{"title":"利用慢速事件相关 fMRI 研究物体识别过程中试验水平的大脑行为关系。","authors":"Stephen J Gotts, Adrian W Gilmore, Alex Martin","doi":"10.3389/fnhum.2024.1506661","DOIUrl":null,"url":null,"abstract":"<p><p>Understanding brain-behavior relationships is the core goal of cognitive neuroscience. However, these relationships-especially those related to complex cognitive and psychopathological behaviors-have recently been shown to suffer from very small effect sizes (0.1 or less), requiring potentially thousands of participants to yield robust findings. Here, we focus on a much more optimistic case utilizing task-based fMRI and a multi-echo acquisition with trial-level brain-behavior associations measured within participant. In a visual object identification task for which the behavioral measure is response time (RT), we show that while trial-level associations between BOLD and RT can similarly suffer from weak effect sizes, converting these associations to their corresponding group-level effects can yield robust peak effect sizes (Cohen's <i>d</i> = 1.0 or larger). Multi-echo denoising (Multi-Echo ICA or ME-ICA) yields larger effects than optimally combined multi-echo with no denoising, which is in turn an improvement over standard single-echo acquisition. While estimating these brain-behavior relationships benefits from the inclusion of a large number of trials per participant, even a modest number of trials (20-30 or more) yields robust group-level effect sizes, with replicable effects obtainable with relatively standard sample sizes (<i>N</i> = 20-30 participants per sample).</p>","PeriodicalId":12536,"journal":{"name":"Frontiers in Human Neuroscience","volume":"18 ","pages":"1506661"},"PeriodicalIF":2.4000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11588689/pdf/","citationCount":"0","resultStr":"{\"title\":\"Harnessing slow event-related fMRI to investigate trial-level brain-behavior relationships during object identification.\",\"authors\":\"Stephen J Gotts, Adrian W Gilmore, Alex Martin\",\"doi\":\"10.3389/fnhum.2024.1506661\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Understanding brain-behavior relationships is the core goal of cognitive neuroscience. However, these relationships-especially those related to complex cognitive and psychopathological behaviors-have recently been shown to suffer from very small effect sizes (0.1 or less), requiring potentially thousands of participants to yield robust findings. Here, we focus on a much more optimistic case utilizing task-based fMRI and a multi-echo acquisition with trial-level brain-behavior associations measured within participant. In a visual object identification task for which the behavioral measure is response time (RT), we show that while trial-level associations between BOLD and RT can similarly suffer from weak effect sizes, converting these associations to their corresponding group-level effects can yield robust peak effect sizes (Cohen's <i>d</i> = 1.0 or larger). Multi-echo denoising (Multi-Echo ICA or ME-ICA) yields larger effects than optimally combined multi-echo with no denoising, which is in turn an improvement over standard single-echo acquisition. While estimating these brain-behavior relationships benefits from the inclusion of a large number of trials per participant, even a modest number of trials (20-30 or more) yields robust group-level effect sizes, with replicable effects obtainable with relatively standard sample sizes (<i>N</i> = 20-30 participants per sample).</p>\",\"PeriodicalId\":12536,\"journal\":{\"name\":\"Frontiers in Human Neuroscience\",\"volume\":\"18 \",\"pages\":\"1506661\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11588689/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Human Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fnhum.2024.1506661\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Human Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fnhum.2024.1506661","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Harnessing slow event-related fMRI to investigate trial-level brain-behavior relationships during object identification.
Understanding brain-behavior relationships is the core goal of cognitive neuroscience. However, these relationships-especially those related to complex cognitive and psychopathological behaviors-have recently been shown to suffer from very small effect sizes (0.1 or less), requiring potentially thousands of participants to yield robust findings. Here, we focus on a much more optimistic case utilizing task-based fMRI and a multi-echo acquisition with trial-level brain-behavior associations measured within participant. In a visual object identification task for which the behavioral measure is response time (RT), we show that while trial-level associations between BOLD and RT can similarly suffer from weak effect sizes, converting these associations to their corresponding group-level effects can yield robust peak effect sizes (Cohen's d = 1.0 or larger). Multi-echo denoising (Multi-Echo ICA or ME-ICA) yields larger effects than optimally combined multi-echo with no denoising, which is in turn an improvement over standard single-echo acquisition. While estimating these brain-behavior relationships benefits from the inclusion of a large number of trials per participant, even a modest number of trials (20-30 or more) yields robust group-level effect sizes, with replicable effects obtainable with relatively standard sample sizes (N = 20-30 participants per sample).
期刊介绍:
Frontiers in Human Neuroscience is a first-tier electronic journal devoted to understanding the brain mechanisms supporting cognitive and social behavior in humans, and how these mechanisms might be altered in disease states. The last 25 years have seen an explosive growth in both the methods and the theoretical constructs available to study the human brain. Advances in electrophysiological, neuroimaging, neuropsychological, psychophysical, neuropharmacological and computational approaches have provided key insights into the mechanisms of a broad range of human behaviors in both health and disease. Work in human neuroscience ranges from the cognitive domain, including areas such as memory, attention, language and perception to the social domain, with this last subject addressing topics, such as interpersonal interactions, social discourse and emotional regulation. How these processes unfold during development, mature in adulthood and often decline in aging, and how they are altered in a host of developmental, neurological and psychiatric disorders, has become increasingly amenable to human neuroscience research approaches. Work in human neuroscience has influenced many areas of inquiry ranging from social and cognitive psychology to economics, law and public policy. Accordingly, our journal will provide a forum for human research spanning all areas of human cognitive, social, developmental and translational neuroscience using any research approach.