Cycling of motif dominance generalized across manipulations of synaptic weights and topologies, demonstrating the robustness of this regime for maintenance of network activity. We quantify the phenomenon as a Markov process and discover that if the network fails to engage this stereotyped regime of motif dominance “cycling”, spiking activity truncates early.
We find, over time in each sustained simulation, low-variance periodic transitions between isomorphic triangle motifs in the recruitment networks. Higher-order patterns, such as triplet or triangle motifs, have been tied to cooperativity and integration.
We then analyzed the intersection between functional edges and synaptic connectivity- i.e. Consequently, in order to achieve mechanistic understanding of sustained asynchronous activity, we summarized activity as functional graphs where edges between units are defined by pairwise spike dependencies.
#Cyclical coherence meaning full#
Synchrony, rate, and criticality do not provide a full explanation of this dichotomy. We find that simulations run on the same topology exhibit sustained asynchronous activity under certain sets of initial membrane voltages but truncated activity under others. Network construction synthesized topological statistics from neocortex with a set of objective functions identifying naturalistic low-rate, asynchronous, and critical activity. Here we algorithmically construct spiking neural network models, each composed of 5000 neurons. However, it remains unclear how neocortex maintains this asynchronous spiking regime. Stable neocortical activity is asynchronous, critical, and low rate, and these features of spiking dynamics contribute to efficient computation and optimal information propagation.
A basic-yet nontrivial-function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time.
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