Reproducibility and validity of electric source localisation with high-resolution electroencephalography

Kristeva-Feige, Rumyana; Grimm, C; Huppertz, Hans‐Jürgen; Otte, M.; Schreiber, Axel; Jäger, Dominik; Feige, Bernd; Büchert, Martin; Hennig, Jürgen; Mergner, Thomas; Lücking, Carl Hermann

doi:10.1016/s0013-4694(97)00085-0

Cited by 28 publications

(8 citation statements)

References 17 publications

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“…However, the locations of the dipoles for the 5-trial blocks during the non-fatigue experiment showed limited variations (mean standard deviation = ~10 mm; Table 1), which were very similar to the variations caused by noise in the simulation experiment (mean standard deviation = ~12 mm; Table 1). This range (10-12 mm) of error is consistent with that found by other studies that analyzed either real or simulated data (Kristeva-Feige et al, 1997;Cuffin et al, 2001;Schaefer et al, 2002), which demonstrated that the source parameters could be repeatedly determined with reasonable accuracy. For example, Cuffin et al (2001) estimated EEG source error to be about 11 mm using a source reconstruction algorithm similar to the one we used.…”

Section: Eeg Source Location and Strengthsupporting

confidence: 90%

Shifting of activation center in the brain during muscle fatigue: An explanation of minimal central fatigue?

et al. 2007

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Accumulating evidence suggests that the overall level of cortical activation controlling a voluntary motor task that leads to significant muscle fatigue does not decrease as much as the activation level of the motoneuron pool projecting to the muscle. One possible explanation for this "muscle fatigue>cortical fatigue" phenomenon is that the brain is an organ with built-in redundancies: it has multiple motor centers and parallel pathways, and the center of activation may shift from one location to another when neurons in the previous location become fatigued. This hypothesis was tested by estimating the changes of source locations of high-density (64 channels) scalp electroencephalographic (EEG) signals collected during both fatigue and non-fatigue motor tasks. A current dipole model was used to estimate the EEG sources. The fatigue motor task induced significant muscle fatigue, and the non-fatigue task did not. The EEG signal source that indicated the center of brain activation showed substantial location shifts during the fatigue motor task. The shifts could not be explained by variations of source locations caused by error estimated from the non-fatigue task EEG and simulated data. Compared to the non-fatigue condition, the weightedcenter of the source locations for all the participants shifted toward the right hemisphere (ipsilateral to the muscle activation), anterior, and inferior cortical regions under the fatigue condition. Fatigue did not alter dipole (source-signal) strength or the overall level of brain activation. The brain may avoid fatigue by shifting neuron populations that participate in a fatiguing motor task.

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Section: Eeg Source Location and Strengthsupporting

confidence: 90%

Shifting of activation center in the brain during muscle fatigue: An explanation of minimal central fatigue?

et al. 2007

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“…Attempts at precise localization of these sources in the brain led to the development of techniques coupling the spherical model of dipolar analysis with the individual cerebral magnetic resonance image (MRI) 70, 76, 111. Both the tangential and the radial dipoles were localized in the postcentral cortex,19, 69, 84 thus confirming the findings obtained by intracortical recordings in humans and monkeys (for review, see Allison et al4). Although general agreement exists about the postcentral position of the tangential source of the N20 potential, according to the results of Desmedt and colleagues, the radial generator of the P22 response should be localized in front of the rolandic sulcus 34–36.…”

Section: Sep Source Localizationmentioning

confidence: 67%

Characterizing somatosensory evoked potential sources with dipole models: Advantages and limitations

2001

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Several methods have been developed to investigate the cerebral generators of scalp somatosensory evoked potentials (SEPs), because simple visual inspection of the electroencephalographic signal does not allow for immediate identification of the active brain regions. When the neurons fired by the afferent inputs are closely grouped, as usually occurs in SEP generation, they can be represented as a dipole, that is, as a linear source with two opposite poles. Several techniques for dipolar source modeling, which use different algorithms, have been employed to build source models of early, middle‐latency, and late cognitive SEPs. Modifications of SEP dipolar activities after experimental maneuvers or in pathological conditions have also been observed. Although the effectiveness of dipolar source analysis should not be overestimated due to the intrinsic limitations of the approach, dipole modeling provides a means to assess SEPs in terms of cerebral sources and voltage fields that they produce over the head. © 2001 John Wiley & Sons, Inc. Muscle Nerve 24: 325–339, 2001

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“…The N20 component was chosen as it is known to be generated in area 3b of the primary somatosensory cortex (Baumgartner et al ., 1991; Scherg & Buchner, 1993). Reliability and validity of this method has already been demonstrated in previous studies, and the spherical head model has been shown to be equal to a MRI‐based boundary element head model for electrical source reconstruction in the primary somatosensory cortex (Kristeva‐Feige et al ., 1997; Yvert et al ., 1997; Schaefer et al ., 2002; Dinse et al ., 2003). Coordinates of the dipole locations were given relative to a 3‐D head coordinate system.…”

Section: Methodsmentioning

confidence: 87%

Assessment of sensorimotor cortical representation asymmetries and motor skills in violin players

Schwenkreis

Tom

Ragert

et al. 2007

Eur J of Neuroscience

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As a model for use-dependent plasticity, the brains of professional musicians have been extensively studied to examine structural and functional adaptation to unique requirements of skilled performance. Here we provide a combination of data on motor performance and hand representation in the primary motor and somatosensory cortex of professional violin players, with the aim of assessing possible behavioural consequences of sensorimotor cortical asymmetries. We studied 15 healthy right-handed professional violin players and 35 healthy nonmusician controls. Motor and somatosensory cortex asymmetry was assessed by recording the motor output map after transcranial magnetic stimulation from a small hand muscle, and by dipole source localization of somatosensory evoked potentials after electrical stimulation of the median and ulnar nerves. Motor performance was examined using a series of standardized motor tasks covering different aspects of hand function. Violin players showed a significant right-larger-than-left asymmetry of the motor and somatosensory cortex, whereas nonmusician controls showed no significant interhemispheric difference. The amount of asymmetry in the motor and somatosensory cortices of musicians was significantly correlated. At the behavioural level, motor performance did not significantly differ between musicians and nonmusicians. The results support a use-dependent enlargement of the left hand representation in the sensorimotor cortex of violin players. However, these cortical asymmetries were not paralleled by accompanying altered asymmetries at a behavioural level, suggesting that the reorganisation might be task-specific and does not lead to improved motor abilities in general.

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Reproducibility and validity of electric source localisation with high-resolution electroencephalography

Cited by 28 publications

References 17 publications

Shifting of activation center in the brain during muscle fatigue: An explanation of minimal central fatigue?

Shifting of activation center in the brain during muscle fatigue: An explanation of minimal central fatigue?

Characterizing somatosensory evoked potential sources with dipole models: Advantages and limitations

Assessment of sensorimotor cortical representation asymmetries and motor skills in violin players

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