motor systems is primates ability to learn to control brain-computer interfaces (BCIs). This constitutes a completely novel motor behavior, yet primates are capable of learning to control BCIs under a wide range of conditions. BCIs with carefully calibrated decoders, for example, can be learned with only minutes to hours of practice. With a few weeks of practice, even BCIs with randomly constructed decoders can be learned. What are the biological substrates of this learning process? Here, we develop a theory based on a re-aiming strategy, whereby learning operates within a low-dimensional subspace of task-relevant inputs driving the local population of recorded neurons. Through comprehensive numerical and formal analysis, we demonstrate that this theory can provide a unifying explanation for disparate phenomena previously reported in three different BCI learning tasks, and we derive a novel experimental prediction that we verify with previously published data. By explicitly modeling the underlying neural circuitry, the theory reveals an interpretation of these phenomena in terms of biological constraints on neural activity.

neuroscience↗

bioRxiv2023

A neural basis of choking under pressure

Incentives tend to drive improvements in performance. But when incentives get too high, we can "choke under pressure" and underperform when it matters most. What neural processes might lead to choking under pressure? We studied Rhesus monkeys performing a challenging reaching task in which they underperform when an unusually large "jackpot" reward is at stake. We observed a collapse in neural information about upcoming movements for jackpot rewards: in the motor cortex, neural planning signals became less distinguishable for different reach directions when a jackpot reward was made available. We conclude that neural signals of reward and motor planning interact in the motor cortex in a manner that can explain why we choke under pressure. One-Sentence SummaryIn response to exceptionally large reward cues, animals can "choke under pressure", and this corresponds to a collapse in the neural information about upcoming movements.

neuroscience↗

bioRxiv2023

Sensory constraints on volitional modulation of the motor cortex

Voluntary movement is driven by the primary motor cortex (M1), and individuals can learn to modulate even single neurons at will. Yet M1 also receives pronounced sensory inputs and contributes to sensory-driven motor responses. To what extent do these non-volitional signals restrict voluntary modulation of M1? Using a task in which the firing rate of a single neuron directly determines the position of a computer cursor along a visual axis, we assessed the ability of monkeys to modulate individual neurons under different sensory contexts. We found that sensory context persistently affected volitional control of single neurons in M1. For instance, visually rotating the biofeedback axis could render the same neural task effortless or problematic. Notably, extended training within or across days did not resolve this disparity. Our findings suggest that sensory context can limit the degree to which M1 activity is under volitional control.

neuroscience↗

bioRxiv2023

Motor cortex retains and reorients neural dynamics during motor imagery

The most prominent role of motor cortex is generating patterns of neural activity that lead to movement, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioral and imaging studies, it is unknown how the specific activity patterns and temporal dynamics within motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people with residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population-level activity into orthogonal subspaces such that one set of components was similarly active during both action and imagery, and others were only active during a single task type--action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamical features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by recreating the missing components related to motor output and/or feedback within a unique imagery-only subspace.

neuroscience↗

bioRxiv2022

Learning alters neural activity to simultaneously support memory and action

How are we able to learn new behaviors without disrupting previously learned ones? To understand how the brain achieves this, we used a brain-computer interface (BCI) learning paradigm, which enables us to detect the presence of a memory of one behavior while performing another. We found that learning to use a new BCI map altered the neural activity that monkeys produced when they returned to using a familiar BCI map, in a way that was specific to the learning experience. That is, learning left a "memory trace." This memory trace co-existed with proficient performance under the familiar map, primarily by altering dimensions of neural activity that did not impact behavior. Such a memory trace could provide the neural underpinning for the joint learning of multiple motor behaviors without interference.

neuroscience↗

bioRxiv2022

Visual experience has opposing influences on the quality of stimulus representation in adult primary visual cortex

Transient dark exposure, typically 7-10 days in duration, followed by light reintroduction is an emerging treatment for improving the restoration of vison in amblyopic subjects whose occlusion is removed in adulthood. Dark exposure initiates homeostatic mechanisms that together with light-induced changes in cellular signaling pathways result in the re-engagement of juvenile-like plasticity in the adult such that previously deprived inputs can gain cortical territory. It is possible that dark exposure itself degrades visual responses, and this could place constraints on the optimal duration of dark exposure treatment. To determine whether eight days of dark exposure has a lasting negative impact on responses to classic grating stimuli, neural activity was recorded before and after dark exposure in awake head-fixed mice using 2-photon calcium imaging. Neural discriminability, assessed using classifiers, was transiently reduced following dark exposure; a decrease in response reliability across a broad range of spatial frequencies accounted for the disruption. Both discriminability and reliability recovered. Fixed classifiers were used to demonstrated that stimulus representation rebounded to the original, pre-deprivation state, thus DE did not appear to have a lasting negative impact on visual processing. Unexpectedly, we found that dark exposure significantly stabilized orientation preference and signal correlation. Our results reveal that natural vision exerts a disrupting influence on the stability of stimulus preference for classic grating stimuli, and at the same time improves neural discriminability for both low and high spatial frequency stimuli.

neuroscience↗

bioRxiv2022

Dimensionality reduction of calcium-imaged neuronal population activity

Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a novel method to perform deconvolution and dimensionality reduction simultaneously (termed CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from calcium imaging that would have been recovered from spiking activity. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.

neuroscience↗

bioRxiv2021

New skill acquisition does not perturb existing function in sensory cortex

Acquisition of new skills has the potential to disturb existing network function. To directly assess whether previously acquired cortical function is altered during learning, mice were trained in an abstract task in which selected activity patterns were rewarded using an optical brain-computer interface device coupled to primary visual cortex (V1) neurons. Excitatory neurons were longitudinally recorded using 2-photon calcium imaging. Despite significant changes in local neural activity during task performance, tuning properties and stimulus encoding assessed outside of the trained context were not perturbed. Similarly, stimulus tuning was stable in neurons that remained responsive following a different, visual discrimination training task. However, visual discrimination training increased the rate of representational drift. Our results indicate that while some forms of perceptual learning may modify the contribution of individual neurons to stimulus encoding, new skill learning is not inherently disruptive to the quality of stimulus representation in adult V1.

neuroscience↗

bioRxiv2020

Development of natural scene representation in primary visual cortex requires early postnatal experience

The development of the visual system is known to be shaped by early-life experience. To identify response properties that contribute to enhanced natural scene representation, we performed calcium imaging of excitatory neurons in the primary visual cortex (V1) of awake mice raised in three different conditions (standard-reared, dark-reared, and delayed-visual experience) and compared neuronal responses to natural scene features relative to simpler grating stimuli that varied in orientation and spatial frequency. We assessed population selectivity in V1 using decoding methods and found that natural scene discriminability increased by 75% between the ages of 4 to 6 weeks. Both natural scene and grating discriminability were higher in standard-reared animals compared to those raised in the dark. This increase in discriminability was accompanied by a reduction in the number of neurons that responded to low-spatial frequency gratings. At the same time there was an increase in neuronal preference for natural scenes. Light exposure restricted to a 2-4 week window during adulthood did not induce improvements in natural scene nor in grating stimulus discriminability. Our results demonstrate that experience reduces the number of neurons required to effectively encode grating stimuli and that early visual experience enhances natural scene discriminability by directly increasing responsiveness to natural scene features.

neuroscience↗

bioRxiv2020

Learning is shaped by abrupt changes in neural engagement

Internal states such as arousal, attention, and motivation are known to modulate brain-wide neural activity, but how these processes interact with learning is not well understood. During learning, the brain must modify the neural activity it produces to improve behavioral performance. How do internal states affect the evolution of this learning process? Using a brain-computer interface (BCI) learning paradigm in non-human primates, we identified large fluctuations in neural population activity in motor cortex (M1) indicative of arousal-like internal state changes. These fluctuations drove population activity along dimensions we term neural engagement axes. Neural engagement increased abruptly at the start of learning, and then gradually retreated. In a BCI, the causal relationship between neural activity and behavior is known. This allowed us to understand how these changes impacted behavioral performance for different task goals. We found that neural engagement interacted with learning, helping to explain why animals learned some task goals more quickly than others.

neuroscience↗