ArticleScientific reports2019
Possible links between the lag structure in visual cortex and visual streams using fMRI.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
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- Neural network dynamics underlying the bottom-up perception and top-down regulation processes of empathy.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI.Progress in neurobiology · 2021Review
- Regional Homogeneity Abnormalities and Its Correlation With Impulsivity in Male Abstinent Methamphetamine Dependent Individuals.Frontiers in molecular neuroscience · 2021Article
- Time-delay structure predicts clinical scores for patients with disorders of consciousness using resting-state fMRI.NeuroImage. Clinical · 2021Article
- Topological View of Flows Inside the BOLD Spontaneous Activity of the Human Brain.Frontiers in computational neuroscience · 2020Article
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Authors and funding
4 authors at 1 institution in 1 country.
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Abstract
Conventional functional connectivity analysis using functional magnetic resonance imaging (fMRI) measures the correlation of temporally synchronized brain activities between brain regions. Lag structure analysis relaxes the synchronicity constraint of fMRI signals, and thus, this approach might be better at explaining functional connectivity. However, the sources of the lag structure in fMRI are primarily unknown. Here, we applied lag structure analysis to the human visual cortex to identify the possible sources of lag structure. A total of 1,250 fMRI data from two independent databases were considered. We explored the temporal lag patterns between the central and peripheral visual fields in early visual cortex and those in two visual pathways of dorsal and ventral streams. We also compared the lag patterns with effective connectivity obtained with dynamic causal modeling. We found that the lag structure in early visual cortex flows from the central to peripheral visual fields and the order of the lag structure flow was consistent with the order of signal flows in visual pathways. The effective connectivity computed by dynamic causal modeling exhibited similar patterns with the lag structure results. This study suggests that signal flows in visual streams are possible sources of the lag structure in human visual cortex.
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