The brain is an organ that functions as a network of many elements connected in a non-uniform manner. Especially, the cortex is evolutionarily newest, and is thought to be primarily responsible for the high intelligence of mammals. In the mature mammalian brain, all cortical regions are expected to have some degree of homology, but have some variations of local circuits to achieve specific functions enrolled by individual regions. However, few cellular-level studies have examined how the networks within different cortical regions differ. This study aimed to find rules for systematic changes of connectivity (microconnectomes) across 16 different cortical region groups. We also observed unknown trends in basic parameters in vitro such as firing rate and layer thickness across brain regions. The results revealed that the frontal group shows unique characteristics such as dense active neurons, thick cortex and strong connections with deeper layers. This suggests the frontal side of the cortex is inherently capable of driving, even in isolation. This may suggest that deep layers of frontal node provide the driving force generating a global pattern of spontaneous synchronous activity, such as the Default Mode Network. This finding may explain why disruption in this region causes a large impact on mental health.
In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a new “generating” approach, this study evaluated the similarity of activities of neurons at the cellular level within each region after disconnecting between regions. To this end, a multi-layer LSTM (Long-Short Term Memory) model was used. Surprisingly, the results revealed that generation of activity from one region to other regions that had been disconnected was possible with similar reproduction accuracy as generation between the same regions in many cases. Notably, not only firing rates but also synchronization of firing between neuron pairs, which is often used as neuronal representations, could be reproduced with considerable precision. Additionally, their accuracies were associated with the relative distance between brain regions and the strength of the structural connections that initially connected them. This outcome not only enables us to look into principles in neuroscience based on the potential to generate new informative data, but also creates neural activity that has not been measured in adequate amounts and could potentially lead to reduced animal experiments.
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