Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

OBJECTIVE: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy. METHODS: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of (1) leave-one-patient-out cross-validation (LOPO CV) on GCS patients, (2) false alarm rate (FAR) testing on nonseizure patients, and (3) "fixed-and-frozen" prospective testing on a prospective patient cohort. Balanced accuracy, precision, sensitivity, and FAR were used to quantify the performance of the algorithm. Seizure onsets and offsets were determined by using video-electroencephalographic (EEG) monitoring. Feature importance was calculated as the mean decrease in Gini impurity during the LOPO CV testing. RESULTS: LOPO CV results showed balanced accuracy of .93 (95% confidence interval [CI] = .8-.98), precision of .68 (95% CI = .46-.85), sensitivity of .87 (95% CI = .62-.96), and FAR of .21/24 h (interquartile range [IQR] = 0-.90). Testing the algorithm on patients without seizure resulted in an FAR of .28/24 h (IQR = 0-.61). During the "fixed-and-frozen" prospective testing, two patients had three GCS, which were detected by the algorithm, while generating an FAR of .25/24 h (IQR = 0-.89). Feature importance showed that heart rate-based features outperformed accelerometer/gyroscope-based features. SIGNIFICANCE: Commercially available wearable digital watches that reliably detect GCS, with minimum false alarm rates, may overcome usage adoption and other limitations of custom-built devices. Contingent on the outcomes of a prospective phase 3 study, such devices have the potential to provide non-EEG-based seizure surveillance and forecasting in the clinical setting.

Advancing the frontiers of thalamic neuromodulation: A review of emerging targets and paradigms.

The thalamus is a key structure that plays a crucial role in initiating and propagating seizures. Recent advancements in neuroimaging and neurophysiology have identified the thalamus as a promising target for neuromodulation in drug-resistant epilepsies. This review article presents the latest innovations in thalamic targets and neuromodulation paradigms being explored in pilot or pivotal clinical trials. Multifocal temporal plus or posterior quadrant epilepsies are evaluated with pulvinar thalamus neuromodulation, while centromedian thalamus is explored in generalized epilepsies and Lennox Gastaut syndrome. Multinodal thalamocortical neuromodulation with novel stimulation paradigms such as long bursting or low-frequency stimulation is being investigated to quench the epileptic network excitability. Beyond seizure control, thalamic neuromodulation to restore consciousness is being studied. This review highlights the promising potential of thalamic neuromodulation in epilepsy treatment, offering hope to patients who have not responded to conventional medical therapies. However, it also emphasizes the need for larger randomized controlled trials and personalized stimulation paradigms to improve patient outcomes further.

Hippocampal network axons respond to patterned theta burst stimulation with lower activity of initially higher spike train similarity from EC to DG and later similarity of axons from CA1 to EC.

Objective. Decoding memory functions for each hippocampal subregion involves extensive understanding of how each hippocampal subnetwork processes input stimuli. Theta burst stimulation (TBS) recapitulates natural brain stimuli which potentiates synapses in hippocampal circuits. TBS is typically applied to a bundle of axons to measure the immediate response in a downstream subregion like the cornu ammonis 1 (CA1). Yet little is known about network processing in response to stimulation, especially because individual axonal transmission between subregions is not accessible.Approach. To address these limitations, we reverse engineered the hippocampal network on a micro-electrode array partitioned by a MEMS four-chambered device with interconnecting microfluidic tunnels. The micro tunnels allowed monitoring single axon transmission which is inaccessible in slices orin vivo. The four chambers were plated separately with entorhinal cortex (EC), dentate gyrus (DG), CA1, and CA3 neurons. The patterned TBS was delivered to the EC hippocampal gateway. Evoked spike pattern similarity in each subregions was quantified with Jaccard distance metrics of spike timing.Main results. We found that the network subregion produced unique axonal responses to different stimulation patterns. Single site and multisite stimulations caused distinct information routing of axonal spikes in the network. The most spatially similar output at axons from CA3 to CA1 reflected the auto association within CA3 recurrent networks. Moreover, the spike pattern similarities shifted from high levels for axons to and from DG at 0.2 s repeat stimuli to greater similarity in axons to and from CA1 for repetitions at 10 s intervals. This time-dependent response suggested that CA3 encoded temporal information and axons transmitted the information to CA1.Significance. Our design and interrogation approach provide first insights into differences in information transmission between the four subregions of the structured hippocampal network and the dynamic pattern variations in response to stimulation at the subregional level to achieve probabilistic pattern separation and novelty detection.

Pulvinar neuromodulation for seizure monitoring and network modulation in temporal plus epilepsy.

Deep brain stimulation (DBS) is a promising treatment for drug-refractory epilepsies (DRE) when targeting the anterior nuclei of thalamus (ANT). However, targeting other thalamic nuclei, such as the pulvinar, shows therapeutic promise. Our pioneering case study presents the application of ambulatory seizure monitoring using spectral fingerprinting (12.15-17.15 Hz) recorded through Medtronic Percept DBS implanted bilaterally in the medial pulvinar thalami. This technology offers unprecedented opportunities for real-time monitoring of seizure burden and thalamocortical network modulation for effective seizure reduction in patients with bilateral mesial temporal and temporal plus epilepsies that are not suitable for resection.