Statistical non-parametric mapping in sensor space

Establishing the significance of observed effects is a preliminary requirement for any meaningful interpretation of clinical and experimental Electroencephalography or Magnetoencephalography (MEG) data. We propose a method to evaluate significance on the level of sensors whilst retaining full temporal or spectral resolution. Input data are multiple realizations of sensor data. In this context, multiple realizations may be the individual epochs obtained in an evoked-response experiment, or group study data, possibly averaged within subject and event type, or spontaneous events such as spikes of different types. In this contribution, we apply Statistical non-Parametric Mapping (SnPM) to MEG sensor data. SnPM is a non-parametric permutation or randomization test that is assumption-free regarding distributional properties of the underlying data. The method, referred to as Maps SnPM, is demonstrated using MEG data from an auditory mismatch negativity paradigm with one frequent and two rare stimuli and validated by comparison with Topographic Analysis of Variance (TANOVA). The result is a time- or frequency-resolved breakdown of sensors that show consistent activity within and/or differ significantly between event or spike types. TANOVA and Maps SnPM were applied to the individual epochs obtained in an evoked-response experiment. The TANOVA analysis established data plausibility and identified latencies-of-interest for further analysis. Maps SnPM, in addition to the above, identified sensors of significantly different activity between stimulus types.

Cortical Representation to Odorant Stimulation: Statistical Non-parametric Mapping of Low Resolution Electro magnetic Tomography (LORETA)

BACKGROUND: Although olfactory stimulation has been known to produce effects on human mood and cognition, the specific EEG patterns of activity was reported diversely. The purpose of this study was to investigate EEG changes by odorant using low resolution electromagnetic tomography (LORETA) in young healthy subjects. METHODS: The EEG's of nineteen (10 males, 9 females) non-smoking right-handed college students were recorded after odorant stimulation. A nineteen-channel EEG was recorded referenced to linked ears before and during olfactory stimulation. Olfactory stimulation was presented with lavender essential oil by blotter method. The LORETA power was computed from ten 2-s epochs, separately for the different EEG frequencies. The power values were logarithmically transformed and paired sample t-tests were done for each voxel and frequency band (1.5-30 Hz). Statistical results were displayed 3-dimensionally on the standard brain template. RESULTS: All subjects experienced positive feelings (relaxed and pleasant) by olfactory stimulation with lavender oil (p<0.01). The LORETA power of theta and alpha band was increased in the dorsolateral and medial frontal areas, predominantly in the posterior cingulate gyri. The alpha LORETA power was also increased in bilateral orbitofrontal regions and the left perisylvian region including the insular cortex. Beta power was increased in the posterior cingulated gyri and mesial temporal region, predominantly on the left side. CONCLUSIONS: These results suggest that olfaction associated with emotional feeling might induce brain electrical power changes not only in the limbic system but also in the neocortex with lateralization to the dominant hemisphere.