Gamma Oscillations of Spiking Neural Populations Enhance Signal Discrimination

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Abstract
Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive. Rhythmic brain activity is observed in many neural structures and is an inferred critical component of neural processing. In particular, stimulus induced oscillations in the gamma-frequency band (30–80 Hz) are common in several cortical networks. Many experimental and theoretical studies have established the neural mechanisms by which a population of neurons produce and control gamma-band activity. However, the beneficial role, if any, of gamma activity in neural processing is rarely discussed. It is increasingly apparent that gamma oscillatory power increases with subject attention to a sensory scene. Attention is associated with enhanced performance of discrimination tasks, where relevant stimuli compete with distracters. In this study we explore how gamma-band activity serves to enhance the discrimination of stimuli. We use computational models to show that the gamma rhythmicity in a population of spiking neurons drastically reduces the response variability when a preferred stimulus is present. This drop in response variability enhances stimulus discrimination and increases the overall information throughput in sensory cortex. Our results provide a much-needed link between the dynamics of neural populations and the coding tasks they perform, as well as give insight on why—rather than how—attention mediates gamma activity.