Reward information encoded by power of local field potentials in the primate prefrontal cortex and striatum.
- Author:
Yu-Ying CHEN
1
;
Xiao-Chuan PAN
2
;
Ru-Bin WANG
1
;
Masamichi SAKAGAMI
3
Author Information
1. Institute of Cognitive Neurodynamics, East China University of Science and Technology, Shanghai 200237, China.
2. Institute of Cognitive Neurodynamics, East China University of Science and Technology, Shanghai 200237, China. pxc@ecust.edu.cn.
3. Brain Science Institute, Tamagawa University, Tokyo 194-8610, Japan.
- Publication Type:Journal Article
- From:
Acta Physiologica Sinica
2017;69(4):385-396
- CountryChina
- Language:Chinese
-
Abstract:
Prefrontal cortex and striatum are two major areas in the brain. Some research reports suggest that both areas are involved in many advanced cognitive processes, such as learning and memory, reward processing, and behavioral decision. Single-unit recording experiments have found that neurons in the prefrontal cortex and striatum can represent reward information, but it remains elusive whether and how local field potentials (LFPs) in the two areas encode reward information. To investigate these issues, we recorded LFPs simultaneously in the prefrontal cortex and striatum of two monkeys by performing a reward prediction task (a large amount reward vs a small amount reward). Recorded LFP signals were transformed from the time domain to the time and frequency domain using the method of short-time Fourier transform (STFT). We calculated the power in each frequency and time, and examined whether they were different in the two reward conditions. The results showed that power of LFPs in both the prefrontal cortex and striatum distinguished one reward condition from the other one. And the power in small reward trials was greater than that in large reward trials. Furthermore, it was found that the LFPs better encoded reward information in the beta band (14-30 Hz) rather than other frequency bands. Our results suggest that the LFPs in the prefrontal cortex and striatum effectively represent reward information, which would help to further understand functional roles of LFPs in reward processing.
