ArticleNeuroImage2017
Assessing dynamic functional connectivity in heterogeneous samples.
Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Fifteen years on: a review of the Cam-CAN study of the cognitive neuroscience of ageing.GeroScience · 2026Review
- Brain-wide network analysis of resting-state neuromagnetic data.Human brain mapping · 2023Article
- Article
- Data and model considerations for estimating time-varying functional connectivity in fMRI.NeuroImage · 2022Article
- Transient neural network dynamics in cognitive ageing.Neurobiology of aging · 2021Article
- Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations.NeuroImage · 2021Article
- The "Neural Shift" of Sleep Quality and Cognitive Aging: A Resting-State MEG Study of Transient Neural Dynamics.Frontiers in aging neuroscience · 2021Article
- Statistical model for dynamically-changing correlation matrices with application to brain connectivity.Journal of neuroscience methods · 2020Review
- A systematic investigation of the association between network dynamics in the human brain and the state of consciousness.Neuroscience of consciousness · 2020Article
- Questions and controversies in the study of time-varying functional connectivity in resting fMRI.Network neuroscience (Cambridge, Mass.) · 2020Review
- Transient states of network connectivity are atypical in autism: A dynamic functional connectivity study.Human brain mapping · 2019Article
- An average sliding window correlation method for dynamic functional connectivity.Human brain mapping · 2019Article
- Tracking the dynamic functional connectivity structure of the human brain across the adult lifespan.Human brain mapping · 2019Article
- Network Approaches to Understand Individual Differences in Brain Connectivity: Opportunities for Personality Neuroscience.Personality neuroscience · 2018Article
- Brain networks of the imaginative mind: Dynamic functional connectivity of default and cognitive control networks relates to openness to experience.Human brain mapping · 2018Article
- Aberrant hemodynamic responses in autism: Implications for resting state fMRI functional connectivity studies.NeuroImage. Clinical · 2018Article
- Spatio-Temporal Dynamics of Intrinsic Networks in Functional Magnetic Imaging Data Using Recurrent Neural Networks.Frontiers in neuroscience · 2018Article
- Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset.Frontiers in neuroscience · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brain's functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.