Scale-Free Dynamics of Brain Network Activity in Mice During Novelty and Exploration.
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The brain is considered a "critical system," which continuously transitions between two phases: in one the neural activity amplifies and spreads over the largest distances in the network, and in the other the neural activity is reduced and localized. A strong indication that a system is in a critical state is scale-free behaviour, which is best described by the exponent of a power-law function. This scaling exponent can be obtained from Demeaned Fluctuation Analysis (DMA), and indicates in which state the system is. In this study, we analyzed local field potential (LFP) recordings from the hippocampal-cortical network in 6 mice during an object recognition task, and DMA was applied for frequencies from 2 Hz to 150 Hz to identify neural oscillations and regions indicating above-noise level scaling exponents for each experimental stage. Our results suggest that there is a significant increase of hippocampal scaling exponents in beta (24-29 Hz) associated with novelty and exploration compared to rest. We also found evidence suggesting that different CA1 hippocampal sides might be contributing differently to the scaling properties of theta (4-7 Hz) associated with novelty detection. We hypothesize that scaling dynamics in theta might be reflecting coordination of information in the hippocampal-cortical network during object recognition. The greatest variability in scaling dynamics was observed in gamma (96-102) in the parietal cortex during object exploration. We therefore hypothesize that parietal gamma scaling dynamics reflect a rather general mechanism involved in the task. Overall, our results suggest that the scaling dynamics of different frequency bands can be linked to behavioral outcomes, and reflect different processes involved in the object recognition task.
Faculteit der Sociale Wetenschappen