they record the hemodynamic response of structures throughout the brain and thus provide important information in addition to EEGs. ”During these experiments, Tarun relied on the EEG to determine when the study participants had fallen asleep and to determine the different phases of sleep. Then she examined the MRI images to generate spatial maps of neural activity and to determine various brain states.

Data that is difficult to obtain

The only catch was that getting brain MRIs on participants while they slept wasn’t easy. The machines are noisy, making it difficult for participants to get into a deep sleep state. In collaboration with Prof. Sophie Schwartz from the University of Geneva and Prof. Nikolai Axmacher from the Ruhr University Bochum, Tarun was able to use simultaneous MRT and EEG data from around 30 people. Brain activity data was recorded over a period of nearly two hours while participants slept in an MRI machine. “Two hours is a relatively long time, which means we were able to get a range of rare, reliable data,” says Tarun. “MRIs that are done while a patient is performing a cognitive task typically last about 10 to 30 minutes.”

Brain activity during sleep

After reviewing, analyzing, and comparing all the data, what Tarun found was surprising. “We calculated exactly how often networks from different parts of the brain became active during each sleep phase,” she says. “We found that during light periods of sleep, that is, between falling asleep and entering a deep sleep state, overall brain activity decreases. However, communication between different parts of the brain becomes much more dynamic. We believe this is the case.” due to the instability of brain states during this phase. “

Van De Ville adds, “What really surprised us in all of this was the paradox that resulted. During the transition from light to deep sleep, local brain activity increased and mutual interaction decreased. This indicates the inability of the brain networks to synchronize. “

The role of networks in standard mode and the cerebellum

Consciousness is generally associated with neural networks that may be associated with our introspective processes, episodic memory, and spontaneous thinking. “We saw that the network between the anterior and posterior regions collapsed, and this became more apparent as the depth of sleep increased,” says Van De Ville. “A similar breakdown in neural networks has also been observed in the cerebellum, which is typically associated with motor control.” Right now, scientists don’t know exactly why this is happening. However, your results are the first step towards a better understanding of the states of consciousness during sleep. “Our results show that awareness is the result of interactions between different brain regions and not of localized brain activity,” says Tarun. “By examining how our state of consciousness changes in different phases of sleep and what this means for the network activity of the brain, we can better understand and explain the broad spectrum of brain functions that characterize us as humans.”
Explore further

The brain network drives changes in consciousness

Further information: Anjali Tarun et al., NREM sleep stages specifically alter the dynamic integration of large brain networks, iScience (2020). DOI: 10.1016 / j.isci.2020.101923
Journal information: iScience