EEG CONNECT: Proponowana lista kontrolna do raportowania badań łączności mózgu na podstawie EEG w klinicznej diagnostyce epilepsji

EEG-based connectivity analysis has emerged as a promising approach for investigating brain network dynamics in clinical epilepsy research. However, the diversity of analytical approaches, preprocessing pipelines, and reporting practices poses challenges to reproducibility and clinical translation. Existing guidelines such as STROBE and GREENBEAN provide valuable frameworks for clinical research and EEG-based biomarker reporting, but they were not designed to address the methodological complexities unique to EEG-based connectivity studies. To address this gap, we propose the Electroencephalography-based Connectivity Studies Evaluation Checklist for Clinical Epilepsy Research (EEG CONNECT), a proposed 24-item reporting checklist tailored to EEG-based connectivity analysis. This checklist covers key elements of study design, data acquisition, analysis methods, and interpretation, and is applicable to both scalp and intracranial EEG. To evaluate current reporting practices and explore the feasibility of the proposed checklist, we conducted a systematic review of 45 peer-reviewed clinical studies published between 2022 and 2024 that used one of four connectivity analysis methods: coherence, transfer entropy, Granger causality, and neural responses to single-pulse electrical stimulation. Articles were assessed based on whether each checklist item was sufficiently, partially, or not reported. The overall mean reporting adherence was 70.3% (standard deviation ±12.9%). Items related to connectivity estimation approach, biological plausibility, and methodological limitations were most frequently underreported. Checklist adherence was correlated with the publishing journal's impact factor (Spearman's rho = 0.358, p = 0.018) and with article citation rate (rho = 0.363, p = 0.014). These findings underscore the need for standardized reporting in EEG connectivity research. EEG CONNECT is a proposed practical framework to support systematic methodological reporting, although its use is not intended to be mandatory. Adoption of this checklist may facilitate comparisons across studies and support the translation of EEG-based connectivity findings into improved understanding and treatment of epilepsy and other brain disorders. PLAIN LANGUAGE SUMMARY: EEG connectivity analysis can help researchers understand how different brain regions interact in epilepsy, but reporting practices vary across studies. We developed EEG CONNECT, a proposed 24-item checklist to support clearer and more consistent reporting of EEG connectivity research. We applied the checklist to 45 recent clinical studies and found that several important methodological details were often underreported, particularly how connectivity was estimated, its biological plausibility, and methodological limitations. EEG CONNECT provides a practical framework that may improve transparency, facilitate comparisons across studies, and support the clinical translation of EEG connectivity research.