Estimation of the spatiotemporal structure of event-related desynchronization and synchronization in magnetoencephalography.

We present a comprehensive methodology for identifying cerebral areas involved in event-related changes of electromagnetic activity of the human brain, and also for tracing the temporal evolution of this activity. Information from pre- and peristimulus time intervals--in terms of event-related synchronization (ERS) and desynchronization (ERD) of the magnetoencephalographic (MEG) signal--was directly incorporated in the relevant test statistics. For the individual steps of the analysis, we used particular estimations of the time-frequency distribution of the energy along with particular error control methods, that is, short-time Fourier transform and false-discovery rate at the sensor level and multitapers and familywise error rate at the source level. This procedure was applied to two types of group-level tests, a within-condition test and a between-conditions test. The performance of the proposed methodology is assessed by (1) analyzing the event-related brain activity from two experimental conditions of an auditory MEG experiment--passive listening to a sequence of frequency-modulated sweeps and their active categorization with respect to the direction of frequency modulation, and (2) comparing the findings with those obtained with a widely used cluster-based analysis.

Single-trial reconstruction of auditory evoked magnetic fields by means of Template Matching Pursuit.

We present a new paradigm for the adaptive estimation of evoked brain responses in single trials, based upon the combination of the matching pursuit (MP) algorithm and template matching, and referred to as Template Matching Pursuit (TMP). In contrast to the classical template matching with invariant single-trial morphology and to previous approaches using MP with strong similarity constraint on functions in sequential trials, this adaptive approach allows for a wide variety of waveforms, and its universality is retained by parametrizing all relevant waveforms in terms of Gabor functions. A survey of single-trial estimates obtained for 10 subjects (∼4000 individual trials in total) confirms the validity of the assumption of a good approximation of single-trial waveforms. Owing to the fully parametric approach, we can easily perform also any quantitative analysis of such a huge dataset. As an example we take the trial-to-trial variability of the peak amplitude and latency of the auditory M100 component. This methodology provides estimates of diversified morphologies, which makes it free from the limitations inherent to any restrictive model. This seems advantageous in the context of the ongoing debate as to the neural mechanisms of average evoked brain responses.

Event-related desynchronization and synchronization in MEG: Framework for analysis and illustrative datasets related to discrimination of frequency-modulated tones.

We introduce a complete framework for the calculation of statistically significant event-related desynchronization and synchronization (ERD/ERS) in the time-frequency plane for magnetoencephalographic (MEG) data, and provide free Internet access to software and illustrative datasets related to a classification task of frequency-modulated (FM) tones. Event-related changes in MEG were analysed on the basis of the normal component of the magnetic field acquired by the 148 magnetometers of the hardware configuration of our whole-head MEG device, and by computing planar gradients in longitudinal and latitudinal direction. Time-frequency energy density for the magnetometer as well as the two gradient configurations is first approximated using short-time Fourier transform. Subsequently, detailed information is obtained from high-resolution time-frequency maps for the most interesting sensors by means of the computationally much more demanding matching pursuit parametrization. We argue that the ERD/ERS maps are easier to interpret in the gradient approaches and discuss the superior resolution of the matching pursuit time-frequency representation compared to short-time Fourier and wavelet transforms. Experimental results are accompanied by the following resources, available from http://brain.fuw.edu.pl/MEG: (a) 48 high-resolution figures presenting the results of four subjects in all applicable settings, (b) raw datasets, and (c) complete software environment, allowing to recompute these figures from the raw datasets.