We address the complex relationship between the stability, variability, and adaptability of psychological systems by decomposing the global variance of serial performance into two independent parts: the local variance (LV) and the serial correlation structure. For two time series with equal LV, the presence of persistent long-range correlations (or 1/f[superscript][beta] noise) increases the global variance. We hypothesized that a coadjustment between these two determinants of variability constitutes a resource for adaptive systems whose appropriate functioning under critical conditions requires the outcome variance to be limited. To test this hypothesis, we looked at the bimanual coordination dynamics at comfortable (stable) and critical (close to phase transition) frequencies. Results showed that a negative correlation appeared gradually as the theoretical stability of coordination modes decreased and reached significance only in the critical condition. We propose that the emergence of a mutual adjustment between LV and serial correlations might be an indicator of effective adaptation to stabilize behavior. (Contains 2 tables and 5 figures.)