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  • Title: ➤  Neural Computing Mechanism Of Badminton Decision-making Based On Drift-diffusion Model
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Experiment 1: The Impact of Action Information on the Accumulation Speed and Threshold of Badminton Decision-Making: Based on Behavioral Models Purpose: 1. To construct a drift diffusion model to clarify the differences in the speed of evidence accumulation and thresholds between experts and novices. 2. To determine whether the greatest difference in the processing of action information occurs 50ms before the stroke between experts and novices. Method: A mixed design with two factors: 2 (Sports Experience: Expert vs. Novice) * 3 (Information Quantity: 950ms vs. 1000ms vs. 1050ms). Experiment 2: The Influence of Sports Experience on the Accumulation Speed and Threshold of Badminton Decision-Making 1. To clarify indicators related to the speed of information accumulation and thresholds in the decision-making process. 2. To integrate electroencephalogram (EEG) indicators into a neural computational model of action information processing. Method: A single-factor between-subjects design: 2 (Sports Experience: Expert vs. Novice). Neural modeling. Experiment 3: The Impact of Prior Information Consistency on Badminton Decision-Making Purpose: 1. To clarify how static situational information (prior information) facilitates decision-making by accelerating the speed of evidence accumulation and reducing the decision-making threshold. Method: A mixed design with two factors: 2 (Sports Experience: Expert vs. Novice) * 2 (Consistency: Consistent vs. Inconsistent vs. Neutral). Experiment 4: The Influence of Prior Information on Badminton Decision-Making: The Moderating Role of Time Pressure Purpose: 1. To clarify the moderating role of dynamic situational information (time pressure) in the influence of prior information on badminton decision-making. Method: A two-factor within-subjects design: 2 (Consistency: Consistent vs. Inconsistent) * 2 (Time Pressure: Long Response Window vs. Short Response Window).

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