Artificial neuron-glial networks show astrocytes as key players in the cognition of working memory.

What is it about?

The biophysical underpinnings of working memory are of paramount interest in modern neuroscience. Working memory could be encoded by diverse patterns of neural activity, ranging from persistent firing of neuronal populations to more dynamic patterns of network activity. Silent mechanisms whereby synaptic variables maintain working memory have also been suggested. Multiple models exist for these mechanisms but only consider neurons, ignoring glia. We propose that glia could underpin working memory, introducing models of cortical neuron–glial networks where synapse–glia signaling could account for firing and silent working memory encoding. Our theoretical arguments can explain emerging accounts of the variegated nature of working memory encoding and the possible contribution of glia to it.

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Photo by Microsoft 365 on Unsplash

Photo by Microsoft 365 on Unsplash

Why is it important?

The study introduces the first spiking neuron-glial network models and provides analytical tools to analyze those networks. We show that synaptic transmission is bistable in the presence of astrocytic signaling. This phenomenon also promotes multiple co-existing asynchronous states in the networks, resulting in multiple coding channels. Additionally, the structure of connections of astrocytes with neuronal elements can account for clustered neural activity and modulate the network's storing capacity for working memory of multiple items.

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