How does cognitive fatigue affect Young, Middle-aged, and Older people? A distribution analysis of Time-on-Task effect by fitting the ex-Gaussian parameters to the response time distributions.

Introduction. Young people experiment cognitive fatigue with Time-on-Task, evidenced by increased response time (RT). Since RT data are often positively skewed, the ex-Gaussian function (characterized by parameters mu, sigma, and tau) properly fits RT data. In Young people, tau (representing the extreme RT) suffers from Time-on-Task. Aim. Testing Time-on-Task in Middle-aged and Older people.
Method. Twenty-one Young, 17 Middle-aged, and 17 Older performed a 160-min Stroop task comprising Facilitatory, Interfering, and Neutral items which was divided into four 40-min blocks. Ex-Gaussian parameters were fitted in each block for each item types. Measures (Facilitatory_mu, Interfering_mu, Neutral_mu, Facilitatory_tau, Interfering_tau, Neutral_tau) were analyzed with GLIMMIX repeated models.
Results. All mu were smaller for Young than Middle-aged and Older. Moreover, Older had a greater I_mu in Block4 as compared to Block1 and Block2. Facilitatory_tau: Middle-aged significantly increased between Block2 and Block4. I_tau: Middle-aged significantly increased between both Block1 and Block2 with Block4. NE_tau: Young significantly increased between Block1 and both Block3 and Block4 (p<.01); Middle-aged increased between both Block1 and Block2 with Block4; Older increased between Block1 and Block4.
Discussion. The three groups evidenced increases in their extreme RT (tau) with Time-on-Task. Very interestingly, Middle-aged people seemed the most cognitively fatigued by the task.