Literature DB >> 8813418

A correlation study of averaged and single trial MEG signals: the average describes multiple histories each in a different set of single trials.

L Liu1, A A Ioannides.   

Abstract

Our understanding of the link between electrical events in the brain and behaviour is based on indirect measures. Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI) rely on haemodynamic processes which are slower by two to three orders of magnitude than the processes characterizing normal and pathological brain function. Direct invasive measurements of the electrical activity on the other hand produce too local a view which fails to show the large scale coherence which sustains awareness and cognition. On the opposite extreme, gross measures of the electrical activity like Electroencephalography (EEG) and single or few channel Magetoencephalography (MEG) had until recently to rely on simplistic point like models extracted from the averages of many repetitions of physiologically irrelevant stimuli. The introduction of multichannel probes with over 30 channels (Hämälainen et al. 1993), and the use of distributed source analysis (Ioannides et al. 1990a) opened up for the first time the possibility to study the response of single trials. In this work we address directly the question how representative is the description of events extracted from the analysis of the average signal. We use the simplest possible example: the cortical response to a simple 1 kHz tone, focusing on the early and by general admission "automatic" response around 100 ms after stimulus onset. To avoid the confounding inter-subject variability we have studied the responses over the left and right cortical areas to ipsi- and contralateral stimulation in a single subject; for testing reproducibility, we have used both the eyes open and eyes closed conditions. Since the computational demands involved in extracting a full three dimensional description from each trial are too great, we have complemented the distributed source analysis with special techniques, which allow us to scan through each and every single trial and identify each cortical activation similar to the ones picked out in the average signal. We are thus able to show conclusively that the sequence of events suggested by the analysis of the average signal is not representative of what is happening in individual trials. The sequence is made up of events which occurred in different trials reflecting probably the existence of many parallel routes each of which leads from the input at the ear to a final "computation".

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Year:  1996        PMID: 8813418     DOI: 10.1007/bf01186914

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  27 in total

1.  Topographic mapping of single sweep evoked potentials in the brain.

Authors:  D Liberati; S DiCorrado; S Mandelli
Journal:  IEEE Trans Biomed Eng       Date:  1992-09       Impact factor: 4.538

Review 2.  Of dreaming and wakefulness.

Authors:  R R Llinás; D Paré
Journal:  Neuroscience       Date:  1991       Impact factor: 3.590

3.  Magnetic field tomography of cortical and deep processes: examples of "real-time mapping" of averaged and single trial MEG signals.

Authors:  A A Ioannides; M J Liu; L C Liu; P D Bamidis; E Hellstrand; K M Stephan
Journal:  Int J Psychophysiol       Date:  1995-12       Impact factor: 2.997

4.  Comparison of single current dipole and magnetic field tomography analyses of the cortical response to auditory stimuli.

Authors:  A A Ioannides; K D Singh; R Hasson; S B Baumann; R L Rogers; F C Guinto; A C Papanicolaou
Journal:  Brain Topogr       Date:  1993       Impact factor: 3.020

5.  Dynamics of neuronal interactions in monkey cortex in relation to behavioural events.

Authors:  E Vaadia; I Haalman; M Abeles; H Bergman; Y Prut; H Slovin; A Aertsen
Journal:  Nature       Date:  1995-02-09       Impact factor: 49.962

6.  Scalp electrical potentials reflect regional cerebral blood flow responses during processing of written words.

Authors:  A Z Snyder; Y G Abdullaev; M I Posner; M E Raichle
Journal:  Proc Natl Acad Sci U S A       Date:  1995-02-28       Impact factor: 11.205

7.  Macroscopic ionic currents within the human leg.

Authors:  D I Grimes; R F Lennard; S J Swithenby
Journal:  Phys Med Biol       Date:  1985-10       Impact factor: 3.609

8.  Comparison of evoked potentials and high-frequency (gamma-band) oscillating potentials in rat auditory cortex.

Authors:  M N Franowicz; D S Barth
Journal:  J Neurophysiol       Date:  1995-07       Impact factor: 2.714

9.  Magnetic field tomography of coherent thalamocortical 40-Hz oscillations in humans.

Authors:  U Ribary; A A Ioannides; K D Singh; R Hasson; J P Bolton; F Lado; A Mogilner; R Llinás
Journal:  Proc Natl Acad Sci U S A       Date:  1991-12-15       Impact factor: 11.205

10.  Human oscillatory brain activity near 40 Hz coexists with cognitive temporal binding.

Authors:  M Joliot; U Ribary; R Llinás
Journal:  Proc Natl Acad Sci U S A       Date:  1994-11-22       Impact factor: 11.205

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  8 in total

1.  Timing and connectivity in the human somatosensory cortex from single trial mass electrical activity.

Authors:  Andreas A Ioannides; George K Kostopoulos; Nikolaos A Laskaris; Lichan Liu; Tadahiko Shibata; Marc Schellens; Vahe Poghosyan; Ara Khurshudyan
Journal:  Hum Brain Mapp       Date:  2002-04       Impact factor: 5.038

2.  Widely distributed magnetoencephalography spikes related to the planning and execution of human saccades.

Authors:  Andreas A Ioannides; Peter B C Fenwick; Lichan Liu
Journal:  J Neurosci       Date:  2005-08-31       Impact factor: 6.167

3.  Neural mechanisms of movement speed and tau as revealed by magnetoencephalography.

Authors:  Heng-Ru May Tan; Arthur C Leuthold; David N Lee; Joshua K Lynch; Apostolos P Georgopoulos
Journal:  Exp Brain Res       Date:  2009-05-08       Impact factor: 1.972

4.  A spatiotemporal framework for estimating trial-to-trial amplitude variation in event-related MEG/EEG.

Authors:  Tulaya Limpiti; Barry D Van Veen; Hagai T Attias; Srikantan S Nagarajan
Journal:  IEEE Trans Biomed Eng       Date:  2008-10-31       Impact factor: 4.538

5.  TopoToolbox: using sensor topography to calculate psychologically meaningful measures from event-related EEG/MEG.

Authors:  Xing Tian; David Poeppel; David E Huber
Journal:  Comput Intell Neurosci       Date:  2011-04-18

6.  Source space analysis of event-related dynamic reorganization of brain networks.

Authors:  Andreas A Ioannides; Stavros I Dimitriadis; George A Saridis; Marotesa Voultsidou; Vahe Poghosyan; Lichan Liu; Nikolaos A Laskaris
Journal:  Comput Math Methods Med       Date:  2012-10-11       Impact factor: 2.238

7.  Activation of the left inferior frontal gyrus in the first 200 ms of reading: evidence from magnetoencephalography (MEG).

Authors:  Piers L Cornelissen; Morten L Kringelbach; Andrew W Ellis; Carol Whitney; Ian E Holliday; Peter C Hansen
Journal:  PLoS One       Date:  2009-04-27       Impact factor: 3.240

8.  EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network.

Authors:  Muthuraman Muthuraman; Vera Moliadze; Kidist Gebremariam Mideksa; Abdul Rauf Anwar; Ulrich Stephani; Günther Deuschl; Christine M Freitag; Michael Siniatchkin
Journal:  PLoS One       Date:  2015-10-28       Impact factor: 3.240

  8 in total

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