Scientific Publications

This analysis aims to assess if daridorexant, a dual orexin receptor antagonist, preserves or modifies sleep architecture, with specific focus on hyperarousal-related patterns such as elevated fast frequencies and disrupted sleep continuity using pooled data from two phase 3 studies.

The aim of this study was to assess the signal acquisition and the performance of the automatic sleep staging algorithms of a reduced-montage dry-electroencephalographic (EEG) device (Dreem headband, DH) compared to the gold-standard polysomnography (PSG) scored by five sleep experts.

We conducted a preliminary examination of polysomnographic (PSG) macro- and microarchitectural changes in subjects with Alzheimer’s Dementia (AD) and mild cognitive impairment (MCI) in a large retrospective cohort.

Interictal epileptiform discharges (IEDs) are detectable in routine EEGs from patients with Alzheimer’s Dementia or MCI (with or without epilepsy). IEDs in these patients can be reliably and quickly detected on routine EEGs using ML algorithms, enabling rapid patient characterization.

Machine learning models for detection of IEDs are improving to the point of matching expert human performance. We demonstrate robustness of our IED detector to real-world scenarios which enables biomarker evaluation for clinical trials and neurodiagnostics.

Spectral analysis allows the quantification of sleep measured by EEG by dissecting the signals into power frequency bands

A Phase 1 Translational Pharmacology Study in Healthy Elderly Volunteers Evaluating the Safety, Tolerability, Pharmacokinetics, and CNS Activity of CY6463*, a CNS-penetrant, Soluble Guanylate Cyclase (sGC) Stimulator

Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

Developed a method based on embedding maps to create high quality pseudo labels to enhance the training of machine learning models. Our results provide guidance regarding the use of AL to efficiently label large EEG datasets in critically ill patients.

Automated measurement of peak epileptiform activity burden affords a convenient, consistent, and quantifiable target for future multicenter randomized trials investigating whether suppressing epileptiform activity improves outcomes.

The 2HELPS2B model is a quick accurate tool to aid clinical judgment of the risk of seizures in critically ill patients.

These findings shed light on how the human alpha rhythm coordinates activity throughout the brain.

The onset region sculpts neurodynamics at seizure initiation and that unique features of the cytoarchitecture and/or connectivity of that region play a significant role in determining seizure mechanism.

Our ideas allow us to solve higher-level time series data mining problem such as motif discovery and clustering at scales that would otherwise be untenable.

Replay occurs in NREM sleep of the neural activity related to previous waking experience, i.e. that a basic tenet of the reactivation theory does occur in human sleep.

LCM was noninferior to fPHT in controlling NCS, and treatment emergent adverse events were comparable.

Deep neural networks, which have recently achieved expert-level performance for other complex medical tasks, are ideally suited to PSG scoring, given sufficient training data.

BAI, a sleep EEG-based biomarker of the deviation of sleep microstructure from patterns normal for age, is an independent predictor of life expectancy.

An interactive method that generates EEG reports in a sentence by sentence fashion based on doctors’ anchor words and partially completed sentences.

The findings raise the prospect of using the sleep EEG as a potential biomarker for healthy brain aging.

When harnessed appropriately in conjunction with human expertise, AI will improve the practice of sleep medicine and further sleep science for the health and well-being of our patients.

Epileptiform abnormalities are common in AD but not all equivalent. This may represent a sign of hyperexcitability in a subpopulation of these patients.

Unconsciousness is linked to cortical and thalamic slow frequency synchrony coupled with decreased spiking, and loss of higher-frequency dynamics. This may disrupt cortical communication/integration.

This is the first study of large ensembles of single neurons during seizures in persons with epilepsy. Contrary to the traditional view, neuronal spiking activity during seizures was highly heterogeneous and changed significantly preceding clinical onset.

These results provide new insights into the neural basis required for light to influence mood & learning.

We studied how WM is integrated across hemifields by recording neural activity bilaterally from prefrontal cortex. Around the time of transfer, synchrony between the two prefrontal hemispheres peaked in theta and beta frequencies, with a directionality consistent with memory trace transfer. This illustrates how the two cortical hemispheres can stitch together WM traces across visual hemifields.

Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating with slow-delta (0.1-4 Hz) oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. Here, we characterize ketamine’s neural dynamics using a hidden Markov model (HMM).

Training with a large data set enables automated sleep staging that compares favorably with human scorers. Because testing was performed on a large and heterogeneous data set, the performance estimate has low variance and is likely to generalize broadly.

This study’s findings suggest that experts can identify whether EEGs contain IEDs with substantial reliability. Lower reliability regarding individual IEDs may be largely explained by various experts applying different thresholds to a common underlying statistical model.

The brain age index may be a useful biomarker associated with dementia and could have utility as a screening tool for the presence of underlying neurodegenerative disease and monitoring of disease progression.