Relationship between reward-related brain activity and opportunities to sit

Reinforcement learning in motor skill acquisition: using the reward positivity to understand the mechanisms underlying short- and long-term behavior adaptation

Introduction

According to reinforcement learning, humans adjust their behavior based on the difference between actual and anticipated outcomes (i.e., prediction error) with the main goal of maximizing rewards through their actions. Despite offering a strong theoretical framework to understand how we acquire motor skills, very few studies have investigated reinforcement learning predictions and its underlying mechanisms in motor skill acquisition.

Methods

In the present study, we explored a 134-person dataset consisting of learners' feedback-evoked brain activity (reward positivity; RewP) and motor accuracy during the practice phase and delayed retention test to investigate whether these variables interacted according to reinforcement learning predictions.

Results

Results showed a non-linear relationship between RewP and trial accuracy, which was moderated by the learners' performance level. Specifically, high-performing learners were more sensitive to violations in reward expectations compared to low-performing learners, likely because they developed a stronger representation of the skill and were able to rely on more stable outcome predictions. Furthermore, contrary to our prediction, the average RewP during acquisition did not predict performance on the delayed retention test.

Discussion

Together, these findings support the use of reinforcement learning models to understand short-term behavior adaptation and highlight the complexity of the motor skill consolidation process, which would benefit from a multi-mechanistic approach to further our understanding of this phenomenon.

Electroencephalogram of Normotensive Individuals During Sitting and Standing Blood Pressure Measurement Positions

Background Investigating changes in brain electroencephalogram activity during blood pressure measurement in sitting and standing positions is clinically significant for understanding the neural correlates of postural changes, which may affect cerebral perfusion and autonomic regulation. Shifts in blood pressure can influence visual cortical activity, potentially altering cognitive and sensory processing. This research holds clinical relevance in evaluating disorders like orthostatic hypotension and syncope, where postural changes compromise cerebral blood flow. Furthermore, it can help refine diagnostic protocols and management strategies for neurovascular and autonomic dysfunction. The study also highlighted the possibility of using polygraphs to identify and manage discrepancies in blood pressure measurement caused by posture-induced changes in brain activities for accurate diagnosis. Methodology The electroencephalogram of healthy normotensive female individuals undergoing blood pressure measurements at sitting and standing positions was investigated. Ten healthy young adult females who satisfy the inclusion criteria were selected. Electroencephalographic (EEG) waves were recorded with the aid of Powerlab 26T (ADInstruments Pty Ltd., Bella Vista, Australia). Blood pressure and pulse rate measurements were conducted using a sphygmomanometer and stopwatch. Results During sitting and standing blood pressure positions, diastolic blood pressure and pulse rate were higher when compared to baseline values but the standing blood pressure position showed a higher pulse rate than the sitting blood pressure position. Although alpha wave frequency was higher during both sitting and standing blood pressure measurement positions, the standing blood pressure position caused lower alpha wave frequency when compared with the sitting blood pressure measurement position. While a strong negative correlation was found between alpha wave frequency and pulse rate, beta wave frequency positively correlated with pulse rate during sitting blood pressure measurement position. Furthermore, during standing blood pressure measurement position, the alpha wave did not correlate with pulse rate nor was there a correlation between beta wave frequency and pulse rate. In conclusion, the present study indicated that both sitting and standing blood pressure measurement positions caused a decrease in alpha wave frequency when compared with baseline, but the standing blood pressure measurement position elicited a lower alpha wave frequency when compared with the sitting blood pressure measurement position.

Development and validation of the physical effort scale (PES)

OBJECTIVES

Previous literature has primarily viewed physical effort as an aversive experience. However, recent research suggests that effort can also be valued positively. These differences in approach and avoidance tendencies toward physical effort may play a key role in the self-regulation of physical activity behaviors. The aim of this study was to develop a scale that measures these tendencies and contributes to a better understanding of physical effort and how it affects behavior.

METHODS

The Physical Effort Scale (PES) was developed in Study 1 based on expert evaluations (n = 9) and cognitive interviews (n = 10). In Study 2 (n = 680, 69% female), content validity and dimensional structure were examined using principal component analysis and confirmatory factor analysis. Item reduction was conducted using item response theory. Preliminary construct validity was explored using regression. Study 3 (n = 297, 71% female) was used to validate dimensional structure, internal consistency, and construct validity, and to assess test-retest reliability.

RESULTS

In Study 1, 44 items were rated for content validity, of which 18 were selected and refined based on cognitive interviews. Analyses from Study 2 allowed reducing the scale to 8 items with a two-dimension structure: tendency to approach (n = 4) and to avoid physical effort (n = 4). The two subscales showed high internal consistency (α = 0.897 for the approach dimension and 0.913 for the avoidance dimension) and explained usual levels of physical activity, providing preliminary evidence of construct validity. Study 3 confirmed the two-dimension structure with high internal consistency (α = 0.907 and 0.916 for the approach and avoidance dimension, respectively) and revealed acceptable test-retest reliability (intraclass correlation >0.66). Patterns of associations with other constructs showed expected relationships, confirming the concurrent, convergent, and discriminant validity of the scale.

CONCLUSIONS

The PES is a valid and reliable measure of individual differences in the valuation of physical effort. This scale can assess the propensity to engage in physically demanding tasks in non-clinical populations. The PES and its manual are available in the Supplementary Material.