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Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (

BACKGROUND:Psoriasis is the most common chronic inflammatory condition involving the T helper cell system. Population studies have demonstrated that patients with psoriasis and/or psoriatic arthritis have an increased risk of developing vascular risk factors, including diabetes, hypertension, and obesity, and increased risk of adverse vascular events, including myocardial infarction and stroke. Population studies have generally investigated the individual contributions of psoriasis and psoriatic arthritis to development of vascular risk factors; fewer studies have investigated the additive contribution of comorbid inflammatory disorders. We present a case of a woman with psoriasis, psoriatic arthritis, and comorbid vascular risk factors. CASE PRESENTATION:A 49 year-old Caucasian woman with a history of severe psoriasis and psoriatic arthritis since adolescence presented with bilateral lower extremity weakness. She was found to have acute bilateral watershed infarcts and multifocal subacute infarcts. Her evaluation revealed vascular risk factors and elevated non-specific systemic inflammatory markers; serum and cerebral spinal fluid did not reveal underlying infection, hypercoagulable state, or vasculitis. Over the course of days, she exhibited precipitous clinical deterioration related to multiple large vessel occlusions, including the bilateral anterior cerebral arteries and the left middle cerebral artery. Autopsy revealed acute thrombi and diffuse, severe atherosclerosis. CONCLUSION:Patients with early onset inflammatory disease activity or comorbid inflammatory disorders may have an even higher risk of developing metabolic syndrome and adverse vascular events compared to patients with late-onset disease activity or with a single inflammatory condition. The described case illustrates the complex relationship between inflammatory disorders and vascular risk factors. The degree of systemic inflammation, as measured by severity of disease activity, has been shown to have a dose-response relationship with comorbid vascular risk factors and vascular events. Dysregulation of the Th1 and Th17 system has been implicated in the development of atherosclerosis and may explain the severe atherosclerosis seen in such chronic inflammatory conditions. Further research will help refine screening and management guidelines to account for comorbid inflammatory disorders and related disease severity.

Aphasia classifications and specialized language batteries differ across the fields of neurodegenerative disorders and lesional brain injuries, resulting in difficult comparisons of language deficits across etiologies. In this study, we present a simplified framework, in which a widely-used aphasia battery captures clinical clusters across disease etiologies and provides a quantitative and visual method to characterize and track patients over time. The framework is used to evaluate populations representing three disease etiologies: stroke, primary progressive aphasia (PPA), and post-operative aphasia. A total of 330 patients across three populations with cerebral injury leading to aphasia were investigated, including 76 patients with stroke, 107 patients meeting criteria for PPA, and 147 patients following left hemispheric resective surgery. Western Aphasia Battery (WAB) measures (Information Content, Fluency, answering Yes/No questions, Auditory Word Recognition, Sequential Commands, and Repetition) were collected across the three populations and analyzed to develop a multi-dimensional aphasia model using dimensionality reduction techniques. Two orthogonal dimensions were found to explain 87% of the variance across aphasia phenotypes and three disease etiologies. The first dimension reflects shared weighting across aphasia subscores and correlated with aphasia severity. The second dimension incorporates fluency and comprehension, thereby separating Wernicke's from Broca's aphasia, and the non-fluent/agrammatic from semantic PPA variants. Clusters representing clinical classifications, including late PPA presentations, were preserved within the two-dimensional space. Early PPA presentations were not classifiable, as specialized batteries are needed for phenotyping. Longitudinal data was further used to visualize the trajectory of aphasias during recovery or disease progression, including the rapid recovery of post-operative aphasic patients. This method has implications for the conceptualization of aphasia as a spectrum disorder across different disease etiology and may serve as a framework to track the trajectories of aphasia progression and recovery.

Objective: This study was undertaken to measure the duration of chronic electrocorticography (ECoG) needed to attain stable estimates of the seizure laterality ratio in patients with drug‐resistant bilateral temporal lobe epilepsy (BTLE). Methods: We studied 13 patients with drug‐resistant BTLE who were implanted for at least 1 year with a responsive neurostimulation device (RNS System) that provides chronic ambulatory ECoG. Bootstrap analysis and nonlinear regression were applied to model the relationship between chronic ECoG duration and the probability of capturing at least one seizure. Laterality of electrographic seizures in chronic ECoG was compared with the seizure laterality ratio from Phase 1 scalp video‐electroencephalographic (vEEG) monitoring. The Kaplan–Meier estimator was used to evaluate time to seizure laterality ratio convergence. Results: Seizure laterality ratios from Phase 1 scalp vEEG monitoring correlated poorly with those from RNS chronic ECoG (r =.31, p =.30). Across the 13 patients, average electrographic seizure frequencies ranged from 1.4 seizures/month to 5.1 seizures/day. A 50% probability of recording at least one electrographic seizure required 9.1 days of chronic ECoG, and 90% probability required 44.3 days of chronic ECoG. A median recording duration of 150.9 days (5 months), corresponding to a median of 16 seizures, was needed before confidence intervals for the seizure laterality ratio reliably contained the long‐term value. The median recording duration before the point estimate of the seizure laterality ratio converged to a stationary value was 236.8 days (7.9 months). Significance: RNS chronic ECoG overcomes temporal sampling limitations intrinsic to inpatient Phase 1 vEEG evaluations. In patients with drug‐resistant BTLE, approximately 8 months of chronic RNS ECoG are needed to precisely estimate the seizure laterality ratio, with 75% of people with BTLE achieving convergence after 1 year of RNS recording. For individuals who are candidates for unilateral resection based on seizure laterality, optimized recording duration may help avert morbidity associated with delay to definitive treatment. [ABSTRACT FROM AUTHOR]

Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major depressive disorder (MDD), most studies to date have administered continuous or open-loop stimulation with promising but mixed results. One factor contributing to these mixed results may stem from when the stimulation is applied. Stimulation administration specific to high-symptom states in a personalized and responsive manner may be more effective at reducing symptoms compared to continuous stimulation and may avoid diminished therapeutic effects related to habituation. Additionally, a lower total duration of stimulation per day is advantageous for reducing device energy consumption. This protocol describes an experimental workflow using a chronically implanted neurostimulation device to achieve closed-loop stimulation for individuals with treatment-refractory MDD. This paradigm hinges on determining a patient-specific neural biomarker that is related to states of high symptoms and programming the device detectors, such that stimulation is triggered by this read-out of symptom state. The described procedures include how to obtain neural recordings concurrent with patient symptom reports, how to use these data in a state-space model approach to differentiate low- and high-symptom states and corresponding neural features, and how to subsequently program and tune the device to deliver closed-loop stimulation therapy.

Objective: Recent trends have moved from subdural grid electrocorticography (ECoG) recordings toward stereo-electroencephalography (SEEG) depth electrodes for intracranial localization of seizures, in part because of perceived morbidity from subdural grid and strip electrodes. For invasive epilepsy monitoring, the authors describe the outcomes of a hybrid approach, whereby patients receive a combination of subdural grids, strips, and frameless stereotactic depth electrode implantations through a craniotomy. Evolution of surgical techniques was employed to reduce complications. In this study, the authors review the surgical hemorrhage and functional outcomes of this hybrid approach., Methods: A retrospective review was performed of consecutive patients who underwent hybrid implantation from July 2012 to May 2022 at an academic epilepsy center by a single surgeon. Outcomes included hemorrhagic and nonhemorrhagic complications, neurological deficits, length of monitoring, and number of electrodes., Results: A total of 137 consecutive procedures were performed; 113 procedures included both subdural and depth electrodes. The number of depth electrodes and electrode contacts did not increase the risk of hemorrhage. A mean of 1.9 ± 0.8 grid, 4.9 ± 2.1 strip, and 3.0 ± 1.9 depth electrodes were implanted, for a mean of 125.1 ± 32 electrode contacts per patient. The overall incidence of hematomas over the study period was 5.1% (7 patients) and decreased significantly with experience and the introduction of new surgical techniques. The incidence of hematomas in the last 4 years of the study period was 0% (55 patients). Symptomatic hematomas were all delayed and extra-axial. These patients required surgical evacuation, and there were no cases of hematoma recurrence. All neurological deficits related to hematomas were temporary and were resolved at hospital discharge. There were 2 nonhemorrhagic complications. The mean duration of monitoring was 7.3 ± 3.2 days. Seizures were localized in 95% of patients, with 77% of patients eventually undergoing resection and 17% undergoing responsive neurostimulation device implantation., Conclusions: In the authors' institutional experience, craniotomy-based subdural and depth electrode implantation was associated with low hemorrhage rates and no permanent morbidity. The rate of hemorrhage can be nearly eliminated with surgical experience and specific techniques. The decision to use subdural electrodes or SEEG should be tailored to the patient's unique pathology and surgeon experience.

We present a novel brain machine interface (BMI) control algorithm, the recalibrated feedback intention-trained Kalman filter (ReFIT-KF). The design of ReFIT-KF is motivated from a feedback control perspective applied to existing BMI control algorithms. The result is two design innovations that alter the modeling assumptions made by these algorithms and the methods by which these algorithms are trained. In online neural control experiments recording from a 96-electrode array implanted in M1 of a macaque monkey, the ReFIT-KF control algorithm demonstrates large performance improvements over the current state of the art velocity Kalman filter, reducing target acquisition time by a factor of two, while maintaining a 500 ms hold period, thereby increasing the clinical viability of BMI systems.

Brain-machine interfaces (BMIs) aim to help disabled patients by translating neural signals from the brain into control signals for guiding prosthetic arms, computer cursors, and other assistive devices. Animal models are central to the development of these systems and have helped enable the successful translation of the first generation of BMIs. As we move toward next-generation systems, we face the question of which animal models will aid broader patient populations and achieve even higher performance, robustness, and functionality. We review here four general types of rhesus monkey models employed in BMI research, and describe two additional, complementary models. Given the physiological diversity of neurological injury and disease, we suggest a need to maintain the current diversity of animal models and to explore additional alternatives, as each mimic different aspects of injury or disease.