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Vitek, J.

Publications and source records attributed to Vitek, J..

5 recordsLinked to original sources

Fast Generalized Longitudinal Functional Principal Components Analysis with Applications to Population-Level Neuronal Dynamics

Functional data are widely collected across many fields. One approach for modeling functional data collected across repeated measures is longitudinal functional PCA (LFPCA), which allows for the decomposition of variability at multiple levels. However, existing estimation approaches for LFPCA can be computationally demanding for large or high-dimensional datasets. Here, we propose fast generalized LFPCA, a novel estimation technique that bins data along the functional domain and fits a marginal mixed model at each bin. Simulation results show that the proposed method is orders of magnitude faster than existing techniques while achieving similar accuracy, making LFPCA scalable to datasets with more densely sampled observations and larger sample sizes. We apply the proposed technique to model neuronal firing rate data both on and off deep brain stimulation (DBS) to investigate how the intervention modulates population-level neuronal activity. Our results suggest that the vast majority of between-neuron variation can be explained by four principal components, which relate to individual differences in neuronal firing as well as the arm manipulation paradigm under study. We also find that DBS significantly increases the variability of firing activity, likely driven by increased firing from a subset of neurons in response to DBS, a novel insight not obtained in previous analyses. Code to implement the proposed method and run simulation studies is included in the supplement.

neuroscience↗

Transcranial Alternating Current Stimulation can disrupt or reestablish neural entrainment in a primate model of Parkinson's disease

Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation method which can affect brain oscillations by inducing neuronal entrainment through modulation of spike timings. tACS has high potential for clinical applications in many neurological disorders in which the stimulation can be delivered to modulate oscillatory activity and disrupt pathological brain oscillations. For instance, in Parkinsons Disease (PD), electrophysiological activity in the motor network often exhibits excessive and hyper-synchronized beta oscillations. However, the development of tACS as a therapeutic intervention for pathological oscillations requires the prior establishment of physiologically effective stimulation parameters. We recorded neuronal activity in the motor cortical area of three parkinsonian non-human primates and examined the influence of tACS-induced electric fields on neural firing patterns. We found that weak extracellular electric fields first disrupt beta-band spike timing patterns by changing the preferred spiking phase of neurons but eventually reestablish neural entrainment with altered phase preferences when electric fields are high. Additionally, we show that frequency-matched stimulation, when stimulation frequency corresponds to endogenous oscillatory activity, significantly enhances neural entrainment. Thus, tACS exhibits significant potential for controlling and modulating pathological oscillatory patterns in many neurological disorders such as PD.

neuroscience↗

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↗

Dose-dependent effects of transcranial alternating current stimulation on spike timing in awake nonhuman primates

Weak extracellular electric fields can influence spike timing in neural networks. Approaches to impose such fields on the brain in a noninvasive manner have high potential for novel treatments of neurological and psychiatric disorders. One of these methods, transcranial alternating current stimulation (TACS), is hypothesized to affect spike timing and cause neural entrainment. However, the conditions under which these effects occur in-vivo are unknown. Here, we show that TACS modulates spike timing in awake nonhuman primates (NHPs) in a dose-dependent fashion. Recording single-unit activity from pre-and post-central gyrus regions in NHPs during TACS, we found that a larger population of neurons became entrained to the stimulation waveform for higher stimulation intensities. Performing a cluster analysis of changes in interspike intervals, we identified two main types of neural responses to TACS - increased burstiness and phase entrainment. Our results demonstrate the ability of TACS to affect spike-timing in the awake primate brain and identify fundamental neural mechanisms. Concurrent electric field recordings demonstrate that spike-timing changes occur with stimulation intensities readily achievable in humans. These results suggest that novel TACS protocols tailored to ongoing brain activity may be a potent tool to normalize spike-timing in maladaptive brain networks and neurological disease.

neuroscience↗

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↗