Common neural network for different functions: an investigation of proactive and reactive inhibition

• ZHANG FAN

  AIST University of Tsukuba

• 岩木 直

  産業技術総合研究所 自動車ヒューマンファクター研究センター

Abstract

Successful behavioral inhibition involves both proactive and reactive inhibition. We created 70 dynamic causal models (DCMs) representing the alternative hypotheses of modulatory effects from proactive and reactive inhibition in the IFG-SMA-STN-M1 network. Bayesian model selection (BMS) showed that causal connectivity from the IFG to the SMA was modulated by both proactive and reactive inhibition. We then compared 13 DCMs representing the alternative hypotheses of proactive modulation, and BMS revealed that the effective connectivity from the caudate to the IFG is modulated only in the proactive inhibition condition but not in the reactive inhibition. Together, our results demonstrate that a longer pathway (DLPFC-caudate-IFG-SMA-STN-M1) playing a modulatory role in proactive inhibitory control, and a shorter pathway (IFG-SMA-STN-M1) involved in reactive inhibition. These results provide causal evidence for the roles of indirect and hyperdirect pathways in mediating proactive and reactive inhibitory control.

Journal

• Transactions of Japanese Society for Medical and Biological Engineering

  Transactions of Japanese Society for Medical and Biological Engineering Annual57 (Abstract), S28_1-S28_1, 2019

  Japanese Society for Medical and Biological Engineering

Details

• CRID: 1390565134812142720
• NII Article ID: 130007776878
• DOI: 10.11239/jsmbe.annual57.s28_1
• ISSN: 18814379
• ISSN: 1347443X
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
• Abstract License Flag: Disallowed