Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Procedural motor learning includes sequence learning and random learning. Neuroimaging studies have shown that the dorsolateral prefrontal cortex (DLPFC) and primary motor cortex (M1) play significant roles in procedural motor learning; however, the connectivity between the DLPFC and M1 and its relationship with different procedural motor learning are still unclear. In this study, the serial response time task (SRTT) and transcranial magnetic stimulation (TMS) were used to explore the differences in left DLPFC-M1 connectivity between the different types of procedural motor learning. In experiment 1, dual-site paired-pulse TMS was used to detect the optimal interval from the DLPFC to the M1. In experiment 2, the participants were divided into two groups that underwent sequence learning or random learning. Behavioral data, motor evoked potentials from the M1 and electrophysiological data of DLPFC-M1 connectivity were assessed before and after learning. The behavioral results showed that the learning effect of the sequence learning group was better. The electrophysiological results showed that motor evoked potentials from the M1 were the same before and after learning in both groups. At the optimal interval and appropriate stimulation intensity, the DLPFC-M1 connectivity in the sequence learning group was changed, and it was related to learning performance; however that in the random learning group was not significantly changed. The results suggest that enhanced connectivity between the DLPFC and M1 may be an important explanation for the better performance in sequence learning. The results provide robust electrophysiological evidence for the role of DLPFC in motor learning.
Subjects: Psychology >> Statistics in Psychology submitted time 2020-10-17
Abstract： P-value is the most widely used statistical index for inference in science. Unfortunately, researchers in psychological science may not be able to interpret p-value correctly, resulting in possible mistakes in statistical inference. Our specific goal was to estimate how nonsignificant results were interpreted in the empirical studies published in Chinese Journals. Frist, We randomly selected 500 empirical research papers published in 2017 and 2018 in five Chinese prominent journals (Acta Psychological Sinica, Psychological Science, Chinese Journal of Clinical Psychology, Psychological Development and Education, Psychological and Behavioral Studies). Secondly, we screened the abstracts of the selected articles and judged whether they contained negative statements. Thirdly, we categorized each negative statement into 4 categories (Correct-frequentist, Incorrect-frequentist: whole population, Incorrect-frequentist: current sample, Difficult to judge). Finally, we calculated Bayes factors based on the t values and sample size associated with the nonsignificant results to investigate whether empirical data provide enough evidence in favor of null hypothesis. Our survey revealed that: (1) 36% of these abstracts (n = 180) mentioned nonsignificant results; (2) there were 236 negative statements in the article that referred to nonsignificant results in abstracts, and 41% negative statements misinterpreted nonsignificant results; (3) 5.1% (n = 2) nonsignificant results can provide strong evidence in favor of null hypothesis (BF01 > 10). The results suggest that Chinese researchers need to enhance their understanding of nonsignificant results and use more appropriate statistical methods to extract information from non-significant results.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Physiological Psychology submitted time 2019-12-24
Abstract： Procedural motor learning includes sequence learning and random learning. Neuroimaging studies have shown that the dorsolateral prefrontal cortex (DLPFC) and primary motor cortex (M1) play significant roles in procedural motor learning; however, the connectivity between the DLPFC and M1 and its relationship with different procedural motor learning are still unclear. In this study, the serial response time task (SRTT) and transcranial magnetic stimulation (TMS) were used to explore the differences in left DLPFC-M1 connectivity between the different types of procedural motor learning. In experiment 1, dual-site paired-pulse TMS was used to detect the optimal interval from the DLPFC to the M1. In experiment 2, the participants were divided into two groups that underwent sequence learning or random learning. Behavioral data, motor evoked potentials from the M1 and electrophysiological data of DLPFC-M1 connectivity were assessed before and after learning. The behavioral results showed that the learning effect of the sequence learning group was better. The electrophysiological results showed that motor evoked potentials from the M1 were the same before and after learning in both groups. At the optimal interval and appropriate stimulation intensity, the DLPFC-M1 connectivity in the sequence learning group was changed, and it was related to learning performance; however that in the random learning group was not significantly changed. The results suggest that enhanced connectivity between the DLPFC and M1 may be an important explanation for the better performance in sequence learning. The results provide robust electrophysiological evidence for the role of DLPFC in motor learning. "
Peer Review Status:Awaiting Review
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