Efficient “Communication through Coherence” Requires Oscillations Structured to Minimize Interference between Signals

The ‘communication through coherence’ (CTC) hypothesis proposes that selective communication among neural networks is achieved by coherence between firing rate oscillation in a sending region and gain modulation in a receiving region. Although this hypothesis has stimulated extensive work, it remains unclear whether the mechanism can in principle allow reliable and selective information transfer. Here we use a simple mathematical model to investigate how accurately coherent gain modulation can filter a population-coded target signal from task-irrelevant distracting inputs. We show that selective communication can indeed be achieved, although the structure of oscillatory activity in the target and distracting networks must satisfy certain previously unrecognized constraints. Firstly, the target input must be differentiated from distractors by the amplitude, phase or frequency of its oscillatory modulation. When distracting inputs oscillate incoherently in the same frequency band as the target, communication accuracy is severely degraded because of varying overlap between the firing rate oscillations of distracting inputs and the gain modulation in the receiving region. Secondly, the oscillatory modulation of the target input must be strong in order to achieve a high signal-to-noise ratio relative to stochastic spiking of individual neurons. Thus, whilst providing a quantitative demonstration of the power of coherent oscillatory gain modulation to flexibly control information flow, our results identify constraints imposed by the need to avoid interference between signals, and reveal a likely organizing principle for the structure of neural oscillations in the brain. Author Summary: Distributed regions of mammalian brains transiently engage in coherent oscillations, often at specific stages of behavioral or cognitive tasks. This activity may play a role in controlling information flow among connected regions, allowing the brain's connectivity structure to be flexibly reconfigured in response to changing task demands. We have used a computational model to investigate the conditions under which oscillations can generate selective communication through a mechanism in which the excitability of neurons in one region is modulated coherently with a firing rate oscillation in another region. Our results demonstrate that this mechanism is able to accurately and selectively control the flow of signals encoded as spatial patterns of firing rate. However, we found that the requirement to avoid interference between different signals imposes previously unrecognised constraints on the structures of oscillatory activity that can efficiently support this mechanism. These constraints may be an organizing principle for the structured oscillatory activity observed in vivo.