Combining time-frequency and spatial information for the detection of sleep spindles

Frontiers in Human Neuroscience
Christian O'ReillyJean-Marc Lina

Abstract

EEG sleep spindles are short (0.5-2.0 s) bursts of activity in the 11-16 Hz band occurring during non-rapid eye movement (NREM) sleep. This sporadic activity is thought to play a role in memory consolidation, brain plasticity, and protection of sleep integrity. Many automatic detectors have been proposed to assist or replace experts for sleep spindle scoring. However, these algorithms usually detect too many events making it difficult to achieve a good tradeoff between sensitivity (Se) and false detection rate (FDr). In this work, we propose a semi-automatic detector comprising a sensitivity phase based on well-established criteria followed by a specificity phase using spatial and spectral criteria. In the sensitivity phase, selected events are those which amplitude in the 10-16 Hz band and spectral ratio characteristics both reject a null hypothesis (p < 0.1) stating that the considered event is not a spindle. This null hypothesis is constructed from events occurring during rapid eye movement (REM) sleep epochs. In the specificity phase, a hierarchical clustering of the selected candidates is done based on events' frequency and spatial position along the anterior-posterior axis. Only events from the classes grouping most (at l...Continue Reading

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Citations

Oct 17, 2017·Journal of Sleep Research·Chanakya Reddy PattiDean Cvetkovic
Jul 11, 2018·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Mark P WachowiakF Michael Williams-Bell

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