We show that it is feasible to monitor the synchronized population spikes of the thalamocortical axonal terminals and cortical neurons outside the brain using high-resolution magnetoencephalography (MEG). Electrical stimulation of the snout elicited somatic-evoked magnetic fields (SEFs) above the primary somatosensory cortex (SI) of the piglet. The SEFs contained high-frequency oscillations (HFOs) around 600 Hz similar in many respects to the noninvasively measured HFOs from humans with MEG and electroencephalography (EEG). These HFOs were highly correlated with those in simultaneously measured intracortical somatic-evoked potentials (SEPs) in the snout projection area in SI. Both HFOs in SEFs and SEPs consisted of an initial component insensitive to cortically injected kynurenic acid (Kyna, 20 mM), a nonspecific antagonist of glutamatergic receptors, and a subsequent Kyna-sensitive component. The former was localized in cortical layer IV, indicating that it was due to spikes produced by the specific thalamocortical axonal terminals, whereas the latter was initially localized in layer IV and subsequently in the superficial and deeper layers. These results suggest that it may be possible to study properties of the thalamocortical and cortical spike activities in humans with MEG.

The diaphragm electromyogram (EMGdi) conveys information relating to the mechanisms of respiration; however, electrocardiogram (ECG) contamination can compromise the accuracy of data derived from this signal. We examine the EMGdi recorded from anesthetized spontaneously breathing dogs via implanted electrodes to assess the extent of the error introduced by the ECG contamination and the effectiveness of ECG gating in reducing this error. Because ECG subtraction has been shown to generate accurate results for such applications, it is used as the gold standard. Analysis of variance methods are employed to compare results derived from the EMGdi data after ECG subtraction with corresponding results derived from the original data and from the data after ECG gating. Estimates of EMGdi variables obtained by using subtraction and gating techniques were not significantly different, indicating that gating can be employed on these signals to reduce ECG contamination without affecting the accuracy of the derived data. Results also show that at EMG-to-ECG power ratios > 13.3 dB, ECG contamination does not significantly affect estimates of the EMGdi variables.

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We present an algorithm for automatic on-line analysis of the electrocardiography (ECG) channel acquired during overnight polysomnography (PSG) studies. The system is independent of ECG morphology, requires no manual initialization, and operates automatically throughout the night. It highlights likely occurrences of arrhythmias and intervals of bad signal quality while outputting a continual estimate of heart rate. Algorithm performance is validated against standard ECG databases and PSG data. Results demonstrate a minimal false negative rate and a low false positive rate for arrhythmia detection, and robustness over a wide range of noise contamination.