Biology subjects

Gonzalez-Martinez, J. A.

Publications and source records attributed to Gonzalez-Martinez, J. A..

5 recordsLinked to original sources

bioRxiv2026

Stimulus-response correlation analysis dissociates spatiotemporal cortical networks supporting speech production

IntroductionUnderstanding the spatiotemporal distribution of cortical activation during language production is a central question in cognitive neuroscience with broad clinical applications. High spatial/temporal resolution recording over multiple brain regions and specific psycholinguistic manipulations with testable behavioral predictions are necessary to separate neural variance attributable to processing stages. ObjectiveWe combine a delayed naming paradigm with intracranial electrophysiology to identify spatiotemporally dissociated cortical networks supporting stages of speech production. MethodsSubjects (20 healthy, 15 intracranial electrophysiology) are presented visual stimuli to name but are instructed to delay response until a go cue at 0/400/1000ms. Exploiting the temporal variance induced by delay, we calculate stimulus/response-locked correlation of high gamma (70-200Hz) activity at each contact. We compare shifts in stimulus-response correlation space to response time (RT) to validate separation of networks. ResultsBehaviorally, the factor delay modulated the effect of lexical selection on RT (p=0.021) but did not modulate the effect of phonological planning (p=0.4), confirming the paradigm separates processing stages. Stimulus-response correlation analyses revealed globally-invariant structure across subjects. Certain regions showed strong stimulus-locking (occipital lobe) or response-locking (motor cortex), but most regions were intermediate. Shifts in correlation space identified dissociated networks that predicted substantial variance in RT from lexical selection (R2=0.64) and phonological density (R2=0.75). Using a leave-one-subject-out cross validation approach, these shifts explained 31.4% of variance in RT at the trial level. ConclusionStimulus-response correlation space reveals stable spatiotemporal signatures of psycholinguistic processing that generalize across individuals. This approach permits hyperalignment of neurophysiological data and functional separation of cortical networks in speech production across subjects.

neuroscience↗

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↗

bioRxiv2023

GABA Increases Sensory Transmission In Monkeys

Sensory input flow is central to voluntary movements. For almost a century, GABA was believed to modulate this flow by inhibiting sensory axons in the spinal cord to sculpt neural inputs into skilled motor output. Instead, here we show that GABA can also facilitate sensory transmission in monkeys and consequently increase spinal and cortical neural responses to sensory inputs challenging our understanding of generation and perception of movement.

neuroscience↗

bioRxiv2022

Internal states as a source of subject-dependent movement variability and their representation by large-scale networks

A humans ability to adapt and learn relies on reflecting on past performance. Such reflections form latent factors called internal states that induce variability of movement and behavior to improve performance. Internal states are critical for survival, yet their temporal dynamics and neural substrates are less understood. Here, we link internal states with motor performance and neural activity using state-space models and local field potentials captured from depth electrodes in over 100 brain regions. Ten human subjects performed a goal-directed center-out reaching task with perturbations applied to random trials, causing subjects to fail goals and reflect on their performance. Using computational methods, we identified two internal states, indicating that subjects kept track of past errors and perturbations, that predicted variability in reaction times and speed errors. These states granted access to latent information indicative of how subjects strategize learning from trial history, impacting their overall performance. We further found that large-scale brain networks differentially encoded these internal states. The dorsal attention network encoded past errors in frequencies above 100 Hz, suggesting a role in modulating attention based on tracking recent performance in working memory. The default network encoded past perturbations in frequencies below 15 Hz, suggesting a role in achieving robust performance in an uncertain environment. Moreover, these networks more strongly encoded internal states and were more functionally connected in higher performing subjects, whose learning strategy was to respond by countering with behavior that opposed accumulating error. Taken together, our findings suggest large-scale brain networks as a neural basis of strategy. These networks regulate movement variability, through internal states, to improve motor performance. Key pointsO_LIMovement variability is a purposeful process conjured up by the brain to enable adaptation and learning, both of which are necessary for survival. C_LIO_LIThe culmination of recent experiences--collectively referred to as internal states--have been implicated in variability during motor and behavioral tasks. C_LIO_LITo investigate the utility and neural basis of internal states during motor control, we estimated two latent internal states using state-space representation that modeled motor behavior during a goal-directed center-out reaching task in humans with simultaneous whole-brain recordings from intracranial depth electrodes. C_LIO_LIWe show that including these states--based on error and environment uncertainty--improves the predictability of subject-specific variable motor behavior and reveals latent information related to task performance and learning strategies where top performers counter error scaled by trial history while bottom performers maintain error tendencies. C_LIO_LIWe further show that these states are encoded by the large-scale brain networks known as the dorsal attention network and default network in frequencies above 100 Hz and below 15 Hz but found neural differences between subjects where network activity closely modulates with states and exhibits stronger functional connectivity for top performers. C_LIO_LIOur findings suggest the involvement in large-scale brain networks as a neural basis of motor strategy that orchestrates movement variability to improve motor performance. C_LI

neuroscience↗

bioRxiv2021

A Multimodal Approach to Investigate the Neural Mechanisms of Real World Social Vision

Eye tracking and other behavioral measurements collected from patient-participants in their hospital rooms afford a unique opportunity to study immersive natural behavior for basic and clinical translational research. We describe an immersive social and behavioral paradigm implemented in patients undergoing evaluation for surgical treatment of epilepsy, with electrodes implanted in the brain to determine the source of their seizures. Our studies entail collecting eye tracking with other behavioral and psychophysiological measurements from patient-participants during unscripted behavior, including social interactions with clinical staff, friends and family, in the hospital room. This approach affords a unique opportunity to study the neurobiology of natural social behavior, though it requires carefully addressing distinct logistical, technical, and ethical challenges. Collecting neurophysiological data synchronized to behavioral and psychophysiological measures helps us to study the relationship between behavior and physiology. Combining across these rich data sources while participants eat, read, converse with friends and family, etc., enables clinical-translational research aimed at understanding the participants disorders and clinician-patient interactions, as well as basic research into natural, real-world behavior. We discuss data acquisition, quality control, annotation, and analysis pipelines that are required for our studies. We also discuss the clinical, logistical, and ethical and privacy considerations critical to working in the hospital setting.

neuroscience↗