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Front. Comput. Neurosci. | doi: 10.3389/fncom.2018.00016

Dynamic Information Encoding with Dynamical Synapses in Neural Adaptation

 Luozheng Li1,  Yuanyuan Mi2, Wenhao Zhang3,  Dahui Wang1, 4* and  Si Wu1*
  • 1State Key Laboratory of Cognitive Neuroscience & Learning, Beijing Normal University, China
  • 2Brain Science Center,, Institute of Basic Medical Sciences (CAMS), China
  • 3Center for the Neural Basis of Cognition and Computer Science Department,, Carnegie Mellon University, United States
  • 4School of System Science, Beijing Normal University, China

Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, that is, at the early stage of the adaptation, the stimulus information is encoded mainly by the strong independent firings of neurons; and as time goes on, the encoding of the stimulus information is shifted to the weak but synchronized firings of neurons. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural encoding. We hope this study gives us insight into understanding how the brain processes information efficiently via adaptation.

Keywords: adaptation, Dynamical coding, short-term plasticity, dynamical synapses, balanced inputs

Received: 20 Oct 2017; Accepted: 05 Mar 2018.

Edited by:

Paul Miller, Brandeis University, United States

Reviewed by:

Gianluigi Mongillo, Université Paris Descartes, France
Zachary P. Kilpatrick, University of Houston, United States  

Copyright: © 2018 Li, Mi, Zhang, Wang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Prof. Dahui Wang, Beijing Normal University, State Key Laboratory of Cognitive Neuroscience & Learning, Beijing, 100875, China,
Prof. Si Wu, Beijing Normal University, State Key Laboratory of Cognitive Neuroscience & Learning, Beijing, 100875, China,