Magnetenzephalogramm, MEG  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential.

Equivalent dipole  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential.

MEG

EEG vs. MEG  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential.

Differences between EEG and MEG MEG is only sensitive to the tangential component of the dipoles, but insensitive to the radial component. EEG measures both. This implies that MEG recordings are mainly based on activity in the sulci, but not in the gyri (1/3 of the cortex).  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential. In contrast to EEG, MEG is insensitive to the inhomogeneities of skull and scalp which result in field spreading. As a consequence, the ERF is often more focal than the ERP.

Recording of ERPs and ERFs Strength: - high temporal resolution - direct measure of neural activity Weakness: - measures only a part of the neural activity (open fields) - poor spatial resolution (inverse problem)  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential.

Mismatch negativity (MMN) entdeckt durch Näätänen 1978

Winkler et al. 1999 EEG Mismatch Negativity Erwerb eines finnischen Vokalkontrastes durch Ungarn

Phillips et al. 2000 J Cog Neuroscience

Phillips et al. 2000 J Cog Neuroscience

Phillips et al. 2000 J Cog Neuroscience

Phillips et al. 2000 J Cog Neuroscience

The inverse problem Aim: Finding the source distribution underlying a given scalp potential map. Problem: The inverse problem in EEG and MEG has no unique solution. For any given potential (or magnetic field) distribution over the scalp surface, a variety of possible neural source distributions exists that can produce the same surface map. The number of possible current source distributions that matches a given set of surface data may be large.  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential.

Dipole analysis A head model is assumed, e.g. a three-shell model (brain, skull, scalp), or a more realistic head model. This model allows the calculation of the scalp electrical potential generated at a particular location on the scalp by an intracerebral source with a particular location, orientation and strength.  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential. In a number of iterative steps the source parameters can be changed until the difference between the modelled and the recorded waveforms is minimized.

Constraining the inverse problem Actual solutions often involve information about neurophysiology and anatomy to reduce the solution space. Sources (dipoles) may change strength, but not location or orientation during a specified time interval (spatial-temporal constraint).  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential. Sources are all located at the same depth (e.g. in the neocortex). This approach is referred to as “spatial deconvolution”, “de-blurring”, or “cortical imaging”. It is based on the unique relation between surface potentials and sources at a fixed depth.

A source dipole is defined by its location, orientation, and strength Dipole analysis A source dipole is defined by its location, orientation, and strength  I’m going to review attempts to explore error-related processing within the framework of cognitive neuroscience, focussing on measures of the event-related brain potential. Sources for the Bereitschaftspotential: fit with 1 and 2 stationary dipoles (extension of the left middle finger)

Die Kombination von hämodynamischen und elektromagnetischen Daten kann Informationen über räumliche UND zeitliche Eigenschaften von Hirnaktivierungen bieten.

Geschätzte Zeitfenster der Wortproduktionsprozesse Konzeptuelle Vorbereitung von der Bildpräsentation bis zum lexikalischen Konzept 175 ms (Thorpe et al.,1996; Schmitt et al., 2000) Lemmazugriff 115 ms (Levelt et al., 1992; Roelofs, 1992; Schmitt et al., 2001) Formenkodierung * Wortformzugriff 40 ms (van Turennout et al., 1998) * Syllabifizierung 125 ms (van Turennout et al., 1997; Wheeldon & Levelt, 1995) * Phonetische Enkodierung bis Beginn der Aussprache 145 ms Gesamt 600 ms (Jescheniak & Levelt, 1994; Levelt et al., 1998; Damian et al., 2002)

Salmelin, Hari, Lounasmaa, & Sams (1994), Fig. 1 Picture naming: MEG Salmelin, Hari, Lounasmaa, & Sams (1994), Fig. 1

Gemessene (links) und erwartete (rechts) Zeitfenster bei Bildbenennung MEG data from: Salmelin et al., 1994; Levelt et al., 1998; Maess et al., 2002 Indefrey, P. and Levelt, W.J.M. (2004) Cognition