Abstract
Recent experiments demonstrate substantial volatility of excitatory connectivity in the absence of any learning. This challenges the hypothesis that stable synaptic connections are necessary for long-term maintenance of acquired information. Here we measure ongoing synaptic volatility and use theoretical modeling to study its consequences on cortical dynamics. We show that in the balanced cortex, patterns of neural activity are primarily determined by inhibitory connectivity, despite the fact that most synapses and neurons are excitatory. Similarly, we show that the inhibitory network is more effective in storing memory patterns than the excitatory one. As a result, network activity is robust to ongoing volatility of excitatory synapses, as long as this volatility does not disrupt the balance between excitation and inhibition. We thus hypothesize that inhibitory connectivity, rather than excitatory, controls the maintenance and loss of information over long periods of time in the volatile cortex.
| Original language | American English |
|---|---|
| Pages (from-to) | 1463-1470 |
| Number of pages | 8 |
| Journal | Nature Neuroscience |
| Volume | 21 |
| Issue number | 10 |
| DOIs | |
| State | Published - 1 Oct 2018 |
Bibliographical note
Funding Information:We thank L. Abbott and D. Hansel for their careful reading of our manuscript and their insightful comments. This work was performed in the framework of the the France-Israel Center for Neural Computation and was supported by the Israel Science Foundation (Grant No. 757/16, Y.L.), the DFG (CRC 1080, Y.L. and S.R.), the Gatsby Charitable Foundation (Y.L.), and by ANR (14-NEUC-0001-01 and 13-BSV4-0014-02, G.M.).
Publisher Copyright:
© 2018, The Author(s), under exclusive licence to Springer Nature America, Inc.