Author

Carolyn F. Berryman

The University of AdelaideORCID 0000-0002-5316-0847Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Bahar MoezziiD· 2 shared Brenton G. HordacreiD· 2 shared Michael C. RiddingiD· 2 shared Mitchell R. GoldsworthyiD· 2 shared Hannah A. D. KeageiD· 1 shared Latha Madhuri Pratti· 1 shared Louise M. LavrenciciD· 1 shared Lynton J. GraetziD· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 36 mutual co-author links

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2 shared papersNeuroscience

Bahar MoezziORCID

Mutual co-authors in cluster

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2 papers

Recent·Most cited

Characterization of young and old adult brains: An EEG functional connectivity analysis

Bahar Moezzi, Latha Madhuri Pratti, Brenton G. Hordacre, Lynton J. Graetz, Carolyn F. Berryman, Louise M. Lavrencic, Michael C. Ridding, Hannah A. D. Keage, Mark D. McDonnell, Mitchell R. Goldsworthy

This study uses EEG functional connectivity analysis to distinguish young and old adults, finding decreased connectivity in theta, alpha, and gamma bands and increased in beta band with aging.

Neuroscience · Dec 1, 2019Peer-reviewedNeuroscience

Test-retest reliability of functional brain network characteristics using resting-state EEG and graph theory

Bahar Moezzi, Brenton G. Hordacre, Carolyn F. Berryman, Michael C. Ridding, Mitchell R. Goldsworthy

This study assesses the test-retest reliability of functional brain network metrics from resting-state EEG using graph theory, finding varying reliability across analysis levels and frequency bands.

bioRxiv · Aug 5, 2018 · PreprintNeuroscience