Don’t look, don’t think, just do it! Toward an understanding of alpha gating in a discrete aiming task

Abstract

Prior to and during movement, oscillatory alpha activity gates cognitive resources toward motor areas of the cortex by inhibiting neuronal excitability in nonmotor areas. The present study examined the effect of manipulating target variability on this alpha gating phenomenon. Using a baseline‐test‐retention design, we measured EEG alpha power, performance accuracy, and task difficulty in 32 recreational golfers as they putted golf balls (20 per target) to one central target (baseline, retention) and four targets of different directions and extents (manipulation). For participants in the random group (n = 16), target location varied with each repetition in a random fashion, whereas for participants in the blocked group (n = 16), it was kept constant within blocks. Regional analyses revealed a focal pattern of lower central alpha and higher occipital and temporal alpha. This topography was specific to preparation for movement and was associated with performance: smallest performance errors were preceded by decreased central combined with increased occipital alpha. The random group performed worse than the blocked group and found the task more difficult. Importantly, left temporal alpha prior to movement onset was lower for the random group than the blocked group. No group differences were found at baseline or retention. Our study proved that alpha gating can be altered by manipulating intertrial variability and thereby demonstrated the utility of the alpha gating model. Our findings underscore the importance of inhibiting occipital and left temporal areas when performing movements and provide further evidence that alpha gating reflects neural efficiency during motor tasks.

Always Pay Attention to Which Model of Motor Learning You Are Using

“…Supporting evidence for both CI phenomena is provided from fMRI studies also limited to movements with sDGF and a dominant visual component [ 180 ] (for a summary, see [ 180 ]). Similar features are found in positive findings on movements with lDGF, in all of which a dominant visual component was involved, such as in badminton [ 181 ] (target focusing), golf putting [ 182 ] (visually estimating distance), or shooting [ 183 ] (target focusing).…”

Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector Machine

“…Having profiles in mind supports the disposition for comparison, which drags mental resources and increases the probability of frustration ( Fillauer et al, 2020 ). As a consequence, this could suggest the need to move toward an alternative approach that is not oriented on set targets as in the closed-loop approach to learning ( Adams, 1987 ) but instead fosters constant changes that support approaches originating from Far Eastern philosophy ( Purser et al, 2016 ; Gallicchio and Ring, 2019 ) and which help one to be in the moment in order to achieve a brain state that is optimal for performing and learning ( Henz and Schöllhorn, 2018 ). Being in the moment can be associated with the term situatedness as it is understood in pragmatism under contextuality ( Dewey et al, 1982 ) or in phenomenology under situativity ( Heidegger, 1927 ; Merleau-Ponty, 1945 ).…”

Visual attention, EEG alpha power and T7-Fz connectivity are implicated in prosthetic hand control and can be optimized through gaze training

“…To detect an effect size of ηp2 = . 21 with an alpha of .05, a sample size of at least 18 was required to yield 80% power. Additional participants helped safeguard against possible data loss.…”

“…At this stage, if epochs were deemed too noisy they were removed from further analysis. Although ICA was used for artefact rejection purposes, subsequent analyses were conducted on EEG channel data, as the most relevant literature within the psychomotor domain has tested the alpha-gating phenomenon via the mean regional activation occurring across selected EEG channels [19,21,31]. The spatial information of the processed epochs was then enhanced by surface Laplacian estimation that acts as a spatial filter of EEG potential distribution to reduce head volume conductor effects and eliminate electrode reference influence [32].…”

“…Using this gating model, research has shown that enhanced performance in motor tasks can be characterised by more efficient topographical alpha power distributions. For example, Gallicchio and colleagues have shown that lower central alpha power and higher temporal alpha power preceded improved performance in a biathlon shooting task [19] and were evident following a training period in golf-putting [20,21]. Indeed, higher alpha power over the left-temporal region has been generally associated with improvements in motor learning and performance [22,23], as conscious, verbal-analytical processes diminish as a function of automaticity and expertise [14,[24][25][26][27].…”