Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks

Brendan Chambers and Jason N MacLean

PLOS Computational Biology, 2016, vol. 12, issue 8, 1-23

Abstract: Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex.Author Summary: Active networks of neurons exhibit beyond-pairwise dynamical features. In this work, we identify a canonical higher-order correlation in network dynamics and trace its emergence to synaptic integration. We find that temporally coordinated firing preferentially occurs at sites of fan-in triangles—a synaptic motif which coordinates presynaptic timing, leading to greater likelihood of postsynaptic spiking. The influence of fan-in clustering leads to the surprising emergence of non-random routing of spiking in random synaptic networks. When synaptic weights are made artificially stronger in simulation, so that cooperative input is less crucial, dynamics are no longer dominated by fan-in triangles but instead more closely reflect the random synaptic network. Thus, the emergence of fan-in clustering in maps of synaptic recruitment is a collective property of individually weak connections in neuronal networks. Because higher-order interactions are necessary to shape the timing of presynaptic inputs, activity does not propagate uniformly through the synaptic network. Like water finding the deepest channels as it flows downhill, spiking activity follows the path of least resistance and is routed through triplet motifs of connectivity. These results argue that clustered fan-in triangles are a canonical network motif and mechanism for spike routing in local neocortical circuitry.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005078

DOI: 10.1371/journal.pcbi.1005078

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