Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR.
Artifacts ; Dataset ; Electroencephalography* ; Head ; Magnetic Fields ; Magnetoencephalography ; Neurons ; Noise

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.
Electroencephalography ; Magnetoencephalography ; Methods ; Random Allocation

BACKGROUND/AIMS: Motility disorders are common and may affect the entire gastrointestinal (GI) tract but current treatment is limited. Multilocular sensing of GI electrical activity and variable electrical stimulation (ES) is a promising option. The aim of our study is to investigate the effects of adjustable ES on poststimulatory spike activities in 5 GI segments. METHODS: Six acute porcine experiments were performed with direct ES by 4 ES parameter sets (30 seconds, 25 mA, 500 microseconds or 1000 microseconds, 30 Hz or 130 Hz) applied through subserosal electrodes in the stomach, duodenum, ileum, jejunum, and colon. Multi-channel electromyography of baseline and post-stimulatory GI electrical activity were recorded for 3 minutes with hook needle and hook-wire electrodes. Spike activities were algorithmically calculated, visualized in a heat map, and tested for significance by Poisson analysis. RESULTS: Post-stimulatory spike activities were markedly increased in the stomach (7 of 24 test results), duodenum (8 of 24), jejunum (23 of 24), ileum (18 of 24), and colon (5 of 24). ES parameter analysis revealed that 80.0% of the GI parts (all but duodenum) required a pulse width of 1000 microseconds, and 60.0% (all but jejunum and colon) required 130 Hz frequency for maximum spike activity. Five reaction patterns were distinguished, with 30.0% earlier responses (type I), 42.5% later or mixed type responses (type II, III, and X), and 27.5% non-significant responses (type 0). CONCLUSIONS: Multilocular ES with variable ES parameters is feasible and may significantly modulate GI electrical activity. Automated electromyography analysis revealed complex reaction patterns in the 5 examined GI segments.
Colon ; Duodenum ; Electric Stimulation ; Electrodes ; Electromyography ; Gastrointestinal Tract ; Hot Temperature ; Ileum ; Jejunum ; Needles ; Stomach ; Theranostic Nanomedicine