@article {4565, title = {The effect of transcutaneous auricular vagus nerve stimulation on cardiovascular function in subarachnoid hemorrhage patients: A randomized trial.}, journal = {Elife}, volume = {13}, year = {2025}, month = {2025 Jan 09}, abstract = {

BACKGROUND: Subarachnoid hemorrhage (SAH) is characterized by intense central inflammation, leading to substantial post-hemorrhagic complications such as vasospasm and delayed cerebral ischemia. Given the anti-inflammatory effect of transcutaneous auricular vagus nerve stimulation (taVNS) and its ability to promote brain plasticity, taVNS has emerged as a promising therapeutic option for SAH patients. However, the effects of taVNS on cardiovascular dynamics in critically ill patients, like those with SAH, have not yet been investigated. Given the association between cardiac complications and elevated risk of poor clinical outcomes after SAH, it is essential to characterize the cardiovascular effects of taVNS to ensure this approach is safe in this fragile population. Therefore, this study assessed the impact of both acute and repetitive taVNS on cardiovascular function.

METHODS: In this randomized clinical trial, 24 SAH patients were assigned to either a taVNS treatment or a sham treatment group. During their stay in the intensive care unit, we monitored patient electrocardiogram readings and vital signs. We compared long-term changes in heart rate, heart rate variability (HRV), QT interval, and blood pressure between the two groups. Additionally, we assessed the effects of acute taVNS by comparing cardiovascular metrics before, during, and after the intervention. We also explored acute cardiovascular biomarkers in patients exhibiting clinical improvement.

RESULTS: We found that repetitive taVNS did not significantly alter heart rate, QT interval, blood pressure, or intracranial pressure (ICP). However, repetitive taVNS increased overall HRV and parasympathetic activity compared to the sham treatment. The increase in parasympathetic activity was most pronounced from 2 to 4 days after initial treatment (Cohen{\textquoteright}s = 0.50). Acutely, taVNS increased heart rate, blood pressure, and peripheral perfusion index without affecting the corrected QT interval, ICP, or HRV. The acute post-treatment elevation in heart rate was more pronounced in patients who experienced a decrease of more than one point in their modified Rankin Score at the time of discharge.

CONCLUSIONS: Our study found that taVNS treatment did not induce adverse cardiovascular effects, such as bradycardia or QT prolongation, supporting its development as a safe immunomodulatory treatment approach for SAH patients. The observed acute increase in heart rate after taVNS treatment may serve as a biomarker for SAH patients who could derive greater benefit from this treatment.

FUNDING: The American Association of Neurological Surgeons (ALH), The Aneurysm and AVM Foundation (ALH), The National Institutes of Health R01-EB026439, P41-EB018783, U24-NS109103, R21-NS128307 (ECL, PB), McDonnell Center for Systems Neuroscience (ECL, PB), and Fondazione Neurone (PB).

CLINICAL TRIAL NUMBER: NCT04557618.

}, keywords = {Adult, Aged, Blood Pressure, Electrocardiography, Female, Heart Rate, Humans, Male, Middle Aged, Subarachnoid Hemorrhage, Transcutaneous Electric Nerve Stimulation, Vagus Nerve Stimulation}, issn = {2050-084X}, doi = {10.7554/eLife.100088}, author = {Tan, Gansheng and Huguenard, Anna L and Donovan, Kara M and Demarest, Phillip and Liu, Xiaoxuan and Li, Ziwei and Adamek, Markus and Lavine, Kory and Vellimana, Ananthv K and Kummer, Terrance T and Osbun, Joshua W and Zipfel, Gregory J and Brunner, Peter and Leuthardt, Eric C} } @article {4567, title = {IpsiHand Brain-Computer Interface Therapy Induces Broad Upper Extremity Motor Rehabilitation in Chronic Stroke.}, journal = {Neurorehabil Neural Repair}, volume = {39}, year = {2025}, month = {2025 Jan}, pages = {74-86}, abstract = {

BACKGROUND: Chronic hemiparetic stroke patients have very limited benefits from current therapies. Brain-computer interface (BCI) engaging the unaffected hemisphere has emerged as a promising novel therapeutic approach for chronic stroke rehabilitation.

OBJECTIVES: This study investigated the effectiveness of contralesionally-controlled BCI therapy in chronic stroke patients with impaired upper extremity motor function. We further explored neurophysiological features of motor recovery driven by BCI. We hypothesized that BCI therapy would induce a broad motor recovery in the upper extremity, and there would be corresponding changes in baseline theta and gamma oscillations, which have been shown to be associated with motor recovery.

METHODS: Twenty-six prospectively enrolled chronic hemiparetic stroke patients performed a therapeutic BCI task for 12 weeks. Motor function assessment data and resting state electroencephalogram signals were acquired before initiating BCI therapy and across BCI therapy sessions. The Upper Extremity Fugl-Meyer assessment served as a primary motor outcome assessment tool. Theta-gamma cross-frequency coupling (CFC) was computed and correlated with motor recovery.

RESULTS: Chronic stroke patients achieved significant motor improvement in both proximal and distal upper extremity with BCI therapy. Motor function improvement was independent of Botox application. Theta-gamma CFC enhanced bilaterally over the C3/C4 motor electrodes and positively correlated with motor recovery across BCI therapy sessions.

CONCLUSIONS: BCI therapy resulted in significant motor function improvement across the proximal and distal upper extremities of patients, which significantly correlated with theta-gamma CFC increases in the motor regions. This may represent rhythm-specific cortical oscillatory mechanism for BCI-driven rehabilitation in chronic stroke patients.

TRIAL REGISTRATION: Advarra Study: https://classic.clinicaltrials.gov/ct2/show/NCT04338971 and Washington University Study: https://classic.clinicaltrials.gov/ct2/show/NCT03611855.

}, keywords = {Adult, Aged, brain-computer interfaces, Chronic Disease, Electroencephalography, Female, Gamma Rhythm, Humans, Male, Middle Aged, Motor Activity, Paresis, Prospective Studies, Recovery of Function, Stroke, Stroke Rehabilitation, Theta Rhythm, Upper Extremity}, issn = {1552-6844}, doi = {10.1177/15459683241287731}, author = {Rustamov, Nabi and Souders, Lauren and Sheehan, Lauren and Carter, Alexandre and Leuthardt, Eric C} } @article {4573, title = {Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.}, journal = {J Neurooncol}, volume = {169}, year = {2024}, month = {2024 Aug}, pages = {175-185}, abstract = {

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care.

METHODS: Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS >= 70).

RESULTS: The models achieved a nested cross-validation accuracy of 94.1\% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor.

CONCLUSION: The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor{\textquoteright}s location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.

}, keywords = {Adult, Aged, Brain, Brain Neoplasms, Female, Glioma, Humans, machine learning, Magnetic Resonance Imaging, Male, Middle Aged, Neoplasm Grading, Prognosis, Rest, Retrospective Studies}, issn = {1573-7373}, doi = {10.1007/s11060-024-04715-1}, author = {Luckett, Patrick H and Olufawo, Michael O and Park, Ki Yun and Lamichhane, Bidhan and Dierker, Donna and Verastegui, Gabriel Trevino and Lee, John J and Yang, Peter and Kim, Albert and Butt, Omar H and Chheda, Milan G and Snyder, Abraham Z and Shimony, Joshua S and Leuthardt, Eric C} }