Suprathreshold stochastic resonance in a neuronal network model: A possible strategy for sensory coding

The possible mechanism To explain the dynamics of the transduction in sensory neurons is investigated. We consider a parallel array of noisy FitzHugh-Nagumo model neurons, subject to a common input signal. The information transmission of the signal through the array is studied as a function of the internal noise intensity. The threshold of each neuron is set suprathreshold with respect to the input signal. A form of stochastic resonance, termed suprathreshold stochastic resonance (SSR), which has recently been observed in a network of threshold devices [8] is also found to occur in the FHN array. It is demonstrated that significant information gain, over and above that attainable in a single FHN element, can be achieved via the SSR effect. These information gains are still achievable under the assumption that the thresholds are fully adjustable