Back

Cycling reduces the entropy of neuronal activity in the human adult cortex

Ferre, I. B. S.; Corso, G.; dos Santos Lima, G. Z.; Lopes, S. R.; Leocadio-Miguel, M. A.; Franca, L.; de Lima Prado, T.; Araujo, J. F.

2024-02-01 neuroscience
10.1101/2024.01.31.578253 bioRxiv
Show abstract

Electroencephalogram (EEG) data is often analyzed from a Brain Complexity (BC) perspective, having successfully been applied to study the brain in both health and disease. In this study, we employed recurrence entropy to quantify BC associated with the neurophysiology of movement by comparing BC in both resting state and cycling movement. We measured EEG in 24 healthy adults, and placed the electrodes on occipital, parietal, temporal and frontal sites, on both the right and left sides. EEG measurements were performed for cycling and resting states and for eyes closed and open. We then computed recurrence entropy for the acquired EEG series. Our results show that open eyes show larger entropy compared to closed eyes; the entropy is also larger for resting state, compared to cycling state for all analyzed brain regions. The decrease in neuronal complexity measured by the recurrence entropy could explain the neural mechanisms involved in how the cycling movements suppress the freezing of gate in patients with Parkinsons disease due to the constant sensory feedback caused by cycling that is associated with entropy reduction.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.