schizophrenia, Parkinson, Alzheimer, autism, mental retardation), recovery processes (e.g., post brain stroke), and cognitive faculties (e.g., memory consolidation, intelligence, dream recall, sleep preservation). Nonetheless, a methodological wall has impeded the study of sleep spindles. Their investigation rests heavily on our ability to reliably and consistently identify spindle patterns from background EEG activity, a task involving many obstacles, including: a fuzzy definition of spindles, low inter-expert agreement on their scoring, lack of consensus on standard techniques for their automated detection, low reproducibility of observed characteristics and correlates, unavailability of large, standardized, high-quality databases, and inconsistencies in the methods used to evaluate the performance of automated detectors. The primary aims of this research topic were to bring together world-class researchers on a project designed to facilitate exchanges on methodological difficulties encountered in assessing sleep spindles and to promote standardized spindle-related resources. In preparing their contributions, authors were encouraged to use existing - or to propose new - publicly available resources for assessing sleep spindles. To allow fair and accurate comparison of reported results, the authors were also encouraged to validate their tools on a common benchmark. A database containing expert spindle scoring (i.e., the Montreal Archive of Sleep Studies) was made publicly available for that purpose. |