Magnetoencephalography Dipole Research Articles

Detection of stimulus deviance within primate primary auditory cortex: intracortical mechanisms of mismatch negativity (MMN) generation

Mismatch negativity (MMN) is a cognitive, auditory event-related potential (AEP) that reflects preattentive detection of stimulus deviance and indexes the operation of the auditory sensory (‘echoic’) memory system. MMN is elicited most commonly in an auditory oddball paradigm in which a sequence of repetitive standard stimuli is interrupted infrequently and unexpectedly by a physically deviant ‘oddball’ stimulus. Electro- and magnetoencephalographic dipole mapping studies have localized the generators of MMN to supratemporal auditory cortex in the vicinity of Heschl's gyrus, but have not determined the degree to which MMN reflects activation within primary auditory cortex (AI) itself. The present study, using moveable multichannel electrodes inserted acutely into superior temporal plane, demonstrates a significant contribution of AI to scalp-recorded MMN in the monkey, as reflected by greater response of AI to loud or soft clicks presented as deviants than to the same stimuli presented as repetitive standards. The MMN-like activity was localized primarily to supragranular laminae within AI. Thus, standard and deviant stimuli elicited similar degrees of initial, thalamocortical excitation. In contrast, responses within supragranular cortex were significantly larger to deviant stimuli than to standards. No MMN-like activity was detected in a limited number to passes that penetrated anterior and medial to AI. AI plays a well established role in the decoding of the acoustic properties of individual stimuli. The present study demonstrates that primary auditory cortex also plays an important role in processing the relationships between stimuli, and thus participates in cognitive, as well as purely sensory, processing of auditory information.

Error bounds for EEG and MEG dipole source localization

General formulas are presented for computing a lower bound on localization and moment error for electroencephalographic (EEG) or magnetoencephalographic (MEG) current source dipole models with arbitrary sensor array geometry. Specific EEG and MEG formulas are presented for multiple dipoles in a head model with 4 spherical shells. Localization error bounds are presented for both EEG and MEG for several different sensor configurations. Graphical error contours are presented for 127 sensors covering the upper hemisphere, for both 37 sensors and 127 sensors covering a smaller region, and for the standard 10–20 EEG sensor arrangement. Both 1- and 2-dipole cases were examined for all possible dipole orientations and locations within a head quadrant. The results show a strong dependence on absolute dipole location and orientation. The results also show that fusion of the EEG and MEG measurements into a combined model reduces the lower bound. A Monte Carlo simulation was performed to check the tightness of the bounds for a selected case. The simple head model, the low power noise and the few strong dipoles were all selected in this study as optimistic conditions to establish possibly fundamental resolution limits for any localization effort. Results, under these favorable assumptions, show comparable resolutions between the EEG and the MEG models, but accuracy for a single dipole, in either case, appears limited to several millimeters for a single time slice. The lower bounds increase markedly with just 2 dipoles. Observations are given to support the need for full spatiotemporal modeling to improve these lower bounds. All of the simulation results presented can easily be scaled to other instances of noise power and dipole intensity.