Proficient brain for optimal performance: the MAP model perspective.

Maurizio Bertollo,Silvia Comani,Edson Filho,Maurizio Schmid,Laura Bortoli,Claudio Robazza,Silvia Conforto,Selenia Di Fronso

doi:10.7717/peerj.2082

Abstract

Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances.Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged.Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the “neural efficiency hypothesis.” We also observed more ERD as related to optimal-controlled performance in conditions of “neural adaptability” and proficient use of cortical resources.Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques.

Highlights

This article is based on the distinction between performance effectiveness and processing efficiency (Eysenck & Calvo, 1992; Eysenck et al, 2007), and concerns the functioning of athletes during different types of optimal and suboptimal performance as conceived inHow to cite this article Bertollo et al (2016), Proficient brain for optimal performance: the multi-action plan (MAP) model perspective
Using the same psychophysiological and methodological perspective, the present study focuses on the neural efficiency hypothesis as a framework to test the relationship between performance effectiveness and the use of resources or effort during elite performance in sport
Given that the individual alpha frequency was similar across participants (9.9–10.1 Hz), we considered the following frequency bands: 4–8 Hz, 8–10 Hz, and 10–12 Hz for analysis

Summary

Introduction

This article is based on the distinction between performance effectiveness and processing efficiency (Eysenck & Calvo, 1992; Eysenck et al, 2007), and concerns the functioning of athletes during different types of optimal and suboptimal performance as conceived inHow to cite this article Bertollo et al (2016), Proficient brain for optimal performance: the MAP model perspective. Applied and theoretical studies observing the interaction between performance effectiveness and processing efficiency have shown that elite athletes can function in different modes when experiencing optimal performance (Bortoli et al, 2012; Bertollo et al, 2013; Carson & Collins, 2016; Furley, Schweizer & Bertrams, 2015; Swann et al, 2016). The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were averaged. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the ‘‘neural efficiency hypothesis.’’ We observed more ERD as related to optimal-controlled performance in conditions of ‘‘neural adaptability’’ and proficient use of cortical resources. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques

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Conclusion