1999
DOI: 10.1046/j.1440-1819.1999.00509.x
|View full text |Cite
|
Sign up to set email alerts
|

Topographic mapping of EEG spectral power and coherence in delta activity during the transition from wakefulness to sleep

Abstract: The present study examined the topographic characteristics in delta band activity during the transition from wakefulness to sleep, using topographic mapping of electroencephalogram (EEG) power and coherence corresponding to nine EEG stages. The dominant topographic components of delta band activity increased clearly from the vertex sharp-wave stage EEG stage 6) in the anterior-central area. Principal component maps revealed the scalp distribution of EEG. Delta activity in the sleep onset period were composed o… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
6
0

Year Published

2007
2007
2023
2023

Publication Types

Select...
6
1

Relationship

0
7

Authors

Journals

citations
Cited by 8 publications
(6 citation statements)
references
References 6 publications
(8 reference statements)
0
6
0
Order By: Relevance
“…As the user begins to drift off to sleep, finger flexion begins to decrease as they forget or fail at this passive behavioral task. Changes in these signals-heart rate, skin conductance and muscle tone-have been historically used as markers of sleep onset, each offering insight into Hori sleep onset stages (Hori, Hayashi, and Morikawa 1994;Tanaka, Hayashi, and Hori 1999). Passive behavioral measures have been shown to be unobtrusive sleep onset trackers that offer information that can supplement physiological measures (Ogilvie 2001;Mavromatis and University of Brunel 1983;Casagrande et al 1997;Prerau et al 2014).…”
Section: The Dormio Targeted Dream Incubation (Tdi) Protocolmentioning
confidence: 99%
“…As the user begins to drift off to sleep, finger flexion begins to decrease as they forget or fail at this passive behavioral task. Changes in these signals-heart rate, skin conductance and muscle tone-have been historically used as markers of sleep onset, each offering insight into Hori sleep onset stages (Hori, Hayashi, and Morikawa 1994;Tanaka, Hayashi, and Hori 1999). Passive behavioral measures have been shown to be unobtrusive sleep onset trackers that offer information that can supplement physiological measures (Ogilvie 2001;Mavromatis and University of Brunel 1983;Casagrande et al 1997;Prerau et al 2014).…”
Section: The Dormio Targeted Dream Incubation (Tdi) Protocolmentioning
confidence: 99%
“…Higher current source density immediately after SO than at the end of the first NREM sleep cycle, in the SFG and SPL for slow and fast spindles, respectively (Alfonsi et al, 2019). (Morikawa et al, 1997;Tanaka et al, 1998Tanaka et al, , 1999. Progressive decrease of antero-posterior synchrony (De Gennaro et al, 2004;Morikawa et al, 1997), with a post-SO switch to an anterior-to-posterior propagation of the information flow (De Gennaro et al, 2004).…”
Section: Bslmentioning
confidence: 99%
“…Connectivity: coherence of cortical activity within the delta range gradually increases within ipsilateral frontal and central areas and between contralateral frontal and central homologues (Morikawa et al, 1997;Tanaka et al, 1998Tanaka et al, , 1999Tanaka et al, , 2000 in the transition between wake and sleep, while it starts to decrease during deeper sleep within and between the more posterior regions (Morikawa et al, 1997;Tanaka et al, 2000). Antero-posterior synchrony progressively decreases during the falling asleep period (De Gennaro et al, 2004;Morikawa et al, 1997), and this pattern is associated with the inver Values <100 represent a percent reduction of power after the SO.…”
Section: Bslmentioning
confidence: 99%
“…Thus therapy consisted of attempting to drive the EEG away from the dominant frequency to new frequency values [25,31]. Clinical practices in photic driving response are often measured using hemispheric and asymmetric methods which have often shown alterations in the functional states of the brain [12,17,38]. The use of EEG coherence and asymmetric spectral estimates in particular EEG frequency bands was found suitable to identify and characterise brain regions [3,9] and to evaluate the strength of responses due to rhythmic stimulation.…”
Section: Introductionmentioning
confidence: 99%