Unknown

Dataset Information

0

Temporal decorrelation by SK channels enables efficient neural coding and perception of natural stimuli.


ABSTRACT: It is commonly assumed that neural systems efficiently process natural sensory input. However, the mechanisms by which such efficient processing is achieved, and the consequences for perception and behaviour remain poorly understood. Here we show that small conductance calcium-activated potassium (SK) channels enable efficient neural processing and perception of natural stimuli. Specifically, these channels allow for the high-pass filtering of sensory input, thereby removing temporal correlations or, equivalently, whitening frequency response power. Varying the degree of adaptation through pharmacological manipulation of SK channels reduced efficiency of coding of natural stimuli, which in turn gave rise to predictable changes in behavioural responses that were no longer matched to natural stimulus statistics. Our results thus demonstrate a novel mechanism by which the nervous system can implement efficient processing and perception of natural sensory input that is likely to be shared across systems and species.

SUBMITTER: Huang CG 

PROVIDER: S-EPMC4837484 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Temporal decorrelation by SK channels enables efficient neural coding and perception of natural stimuli.

Huang Chengjie G CG   Zhang Zhubo D ZD   Chacron Maurice J MJ  

Nature communications 20160418


It is commonly assumed that neural systems efficiently process natural sensory input. However, the mechanisms by which such efficient processing is achieved, and the consequences for perception and behaviour remain poorly understood. Here we show that small conductance calcium-activated potassium (SK) channels enable efficient neural processing and perception of natural stimuli. Specifically, these channels allow for the high-pass filtering of sensory input, thereby removing temporal correlation  ...[more]

Similar Datasets

| S-EPMC6181564 | biostudies-literature
| S-EPMC3725273 | biostudies-literature
| S-EPMC4851552 | biostudies-literature
| S-EPMC7514067 | biostudies-literature
| S-EPMC5112270 | biostudies-literature
| S-EPMC8175693 | biostudies-literature
| S-EPMC5786107 | biostudies-literature
| S-EPMC8766611 | biostudies-literature
| S-EPMC7007219 | biostudies-literature
| S-EPMC4052983 | biostudies-other