Subjects: Psychology >> Other Disciplines of Psychology Subjects: Biology >> Neurobiology submitted time 2023-12-19
Abstract： Homotopic positions are defined as the two areas with opposite but equal horizonal coordinates in the standard symmetric brain space. Characterizing similarity between two homotopic areas, brain homotopy represents a typical feature of the brain’s two hemispheres for both structure and function. Functional homotopy provides important perspectives for understanding neural correlates of cognition and behavior. Despite the decisive role of spatial geometric constraints and homophilic attachment on the human connectome, traditional practices in mapping functional homotopy only considered the temporal correlations of functional timeseries between homotopic areas, but ignored the homophily factors in generative connectivity models. Here, we proposed a novel method for functional homotopy analysis, namely Homotopic Functional Affinity (HFA). This method quantifies the homotopic affinity as the Cosine distance of the full-brain functional connectivity profiles or fingerprints between the homotopic areas. HFA captures both geometric constraints (homotopic location) and homophily (affinity) simultaneously. By leveraging the resting-state functional magnetic resonance imaging data from the Human Connectome Project (HCP) and the Chinese HCP (CHCP), we mapped the 700ms-2mm high spatiotemporal resolution HFA and evaluated its test-retest reliability with linear mixed models, exhibiting generally fair-to-substantial reliable measurements of individual differences in HFA. The lowest HFA observed in the temporo-parietal junction (TPJ) inspired to perform an edge-detection algorithm on its surface render and derived three clearly differentiable and adjacent TPJ subregions: the anterior TPJ (TPJa), the central TPJ (TPJc), and the posterior TPJ (TPJp). We further validated the HFA for the three TPJ regions through a set of comprehensive analyses, including the delineation of their functional connectivity fingerprints, the meta-analysis of their cognitive functions, and the their task-activation correlation. Finally, we linked the cortical HFA map to those multimodal brain maps of gene expression, evolution, myelination, functional hierarchy, and cognitive association. The systematic subregion analysis revealed the complex hemispheric specialization of TPJ in attention, social cognition, and language functions. In general, functional specialization of the TPJ areas was stronger in the left hemisphere. The findings from the task activation correlation were highly consistent with those of the meta-analysis. Notably, there were significant differences in social cognition relevant to the three TPJ areas between HCP and CHCP datasets. Furthermore, the correlation analysis of multimodal brain maps illustrated a close relationship between the HFA map and multimodal brain maps. The consistency of maps derived in distinct analyses demonstrated the feasibility of HFA in further understanding psychological and behavioral mechanisms on neural lateralization from the perspective of hemispheric functional integration and specialization. We believe that HFA will create a new arena for brain mapping in population neuroscience studies.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Developmental Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Recent advances on functional magnetic resonance imaging (fMRI) demonstrated sex differences in the brain function. However, no standard on fMRI signal’s frequency division limited further biologically plausible explanation of these observations. In this work, we proposed a fast-multi-dimensional ensemble empirical mode decomposition to extract their multi-scale features of fMRI signal. We found that: this method can perform adaptive frequency allocation for the resting-state fMRI signal, whereby the built multi-scale function network in the frequency brain of 0.06 ~ 0.10 Hz showed significant sex differences regarding its connectivity; males had strong functional connectivity primarily within the limbic network and ventral attention network whereas females presented their strong functional connectivity mainly related to the visual network, ventral attention network and frontoparietal control network. These findings present a new method for the analysis of functional MRI images and provided brain imaging evidence on sex differences in functional connectomics.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Background: P-value is the most widely used statistical index for inference in science. A p-value greater than 0.05, i.e., nonsignificant results, however, cannot distinguish the two following cases: the absence of evidence or the evidence of absence. Unfortunately, researchers in psychological science may not be able to interpret p-values correctly, resulting in wrong inference. For example, Aczel et al (2018), after surveying 412 empirical studies published in Psychonomic Bulletin & Review, Journal of Experimental Psychology: General, and Psychological Science, found that about 72% of nonsignificant results were misinterpreted as evidence in favor of the null hypothesis. Misinterpretations of nonsignificant results may lead to severe consequences. One such consequence is missing potentially meaningful effects. Also, in matched-group clinical trials, misinterpretations of nonsignificant results may lead to false “matched” groups, thus threatening the validity of interventions. So far, how nonsignificant results are interpreted in Chinese psychological literature is unknown. Here we surveyed 500 empirical papers published in five mainstream Chinese psychological journals, to address the following questions: (1) how often are nonsignificant results reported; (2) how do researchers interpret nonsignificant results in these published studies; (3) if researchers interpreted nonsignificant as “evidence for absence,” do empirical data provide enough evidence for null effects? Method: Based on our pre-registration (https://osf.io/czx6f), we first randomly selected 500 empirical papers from all papers published in 2017 and 2018 in five mainstream Chinese psychological journals (Acta Psychologica Sinica, Psychological Science, Chinese Journal of Clinical Psychology, Psychological Development and Education, Psychological and Behavioral Studies). Second, we screened abstracts of these selected articles to check whether they contain negative statements. For those studies which contain negative statements in their abstracts, we searched nonsignificant statistics in their results and checked whether the corresponding interpretations were correct. More specifically, all those statements were classified into four categories (Correct-frequentist, Incorrect-frequentist: whole population, Incorrect-frequentist: current sample, Difficult to judge). Finally, we calculated Bayes factors based on available t values and sample sizes associated with those nonsignificant results. The Bayes factors can help us to estimate to what extent those results provided evidence for the absence of effects (i.e., the way researchers incorrectly interpreted nonsignificant results). Results: Our survey revealed that: (1) out of 500 empirical papers, 36% of their abstracts (n = 180) contained negative statements; (2) there are 236 negative statements associated with nonsignificant statistics in those selected studies, and 41% of these 236 negative statements misinterpreted nonsignificant results, i.e., the authors inferred that the results provided evidence for the absence of effects; (3) Bayes factor analyses based on available t-values and sample sizes found that only 5.1% (n = 2) nonsignificant results could provide strong evidence for the absence of effects (BF01 > 10). Compared with the results from Aczel et al (2019), we found that empirical papers published in Chinese journals contain more negative statements (36% vs. 32%), and researchers made fewer misinterpretations of nonsignificant results (41% vs. 72%). It worth noting, however, that there exists a categorization of ambiguous interpretations of nonsignificant results in the Chinese context. More specifically, many statements corresponding to nonsignificant results were “there is no significant difference between condition A and condition B”. These statements can be understood either as “the difference is not statistically significant”, which is correct, or “there is no difference”, which is incorrect. The percentage of misinterpretations of nonsignificant results raised to 64% if we adopt the second way to understand these statements, in contrast to 41% if we used the first understanding. Conclusion: Our results suggest that Chinese researchers need to improve their understanding of nonsignificant results and use more appropriate statistical methods to extract information from nonsignificant results. Also, more precise wordings should be used in the Chinese context.
Subjects: Psychology >> Statistics in Psychology submitted time 2022-07-30
Abstract： Meta-analysis is a crucial tool for accumulating evidence in basic and applied research. In the open science era, meta-analysis becomes an important way for integrating open data from different sources. Meanwhile, because of the great researchers’ degree introduced by multiple-step and multiple-choices in each step of meta-analysis, the openness and transparency are crucial for reproducing results of meta-analysis. To (1) understand the transparency and openness of meta-analysis reports published in Chinese journals and (2) improve the transparency and openness of future meta-analysis by Chinese researchers, we developed a Chinese version of checklist for meta-analysis, which was based on the Preferred Reporting Items for Systematic Review and Meta-Analysis protocols (PRISMA) and the principle of openness and transparency, and then surveyed the methods and results of 68 meta-analysis papers in mainstream Chinese psychological journals in last five years. Our results revealed that openness and transparency of Chinese meta-analysis reports need to be improved, especially in the following aspects: the date/time and limitation of literature search, the details of screening and data collection, the flow chart of article screening, the details of effect size transformation, and the evaluation of individual research bias. The checklist we present, which lists almost all aspects that an open meta-analysis should include, can be used as a guide for future meta-analysis.
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: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc. submitted time 2017-03-23
Abstract：摘要： 目的 介绍“中国彩巢计划：成长在中国（Chinese Color Nest Project – CCNP: Growing Up in China 2013-2022）”大型学龄儿童青少年脑与行为生长曲线项目。 方法 在全国范围内分期分步地开展毕生发展各年龄段的心理行为与脑影像样本积累，未来十年 CCNP 将基于加速纵向实验设计方法，建立中国人脑毕生发展的常模轨线。 结果 作为“彩巢”计划的脑发育项目，devCCNP 已经完成对重庆北碚区 192 名健康儿童青少年（6-18 岁）的 5 年追踪。 结论 devCCNP就实验设计、样本采集策略、数据获取和存储、初步结果和数据共享等方面都说明本计划具备长期实施的可行性。
Peer Review Status:Awaiting Review
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