Biology subjects

Patriat, R.

Publications and source records attributed to Patriat, R..

8 recordsLinked to original sources

bioRxiv2026

Prefrontal cortical pathways mediating cognitive control enhancement from internal capsule stimulation

BackgroundDeep brain stimulation (DBS) targeting the ventral internal capsule/ventral striatum (VCVS) is an effective treatment for several psychiatric disorders, but clinical responses often vary amongst patients likely due to an incomplete mechanistic understanding of the brain pathways mediating response. VCVS DBS can improve cognitive control, a core deficit in multiple psychiatric disorders. Here, we investigated which prefrontal cortical pathway(s) in the internal capsule are associated with improving cognitive control during VCVS DBS. MethodsFour participants with bilateral VCVS DBS completed the Multi-Source Interference Task (MSIT) under 27 stimulation settings varying by side (left/right lead), electrode, amplitude, and frequency. Each condition included 100 trials and response time (RT) assessed task performance. Personalized pathway activation models quantified axonal recruitment across 11 segmented prefrontal cortical fiber bundles per brain hemisphere. Associations between pathway activation and task RT were analyzed to identify circuits linked to improved cognitive control performance. ResultsRight-sided VCVS stimulation produced greater improvements in cognitive control (reductions in MSIT RT) than left-sided stimulation. Activation of right dorsal prefrontal cortical pathways connected to the dorsolateral prefrontal cortex (dlPFC) and dorsomedial prefrontal cortex (dmPFC) most strongly predicted faster MSIT RTs, whereas no left-sided pathways were associated with performance changes. ConclusionsThese findings suggest that the effects of VCVS DBS on cognitive control are primarily mediated by right dorsal prefrontal cortical axons projecting from the dlPFC and dmPFC. Targeting these pathways may improve stimulation strategies and outcomes for psychiatric disorders characterized by impaired cognitive control.

neuroscience↗

bioRxiv2026

Conserved fiber topography of the anterior limb of the internal capsule in treatment-resistant psychiatric patients

IntroductionThe anterior limb of the internal capsule (ALIC) is a major white matter highway connecting prefrontal cortical (PFC) regions to the thalamus, brainstem, and subthalamic nucleus. Structural and functional abnormalities within the ALIC circuit have been associated with many neuropsychiatric disorders, including obsessive-compulsive disorder (OCD) and depression, and deep brain stimulation (DBS) may provide effective treatment to some of these patients. However, it remains unclear whether the well-characterized topographic organization of the ALIC observed in healthy individuals and preclinical models is preserved in treatment-resistant psychiatric populations. MethodsWe first used diffusion tractography to evaluate the topography of PFC and subcortical fibers through the ALIC in patients with treatment-resistant OCD (n=18) and depression (n=5). In depression patients, we also evaluated ALIC topography using cerebro-cerebral evoked potentials (CCEPs) elicited by single-pulse electrical stimulation (SPES) of DBS leads in the ALIC and recordings in the ventral PFC (vPFC). ResultsThe topographic organization of PFC and subcortical projections is preserved in the ALIC among treatment-resistant psychiatric patients, consistent with patterns observed in healthy individuals and preclinical models. CCEP recordings in the ventral PFC showed a ventral ALIC to medial vPFC/dorsal ALIC to lateral vPFC response pattern in the left hemisphere, but not in the right. ConclusionOur findings confirm that topographic patterns within the ALIC previously identified using preclinical models and healthy controls are preserved in treatment-resistant psychiatric patients. Furthermore, by linking white matter topography to stimulation effects, this work supports more precise and individualized neuromodulatory strategies for neuropsychiatric disorders.

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↗

bioRxiv2021

Parkinsonian gait effects with DBS are associated with pallido-peduncular axis activation

BackgroundDeep brain stimulation (DBS) targeting the subthalamic nucleus (STN) often shows variable outcomes on treating gait dysfunction in Parkinsons disease (PD). Such variability may stem from which specific neuronal pathways are modulated by DBS and the extent to which those pathways are modulated relative to one another. ObjectiveLeveraging ultra-high-field (7T) imaging data and subject-specific computational models, this study investigated how activation of seven distinct pathways in and around STN, including the pallidopeduncular and pedunculopallidal pathways, affect step length at clinically-optimized STN-DBS settings. MethodsPersonalized computational models were developed for 10 subjects with a clinical diagnosis of PD and with bilateral STN-DBS implants. ResultsThe subject-specific pathway activation models showed a significant positive association between activation of the pedunculopallidal pathway and increased step length, and negative association on step length with pallidopeduncular pathway and hyperdirect pathway activation. ConclusionsThe STN region includes multiple pathways, including fibers of passage to and from the mesencephalic locomotor area. Future clinical optimization of STN-DBS should consider these fibers of passage in the context of treating parkinsonian gait.

neuroscience↗

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↗

bioRxiv2020

Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI

Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of life for patients with various motor dysfunctions, such as those afflicted with Parkinsons disease (PD), dystonia, and essential tremor (ET), by relieving motor symptoms associated with such pathologies. The success of DBS procedures is directly related to the proper placement of the electrodes, which requires the ability to accurately detect and identify relevant target structures within the subcortical basal ganglia region. In particular, accurate and reliable segmentation of the globus pallidus (GP) interna is of great interest for DBS surgery for PD and dystonia. In this work, we present a deep-learning based neural network, which we term GP-net, for the automatic segmentation of both the external and internal segments of the globus pallidus. High resolution 7 Tesla images from 101 subjects were used in this study; GP-net is trained on a cohort of 58 subjects, containing patients with movement disorders as well as healthy control subjects. GP-net performs 3D inference in a patient-specific manner, alleviating the need for atlas-based segmentation. GP-net was extensively validated, both quantitatively and qualitatively over 43 test subjects including patients with movement disorders and healthy control and is shown to consistently produce improved segmentation results compared with state-of-the-art atlas-based segmentations. We also demonstrate a post-operative lead location assessment with respect to a segmented globus pallidus obtained by GP-net.

neuroscience↗

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↗

bioRxiv2018

Automatic Localization of the Subthalamic Nucleus on Patient-Specific Clinical MRI by Incorporating 7T MRI and Machine Learning: Application in Deep Brain Stimulation

Deep Brain Stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinsons disease. While accurate localization of the STN is critical for consistent across-patients effective DBS, clear visualization of the STN under standard clinical MR protocols is still challenging. Therefore, intraoperative microelectrode recordings (MER) are incorporated to accurately localize the STN. However, MER require significant neurosurgical expertise and lengthen the surgery time. Recent advances in 7T MR technology facilitate the ability to clearly visualize the STN. The vast majority of centers, however, still do not have 7T MRI systems, and fewer have the ability to collect and analyze the data. This work introduces an automatic STN localization framework based on standard clinical MRIs without additional cost in the current DBS planning protocol. Our approach benefits from a large database of 7T MRI and its clinical MRI pairs. We first model in the 7T database, using efficient machine learning algorithms, the spatial and geometric dependency between the STN and its adjacent structures (predictors). Given a standard clinical MRI, our method automatically computes the predictors and uses the learned information to predict the patient-specific STN. We validate our proposed method on clinical T2W MRI of 80 subjects, comparing with experts-segmented STNs from the corresponding 7T MRI pairs. The experimental results show that our framework provides more accurate and robust patient-specific STN localization than using state-of-the-art atlases. We also demonstrate the clinical feasibility of the proposed technique assessing the post-operative electrode active contact locations.

neuroscience↗