Impact of modular organization on dynamical richness in cortical networks
© Yuichiro Chino/Getty
A new brain-like model helps explain how different neural circuits process sights, sounds, smells and other stimuli in a segregated manner before the brain integrates all the information together into a cohesive whole.
Scientists from the Advanced Institute for Materials Research and elsewhere used precision neuroengineering techniques to arrange rat neurons on a glass slide in a simple four-node grid, with each node meant to represent a particular neuronal circuit.
The researchers then manipulated the connectivity of their artificial brain network and showed that the neural dynamics respectively became either fully segregated or fully integrated when the coupling between nodes was too weak or too strong. There was, however, an optimal intermediate number of connections that allowed integration and segregation to coexist.
This greatly simplified model enabled the scientists to glean new insights into the fundamental mechanisms that shape brain dynamics.
- Science Advances 4, eaau4914 (2018). doi: 10.1126/sciadv.aau4914
|Tohoku University, Japan||0.67|
|University of Barcelona (UB), Spain||0.17|
|Yamagata University, Japan||0.08|
|Waseda University, Japan||0.08|