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Proc Natl Acad Sci U S A. 2019 May 14;116(20):10097-10102. doi: 10.1073/pnas.1812171116. Epub 2019 Apr 26.

Differentially synchronized spiking enables multiplexed neural coding.

Author information

1
Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada.
2
Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada.
3
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada.
4
Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; steve.prescott@sickkids.ca.

Abstract

Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.

KEYWORDS:

multiplexing; neural coding; rate code; synchrony; temporal code

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