Advancing the neuroelectrophysiological understanding of attentional switching dysfunction in major depressive disorder

Table 5 Key future research directions to advance the field

Research direction	Core scientific question	Recommended methodological approach	Expected outcome/impact
Longitudinal trajectories	Do ERP abnormalities precede, coincide with, or follow depressive episodes? Are they normalized by treatment	Prospective studies of high-risk cohorts; treatment trials with ERP assessments at multiple timepoints	Determine causal role and clinical utility as predictive/prognostic biomarkers
Circuit mechanisms	Which specific large-scale brain networks show dysfunctional communication during attentional switching	Simultaneous EEG-fMRI; source-localized EEG connectivity analysis during switching tasks	Identify novel neurobiological targets for brain stimulation or circuit-based therapeutics
Personalized prediction	Can a combination of ERP, clinical, and genomic data predict individual treatment outcomes	Machine learning on multimodal datasets from large clinical trials	Move towards personalized medicine in psychiatry
Real-world translation	How do lab-measured ERP deficits manifest in daily life attention and functioning	Studies pairing lab-based EEG with EMA of cognition in daily life	Validate the ecological significance of ERP biomarkers and link them to patient-centered outcomes
Developmental perspective	How do attentional switching circuits and their dysfunction evolve from adolescence to late-life depression	Cross-sectional and longitudinal studies across the lifespan	Identify optimal windows for early intervention and age-specific treatment targets

ERP: Event-related potential; EEG: Electroencephalography; fMRI: Functional magnetic resonance imaging; EMA: Ecological momentary assessment.