Electroencephalographic Biomarkers for Neuropsychiatric Diseases: The State of the Art

Bioengineering, Год журнала: 2025, Номер 12(3), С. 295 - 295

Опубликована: Март 14, 2025

Because of their nature, biomarkers for neuropsychiatric diseases were out the reach medical diagnostic technology until past few decades. In recent years, confluence greater, affordable computer power with need more efficient diagnoses and treatments has increased interest in possibility discovery. This review will focus on progress made over ten years regarding search electroencephalographic diseases. includes algorithms methods analysis, machine learning, quantitative electroencephalography as applied to neurodegenerative neurodevelopmental well traumatic brain injury COVID-19. Our findings suggest that there is a consensus among researchers classification most suit this field; slight disconnection between development increasingly sophisticated analysis what they actually be use clinical setting; finally, are favored type field caveats. The main goal state-of-the-art provide reader general panorama state art field.

Язык: Английский

The Value of Normal Interictal EEGs in Epilepsy Diagnosis and Treatment Planning: A Retrospective Cohort Study using Population-level Spectral Power and Connectivity Patterns

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 5, 2025

Abstract Introduction Scalp electroencephalography (EEG) is a cornerstone in the diagnosis and treatment of epilepsy, but routine EEG often interpreted as normal without identification epileptiform activity during expert visual review. The absence interictal on scalp EEGs can cause delays receiving clinical treatment. These be particularly problematic people with drug-resistant epilepsy (DRE) those structural abnormalities MRI (i.e., negative). Thus, there need for alternative quantitative approaches that inform diagnostic decisions when review inconclusive. In this study, we leverage large population-level database focal to investigate whether segments contain subtle deviations could support epilepsy. Data & Methods We identified multiple epochs representing eyes-closed wakefulness from 19-channel diverse neurological patient population (N=13,652 recordings, 12,134 unique patients). then extracted average spectral power phase-lag-index-based connectivity within 1-45Hz each recording using these epochs. decomposed density phase-based information all visually reviewed (N=6,242) unsupervised tensor decompositions extract dominant patterns connectivity. also an independent set cohort patients (N= 121) various classifications, including origin (temporal, frontal), (lesional, non-lesional), response anti-seizure medications (responsive vs. epilepsy). analyzed power-spectral above evaluated their potential clinically relevant binary classifications. Results obtained six distinct interpretable spatio-spectral signatures corresponding putative aperiodic, oscillatory, artifactual recorded EEG. loadings showed associations age expert-assigned grades abnormality. Further analysis physiologically subset differentiated controls history (mean AUC 0.78) were unable differentiate between frontal or temporal lobe best drug-responsive 0.73), well lesional non-lesional 0.67), albeit high variability across patients. Significance Our findings sample suggest differences predictive value may improve overall yield prolonged EEGs. presented approach analyzing has capacity several classifications quantitatively characterize scalable, expert-interpretable, patient-specific fashion. technical development validation EEG-derived computational biomarkers augment assist decision-making future.

Язык: Английский

A QR Code for the Brain: A dynamical systems framework for computing neurophysiological biomarkers

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Сен. 18, 2024

Neural circuits are often considered the bridge connecting genetic causes and behavior. Whereas prenatal neural believed to be derived from a combination of intrinsic activity, postnatal largely influenced by exogenous activity experience. A dynamical neuroelectric field maintained is proposed as fundamental information processing substrate cognitive function. Time series measurements can collected scalp sensors used mathematically quantify essential features constructing digital twin system phase space. The multiscale nonlinear values that result organized into tensor data structures, which latent extracted using factorization. These mapped behavioral constructs derive biomarkers. This computational framework provides robust method for incorporating neurodynamical measures neuropsychiatric biomarker discovery.

Язык: Английский