Frequency adaptation in controlled stochastic resonance utilizing delayed feedback method: two-pole approximation for response function

Resonance Effects in Variable Practice for Handball, Basketball, and Volleyball Skills: A Study on Contextual Interference and Differential Learning

Effective sports training should be attuned to the athlete's specific conditionings and characteristics. In motor learning research, two often neglected factors that influence this resonance are the learner's athletic background and the structural diversity of exercises (e.g., relative similarity). In the setting of real-word training with higher external validity, this study examines the effects of three learning approaches (i.e., contextual interference (CI), differential learning (DL), and free-play control condition (CO)) on the parallel learning of handball (HB), volleyball (VB), and basketball (BB) skills, considering participants' prior sport backgrounds. Forty-five males (15 HB, 15 VB, and 15 BB players) with a mean age of 22 ± 1.4 years and at least 6 years of experience in the mastered discipline voluntarily participated in this study. A pre-post-retention test design including a 6-week-intervention program was employed. During the intervention period, participants engaged in three training sessions a week, with each one lasting approximately 80 min. Each of the three test sessions involved the execution of ten attempts of BB free-throw shooting, HB three-step goal throwing, and VB underarm passing following a blocked order. In terms of short-term (pre-post) gain, only the DL group significantly improved their performance in both non-mastered disciplines (p = 0.03, ES = 1.58 for the BB free-throw and p = 0.05, ES = 0.9 for the HB shooting tests), with a trend (ES = 0.53) towards an improvement in the performance of the mastered VB underarm-pass skill. In terms of relatively permanent gains, the CI group significantly improved their performances from pre- to retention test only in the non-mastered BB free-throw skill (p = 0.018, ES = 1.17). In contrast, the DL group significantly improved their performance at retention compared to the pre-test in both non-mastered BB (p = 0.004, ES = 1.65) and HB (p = 0.003, ES = 2.15) skills, with a trend (ES = 0.4) towards improvement in the mastered VB test. In both the short-term and relatively long-term, higher composite score gains were observed in DL compared to CI (p = 0.006, ES = 1.11 and 0.049, ES = 1.01) and CO (p = 0.001, ES = 1.73 and <0.0001, ES = 2.67). In conclusion, the present findings provide additional support for the potential advantages of the DL model over those of CI. These findings can serve as the basis for tailored training and intervention strategies and provide a new perspective for addressing various issues related to individual and situational learning.

Stochastic thermodynamic limit on E. coli adaptation by information geometric approach

Biological systems process information under noisy environment. Sensory adaptation model of E. coli is suitable for investigation because of its simplicity. To understand the adaptation processing quantitatively, stochastic thermodynamic approach has been attempted. Information processing can be assumed as state transition of a system that consists of signal transduction molecules using thermodynamic approach, and efficiency can be measured as thermodynamic cost. Recently, using information geometry and stochastic thermodynamics, a relationship between speed of the transition and the thermodynamic cost has been investigated for a chemical reaction model. Here, we introduce this approach to sensory adaptation model of E. coli, and examined a relationship between adaptation speed and the thermodynamic cost, and efficiency of the adaptation speed. For increasing external noise level in stimulation, the efficiency decreased, but the efficiency was highly robust to external stimulation strength. Moreover, we demonstrated that there is the best noise to achieve the adaptation in the aspect of thermodynamic efficiency. Our quantification method provides a framework to understand the adaptation speed and the thermodynamic cost for various biological systems.