Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Assessing interactions of linear and nonlinear neuronal sources using MEG beamformers: a proof of concept

Hadjipapas, Avgis, Hillebrand, Arjan, Holliday, Ian E., Singh, Krish Devi ORCID: https://orcid.org/0000-0002-3094-2475 and Barnes, Gareth R. 2005. Assessing interactions of linear and nonlinear neuronal sources using MEG beamformers: a proof of concept. Clinical Neurophysiology 116 (6) , pp. 1300-1313. 10.1016/j.clinph.2005.01.014

Full text not available from this repository.

Abstract

Objective This study aimed to explore methods of assessing interactions between neuronal sources using MEG beamformers. However, beamformer methodology is based on the assumption of no linear long-term source interdependencies [VanVeen BD, vanDrongelen W, Yuchtman M, Suzuki A. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans Biomed Eng 1997;44:867–80; Robinson SE, Vrba J. Functional neuroimaging by synthetic aperture magnetometry (SAM). In: Recent advances in Biomagnetism. Sendai: Tohoku University Press; 1999. p. 302–5]. Although such long-term correlations are not efficient and should not be anticipated in a healthy brain [Friston KJ. The labile brain. I. Neuronal transients and nonlinear coupling. Philos Trans R Soc Lond B Biol Sci 2000;355:215–36], transient correlations seem to underlie functional cortical coordination [Singer W. Neuronal synchrony: a versatile code for the definition of relations? Neuron 1999;49–65; Rodriguez E, George N, Lachaux J, Martinerie J, Renault B, Varela F. Perception's shadow: long-distance synchronization of human brain activity. Nature 1999;397:430–3; Bressler SL, Kelso J. Cortical coordination dynamics and cognition. Trends Cogn Sci 2001;5:26–36]. Methods Two periodic sources were simulated and the effects of transient source correlation on the spatial and temporal performance of the MEG beamformer were examined. Subsequently, the interdependencies of the reconstructed sources were investigated using coherence and phase synchronization analysis based on Mutual Information. Finally, two interacting nonlinear systems served as neuronal sources and their phase interdependencies were studied under realistic measurement conditions. Results Both the spatial and the temporal beamformer source reconstructions were accurate as long as the transient source correlation did not exceed 30–40 percent of the duration of beamformer analysis. In addition, the interdependencies of periodic sources were preserved by the beamformer and phase synchronization of interacting nonlinear sources could be detected. Conclusions MEG beamformer methods in conjunction with analysis of source interdependencies could provide accurate spatial and temporal descriptions of interactions between linear and nonlinear neuronal sources. Significance The proposed methods can be used for the study of interactions between neuronal sources.

Item Type: Article
Status: Published
Schools: Psychology
Neuroscience and Mental Health Research Institute (NMHRI)
Uncontrolled Keywords: MEG; Beamformer; Coherence; Mutual information; Phase synchronization; Nonlinear oscillators
Publisher: Elsevier
ISSN: 1388-2457
Last Modified: 20 Oct 2022 09:39
URI: https://orca.cardiff.ac.uk/id/eprint/32700

Citation Data

Cited 62 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item