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Is cortical connectivity optimized for storing information?

Nature Neuroscience volume 19, pages 749–755 (2016)Cite this article

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Abstract

Cortical networks are thought to be shaped by experience-dependent synaptic plasticity. Theoretical studies have shown that synaptic plasticity allows a network to store a memory of patterns of activity such that they become attractors of the dynamics of the network. Here we study the properties of the excitatory synaptic connectivity in a network that maximizes the number of stored patterns of activity in a robust fashion. We show that the resulting synaptic connectivity matrix has the following properties: it is sparse, with a large fraction of zero synaptic weights ('potential' synapses); bidirectionally coupled pairs of neurons are over-represented in comparison to a random network; and bidirectionally connected pairs have stronger synapses on average than unidirectionally connected pairs. All these features reproduce quantitatively available data on connectivity in cortex. This suggests synaptic connectivity in cortex is optimized to store a large number of attractor states in a robust fashion.

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Figure 1: Model and space of synaptic weights.
Figure 2: Distribution of synaptic weights of an optimal network.
Figure 3: Joint distribution of synaptic weights connecting a pair of neurons.
Figure 4: Distributions of degrees in optimal network (N = 800, f = 0.5, for two values of ρ, ρ = 0 (black) and ρ = 4 (red).
Figure 5: Higher order motifs: probabilities of observing k connections in n-neuron subnetworks, as a function of k, for different values of n (3 ≤ n ≤ 8; N = 800, f = 0.5, ρ = 4).
Figure 6: Effect of inhibition on statistics of connectivity.
Figure 7: Reciprocal connection probability as a function of connection probability: Fixed-point attractors versus sequences of activity.

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Acknowledgements

I warmly thank J. Sjöström for providing his data, and Y. Amit, C. Baldassi, B. Barbour, V. Hakim, D. Marti, G. Mongillo, S. Ostojic, A. Roxin, J. Sjöström and R. Zecchina for discussions and/or comments on previous versions of the manuscript.

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  1. Department of Statistics, The University of Chicago, Chicago, Illinois, USA

    Nicolas Brunel

  2. Department of Neurobiology, The University of Chicago, Chicago, Illinois, USA

    Nicolas Brunel

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Correspondence to Nicolas Brunel.

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Brunel, N. Is cortical connectivity optimized for storing information?. Nat Neurosci 19, 749–755 (2016). https://doi.org/10.1038/nn.4286

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