Author

Fran Hancock

King's College LondonORCID 0000-0001-7383-7205Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:imaging· 3 Approach:statistical model· 3 Research Focus:cell-cell communication· 2 Organism:human· 2 Research Focus:benchmarking· 1 Approach:contrastive learning· 1 Research Focus:dimensionality reduction· 1 Organism:rat· 1

Frequent Co-Authors

Federico TurkheimeriD· 2 shared Fernando E. RosasiD· 2 shared Alessandro CiaramellaiD· 1 shared Andrea I. LuppiiD· 1 shared Diana CashiD· 1 shared Eilidh MacNicoliD· 1 shared Giuseppe de AlteriisiD· 1 shared Joana CabraliD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersNeuroscience

Federico TurkheimerORCID

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3 papers

Recent·Most cited

NeuroscienceNeuroImagePeer-reviewedJun 11, 2026

A Complexity-Science Framework for Studying Flow: Using Media to Probe Brain-Phenomenology Dynamics

Fran Hancock, Rachael Kee, Fernando E. Rosas…·Richard Huskey

The paper uses complexity science to analyze brain dynamics during flow, boredom, and frustration induced by video games, finding distinct patterns in global entropy and network metrics.

1 citationtop 4%

humanimaging

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NeurosciencebioRxivPreprintFeb 27, 2023

EiDA: A lossless approach for the dynamic analysis of connectivity patterns in signals; application to resting state fMRI of a model of ageing

Giuseppe de Alteriis, Eilidh MacNicol, Fran Hancock…·Federico Turkheimer

EiDA is a method for analyzing dynamic functional connectivity in resting-state fMRI data from ageing rats, revealing reduced phase-locking intensity and structural complexity with age.

3 citations

ratimaging

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NeuroscienceNeuroImagePeer-reviewedJul 1, 2022

Metastability, fractal scaling, and synergistic information processing: what phase relationships reveal about intrinsic brain activity

Fran Hancock, Joana Cabral, Andrea I. Luppi…·Federico Turkheimer

The paper evaluates phase-based dynamic functional connectivity metrics in resting-state fMRI to identify reliable and interpretable measures of brain dynamics and their relationships.

39 citationstop 4%

humanimaging

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