September 2005
Volume 5, Issue 8
Vision Sciences Society Annual Meeting Abstract  |   September 2005
Predicting manual reaction time to visual motion by temporal integrator model of meg response
Author Affiliations
  • Kaoru Amano
    The University of Tokyo
  • Shin'ya Nishida
    NTT Communication Science Laboratories
  • Yoshio Ohtani
    Kyoto Institute of Technology
  • Naokazu Goda
    National Institute for Physiological Sciences
  • Yoshimichi Ejima
    Kyoto Institute of Technology
  • Tsunehiro Takeda
    The University of Tokyo
Journal of Vision September 2005, Vol.5, 844. doi:
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      Kaoru Amano, Shin'ya Nishida, Yoshio Ohtani, Naokazu Goda, Yoshimichi Ejima, Tsunehiro Takeda; Predicting manual reaction time to visual motion by temporal integrator model of meg response. Journal of Vision 2005;5(8):844. doi:

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      © ARVO (1962-2015); The Authors (2016-present)

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Manual reaction time (RT) is a useful behavioral measure of the latency of visual responses, but its underlying neural processes are relatively unknown. We examined how RTs are related with the time course of simultaneously measured magnetoencephalography (MEG). Transitions of a dynamic random-dot pattern from incoherent motion to coherent motion were used as visual stimuli, which are known to evoke MEG responses mainly at around MT. The results showed that both the RT and the peak latency of evoked MEGs decreased as the motion coherency was increased from 20 to 80%. However, the change in the peak latency was much smaller than that in the RT, as reported by previous EEG and MEG studies. We then compared the RT with the predictions of the two models the level detection model (Grice, 1968) and the temporal integrator model (Cook and Maunsell, 2002). The two models assume that a stimulus is detected when the MEG amplitude or its temporally integrated value exceeds a threshold, respectively. The time required for motor preparation and execution was assumed to be constant. The threshold of each model was determined individually to best account for the variation in RT. The analysis showed that the integrator model can, but the level detection model cannot, fully account for the variation of RT depending on the stimulus change. Additionally, the validity of the integrator model was supported by the result that the fluctuation of MEGs across trials could account for the variations in perception (correct detection / miss) and in RT for identical stimuli. Namely, for 20% coherence, the integrated MEGs exceeded the threshold for correct detection trials, but not for miss trials. For the higher coherence levels, the integrated MEGs exceeded the threshold earlier for the shorter RT trials than for the longer RT trials. These results suggest that temporal integration of the sensory signal at the higher visual areas, such as MT, may be correlated with the detection of visual motion.

Amano, K. Nishida, S. Ohtani, Y. Goda, N. Ejima, Y. Takeda, T. (2005). Predicting manual reaction time to visual motion by temporal integrator model of meg response [Abstract]. Journal of Vision, 5(8):844, 844a,, doi:10.1167/5.8.844. [CrossRef]

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