Washington University School of Medicine/Barnes-Jewish Hospital
St Louis, Missouri, 63110, United States
Location status: Recruiting
NCT Number: NCT05905705
Electroconvulsive therapy (ECT) alleviates treatment-resistant depression (TRD) through repeated generalized seizures. The goal of this study is to evaluate how ECT impacts sleep-wake regulation and efficiency of information transfer in functional networks in different states of arousal.
Interested in participating?
Request Info21 year–65 year
All sexes
Observational
St Louis, Missouri, 63110, United States
Location status: Recruiting
Graph-based network analyses of electroencephalographic (EEG) signals allow characterization of functional networks. The robustness of local networks to disruption is quantified as local efficiency (Elocal), while network integration is quantified as global information transfer (Eglobal).
Aim 1: Assess relationships between sleep slow-wave activity (SWA) and awake Elocal over the course of ECT.
Aim 2: Quantify relationships between depression severity and awake Elocal over the course of ECT.
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
High-density EEG will be acquired during resting wakefulness before each ECT session.
Overnight sleep EEG will be recorded one day before each ECT session using the DREEM device. The DREEM device allows continuous recording of multichannel EEG.
Time frame: Up to 4 weeks during patients ECT treatment course
Total power of EEG slow waves per minute present during N2/N3 sleep
Time frame: Up to 4 weeks during patients ECT treatment course
Elocal will be calculated as the average inverse shortest path length among neighbors of a node within the network. Nodes will be constructed based on 5-minute recordings of eyes closed wakefulness theta band (4-8 Hz) EEG.
Time frame: Up to 4 weeks during patients ECT treatment course
Eglobal will be calculated as the average inverse shortest path length between node pairs in the networks. Nodes will be constructed based on ECT-induced seizure EEG data within the alpha band (8-13 Hz).
Contact information is provided by the study sponsor or research team.
MohammadMehdi Kafashan
CONTACT
Robby Greenspan
CONTACT
Washington University School of Medicine
Other
Acronym: DNS-ECT
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