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Electromagnetic signature of human cortical dynamics during wakefulness and sleep

Abstract : Analyzing brain function at multiple scales is a necessary step to understand its complexities. In this thesis work, we tackled this issue at both macro and micro-scales using non-invasive and invasive recordings. We have used a series of computational techniques and correlation analyses to analyze recordings of the human brain activity during wakefulness and sleep. In a first study, we analyzed simultaneous elecroencephalogram (EEG) and magnetoencephalogram (MEG) recordings in awake human subjects. We showed theoretically that if the medium is resistive, the frequency scaling of EEG and MEG signals should be the same at low frequencies (<10 Hz). To test this prediction, we analyzed the spectrum of simultaneous EEG and MEG measurements in four human subjects. In a given region, although the variability of the frequency scaling exponent was higher for MEG compared to EEG, both signals consistently scale with a different exponent. In some cases, the scaling was similar, but only when the signal-to-noise ratio of the MEG was low. Several methods of noise correction for environmental and instrumental noise were tested, and they all increased the difference between EEG and MEG scaling. We conclude that there is a significant difference in frequency scaling between EEG andMEG, which can be explained if the extracellular medium (including other layers such as dura matter and skull) is globally non-resistive. The resistive or non-resistive nature of the extracellular space in the brain is an important determinant for correctly modeling extracellular potentials. In a second study, we analyzed the spatio-temporal dynamics of excitation and inhibition during human sleep from high-density intracranial recordings. We used high-density recordings obtained in epileptic patients and from unit recordings, we successfully separated between RS neurons (regular or bursting cells) from fast-spiking (FS) cells. The high density of the array allowing recording from large number of cells (up to 90) helped us to identify apparent monosynaptic connections, which confirmed the excitatory and inhibitory nature of RS and FS cells, thus categorized as putative pyramidal and interneurons, respectively. Using such a separation, we investigated the dynamics of correlations within each class. A marked exponential decay with distance was observed in the case of excitatory but not for inhibitory cells. Thus, our study provides, for a first time, insight on the interplay of excitation and inhibition in the human neocortex. In a third study, we investigated dynamical signatures of complex dynamics, and self)organized activity, from intracranial recordings in cat, monkey and humans. We compared the collective dynamics of different in vivo preparations during wakefulness, slow-wave sleep and REM sleep, in cat parietal cortex (96 electrodes), monkey motor cortex (64/96 electrodes) and human temporal cortex (96 electrodes) in epileptic patients. In neuronal avalanches defined from units (up to 152 single units), the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. Avalanches defined from nLFPs displayed power-law scaling in double logarithmic representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP) peaks, which are not related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using the more severe cumulative distribution function (CDF) representation did not confirm power-law scaling. The same pattern was seen for cats, monkey and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. While simple exponentials yielded very good fits of the avalanche dynamics, the bi-exponential distribution provided the best fit to the data. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states, at the level of spiking activity or local field potential, in the awake and sleeping brain of mammals, from cat to man. Finally, in an appendix, we provide preliminary results about the relations between excitatory and inhibitory cells with local field potentials in human sleep. The high-density intracranial recordings described above (96-electrode array) were used to analyze the differential firing of RS and FS cells during different sleep stages, devoid of interictal activity. Up to 90 simultaneously recorded units (in Layer III), and 96 local field potential (LFP) recordings, provide a good basis to characterize the dynamics of excitation and inhibition during different brain states. During slow-wave sleep (SWS, Stage III or IV), dominated by delta-wave activity, all neurons fired according to Up and Down states, in relation to slow-waves complexes in the LFP, as described previously. Both RS and FS cells were silent during the Down-states. During REM sleep and wakefulness, both types of units fired according to very irregular patterns of discharge, while the LFP or ECoG were desynchronized. In all states, FS cells fired significantly more than RS cells (about 4 to 5 times on average). These results provide a characterization of the different roles of excitation and inhibition in the different wake and sleep states in humans. In conclusion, we have used different measurementmethods, from microscopic scale (single unit activity), mesoscopic (LFP) and macroscopic (ECoG, EEG, MEG) to characterize wake and sleep states in humans (as well as cat and monkey in one study). We conclude that the brain follows complex dynamics at all scales. There is globally no evidence for self-organized critical dynamics, but the brain activity manifests other signs of self-organization, such as large-scale rhythmical activity and multiple exponential processes. We suggest that all results could be explained by the interplay of excitation and inhibition. We anticipate that coupled oscillator network models of interacting excitation and inhibition should reproduce these findings, which constitutes a challenge for future work.
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Contributor : Alain PERIGNON Connect in order to contact the contributor
Submitted on : Thursday, September 6, 2012 - 1:49:24 PM
Last modification on : Sunday, June 26, 2022 - 9:41:56 AM
Long-term archiving on: : Friday, December 7, 2012 - 3:42:21 AM


  • HAL Id : tel-00728697, version 1


Nima Dehghani. Electromagnetic signature of human cortical dynamics during wakefulness and sleep. Neurons and Cognition [q-bio.NC]. Université Pierre et Marie Curie - Paris VI, 2012. English. ⟨NNT : ⟩. ⟨tel-00728697⟩



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