Spreading depression (SD), a slow propagating depolarization wave, plays an important role in pathophysiology of different neurological disorders. Yet, research into SD-related disorders has been hampered by the lack of non-invasive recording techniques of SD. Here we compared the manifestations of SD in continuous non-invasive electroencephalogram (EEG) recordings to invasive electrocorticographic (ECoG) recordings in order to obtain further insights into generator structures and electrogenic mechanisms of surface recording of SD. SD was induced by KCl application and simultaneous SD recordings were performed by scalp EEG as well as ECoG electrodes of somatosensory neocortex of rats using a novel homemade EEG amplifier, AgCl recording electrodes, and high chloride conductive gel. Different methods were used to analyze the data; including the spectrogram, bi-spectrogram, pattern distribution, relative spectrum power, and multivariable Gaussian fit analysis. The negative direct current (DC) shifts recorded by scalp electrodes exhibited a high homogeneity to those recorded by ECoG electrodes. Furthermore, this novel method of recording and analysis was able to separate SD recorded by scalp electrodes from non-neuronal DC shifts induced by other potential generators, such as the skin, muscles, arteries, dura, etc. These data suggest a novel application for continuous non-invasive monitoring of DC potential changes, such as SD. Non-invasive monitoring of SD would allow early intervention and improve outcome in SD-related neurological disorders.
Abstract. In this study, we investigate functional correlates of gamma band oscillations in low-noise EEG signals acquired in the LSBB shielded capsule and compare them to signals acquired in a typical hospital environment. Using a research-grade EEG acquisition system, we acquired 64-channel EEG recordings from three volunteers performing several cognitive, sensory, and motor tasks in both LSBB and hospital settings. Time-frequency analysis on the signals acquired in both environments reveals that the task-induced increase in gamma band (>30 Hz) energy relative to the resting state EEG is more prominent in signals acquired at LSBB, suggesting that task-specific changes in EEG are better reflected and more readily detected in signals acquired at LSBB. These results further demonstrate the potential value of low-noise settings such as the LSBB for conducting challenging highfrequency EEG studies.
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