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 after long-lasting tasks (Time-on-Task effect), evidenced by increased response time (RT). The ex-Gaussian function properly fits RT data. Mu & sigma represent the Gaussian component while tau describes the exponential component (increase in extreme RT). Mu represents motor/peripheral processes and tau decisional processes. In Young, tau suffers from Time-on-Task.
Aim. To test Time-on-Task effect in Middle-aged and Older.
Method. Twenty-one Young, 17 Middle-aged, and 17 Older performed a 160min Stroop task comprising facilitatory (FA), interfering (I), and neutral (NE) items. The task was divided into four 40min blocks and the ex-Gaussian parameters were fitted in each block for each item types. Six measures (FA_mu, I_mu, NE_mu, FA_tau, I_tau, NE_tau) were analyzed with GLIMMIX repeated measure (p<0.05).
Results. All mu were smaller in Young than in Middle-aged and Older. Moreover, Older had a greater I_mu in Block4 as compared to Block1 and Block2. FA_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 were not impaired in their motor/peripheral processes (mu) with Time-on-task except for the Older on the Interfering items, probably due to their baseline difficulties in inhibition. However, the three groups were disabled in their decisional processes as indexed by increases in their extreme RT (tau), with Middle-aged being the most cognitively fatigued.