Biology subjects

Vitek, J. L.

Publications and source records attributed to Vitek, J. L..

14 recordsLinked to original sources

bioRxiv2026

Spontaneous eye behavior is an objective marker of parkinsonian severity

Eye behavior disruption is reported in Parkinson's disease (PD), but its correlation with disease severity has not been well examined. Here, in a nonhuman primate model of PD, we show that spontaneous eye behavior is impaired in parkinsonism and correlates with clinical rating scores and subthalamic beta oscillatory activity. These findings suggest that spontaneous eye behavior could serve as an objective, non-invasive biomarker of parkinsonian severity.

neuroscience↗

bioRxiv2026

Parkinsonism disrupts the population-level organization of cortical dynamics

Parkinsons disease (PD) is marked by impairments in voluntary movement, including prolonged movement preparation and execution, yet how parkinsonism alters neural processing to produce these deficits remains unresolved. Prior work examining M1 spiking activity in parkinsonian states has largely characterized firing-rate changes and motor representations at the level of individual neurons, with inconsistent results and limited insight into population-level organization. Here we investigated how parkinsonism reshapes the population-level organization of neural activity in M1 during movement. We simultaneously recorded large populations of neurons from M1 in two nonhuman primates performing reaching tasks before and after induction of parkinsonism with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). In the parkinsonian state, both preparation and reach durations were significantly prolonged. Population-level analyses revealed that parkinsonism increased the dimensionality of M1 activity during both preparation and movement and reduced the orthogonality between preparatory and movement-related subspaces. Moreover, trial-by-trial variability in reach duration was explained by the alignment of the preparatory and reach subspaces, indicating the functional role of subspace orthogonality. Together, these findings suggest that parkinsonism disrupts the population-level organization of cortical dynamics across computations, providing a population-level framework linking altered cortical dynamics to the movement-related dysfunction observed in PD.

neuroscience↗

bioRxiv2026

Coupled beta and high-frequency oscillations emerge from synchronized bursting in a minimal model of the parkinsonian subthalamic nucleus

Local field potentials recorded from the subthalamic nucleus (STN) in Parkinson's disease (PD) exhibit a distinctive multiscale spectral signature: exaggerated beta-band oscillations (13-30 Hz) coupled to high-frequency oscillations (HFOs, 200-400 Hz), with HFO amplitude being phase-locked to the beta cycle. This phase-amplitude coupling (PAC) has been identified as a promising biomarker of the parkinsonian state, yet no biophysical model has explained how it emerges, what determines the HFO frequency, or how HFOs can exist without beta modulation in the medicated STN. Here we show that a heterogeneous population of excitatory Izhikevich neurons with recurrent coupling produces three dynamical regimes: (i) asynchronous tonic firing, (ii) asynchronous bursting, in which neurons burst individually producing broadband HFO power but without coherent population-level PAC, and (iii) synchronous bursting, which gives rise to beta-HFO PAC. The regimes are governed by two biophysically interpretable parameters that capture complementary effects of dopamine depletion: one reflecting changes in intrinsic neuronal excitability, the other reflecting changes in synaptic coupling strength. The transition from asynchronous to synchronous bursting in this model captures the emergence of pathological STN neuronal activity in the parkinsonian state. HFO peak frequency varies continuously across the two-parameter landscape, suggesting a possible mechanism of the clinically observed shift from slow (200-300 Hz) to fast (300-400 Hz) HFOs between medication states. The character of the synchronization transition depends on baseline excitability, ranging from a sharp co-emergence of bursting and synchrony at low excitability to a decoupled transition at intermediate excitability, where the bursting fraction saturates while the population synchronization continues to increase with coupling. We also extend the model to include reciprocal coupling to an inhibitory population of globus pallidus externa (GPe)-like neurons and report a similar asynchronous-to-synchronous bursting transition and beta-HFO PAC emerging in the STN population, with the beta rhythm being set by the delay in the synaptic coupling between the two populations. The model generates testable predictions for future clinical and experimental studies, provides a numerical dissection of how mesoscopic LFP features map onto microscopic neuronal dynamics, and serves as a computational building block for future circuit-level models that may inform brain stimulation strategies tailored to the patient-specific dynamical state of the STN.

neuroscience↗

bioRxiv2025

Sleep firing rate homeostasis is disrupted in mild parkinsonism

Sleep-associated downscaling of neuronal firing, i.e., firing rate homeostasis (FRH), is essential for restorative sleep. Sleep dysfunction is common in Parkinsons disease (PD), but FRH has not been investigated. Here, using a within-subject design in the nonhuman primate model of PD, we report that thalamocortical FRH is disrupted in parkinsonism. These findings can inform therapeutic approaches tailored towards normalizing FRH to reestablish restorative sleep in PD.

neuroscience↗

bioRxiv2024

Parkinsonism disrupts neuronal modulation in the pre-supplementary motor area during movement preparation

Multiple studies suggest that Parkinsons disease (PD) is associated with changes in neuronal activity throughout the basal ganglia-thalamocortical motor circuit. There are limited electrophysiological data, however, describing how parkinsonism impacts neuronal activity in the pre-supplementary motor area (pre-SMA), an area in medial frontal cortex involved in movement planning and motor control. In this study, single unit activity was recorded in the pre-SMA of two non-human primates during a visually cued reaching task in both the naive and parkinsonian state using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of parkinsonism. In the naive state neuronal discharge rates were dynamically modulated prior to the presentation of the instructional go-cue. In a subset of these modulated cells, the magnitude of modulation correlated linearly with reaction time (RT). In the parkinsonian state, however, modulation of discharge rates in the pre-SMA was disrupted and the predictive encoding of RT was significantly diminished. These findings add to our understanding of the role of pre-SMA in motor behavior and suggest that disrupted encoding in this cortical area contributes to the alteration of early preparatory and pre-movement processes that are present in Parkinsons disease. SIGNIFICANCE STATEMENTGoal-directed movements, such as reaching for an object, necessitate temporal preparation and organization of information processing within the basal ganglia-thalamocortical motor network. Impaired movement in people with Parkinsons disease is thought to be the result of pathophysiological activity disrupting information flow within this network. This work provides neurophysiological evidence linking altered motor preplanning processes encoded in pre-supplementary motor area (pre-SMA) neuronal firing to the pathogenesis of motor disturbances in parkinsonism.

neuroscience↗

bioRxiv2024

Impairment of Neuronal Activity in the Dorsolateral Prefrontal Cortex Occurs Early in Parkinsonism

BackgroundParkinsons disease (PD) is often characterized by altered rates and patterns of neuronal activity in the sensorimotor regions of the basal ganglia thalamocortical network. Little is known, however, regarding how neuronal activity in the executive control network of the brain changes in the parkinsonian condition. ObjectiveInvestigate the impact of parkinsonism on neuronal activity in the dorsolateral prefrontal cortex (DLPFC), a key region in executive control, during a go/nogo reaching task. MethodsUsing a within-subject design, single and multi-unit neuronal activity was recorded in the DLPFC of a nonhuman primate before and after the induction of mild parkinsonism using the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). ResultsCoincident with development of mild parkinsonian motor signs, there was a marked reduction in the percentage of DLPFC cells with significant task-related firing rate modulation during go and nogo conditions. ConclusionsThese results suggest that DLPFC dysfunction may occur early in parkinsonism and contribute to cognitive impairments and disrupted executive function often observed in PD patients.

neuroscience↗

bioRxiv2023

Excessive cortical beta oscillations are associated with slow-wave sleep dysfunction in mild parkinsonism

Increasing evidence associates slow-wave sleep (SWS) dysfunction with neurodegeneration. Using a within-subject design in the nonhuman primate model of Parkinsons disease (PD), we found that reduced SWS quantity in mild parkinsonism was accompanied by elevated beta and reduced delta power during SWS in the motor cortex. Our findings support excessive beta oscillations as a mechanism for SWS dysfunction and will inform development of neuromodulation therapies for enhancing SWS in PD.

neuroscience↗

bioRxiv2022

REM Sleep Movements in Parkinson's Disease: Is the Basal Ganglia Engaged?

To elucidate the role of the basal ganglia during REM sleep movements in Parkinsons disease (PD) we recorded pallidal neural activity from four PD patients. Unlike desynchronization commonly observed during wakeful movements, beta oscillations (13-35 Hz) synchronized during REM sleep movements; furthermore, high-frequency oscillations (150-350 Hz) synchronized during movement irrespective of sleep-wake states. Our results demonstrate differential engagement of the basal ganglia during REM sleep and awake movements.

neuroscience↗

bioRxiv2022

Classification of electrically-evoked compound action potentials in the parkinsonian subthalamic nucleus of non-human primates

Electrically evoked compound action potentials (ECAPs) generated in the subthalamic nucleus (STN) contain features that may be useful for titrating deep brain stimulation (DBS) therapy for Parkinsons disease. Delivering a strong therapeutic effect with DBS therapies, however, relies on selectively targeting neural pathways to avoid inducing side effects. In this study, we investigated the spatiotemporal features of ECAPs in and around the STN across parameter sweeps of stimulation current amplitude, pulse width, and electrode configuration, and used a linear classifier of ECAP responses to predict electrode location. Four non-human primates were implanted unilaterally with either a directional (n=3) or non-directional (n=1) DBS lead targeting the sensorimotor STN. ECAP responses were characterized by primary features (within 1.6 ms after a stimulus pulse) and secondary features (between 1.6-7.4 ms after a stimulus pulse). Using these ECAP features, a linear classifier was able to accurately differentiate electrodes within the STN versus dorsal to the STN in all four subjects. ECAP responses varied systematically with recording and stimulating electrode locations, which provides a subject-specific neuroanatomical basis for selecting electrode configurations in the treatment of Parkinsons disease with DBS therapy.

neuroscience↗

bioRxiv2022

Deep brain stimulation pulse sequences to optimally modulate frequency-specific neural activity

Precise neuromodulation systems are needed to identify the role of neural oscillatory dynamics in brain function, and to advance the development of electrical stimulation therapies tailored to each patients signature of brain dysfunction. Low-frequency, local field potentials (LFPs) are of increasing interest for the development of these systems because they reflect the synaptic inputs to a recorded neuronal population and can be chronically recorded in humans. Here, we identified stimulation pulse sequences to optimally minimize or maximize the 2-norm of frequency-specific LFP oscillations using a generalized mathematical model of spontaneous and stimulation-evoked LFP activity, and a subject-specific model of neural dynamics in the pallidum of a Parkinsons disease patient. We leveraged convex and mixed-integer optimization tools to identify the pulse patterns, and employed constraints on the pulse frequency and amplitude that are required to keep electrical stimulation within its safety envelope. Our analysis revealed that a combination of phase, amplitude, and frequency pulse modulation is needed to attain optimal suppression or amplification of the targeted oscillations. Phase modulation is sufficient to modulate oscillations with a constant amplitude envelope. To attain optimal modulation for oscillations with a time-varying envelope, a trade-off between frequency and amplitude pulse modulation is needed. The optimized pulse sequences identified here were invariant to changes in the dynamics of stimulation-evoked neural activity, including the damping and natural frequency or complexity (i.e., generalized vs. patient-specific model). Our results reveal the structure of pulse sequences that can be used in closed-loop brain stimulation devices to control neural activity in real-time. Significance StatementThis computational study reveals the structure of electrical pulse sequences that optimally modulate spontaneous, synaptic-related neural oscillations measured using local field potentials (LFPs). We considered constraints on the pulse amplitude and frequency, relevant to keep stimulation pulses within the safety envelope. Our mathematical analysis indicate that these optimized pulse sequences are invariant to changes in the studied neural dynamics, and a trade-off between amplitude and frequency pulse modulation is critical when the pulse amplitude is constrained. The pulse sequences identified here provide the rationale for the development of closed-loop neuromodulation systems that employ stimulation-evoked responses to control neural activity. These closed-loop systems will be key to characterize the role of neural activity in brain function and ultimately advance personalized neuromodulation devices.

bioengineering↗

bioRxiv2021

Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): proof of concept in the human

Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 8-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinsons disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulse with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequencyspecific (16-22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.

neuroscience↗

bioRxiv2021

Quantifying Viscous Damping and Stiffness in Parkinsonism Using Data-Driven Model Estimation

Rigidity of upper and lower limbs in Parkinsons disease (PD) is typically assessed via a clinical rating scale that is subject to biases inherent to human perception. Methodologies and systems to systematically quantify changes in rigidity associated with angular position (stiffness) or velocity (viscous damping) are needed to enhance our understanding of PD pathophysiology and objectively assess therapies. We developed a robotic system and a model-based approach to estimate viscous damping and stiffness of the elbow. Our methodology enables the subject to freely rotate the elbow, while torque perturbations tailored to identify the arm dynamics are delivered. The viscosity and stiffness are calculated based on the experimental data using least-squares optimization. We validated our technique using computer simulations of the arm dynamics and experiments with a nonhuman animal model of PD in the presence and absence of deep brain stimulation (DBS) therapy. Computer simulations of the arm demonstrate that the proposed approach can accurately estimate viscous damping and stiffness. The experimental data show that both viscosity and stiffness significantly decreased when DBS was delivered. Computer simulations and experiments showed that stiffness and viscosity measurements obtained with the proposed methodology could better differentiate changes in rigidity than scores previously used for research, including the work score, impulse score, and modified Unified Parkinsons Disease Rating Scale (mUPDRS). The proposed estimation method is suitable to quantify the effect of therapies on viscous damping and stiffness and study the pathophysiological mechanisms underlying rigidity in PD.

bioengineering↗

bioRxiv2020

High-frequency oscillations in the internal globus pallidus: a pathophysiological biomarker in Parkinson's disease?

Abnormal oscillatory neural activity in the basal ganglia is thought to play a pathophysiological role in Parkinsons disease. Many patient studies have focused on beta frequency band (13-35 Hz) local field potential activity in the subthalamic nucleus, however increasing evidence points to alterations in neural oscillations in high frequency ranges (>100 Hz) having pathophysiological relevance. Prior studies have found that power in subthalamic high frequency oscillations (HFOs) is positively correlated with dopamine tone and increased during voluntary movements, implicating these brain rhythms in normal basal ganglia function. Contrary to this idea, in the current study we present a combination of clinical and preclinical data that support the hypothesis that HFOs in the internal globus pallidus (GPi) are a pathophysiological feature of Parkinsons disease. Spontaneous and movement-related pallidal field potentials were recorded from deep brain stimulation (DBS) leads targeting the GPi in five externalized Parkinsons disease patients, on and off dopaminergic medication. We identified a prominent oscillatory peak centered at 200-300 Hz in the off-medication rest recordings in all patients. High frequency power increased during movement, and the magnitude of modulation was negatively correlated with bradykinesia. Moreover, high frequency oscillations were significantly attenuated in the on-medication condition, suggesting they are a feature of the parkinsonian condition. To further confirm that GPi high frequency oscillations are characteristic of dopamine depletion, we also collected field potentials from DBS leads chronically implanted in three rhesus monkeys before and after the induction of parkinsonism with the neurotoxin 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine (MPTP). High frequency oscillations and their modulation during movement were not prominent in the normal condition but emerged in the parkinsonian condition in the monkey model. These data provide the first evidence demonstrating that exaggerated, movement-modulated high frequency oscillations in the internal globus pallidus are a pathophysiological feature of Parkinsons disease, and motivate additional investigations into the functional roles of high frequency neural oscillations across the basal ganglia-thalamocortical motor circuit and their relationship to motor control in normal and diseased states. These findings also provide rationale for further exploration of these signals for electrophysiological biomarker-based device programming and stimulation strategies in patients receiving deep brain stimulation therapy.

neuroscience↗

bioRxiv2020

Suppressing and amplifying neural oscillations in real-time using phase-locked electrical stimulation: concept, optimization and in-vivo testing

BackgroundApproaches to predictably control neural oscillations are needed to understand their causal role in brain function in healthy or diseased states and to advance the development of neuromodulation therapies. In this study, we present a closed-loop neural control and optimization framework to actively suppress or amplify low-frequency neural oscillations observed in local field potentials in real-time by using electrical stimulation. Objective/HypothesisThe rationale behind this control approach and our working hypothesis is that neural oscillatory activity evoked by electrical pulses can suppress or amplify spontaneous oscillations via destructive or constructive interference when stimulation pulses are continuously delivered with appropriate amplitudes and at precise phases of these oscillations in a closed-loop scheme. MethodsWe tested our hypothesis in two nonhuman primates that exhibited a robust increase in low-frequency (8-30 Hz) oscillatory power in the subthalamic nucleus (STN) following administration of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). To test our neural control approach, we targeted 8-17 Hz oscillations and used electrode arrays and electrical stimulation waveforms similar to those used in humans chronically implanted with brain stimulation systems. Stimulation parameters that maximize the suppression or amplification of neural oscillations were predicted using mathematical models of the stimulation evoked oscillations. ResultsOur neural control and optimization approach was capable of actively and robustly suppressing or amplifying oscillations in the targeted frequency band (8-17 Hz) in real-time in the studied subjects. ConclusionsThe results from this study support our hypothesis and suggest that the proposed neural control framework allows one to characterize in controlled experiments the functional role of frequency-specific neural oscillations by using electrodes and stimulation waveforms currently being employed in humans.

neuroscience↗