MEG and complex systems

Gareth R. Barnes; Michael I.G. Simpson; Arjan Hillebrand; Avgis Hadjipapas; Caroline Witton; Paul L. Furlong

doi:10.1007/978-4-431-30962-8_32

MEG and complex systems

Gareth R. Barnes, Michael I.G. Simpson, Arjan Hillebrand, Avgis Hadjipapas, Caroline Witton, Paul L. Furlong

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.

Original language	English
Title of host publication	Complex medical engineering
Editors	Jing Long Wu, Koji Ito, Shozo Tobimatsu, Toyoaki Nishida, Hidenao Fukuyama
Place of Publication	Tokyo (JP)
Publisher	Springer
Pages	375-382
Number of pages	8
ISBN (Electronic)	978-4-431-30962-8
ISBN (Print)	978-4-431-30961-1
DOIs	https://doi.org/10.1007/978-4-431-30962-8_32
Publication status	Published - 15 May 2007
Event	1st International Conference on Complex Medical Engineering - Takamatsu , Japan Duration: 15 May 2005 → 18 May 2005 http://biomecha.eng.kagawa-u.ac.jp/CME2005/

Conference

Conference	1st International Conference on Complex Medical Engineering
Abbreviated title	CME2005
Country/Territory	Japan
City	Takamatsu
Period	15/05/05 → 18/05/05
Internet address	http://biomecha.eng.kagawa-u.ac.jp/CME2005/

Keywords

MEG
beamformer
promax
factor

Access to Document

10.1007/978-4-431-30962-8_32

Cite this

@inproceedings{9479ae3d86554afc8306f920736384a7,

title = "MEG and complex systems",

abstract = "MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.",

keywords = "MEG, beamformer, promax, factor",

author = "Barnes, {Gareth R.} and Simpson, {Michael I.G.} and Arjan Hillebrand and Avgis Hadjipapas and Caroline Witton and Furlong, {Paul L.}",

year = "2007",

month = may,

day = "15",

doi = "10.1007/978-4-431-30962-8_32",

language = "English",

isbn = "978-4-431-30961-1",

pages = "375--382",

editor = "{Long Wu}, Jing and Koji Ito and Shozo Tobimatsu and Toyoaki Nishida and Hidenao Fukuyama",

booktitle = "Complex medical engineering",

publisher = "Springer",

address = "Germany",

note = "1st International Conference on Complex Medical Engineering, CME2005 ; Conference date: 15-05-2005 Through 18-05-2005",

url = "http://biomecha.eng.kagawa-u.ac.jp/CME2005/",

}

Barnes, GR, Simpson, MIG, Hillebrand, A, Hadjipapas, A, Witton, C & Furlong, PL 2007, MEG and complex systems. in J Long Wu, K Ito, S Tobimatsu, T Nishida & H Fukuyama (eds), Complex medical engineering. Springer, Tokyo (JP), pp. 375-382, 1st International Conference on Complex Medical Engineering, Takamatsu , Japan, 15/05/05. https://doi.org/10.1007/978-4-431-30962-8_32

TY - GEN

T1 - MEG and complex systems

AU - Barnes, Gareth R.

AU - Simpson, Michael I.G.

AU - Hillebrand, Arjan

AU - Hadjipapas, Avgis

AU - Witton, Caroline

AU - Furlong, Paul L.

PY - 2007/5/15

Y1 - 2007/5/15

N2 - MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.

AB - MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.

KW - MEG

KW - beamformer

KW - promax

KW - factor

UR - http://link.springer.com/chapter/10.1007%2F978-4-431-30962-8_32

U2 - 10.1007/978-4-431-30962-8_32

DO - 10.1007/978-4-431-30962-8_32

M3 - Conference publication

SN - 978-4-431-30961-1

SP - 375

EP - 382

BT - Complex medical engineering

A2 - Long Wu, Jing

A2 - Ito, Koji

A2 - Tobimatsu, Shozo

A2 - Nishida, Toyoaki

A2 - Fukuyama, Hidenao

PB - Springer

CY - Tokyo (JP)

T2 - 1st International Conference on Complex Medical Engineering

Y2 - 15 May 2005 through 18 May 2005

ER -

MEG and complex systems

Abstract

Conference

Keywords

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