Back

Alpha Oscillatory Imbalance Predicts Attention Deficits in Visuospatial Neglect

Trajkovic, J.; Middag-van Spanje, M.; Leunissen, I.; Schuhmann, T.

2025-07-04 neuroscience
10.1101/2025.06.30.662471 bioRxiv
Show abstract

Background and ObjectivesVisuospatial neglect (VSN) is a common consequence of unilateral stroke, characterized by reduced awareness on the contralesional side of space. This study examines resting-state electrophysiological mechanisms underlying VSN, with a focus on interhemispheric differences in alpha-band oscillations and their association with deficits in visual perception and attention. MethodsResting-state EEG was recorded during three-minute eyes-closed and eyes-open periods in VSN patients. Participants also completed a battery of perceptual and attentional assessments, including the Star Cancellation Task, the Computerized Visual Detection Task, and the Line Bisection Task. Measures of alpha activity, specifically amplitude, peak frequency, and fronto-parietal connectivity,were compared between VSN patients and age- and gender-matched healthy controls. Within the VSN group, alpha activity in the lesioned and non-lesioned hemispheres was used to predict task performance. ResultsCompared to healthy controls, VSN patients displayed a distinct resting-state alpha profile, characterized by slower and less synchronized alpha oscillations and reduced fronto-parietal alpha connectivity in the lesioned hemisphere. In contrast, controls showed symmetrical alpha activity across hemispheres. Crucially, the degree of interhemispheric alpha asymmetry in VSN patients consistently predicted attentional impairments across all behavioral tasks. DiscussionVSN is linked to disrupted alpha oscillatory dynamics and interhemispheric imbalance. The extent of alpha desynchronization between hemispheres predicts symptom severity, supporting the interhemispheric competition model of attention. These findings suggest that hyperactive alpha activity in the non-lesioned hemisphere may suppress the lesioned hemisphere, contributing to attentional bias away from the contralesional space.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.