Noise-assisted traffic of spikes through neuronal junctions

Noise helps cochlear implant listeners to categorize vowels

Theoretical studies demonstrate that controlled addition of noise can enhance the amount of information transmitted by a cochlear implant (CI). The present study is a proof-of-principle for whether stochastic facilitation can improve the ability of CI users to categorize speech sounds. Analogue vowels were presented to CI users through a single electrode with independent noise on multiple electrodes. Noise improved vowel categorization, particularly in terms of an increase in information conveyed by the first and second formant. Noise, however, did not significantly improve vowel recognition: the miscategorizations were just more consistent, giving the potential to improve with experience.

The Impact of Frequency Scale on the Response Sensitivity and Reliability of Cortical Neurons to 1/fβ Input Signals

What type of principle features intrinsic inside of the fluctuated input signals could drive neurons with the maximal excitations is one of the crucial neural coding issues. In this article, we examined both experimentally and theoretically the cortical neuronal responsivity (including firing rate and spike timing reliability) to input signals with different intrinsic correlational statistics (e.g., white-type noise, showed 1/f⁰ power spectrum, pink noise 1/f, and brown noises 1/f²) and different frequency ranges. Our results revealed that the response sensitivity and reliability of cortical neurons is much higher in response to 1/f noise stimuli with long-term correlations than 1/f⁰ with short-term correlations for a broad frequency range, and also higher than 1/f² for all frequency ranges. In addition, we found that neuronal sensitivity diverges to opposite directions for 1/f noise comparing with 1/f⁰ white noise as a function of cutoff frequency of input signal. As the cutoff frequency is progressively increased from 50 to 1,000 Hz, the neuronal responsiveness increased gradually for 1/f noise, while decreased exponentially for white noise. Computational simulations of a general cortical model revealed that, neuronal sensitivity and reliability to input signal statistics was majorly dominated by fast sodium inactivation, potassium activation, and membrane time constants.

Preference of sensory neural coding for 1/f signals

We investigated the influences of different types of temporal correlations in the input signal on the functions and coding properties of neurons in the primary visual cortex (V1). We found that the temporal transfer functions of V1 neurons exhibit higher gain, and the spike responses exhibit higher coding efficiency and information transmission rates, for the 1/f (natural long-term correlation) signals than for 1/f(0) (no correlation) and 1/f(2) (stronger long-term correlation) signals. These results suggest that the intermediate long-term correlation ubiquitous to natural signals may play an important role in shaping and optimizing the machinery of neurons in their adaptation to the natural environment.