Literature DB >> 12648750

Current source density distribution of sleep spindles in humans as found by synthetic aperture magnetometry.

Ryouhei Ishii1, Rainer Dziewas, Wilkin Chau, Peter Sörös, Hidehiko Okamoto, Atsuko Gunji, Christo Pantev.   

Abstract

Previous magnetoencephalography (MEG) studies of sleep spindles have identified a complex and widespread distribution in parietal and frontal cortices by fitting a dipolar model to the data. In this study, we used a whole-head 151-channel MEG system with simultaneous electroencephalography (EEG) recording in eight normal subjects. All subjects fell asleep during stage 2 and 3; EEG spindles have been observed in all cases. The current source density distribution of sleep spindles in the 10-15 Hz frequency band was localized by means of synthetic aperture magnetometry, and statistically tested using a permutation analysis. Source locations of the sleep spindles were found primarily in the frontal cortex, including dorsolateral and medial prefrontal areas, as well as the parietal cortex, including the vicinity of the primary sensorimotor areas. These results suggest that sleep spindles are similar in frequency content and spatial location to mu rhythm, and that these two oscillatory activities might also have a common neural basis and physiological meaning.

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Year:  2003        PMID: 12648750     DOI: 10.1016/s0304-3940(03)00048-x

Source DB:  PubMed          Journal:  Neurosci Lett        ISSN: 0304-3940            Impact factor:   3.046


  12 in total

1.  Spatiotemporal Organization and Cross-Frequency Coupling of Sleep Spindles in Primate Cerebral Cortex.

Authors:  Saori Takeuchi; Rie Murai; Hideki Shimazu; Yoshikazu Isomura; Tatsuya Mima; Toru Tsujimoto
Journal:  Sleep       Date:  2016-09-01       Impact factor: 5.849

2.  Asymptotic SNR of scalar and vector minimum-variance beamformers for neuromagnetic source reconstruction.

Authors:  Kensuke Sekihara; Srikantan S Nagarajan; David Poeppel; Alec Marantz
Journal:  IEEE Trans Biomed Eng       Date:  2004-10       Impact factor: 4.538

Review 3.  A new approach to neuroimaging with magnetoencephalography.

Authors:  Arjan Hillebrand; Krish D Singh; Ian E Holliday; Paul L Furlong; Gareth R Barnes
Journal:  Hum Brain Mapp       Date:  2005-06       Impact factor: 5.038

4.  A simple nonparametric statistical thresholding for MEG spatial-filter source reconstruction images.

Authors:  Kensuke Sekihara; Maneesh Sahani; Srikantan S Nagarajan
Journal:  Neuroimage       Date:  2005-08-15       Impact factor: 6.556

5.  Magnetoencephalography demonstrates multiple asynchronous generators during human sleep spindles.

Authors:  Nima Dehghani; Sydney S Cash; Andrea O Rossetti; Chih Chuan Chen; Eric Halgren
Journal:  J Neurophysiol       Date:  2010-04-28       Impact factor: 2.714

6.  Current source density measures of electroencephalographic alpha predict antidepressant treatment response.

Authors:  Craig E Tenke; Jürgen Kayser; Carlye G Manna; Shiva Fekri; Christopher J Kroppmann; Jennifer D Schaller; Daniel M Alschuler; Jonathan W Stewart; Patrick J McGrath; Gerard E Bruder
Journal:  Biol Psychiatry       Date:  2011-04-20       Impact factor: 13.382

7.  Emergence of synchronous EEG spindles from asynchronous MEG spindles.

Authors:  Nima Dehghani; Sydney S Cash; Eric Halgren
Journal:  Hum Brain Mapp       Date:  2011-02-17       Impact factor: 5.038

8.  Topographical frequency dynamics within EEG and MEG sleep spindles.

Authors:  Nima Dehghani; Sydney S Cash; Eric Halgren
Journal:  Clin Neurophysiol       Date:  2010-07-15       Impact factor: 3.708

9.  High-density EEG sleep correlates of cognitive and affective impairment at 12-month follow-up after COVID-19.

Authors:  Maria Rubega; Luciana Ciringione; Margherita Bertuccelli; Matilde Paramento; Giovanni Sparacino; Andrea Vianello; Stefano Masiero; Antonino Vallesi; Emanuela Formaggio; Alessandra Del Felice
Journal:  Clin Neurophysiol       Date:  2022-06-15       Impact factor: 4.861

10.  Divergent cortical generators of MEG and EEG during human sleep spindles suggested by distributed source modeling.

Authors:  Nima Dehghani; Sydney S Cash; Chih C Chen; Donald J Hagler; Mingxiong Huang; Anders M Dale; Eric Halgren
Journal:  PLoS One       Date:  2010-07-07       Impact factor: 3.240

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