Yoshiaki Horiike is a master’s student in the Berg Lab at the University of Copenhagen.

Quantifying the local irreversibility of a motor neural network

Abstract:
It has been shown that the neuronal population activity in the spinal cord during rhythmic muscle movements shows a low-dimensional rotational pattern (Lindén et al. Nature 2022). Its cycling pattern has been shown to encode movement behaviours, and further quantitative analyses of these dynamics should help to understand the encoding mechanism. Here, we quantified the irreversibility measure associated with the individual transition processes, local irreversibility (Lynn et al. PRL&PRE 2022), from the spike data. We found that when the rhythmic movement is generated, the spike data show higher irreversibility than the case the animal is in the rest.

Host: Chris Lynn

All are welcome. Lunch will be provided - please let us know if you plan to attend.