Cell assemblies and their underlying connectivity in a detailed, large-scale cortical model

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to assemblies remains challenging. To address this, we developed a complementary simulation-based approach, using a detailed, large-scale cortical network model. Using a combination of established methods we detected functional cell assemblies from the stimulus-evoked spiking activity of 185’000 neurons.
Then, we studied how the structure of connectivity influences a neuron's membership in one or more assemblies. Specifically, to what degree does common innervation from external sources (e.g., thalamic afferents) shape assembly membership? Additionally, are afferent synapses from assembly neurons scattered across dendritic trees or clustered on branches employing their nonlinear computational capabilities? We found a clear link between a neuron's assembly membership probability and its indegree (number of connections) from neurons in a given assembly, explaining 25% of the variance, and from thalamic fibers (15% of variance). It is also possible to increase the predictive power by generalizing the notion of indegree to higher dimensions. This is done by taking the presence of highly interconnected motifs in the recurrent connectivity of the innervating population into account. Moreover, synapses from cell assemblies tend to spatially cluster on dendritic branches, and considering this information results in a further 15% drop in entropy.
In summary, reversing Hebb's postulate, we show how cells that are wired together, fire together, quantifying how connectivity patterns interact to shape the emergence of assemblies. This includes a qualitative aspect of connectivity: not just the amount, but also the local structure matters; from the subcellular level in the form of dendritic clustering to the presence of specific local motifs. This connectivity-based characterization of cell assemblies creates an opportunity to study plasticity at the assembly level, and beyond strictly pairwise interactions.