Keyword search (4,163 papers available)

"Sleep spindles" Keyword-tagged Publications:

Title Authors PubMed ID
1 Exploring Deep Magnetoencephalography via Thalamo-Cortical Sleep Spindles Rattray GF; Jourde HR; Baillet S; Coffey EBJ; 41002111
PSYCHOLOGY
2 Neurophysiological effects of targeting sleep spindles with closed-loop auditory stimulation Jourde HR; Sobral M; Beltrame G; Coffey EBJ; 40626105
PSYCHOLOGY
3 Personalizing brain stimulation: continual learning for sleep spindle detection Sobral M; Jourde HR; Marjani Bajestani SE; Coffey EBJ; Beltrame G; 40609549
PSYCHOLOGY
4 Sleep spindles and slow oscillations predict cognition and biomarkers of neurodegeneration in mild to moderate Alzheimer's disease Páez A; Gillman SO; Dogaheh SB; Carnes A; Dakterzada F; Barbé F; Dang-Vu TT; Ripoll GP; 39878233
CONCORDIA
5 Auditory processing up to cortex is maintained during sleep spindles Jourde HR; Coffey EBJ; 39588317
PSYCHOLOGY
6 The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; 37675803
CONCORDIA
7 Different Patterns of Sleep-Dependent Procedural Memory Consolidation in Vipassana Meditation Practitioners and Non-meditating Controls. Solomonova E, Dubé S, Blanchette-Carrière C, Sandra DA, Samson-Richer A, Carr M, Paquette T, Nielsen T 32038390
PSYCHOLOGY
8 Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia Dang-Vu TT; Hatch B; Salimi A; Mograss M; Boucetta S; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; 29157588
PERFORM

 

Title:Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia
Authors:Dang-Vu TTHatch BSalimi AMograss MBoucetta SO'Byrne JBrandewinder MBerthomier CGouin JP
Link:https://pubmed.ncbi.nlm.nih.gov/29157588/
DOI:10.1016/j.sleep.2017.08.012
Publication:Sleep medicine
Keywords:BiomarkersElectroencephalographyInsomniaNeural oscillationsSleep spindles
PMID:29157588 Category:Sleep Med Date Added:2019-05-31
Dept Affiliation: PERFORM
1 Department of Exercise Science, Concordia University, Montréal, QC, Canada; Department of Psychology, Concordia University, Montréal, QC, Canada; Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada; PERFORM Center, Concordia University, Montréal, QC, Canada; Center for Clinical Research in Health, Concordia University, Montréal, QC, Canada; Centre de Recherches de l'Institut Universitaire de Gériatrie de Montréal, Montréal, QC, Canada; Department of Neurosciences, Université de Montréal, Montréal, QC, Canada. Electronic address: tt.dangvu@concordia.ca.
2 Department of Psychology, Concordia University, Montréal, QC, Canada; Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada; PERFORM Center, Concordia University, Montréal, QC, Canada.
3 Department of Exercise Science, Concordia University, Montréal, QC, Canada; Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada; PERFORM Center, Concordia University, Montréal, QC, Canada; Centre de Recherches de l'Institut Universitaire de Gériatrie de Montréal, Montréal, QC, Canada.
4 Department of Exercise Science, Concordia University, Montréal, QC, Canada; Department of Psychology, Concordia University, Montréal, QC, Canada; PERFORM Center, Concordia University, Montréal, QC, Canada; Centre de Recherches de l'Institut Universitaire de Gériatrie de Montréal, Montréal, QC, Canada.
5 Physip SA, Paris, France.
6 Department of Psychology, Concordia University, Montréal, QC, Canada; PERFORM Center, Concordia University, Montréal, QC, Canada; Center for Clinical Research in Health, Concordia University, Montréal, QC, Canada.

Description:

Background: While cognitive-behavioral therapy for insomnia constitutes the first-line treatment for chronic insomnia, only few reports have investigated how sleep architecture relates to response to this treatment. In this pilot study, we aimed to determine whether pre-treatment sleep spindle density predicts treatment response to cognitive-behavioral therapy for insomnia.

Methods: Twenty-four participants with chronic primary insomnia participated in a 6-week cognitive-behavioral therapy for insomnia performed in groups of 4-6 participants. Treatment response was assessed using the Pittsburgh Sleep Quality Index and the Insomnia Severity Index measured at pre- and post-treatment, and at 3- and 12-months' follow-up assessments. Secondary outcome measures were extracted from sleep diaries over 7 days and overnight polysomnography, obtained at pre- and post-treatment. Spindle density during stage N2-N3 sleep was extracted from polysomnography at pre-treatment. Hierarchical linear modeling analysis assessed whether sleep spindle density predicted response to cognitive-behavioral therapy.

Results: After adjusting for age, sex, and education level, lower spindle density at pre-treatment predicted poorer response over the 12-month follow-up, as reflected by a smaller reduction in Pittsburgh Sleep Quality Index over time. Reduced spindle density also predicted lower improvements in sleep diary sleep efficiency and wake after sleep onset immediately after treatment. There were no significant associations between spindle density and changes in the Insomnia Severity Index or polysomnography variables over time.

Conclusion: These preliminary results suggest that inter-individual differences in sleep spindle density in insomnia may represent an endogenous biomarker predicting responsiveness to cognitive-behavioral therapy. Insomnia with altered spindle activity might constitute an insomnia subtype characterized by a neurophysiological vulnerability to sleep disruption associated with impaired responsiveness to cognitive-behavioral therapy.





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