Focal seizures appear to start abruptly and unpredictably when recorded from volumes of brain probed by clinical intracranial electroencephalograms. To investigate the spatiotemporal scale of focal epilepsy, wide-bandwidth electrophysiological recordings were obtained using clinical macro- and research microelectrodes in patients with epilepsy and control subjects with intractable facial pain. Seizure-like events not detectable on clinical macroelectrodes were observed on isolated microelectrodes. These 'microseizures' were sparsely distributed, more frequent in brain regions that generated seizures, and sporadically evolved into large-scale clinical seizures. Rare microseizures observed in control patients suggest that this phenomenon is ubiquitous, but their density distinguishes normal from epileptic brain. Epileptogenesis may involve the creation of these topographically fractured microdomains and ictogenesis (seizure generation), the dynamics of their interaction and spread.

Brain stimulation has emerged as an effective treatment for a wide range of neurological and psychiatric diseases. Parkinson’s disease, epilepsy, and essential tremor have FDA indications for electrical brain stimulation using intracranially implanted electrodes. Interfacing implantable brain devices with local and cloud computing resources have the potential to improve electrical stimulation efficacy, disease tracking, and management. Epilepsy, in particular, is a neurological disease that might benefit from the integration of brain implants with off-the-body computing for tracking disease and therapy. Recent clinical trials have demonstrated seizure forecasting, seizure detection, and therapeutic electrical stimulation in patients with drug-resistant focal epilepsy. In this paper, we describe a next-generation epilepsy management system that integrates local handheld and cloud-computing resources wirelessly coupled to an implanted device with embedded payloads (sensors, intracranial EEG telemetry, electrical stimulation, classifiers, and control policy implementation). The handheld device and cloud computing resources can provide a seamless interface between patients and physicians, and realtime intracranial EEG can be used to classify brain state (wake/sleep, preseizure, and seizure), implement control policies for electrical stimulation, and track patient health. This system creates a flexible platform in which low demand analytics requiring fast response times are embedded in the implanted device and more complex algorithms are implemented in offthebody local and distributed cloud computing environments. The system enables tracking and management of epileptic neural networks operating over time scales ranging from milliseconds to months.

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ObjectiveThis study investigates high‐frequency oscillations (HFOs; 65–600 Hz) as a biomarker of epileptogenic brain and explores three barriers to their clinical translation: (1) Distinguishing pathological HFOs (pathHFO) from physiological HFOs (physHFO). (2) Classifying tissue under individual electrodes as epileptogenic (3) Reproducing results across laboratories.MethodsWe recorded HFOs using intracranial EEG (iEEG) in 90 patients with focal epilepsy and 11 patients without epilepsy. In nine patients with epilepsy putative physHFOs were induced by cognitive or motor tasks. HFOs were identified using validated detectors. A support vector machine (SVM) using HFO features was developed to classify tissue under individual electrodes as normal or epileptogenic.ResultsThere was significant overlap in the amplitude, frequency, and duration distributions for spontaneous physHFO, task induced physHFO, and pathHFO, but the amplitudes of the pathHFO were higher (P < 0.0001). High gamma pathHFO had the strongest association with seizure onset zone (SOZ), and were elevated on SOZ electrodes in 70% of epilepsy patients (P < 0.0001). Failure to resect tissue generating high gamma pathHFO was associated with poor outcomes (P < 0.0001). A SVM classified individual electrodes as epileptogenic with 63.9% sensitivity and 73.7% specificity using SOZ as the target.InterpretationA broader range of interictal pathHFO (65–600 Hz) than previously recognized are biomarkers of epileptogenic brain, and are associated with SOZ and surgical outcome. Classification of HFOs into physiological or pathological remains challenging. Classification of tissue under individual electrodes was demonstrated to be feasible. The open source data and algorithms provide a resource for future studies.

The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in augmenting clinical decision making.

Conclusions | Based on several million athlete exposures, this meta-analysis found no association between concussion incidence at mild altitude compared with at sea level. The myth that higher altitude reduces concussion incidence in athletes is not supported.

Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement in the human brain have been focused on the hippocampus and other mesial temporal lobe structures, with a few reports of memory improvement in small studies of individual brain regions. Here, we investigated the effect of stimulation in four brain regions known to support declarative memory: hippocampus, parahippocampal neocortex, prefrontal cortex and temporal cortex. Intracranial electrode recordings with stimulation were used to assess verbal memory performance in a group of 22 patients (nine males). We show enhanced performance with electrical stimulation in the lateral temporal cortex (paired t-test, P = 0.0067), but not in the other brain regions tested. This selective enhancement was observed both on the group level, and for two of the four individual subjects stimulated in the temporal cortex. This study shows that electrical stimulation in specific brain areas can enhance verbal memory performance in humans.awx373media15704855796001.

Introduction Magnetic Resonance Elastography (MRE) analyzes shear waves’ movement thorough tissue to determine stiffness. In a prior study, measurements using first-generation brain MRE techniques correlated with intraoperative observations regarding overall meningioma stiffness. We evaluated the diagnostic accuracy of a higher-resolution MRE technique to preoperatively detect intratumoral variations as compared to surgeon assessment. Methods Fifteen meningiomas in fourteen patients underwent MRE. Tumors with regions of distinctly different stiffness were considered heterogenous. Intratumoral portions were considered hard if there was a significant area ≥ 6 kiloPascals. A 5-point scale graded intraoperative consistency. A durometer semi-quantitatively measured surgical specimen hardness. Statistics included Chi-squared, sensitivity, specificity, positive and negative predicative values (PPV and NPV), and Spearman’s rank correlation coefficient. Results Between MRE and surgery respectively, 9(60%) vs 7(47%) tumors were homogenous; 6(40%) vs 8(53%) tumors were heterogenous; 6(40%) vs 10(67%) tumors had hard portions; and 14(93%) vs 12(80%) tumors had soft portions. MRE sensitivity, specificity, PPV and NPV were: for heterogeneity, 75%, 100%, 100%, and 87%; for hardness, 60%, 100%, 100%, and 56%; and for softness, 100%, 33%, 86%, and 100%. Overall, 10(67%) tumors matched well with MRE and intraoperative consistency and correlated between intraoperative observations (p=0.018) and durometer readings (p=0.046). Tumor size ≤3.5 cm or vascular tumors were more likely to be inconsistent (p<0.05). Conclusions MRE was excellent at ruling-in heterogeneity with hard portions, but less effective in ruling-out heterogeneity and hard portions, particularly in tumors more vascular or <3.5 cm. MRE is the first technology capable of prospectively evaluating intratumoral stiffness and, with further refinement, will likely prove useful in preoperative planning.