Different neural network for exogenous temporal expectations under sub-second and supra-second in fMRI

Zhihan Xu, Qiong Wu, Yujie Li, Yuta Kataoka, Jinglong Wu, Chunlin Li, Seiichiro Ohno, Susumu Kanazawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Timing is required for both estimating the duration of a presently unfolding event, and forecasting when a future event will occur. When participants used a dynamic visual spatio-temporal trajectory stimulus to predict the final position, exogenous temporal expectations are engaged. However, it is still not clear whether different neural networks are used to measure sub-second and supra-second temporal durations. Here, we used fMRI to find out the differences between brain activity which measure 600ms and 1800ms in an exogenous temporal expectation task. We observe bilateral anterior cingulate cortex (ACC) show significantly activated during sub-second, bilateral MT+ [suggested to contain both middle temporal (MT) and medial superior temporal (MST)], right superior parietal lobule (SPL), and left inferior parietal cortex (IPC) are more active in the 1800ms condition. Overall, this research shows that maybe different components are used for sub-second and supra-second in exogenous temporal expectation.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
PublisherIEEE Computer Society
Pages1734-1739
Number of pages6
ISBN (Print)9781479939787
DOIs
Publication statusPublished - 2014
Event11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014 - Tianjin, China
Duration: Aug 3 2014Aug 6 2014

Other

Other11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
CountryChina
CityTianjin
Period8/3/148/6/14

Fingerprint

Brain
Trajectories
Neural networks
Magnetic Resonance Imaging

Keywords

  • exogenous temporal expectation
  • fMRI
  • Implicit timing
  • Sub-second
  • Supra-second

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering

Cite this

Xu, Z., Wu, Q., Li, Y., Kataoka, Y., Wu, J., Li, C., ... Kanazawa, S. (2014). Different neural network for exogenous temporal expectations under sub-second and supra-second in fMRI. In 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014 (pp. 1734-1739). [6885962] IEEE Computer Society. https://doi.org/10.1109/ICMA.2014.6885962

Different neural network for exogenous temporal expectations under sub-second and supra-second in fMRI. / Xu, Zhihan; Wu, Qiong; Li, Yujie; Kataoka, Yuta; Wu, Jinglong; Li, Chunlin; Ohno, Seiichiro; Kanazawa, Susumu.

2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014. IEEE Computer Society, 2014. p. 1734-1739 6885962.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Xu, Z, Wu, Q, Li, Y, Kataoka, Y, Wu, J, Li, C, Ohno, S & Kanazawa, S 2014, Different neural network for exogenous temporal expectations under sub-second and supra-second in fMRI. in 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014., 6885962, IEEE Computer Society, pp. 1734-1739, 11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014, Tianjin, China, 8/3/14. https://doi.org/10.1109/ICMA.2014.6885962
Xu Z, Wu Q, Li Y, Kataoka Y, Wu J, Li C et al. Different neural network for exogenous temporal expectations under sub-second and supra-second in fMRI. In 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014. IEEE Computer Society. 2014. p. 1734-1739. 6885962 https://doi.org/10.1109/ICMA.2014.6885962
Xu, Zhihan ; Wu, Qiong ; Li, Yujie ; Kataoka, Yuta ; Wu, Jinglong ; Li, Chunlin ; Ohno, Seiichiro ; Kanazawa, Susumu. / Different neural network for exogenous temporal expectations under sub-second and supra-second in fMRI. 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014. IEEE Computer Society, 2014. pp. 1734-1739
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