Biology subjects

Hatsopoulos, N. G.

Publications and source records attributed to Hatsopoulos, N. G..

10 recordsLinked to original sources

bioRxiv2026

Natural prey capture reveals flexible reconfiguration of canonical motor-cortical dynamics for online control

The ability to record neural populations during natural behavior now allows us to ask whether canonical motor-cortical dynamics, defined largely in constrained reaches to static targets, also organize self-paced, feedback-rich actions that require continuous correction. We recorded sensorimotor cortex in marmosets freely capturing live prey, a behavior that separates into ballistic quick captures and dynamic pursuits requiring real-time adjustment. Ballistic captures corresponded to canonical cortical reaching dynamics without an instructed delay, including near-orthogonal premovement and movement subspaces. Pursuits did not recruit additional neural dimensions; despite their elaborate kinematics, dynamics evolved within the same low-dimensional subspace. Corrective movements during pursuit reorganized this geometry into a distinct feedback-dominated regime, in which premovement activity weakly predicted movement, trajectory tangling increased, and a smaller, slower rotation restarted from a shifted initial state. Yet all movement types shared a sequential firing-rate backbone, which during ballistic capture was organized across the cortex as a somatotopically directed propagating wave that weakened when movements required online correction. These results show that sensorimotor cortex preserves canonical dynamical structure while flexibly reconfiguring it for online control in natural behavior.

neuroscience↗

bioRxiv2026

A framework for quantifying the mechanics of dexterous grasp

AO_SCPLOWBSTRACTC_SCPLOWA hallmark of primate behavior is the exceptional ability to dexterously grasp and manipulate objects, yet the investigation of the neural mechanisms that support manual dexterity has been hindered by technical challenges. Optical hand tracking is complicated by frequent occlusions, and contact forces are hard to measure with sufficient precision. Furthermore, while monitoring the kinematics during reaching phase, and the contact forces during object manipulation phase is difficult, joint torques are impossible to measure directly. While challenging, the ability to estimate joint torques in the complex primate hand could provide an invaluable continuous mechanical description spanning both phases. With this in mind, we have developed an experimental apparatus and data processing pipeline for quantifying these variables describing prehension. The apparatus presented objects of various sizes and orientations throughout the workspace, evoking different grasping strategies. Object surfaces were instrumented with thousands of pressure-sensitive elements, enabling high-resolution measurement of distributed contact forces. Simultaneously, eight high-speed cameras were used to reconstruct hand and arm movements with markerless tracking, triangulating 3D landmarks, and mapping them onto a musculoskeletal model, enabling estimation of time-varying joint angles. This posture quantification allowed contact forces to be automatically assigned to specific hand segments, in close agreement with manual human annotations. We used the reconstructed movements and contact forces with the musculoskeletal model of the hand to compute inverse dynamics, yielding joint torques throughout behavior, unifying the hand kinematics and grasp forces into a single physical description. Throughout the processing, we identified individual neurons in the motor cortex of monkeys that were related to grasp force, kinematics, and torques. Together, this framework enabled a comprehensive and precise physical characterization of primate manual behavior, providing a foundation for investigating the neural mechanisms of manual dexterity.

neuroscience↗

bioRxiv2024

How different immersive environments affect intracortical brain computer interfaces

AO_SCPLOWBSTRACTC_SCPLOWAs brain-computer interface (BCI) research advances, many new applications are being developed. Tasks can be performed in different environments, and whether a BCI user can switch environments seamlessly will influence the ultimate utility of a clinical device. Here we investigate the importance of the immersiveness of the virtual environment used to train BCI decoders on the resulting decoder and its generalizability between environments. Two participants who had intracortical electrodes implanted in their precentral gyrus used a BCI to control a virtual arm, either viewed immersively through virtual reality goggles or at a distance on a flat television monitor. Each participant performed better with a decoder trained and tested in the environment they had used the most prior to the study, one for each environment type. The neural tuning to the desired movement was minimally influenced by the immersiveness of the environment. Finally, in further testing with one of the participants, we found that decoders trained in one environment generalized well to the other environment, but the order in which the environments were experienced within a session mattered. Overall, experience with an environment was more influential on performance than the immersiveness of the environment, but BCI performance generalized well after accounting for experience.

neuroscience↗

bioRxiv2021

M1 dynamics share similar inputs for initiating and correcting movement

Primary motor cortex (M1) plays a central role in voluntary movement, but how it integrates sensory-driven corrective instructions is unclear. We analyzed population activity recorded from M1 of macaques during a sequential arm movement task with target updates requiring online adjustments to the motor plan. Using Latent Factor Analysis via Dynamical Systems (LFADS), we separated neural activity into two components: intrinsic dynamics and inferred external inputs influencing those dynamics. Inferred input timing was more strongly locked to target appearance than to movement onset, suggesting that variable reaction times reflect interactions between inputs and ongoing dynamics. Inferred inputs were tuned similarly for both initial and corrective movements, suggesting a shared input encoding across visually-instructed and corrective movements that was previously obscured by M1 dynamics. Because input inference can suffer from the challenge of nonidentifiability, where different models fit the data indistinguishably, we used ensembles of models with varied hyperparameters to diagnose when inputs are identifiable or nonidentifiable. In the monkey data, ensembles produced consistently similar results, suggesting that inputs could be meaningfully inferred and that their encoding was not simply a result of model bias. These results highlight the challenges of nonidentifiability and the potential of model ensembles to identify inputs in ongoing dynamics, at least in some cases.

neuroscience↗

bioRxiv2021

Validating marker-less pose estimation with 3D x-ray radiography

To reveal the neurophysiological underpinnings of natural movement, neural recordings must be paired with accurate tracking of limbs and postures. Here we validate the accuracy of DeepLabCut (DLC) by comparing it to a 3D x-ray video radiography system that tracks markers placed under the skin (XROMM). We record behavioral data simultaneously with XROMM and high-speed video for DLC as marmosets engage in naturalistic foraging and reconstruct three-dimensional kinematics in a shared coordinate system. We find that DLC tracks position and velocity of 12 markers on the forelimb and torso with low median error (0.272 cm and 1.76 cm/s, respectively) corresponding to 2.9% of the full range of marker positions and 5.9% of the range of speeds. For studies that can accept this relatively small degree of error, DLC and similar marker-less pose estimation tools enable the study of more naturalistic, unconstrained behaviors in many fields including non-human primate motor control. Summary StatementWe validate the accuracy of DeepLabCut, a widely used marker-less pose estimation tool, using a marker-based 3D x-ray radiography system (XROMM).

animal behavior and cognition↗

bioRxiv2020

Multiple regions of primate orofacial sensorimotor cortex encode bite force and gape

The precise control of bite force and gape is vital for effective breakdown and manipulation of food inside the oral cavity during feeding. Yet the role of the orofacial sensorimotor cortex (OSMcx) in the control of bite force and gape is still largely unknown. The aim of this study was to elucidate how individual neurons and populations of neurons in multiple regions of OSMcx differentially encode bite force and gape when subjects (Macaca mulatta) generated different levels of bite force at varying gapes. We examined neuronal activity recorded simultaneously from three microelectrode arrays implanted chronically in the primary motor (MIo), primary somatosensory (SIo), and cortical masticatory (CMA) areas of OSMcx. We used generalized linear models to evaluate encoding properties of individual neurons and utilized dimensionality reduction techniques to decompose population activity into components related to specific task parameters. Individual neurons encoded bite force more strongly than gape in all three OSMCx areas although bite force was a better predictor of spiking activity in MIo versus SIo. Population activity differentiated between levels of bite force and gape while preserving task-independent temporal modulation across the behavioral trial. While activation patterns of neuronal populations were comparable across OSMCx areas, the total variance explained by task parameters was context-dependent and differed across areas. These findings suggest that the cortical control of gape may rely on computations at the population level whereas the strong encoding of bite force at the individual neuron level allows for the precise and rapid control of bite force. Significance StatementBiting a piece off an apple requires precise sensorimotor control and coordination of bite force and gape by multiple brain regions. The cortical representations of bite force and gape by individual neurons and large populations of neurons across connected motor and somatosensory areas in orofacial cortex is unknown. Here we showed that bite force was more strongly encoded than gape by individual neurons in primary motor, somatosensory, and cortical masticatory areas. Moreover, bite force was more effectively represented in motor versus somatosensory cortices. At the population level, bite force and gape were distinguishable particularly when gape was randomized from trial-to-trial. The results are important for understanding neurophysiological processes underlying masticatory dysfunctions that may occur in aging, stroke, and Alzheimers disease.

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

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↗

bioRxiv2019

Propagating patterns of activity across motor cortex facilitate movement initiation

Voluntary movement initiation involves the modulation of neurons in the primary motor cortex (M1) around movement onset. Yet, similar modulations of M1 activity occur during movement planning when no movement occurs. Here, we show that a sequential spatio-temporal pattern of excitability based on beta oscillation amplitude attenuation propagates across M1 prior to the initiation of reaching movements in one of two oppositely oriented directions along the rostro-caudal axis. Using spatiotemporal patterns of intracortical microstimulation, we find that reaction time increases significantly when stimulation is delivered against but not with the natural propagation orientation suggesting that movement initiation requires a precise recruitment pattern in M1. Functional connections among M1 units emerge at movement onset that are oriented along the same rostro-caudal axis but not during movement planning. Finally, we show that beta amplitude profiles can more accurately decode muscle activity when these patterns conform to the natural propagating patterns. These findings provide the first causal evidence that large-scale, spatially organized propagating patterns of cortical excitability and activity are behaviorally relevant and may be a necessary component of movement initiation.

neuroscience↗

bioRxiv2017

Non-monotonic spatial structure of interneuronal correlations in prefrontal microcircuits

Correlated fluctuations of single neuron discharges, on a mesoscopic scale, decrease as a function of lateral distance in early sensory cortices, reflecting a rapid spatial decay of lateral connection probability and excitation. However, spatial periodicities in horizontal connectivity and associational input as well as an enhanced probability of lateral excitatory connections in the association cortex could theoretically result in non-monotonic correlation structures. Here we show such a spatially non-monotonic correlation structure, characterized by significantly positive long-range correlations, in the inferior convexity of the macaque prefrontal cortex. This functional connectivity kernel was more pronounced during wakefulness than anesthesia and could be largely attributed to the spatial pattern of correlated variability between functionally similar neurons during structured visual stimulation. These results suggest that the spatial decay of lateral functional connectivity is not a common organizational principle of neocortical microcircuits. A non-monotonic correlation structure could reflect a critical topological feature of prefrontal microcircuits, facilitating their role in integrative processes.\n\nSignificance statementThe spatial structure of correlated activity of neurons in lower-order visual areas has been shown to linearly decrease as a measure of distance. The shape of correlated variability is a defining feature of cortical microcircuits as it constrains the computational power and diversity of a region. We show here for the first time a non-monotonic spatial structure of functional connectivity in the pre-frontal cortex where distal interactions are just as strong as proximal interactions during visual engagement of functionally similar PFC neurons. Such a nonmonotonic structure of functional connectivity could have far-reaching consequences in rethinking the nature and the role of prefrontal microcircuits in various cognitive states.

neuroscience↗