Abstract
Stochastic resonance is a phenomenon in which noise enhances the response of a system to an input signal. The brain is an example of a system that has to detect and transmit signals in a noisy environment, suggesting that it is a good candidate to take advantage of stochastic resonance. In this work, we aim to identify the optimal levels of noise that promote signal transmission through a simple network model of the human brain. Specifically, using a dynamic model implemented on an anatomical brain network (connectome), we investigate the similarity between an input signal and a signal that has traveled across the network while the system is subject to different noise levels. We find that non-zero levels of noise enhance the similarity between the input signal and the signal that has traveled through the system. The optimal noise level is not unique; rather, there is a set of parameter values at which the information is transmitted with greater precision, this set corresponds to the parameter values that place the system in a critical regime. The multiplicity of critical points in our model allows it to adapt to different noise situations and remain at criticality.
Highlights
Random noise has been traditionally considered as an obstacle in the transmission of information, contaminating accurate communication and limiting the achievable information rate[1,2]
In order to gain more insight about the identity of these deaf nodes and what causes these nodes to be deaf to the input signal when the system is critical, we examined the average similarity of each output node across all input nodes and the average similarity of each input node across all outputs
The main goal of this work was to determine whether noise can enhance the transfer of information within a simple dynamic model of the brain, and if so, to determine whether this noise corresponds to the value that tunes the system to a critical state
Summary
Random noise has been traditionally considered as an obstacle in the transmission of information, contaminating accurate communication and limiting the achievable information rate[1,2]. Stimulus intensities that allows network responses to be distinguished)[31], mutual information and information capacity appear to be maximized at critical points[32,33] It is not clear, whether the levels of noise that increase the transmission of information through the brain are related to criticality. Whether the levels of noise that increase the transmission of information through the brain are related to criticality This issue is important because the brain, even when noise sources are present, must be capable of integrating information across multiple sensory modalities and brain systems, in order to generate adaptive neural and behavioral responses[2,17]. In this work we determine quantitatively the amount of noise required for the best transmission of signals through the structural network of the brain’s connectome, and its relationship with the hypothesis of the brain operating near criticality[17,18,20,24,25,26,32]
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