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Averted gaze shift events comprised 2 consecutive 500-ms frames showing leftward gaze followed by rightward gaze or vice versa; this produced a strong illusion of a dynamic gaze shift (Fig. 1 A).
Gaze shift events comprised 2 consecutive 500-ms frames showing leftward gaze followed by rightward gaze or vice versa; this produced a strong illusion of a dynamic gaze shift.
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At 6 10 months of age, we recorded infants' event-related potentials (ERPs) using a 128-channel hydrocel infant net, in response to dynamic gaze shifts toward versus away from the infant.
A novel imaging system based on monocentric multiscale design and foveated imaging is proposed to realize wide field of view (FOV) and high resolution dynamic gaze of the moving target.
To realize large field of view (FOV) and high-resolution dynamic gaze of the moving target, this paper proposes the monocentric multiscale foveated (MMF) imaging system based on monocentric multiscale design and foveated imaging.
This finding suggests that ERP responses to dynamic gaze shifts may help characterize distinct developmental profiles leading to autism.
In the present study, a significant risk group × condition interaction was observed for the P400 response in response to dynamic gaze shifts toward versus away from the infant.
Notably, in the dynamic gaze condition the control group, but not the group of infants at risk, showed a significant difference in response to gaze toward, compared to away from, the infant.
However, these risk-group effects were not restricted to dynamic gaze contrasts but appear to extend to other face processing mechanisms, i.e., static direct vs. averted gaze and face vs. noise.
Although overt behavioral signs of autism are rarely observable in the first year, response to dynamic gaze shifts during the first year of life distinguished the group of infants who later developed autism.
This pattern is consistent with the view that whereas sensitivity to static gaze information emerges early in development, dynamic gaze shifts are likely to engage multiple bottom-up and top-down social brain networks, including those concerned with prediction of future events [ 28].
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