Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys
Abstract
One general principle of sensory information processing is that the brain must optimize efficiency by reducing the number of neurons that process the same information. The sparseness of the sensory representations in a population of neurons reflects the efficiency of the neural code. Here, we employ large-scale two-photon calcium imaging to examine the responses of a large population of neurons within the superficial layers of area V1 with single-cell resolution, while simultaneously presenting a large set of natural visual stimuli, to provide the first direct measure of the population sparseness in awake primates. The results show that only 0.5% of neurons respond strongly to any given natural image — indicating a ten-fold increase in the inferred sparseness over previous measurements. These population activities are nevertheless necessary and sufficient to discriminate visual stimuli with high accuracy, suggesting that the neural code in the primary visual cortex is both super-sparse and highly efficient.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Apr 26, 2018
- Source ID
- 10.7554/elife.33370
Entities
People
- Fang Liu
- Hongfei Jiang
- Ming Li
- Shiming Tang
- Tai Sing Lee
- Yimeng Zhang
- Zhihao Li
Organizations
- Carnegie Mellon University
- Intelligence Advanced Research Projects Activity
- International Data Group
- National Natural Science Foundation of China
- National Science Foundation
- Office of the Director
- Peking University
- Program 973