Chunking, Conscious Processing, and EEG During Sequence Acquisition and Performance Pressure: A Comprehensive Test of Reinvestment Theory

Abstract

This study was designed to test the theorized link between reinvestment, motor chunks, and conscious processing, to provide a thorough examination of reinvestment theory. The authors measured electroencephalographic power and connectivity alongside self-reported conscious processing and behavioral indices of chunking in a 2 (group) × 5 (block) mixed-model design. A total of 55 individuals acquired a motor sequence (blocks A1, A2, A3, and A4) by relatively explicit (errorful) or implicit (errorless) paradigms. Then they performed in a pressure condition (block T). Results confirmed that chunking characterizes both modes of acquisition. However, explicit acquisition resulted in quicker chunking, reduced conscious processing, and increased cortical efficiency (left-temporal high-alpha power). In support of reinvestment theory, self-reported conscious processing tended to increase under pressure among explicit trainees only. In contrast to reinvestment theory, this had no adverse effect on performance. The results endorse explicit acquisition as an effective mode of training and provide a new neurophysiological explanation of this phenomenon.

All talk? Challenging the use of left-temporal EEG alpha oscillations as valid measures of verbal processing and conscious motor control

“…The absence of change in T7-Fz connectivity for the task-unrelated self-talk condition inadvertently addresses concerns that previous research utilising this measure may be confounded by between and within participant variability in the use of motivational self-talk (Bellomo, Cooke, & Hardy, 2018). Our findings suggest that changes in T7-Fz connectivity reflect processes that are not directly related to verbal processes, be it task-related or task-unrelated.…”

“…For example, we found a significant increase in T7-Fz connectivity from t -2 to t +2 for all conditions, suggesting a greater response to the changing demands of our task across time (i.e., movement preparation versus movement execution) than to the between-condition alterations in self-talk and conscious control. It should therefore be reiterated that phase-based connectivity merely measures the phase lag consistency between signals recorded from two sites, with relations drawn to communication pathways being inferred rather than directly assessed (Bellomo et al, 2018;. As such, it also becomes difficult to interpret our finding that T8-Fz connectivity was significantly higher than T7-Fz connectivity for all conditions across the majority of our task phases.…”

The Effect of Attentional Direction on Sub-Stages of Preparing for Motor Skill Execution Across Practice

“…This type of research would benefit from employing brain imaging techniques, such as functional Magnetic Resonance Imaging (fMRI), magnetoencephalography (MEG), and electroencephalography (EEG) to shed light on brain activity during motor skill learning and performance in dual-task conditions. For example, EEG studies have already shown that the power of neural oscillation in the range of high-alpha in the left temporal region (e.g., Kerick et al., 2004 ) and the co-activation (coherence) between the left temporal region and the frontal midline region at the high-alpha frequency bandwidth (e.g., Deeny et al., 2003 ; Zhu et al., 2011 ) reflect the conscious involvement and attentional demands during motor skill learning and performance ( Bellomo et al., 2018 ; Zhu et al., 2011 ). Because the dual-task methodology manipulates the direction of attention and influences the conscious involvement in motor skill learning and performance ( Beilock & Gray, 2012 ), these measures of brain activity could also be sensitive to dual-task conditions.…”

Verbal Instructions and Motor Learning: How Analogy and Explicit Instructions Influence the Development of Mental Representations and Tennis Serve Performance

“…So far, studies tested the concept of chunking in sequence learning tasks (e.g., Bellomo et al, 2018; for an overview, see Abrahamse et al, 2013) that, however, differ from learning complex motor skills with different types of instruction. Recently, Van Duijn et al (2019a) investigated the effect of different types of instruction on cognitive processes by using electroencephalography (EEG).…”