Pub Date : 2023-08-17DOI: 10.1038/s41562-023-01680-z
Marius V. Peelen, Paul E. Downing
Multivariate pattern analysis (MVPA) has emerged as a powerful method for the analysis of functional magnetic resonance imaging, electroencephalography and magnetoencephalography data. The new approaches to experimental design and hypothesis testing afforded by MVPA have made it possible to address theories that describe cognition at the functional level. Here we review a selection of studies that have used MVPA to test cognitive theories from a range of domains, including perception, attention, memory, navigation, emotion, social cognition and motor control. This broad view reveals properties of MVPA that make it suitable for understanding the ‘how’ of human cognition, such as the ability to test predictions expressed at the item or event level. It also reveals limitations and points to future directions. Peelen and Downing review the use of multivariate pattern analysis in cognitive neuroscience to study cognition at the functional level.
{"title":"Testing cognitive theories with multivariate pattern analysis of neuroimaging data","authors":"Marius V. Peelen, Paul E. Downing","doi":"10.1038/s41562-023-01680-z","DOIUrl":"10.1038/s41562-023-01680-z","url":null,"abstract":"Multivariate pattern analysis (MVPA) has emerged as a powerful method for the analysis of functional magnetic resonance imaging, electroencephalography and magnetoencephalography data. The new approaches to experimental design and hypothesis testing afforded by MVPA have made it possible to address theories that describe cognition at the functional level. Here we review a selection of studies that have used MVPA to test cognitive theories from a range of domains, including perception, attention, memory, navigation, emotion, social cognition and motor control. This broad view reveals properties of MVPA that make it suitable for understanding the ‘how’ of human cognition, such as the ability to test predictions expressed at the item or event level. It also reveals limitations and points to future directions. Peelen and Downing review the use of multivariate pattern analysis in cognitive neuroscience to study cognition at the functional level.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 9","pages":"1430-1441"},"PeriodicalIF":29.9,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10374682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1038/s41562-023-01669-8
David Zendle, Catherine Flick, Elena Gordon-Petrovskaya, Nick Ballou, Leon Y. Xiao, Anders Drachen
Governments around the world are considering regulatory measures to reduce young people’s time spent on digital devices, particularly video games. This raises the question of whether proposed regulatory measures would be effective. Since the early 2000s, the Chinese government has been enacting regulations to directly restrict young people’s playtime. In November 2019, it limited players aged under 18 to 1.5 hours of daily playtime and 3 hours on public holidays. Using telemetry data on over seven billion hours of playtime provided by a stakeholder from the video games industry, we found no credible evidence for overall reduction in the prevalence of heavy playtime following the implementation of regulations: individual accounts became 1.14 times more likely to play heavily in any given week (95% confidence interval 1.139–1.141). This falls below our preregistered smallest effect size of interest (2.0) and thus is not interpreted as a practically meaningful increase. Results remain robust across a variety of sensitivity analyses, including an analysis of more recent (2021) adjustments to playtime regulation. This casts doubt on the effectiveness of such state-controlled playtime mandates. The authors show that video game playtime restriction policies in China had no discernible influence on time spent gaming.
{"title":"No evidence that Chinese playtime mandates reduced heavy gaming in one segment of the video games industry","authors":"David Zendle, Catherine Flick, Elena Gordon-Petrovskaya, Nick Ballou, Leon Y. Xiao, Anders Drachen","doi":"10.1038/s41562-023-01669-8","DOIUrl":"10.1038/s41562-023-01669-8","url":null,"abstract":"Governments around the world are considering regulatory measures to reduce young people’s time spent on digital devices, particularly video games. This raises the question of whether proposed regulatory measures would be effective. Since the early 2000s, the Chinese government has been enacting regulations to directly restrict young people’s playtime. In November 2019, it limited players aged under 18 to 1.5 hours of daily playtime and 3 hours on public holidays. Using telemetry data on over seven billion hours of playtime provided by a stakeholder from the video games industry, we found no credible evidence for overall reduction in the prevalence of heavy playtime following the implementation of regulations: individual accounts became 1.14 times more likely to play heavily in any given week (95% confidence interval 1.139–1.141). This falls below our preregistered smallest effect size of interest (2.0) and thus is not interpreted as a practically meaningful increase. Results remain robust across a variety of sensitivity analyses, including an analysis of more recent (2021) adjustments to playtime regulation. This casts doubt on the effectiveness of such state-controlled playtime mandates. The authors show that video game playtime restriction policies in China had no discernible influence on time spent gaming.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 10","pages":"1753-1766"},"PeriodicalIF":29.9,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9965201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1038/s41562-023-01681-y
Yongzheng Yang, Sara Konrath
How does economic inequality relate to prosocial behaviour? Existing theories and empirical studies from multiple disciplines have produced mixed results. Here we conduct a systematic review and meta-analysis to systematically synthesize empirical studies. Results from 192 effect sizes and over 2.5 million observations in 100 studies show that the relationship varies from being negative to positive depending upon the study (95% prediction interval −0.450 to 0.343). However, on average, there is a small, negative relationship between economic inequality and prosocial behaviour (r = −0.064, P = 0.004, 95% confidence interval −0.106 to −0.021). There is generally no evidence that results depend upon characteristics of the studies, participants, the way prosocial behaviour and inequality were assessed, and the publication discipline. Given the prevalence of economic inequality and the importance of prosocial behaviour, this systematic review and meta-analysis provides a timely study on the relationship between economic inequality and prosocial behaviour. This meta-analysis of the relationship between economic inequality and prosocial behaviour finds that the relationship varies from being negative to positive, but, on average, higher economic inequality is associated with lower prosocial behaviour.
经济不平等与亲社会行为有何关系?来自多个学科的现有理论和实证研究产生了不同的结果。本文通过系统综述和元分析，对实证研究进行系统综合。来自192个效应大小和100个研究中超过250万个观察结果的结果表明，根据研究的不同，这种关系从负向正变化(95%预测区间为-0.450至0.343)。然而，平均而言，经济不平等与亲社会行为之间存在较小的负相关(r = -0.064, P = 0.004, 95%置信区间为-0.106至-0.021)。一般来说，没有证据表明结果取决于研究的特征、参与者、评估亲社会行为和不平等的方式以及发表的学科。鉴于经济不平等的普遍存在和亲社会行为的重要性，本系统综述和荟萃分析为经济不平等与亲社会行为之间的关系提供了及时的研究。
{"title":"A systematic review and meta-analysis of the relationship between economic inequality and prosocial behaviour","authors":"Yongzheng Yang, Sara Konrath","doi":"10.1038/s41562-023-01681-y","DOIUrl":"10.1038/s41562-023-01681-y","url":null,"abstract":"How does economic inequality relate to prosocial behaviour? Existing theories and empirical studies from multiple disciplines have produced mixed results. Here we conduct a systematic review and meta-analysis to systematically synthesize empirical studies. Results from 192 effect sizes and over 2.5 million observations in 100 studies show that the relationship varies from being negative to positive depending upon the study (95% prediction interval −0.450 to 0.343). However, on average, there is a small, negative relationship between economic inequality and prosocial behaviour (r = −0.064, P = 0.004, 95% confidence interval −0.106 to −0.021). There is generally no evidence that results depend upon characteristics of the studies, participants, the way prosocial behaviour and inequality were assessed, and the publication discipline. Given the prevalence of economic inequality and the importance of prosocial behaviour, this systematic review and meta-analysis provides a timely study on the relationship between economic inequality and prosocial behaviour. This meta-analysis of the relationship between economic inequality and prosocial behaviour finds that the relationship varies from being negative to positive, but, on average, higher economic inequality is associated with lower prosocial behaviour.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 11","pages":"1899-1916"},"PeriodicalIF":29.9,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9965207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1038/s41562-023-01674-x
Alexandru Marcoci, Ann C. Thresher, Niels C. M. Martens, Peter Galison, Sheperd S. Doeleman, Michael D. Johnson
{"title":"Big STEM collaborations should include humanities and social science","authors":"Alexandru Marcoci, Ann C. Thresher, Niels C. M. Martens, Peter Galison, Sheperd S. Doeleman, Michael D. Johnson","doi":"10.1038/s41562-023-01674-x","DOIUrl":"10.1038/s41562-023-01674-x","url":null,"abstract":"","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 8","pages":"1229-1230"},"PeriodicalIF":29.9,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10432281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1038/s41562-023-01667-w
Brian Guay, Adam J. Berinsky, Gordon Pennycook, David Rand
Progress in the burgeoning field of misinformation research requires some degree of consensus about what constitutes an effective intervention to combat misinformation. We differentiate between research designs that are used to evaluate interventions and recommend one that measures how well people discern between true and false content.
{"title":"How to think about whether misinformation interventions work","authors":"Brian Guay, Adam J. Berinsky, Gordon Pennycook, David Rand","doi":"10.1038/s41562-023-01667-w","DOIUrl":"10.1038/s41562-023-01667-w","url":null,"abstract":"Progress in the burgeoning field of misinformation research requires some degree of consensus about what constitutes an effective intervention to combat misinformation. We differentiate between research designs that are used to evaluate interventions and recommend one that measures how well people discern between true and false content.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 8","pages":"1231-1233"},"PeriodicalIF":29.9,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10056695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-07DOI: 10.1038/s41562-023-01665-y
Fotini Christia, Horacio Larreguy, Elizabeth Parker-Magyar, Manuel Quintero
COVID-19 heightened women’s exposure to gender-based and intimate partner violence, especially in low-income and middle-income countries. We tested whether edutainment interventions shown to successfully combat gender-based and intimate partner violence when delivered in person can be effectively delivered using social (WhatsApp and Facebook) and traditional (TV) media. To do so, we randomized the mode of implementation of an intervention conducted by an Egyptian women’s rights organization seeking to support women amid COVID-19 social distancing. We found WhatsApp to be more effective in delivering the intervention than Facebook but no credible evidence of differences across outcomes between social media and TV dissemination. Our findings show little credible evidence that these campaigns affected women’s attitudes towards gender or marital equality or on the justifiability of violence. However, the campaign did increase women’s knowledge, hypothetical use and reported use of available resources. Christia et al. evaluate the delivery of content to empower women exposed to violence amid COVID-19. The recipients exhibited no credible evidence of a shift in attitudes but increased their knowledge and hypothetical and reported use of resources.
{"title":"Empowering women facing gender-based violence amid COVID-19 through media campaigns","authors":"Fotini Christia, Horacio Larreguy, Elizabeth Parker-Magyar, Manuel Quintero","doi":"10.1038/s41562-023-01665-y","DOIUrl":"10.1038/s41562-023-01665-y","url":null,"abstract":"COVID-19 heightened women’s exposure to gender-based and intimate partner violence, especially in low-income and middle-income countries. We tested whether edutainment interventions shown to successfully combat gender-based and intimate partner violence when delivered in person can be effectively delivered using social (WhatsApp and Facebook) and traditional (TV) media. To do so, we randomized the mode of implementation of an intervention conducted by an Egyptian women’s rights organization seeking to support women amid COVID-19 social distancing. We found WhatsApp to be more effective in delivering the intervention than Facebook but no credible evidence of differences across outcomes between social media and TV dissemination. Our findings show little credible evidence that these campaigns affected women’s attitudes towards gender or marital equality or on the justifiability of violence. However, the campaign did increase women’s knowledge, hypothetical use and reported use of available resources. Christia et al. evaluate the delivery of content to empower women exposed to violence amid COVID-19. The recipients exhibited no credible evidence of a shift in attitudes but increased their knowledge and hypothetical and reported use of resources.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 10","pages":"1740-1752"},"PeriodicalIF":29.9,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9954391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-04DOI: 10.1038/s41562-023-01671-0
Analogical reasoning is a hallmark of human intelligence, as it enables us to flexibly solve new problems without extensive practice. By using a wide range of tests, we demonstrate that GPT-3, a large-scale artificial intelligence language model, is capable of solving difficult analogy problems at a level comparable to human performance.
{"title":"Large-scale AI language systems display an emergent ability to reason by analogy","authors":"","doi":"10.1038/s41562-023-01671-0","DOIUrl":"10.1038/s41562-023-01671-0","url":null,"abstract":"Analogical reasoning is a hallmark of human intelligence, as it enables us to flexibly solve new problems without extensive practice. By using a wide range of tests, we demonstrate that GPT-3, a large-scale artificial intelligence language model, is capable of solving difficult analogy problems at a level comparable to human performance.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 9","pages":"1426-1427"},"PeriodicalIF":29.9,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9930856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.1038/s41562-023-01659-w
Taylor Webb, Keith J. Holyoak, Hongjing Lu
The recent advent of large language models has reinvigorated debate over whether human cognitive capacities might emerge in such generic models given sufficient training data. Of particular interest is the ability of these models to reason about novel problems zero-shot, without any direct training. In human cognition, this capacity is closely tied to an ability to reason by analogy. Here we performed a direct comparison between human reasoners and a large language model (the text-davinci-003 variant of Generative Pre-trained Transformer (GPT)-3) on a range of analogical tasks, including a non-visual matrix reasoning task based on the rule structure of Raven’s Standard Progressive Matrices. We found that GPT-3 displayed a surprisingly strong capacity for abstract pattern induction, matching or even surpassing human capabilities in most settings; preliminary tests of GPT-4 indicated even better performance. Our results indicate that large language models such as GPT-3 have acquired an emergent ability to find zero-shot solutions to a broad range of analogy problems. Webb et al. show that new artificial intelligence language models, such as Generative Pre-trained Transformer 3, are able to solve analogical reasoning problems at a human-like level of performance.
{"title":"Emergent analogical reasoning in large language models","authors":"Taylor Webb, Keith J. Holyoak, Hongjing Lu","doi":"10.1038/s41562-023-01659-w","DOIUrl":"10.1038/s41562-023-01659-w","url":null,"abstract":"The recent advent of large language models has reinvigorated debate over whether human cognitive capacities might emerge in such generic models given sufficient training data. Of particular interest is the ability of these models to reason about novel problems zero-shot, without any direct training. In human cognition, this capacity is closely tied to an ability to reason by analogy. Here we performed a direct comparison between human reasoners and a large language model (the text-davinci-003 variant of Generative Pre-trained Transformer (GPT)-3) on a range of analogical tasks, including a non-visual matrix reasoning task based on the rule structure of Raven’s Standard Progressive Matrices. We found that GPT-3 displayed a surprisingly strong capacity for abstract pattern induction, matching or even surpassing human capabilities in most settings; preliminary tests of GPT-4 indicated even better performance. Our results indicate that large language models such as GPT-3 have acquired an emergent ability to find zero-shot solutions to a broad range of analogy problems. Webb et al. show that new artificial intelligence language models, such as Generative Pre-trained Transformer 3, are able to solve analogical reasoning problems at a human-like level of performance.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 9","pages":"1526-1541"},"PeriodicalIF":29.9,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9986552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.1038/s41562-023-01654-1
Eric Feltham, Laura Forastiere, Marcus Alexander, Nicholas A. Christakis
Epidemic disease can spread during mass gatherings. We assessed the impact of a type of mass gathering about which comprehensive data were available on the local-area trajectory of the COVID-19 epidemic. Here we examined five types of political event in 2020 and 2021: the US primary elections, the US Senate special election in Georgia, the gubernatorial elections in New Jersey and Virginia, Donald Trump’s political rallies and the Black Lives Matter protests. Our study period encompassed over 700 such mass gatherings during multiple phases of the pandemic. We used data from the 48 contiguous states, representing 3,108 counties, and we implemented a novel extension of a recently developed non-parametric, generalized difference-in-difference estimator with a (high-quality) matching procedure for panel data to estimate the average effect of the gatherings on local mortality and other outcomes. There were no statistically significant increases in cases, deaths or a measure of epidemic transmissibility (Rt) in a 40-day period following large-scale political activities. We estimated small and statistically non-significant effects, corresponding to an average difference of −0.0567 deaths (95% CI = −0.319, 0.162) and 8.275 cases (95% CI = −1.383, 20.7) on each day for counties that held mass gatherings for political expression compared to matched control counties. In sum, there is no statistical evidence of a material increase in local COVID-19 deaths, cases or transmissibility after mass gatherings for political expression during the first 2 years of the pandemic in the USA. This may relate to the specific manner in which such activities are typically conducted. The authors show that political gatherings in the USA in 2021–2022 did not have any effect on COVID-19 case counts.
{"title":"Mass gatherings for political expression had no discernible association with the local course of the COVID-19 pandemic in the USA in 2020 and 2021","authors":"Eric Feltham, Laura Forastiere, Marcus Alexander, Nicholas A. Christakis","doi":"10.1038/s41562-023-01654-1","DOIUrl":"10.1038/s41562-023-01654-1","url":null,"abstract":"Epidemic disease can spread during mass gatherings. We assessed the impact of a type of mass gathering about which comprehensive data were available on the local-area trajectory of the COVID-19 epidemic. Here we examined five types of political event in 2020 and 2021: the US primary elections, the US Senate special election in Georgia, the gubernatorial elections in New Jersey and Virginia, Donald Trump’s political rallies and the Black Lives Matter protests. Our study period encompassed over 700 such mass gatherings during multiple phases of the pandemic. We used data from the 48 contiguous states, representing 3,108 counties, and we implemented a novel extension of a recently developed non-parametric, generalized difference-in-difference estimator with a (high-quality) matching procedure for panel data to estimate the average effect of the gatherings on local mortality and other outcomes. There were no statistically significant increases in cases, deaths or a measure of epidemic transmissibility (Rt) in a 40-day period following large-scale political activities. We estimated small and statistically non-significant effects, corresponding to an average difference of −0.0567 deaths (95% CI = −0.319, 0.162) and 8.275 cases (95% CI = −1.383, 20.7) on each day for counties that held mass gatherings for political expression compared to matched control counties. In sum, there is no statistical evidence of a material increase in local COVID-19 deaths, cases or transmissibility after mass gatherings for political expression during the first 2 years of the pandemic in the USA. This may relate to the specific manner in which such activities are typically conducted. The authors show that political gatherings in the USA in 2021–2022 did not have any effect on COVID-19 case counts.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 10","pages":"1708-1728"},"PeriodicalIF":29.9,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9914184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.1038/s41562-023-01670-1
Jianxiao Wu, Jingwei Li, Simon B. Eickhoff, Dustin Scheinost, Sarah Genon
Relating individual brain patterns to behaviour is fundamental in system neuroscience. Recently, the predictive modelling approach has become increasingly popular, largely due to the recent availability of large open datasets and access to computational resources. This means that we can use machine learning models and interindividual differences at the brain level represented by neuroimaging features to predict interindividual differences in behavioural measures. By doing so, we could identify biomarkers and neural correlates in a data-driven fashion. Nevertheless, this budding field of neuroimaging-based predictive modelling is facing issues that may limit its potential applications. Here we review these existing challenges, as well as those that we anticipate as the field develops. We focus on the impacts of these challenges on brain-based predictions. We suggest potential solutions to address the resolvable challenges, while keeping in mind that some general and conceptual limitations may also underlie the predictive modelling approach. Wu et al. discuss the current and future challenges in the prediction of behavioural traits from brain data.
{"title":"The challenges and prospects of brain-based prediction of behaviour","authors":"Jianxiao Wu, Jingwei Li, Simon B. Eickhoff, Dustin Scheinost, Sarah Genon","doi":"10.1038/s41562-023-01670-1","DOIUrl":"10.1038/s41562-023-01670-1","url":null,"abstract":"Relating individual brain patterns to behaviour is fundamental in system neuroscience. Recently, the predictive modelling approach has become increasingly popular, largely due to the recent availability of large open datasets and access to computational resources. This means that we can use machine learning models and interindividual differences at the brain level represented by neuroimaging features to predict interindividual differences in behavioural measures. By doing so, we could identify biomarkers and neural correlates in a data-driven fashion. Nevertheless, this budding field of neuroimaging-based predictive modelling is facing issues that may limit its potential applications. Here we review these existing challenges, as well as those that we anticipate as the field develops. We focus on the impacts of these challenges on brain-based predictions. We suggest potential solutions to address the resolvable challenges, while keeping in mind that some general and conceptual limitations may also underlie the predictive modelling approach. Wu et al. discuss the current and future challenges in the prediction of behavioural traits from brain data.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 8","pages":"1255-1264"},"PeriodicalIF":29.9,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10113319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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