Stephanie Noble

Stephanie Noble

Yale University

H-index: 20

North America-United States

About Stephanie Noble

Stephanie Noble, With an exceptional h-index of 20 and a recent h-index of 20 (since 2020), a distinguished researcher at Yale University, specializes in the field of fMRI, functional connectivity, test-retest reliability, statistical methods, predictive modeling.

His recent articles reflect a diverse array of research interests and contributions to the field:

Brain-phenotype predictions can survive across diverse real-world data

Topological cluster statistic (tcs): Towards structural-connectivity-guided fmri cluster enhancement

Test-Retest Reliability of Functional Connectivity in Adolescents With Depression

The tip of the iceberg: a call to embrace anti-localizationism in human neuroscience research

Data leakage inflates prediction performance in connectome-based machine learning models

156. Association Between Physical Frailty and Incident Depression

Creating Diverse and Inclusive Scientific Practices for Research Datasets and Dissemination

432. Success and Failure of Connectome-Based Prediction of Cognitive Functioning in Early Psychosis

Stephanie Noble Information

University

Position

Postdoctoral Associate

Citations(all)

2207

Citations(since 2020)

2109

Cited By

660

hIndex(all)

20

hIndex(since 2020)

20

i10Index(all)

27

i10Index(since 2020)

27

Email

University Profile Page

Yale University

Google Scholar

View Google Scholar Profile

Stephanie Noble Skills & Research Interests

fMRI

functional connectivity

test-retest reliability

statistical methods

predictive modeling

Top articles of Stephanie Noble

Title

Journal

Author(s)

Publication Date

Brain-phenotype predictions can survive across diverse real-world data

bioRxiv

Brendan D Adkinson

Matthew Rosenblatt

Javid Dadashkarimi

Link Tejavibulya

Rongtao Jiang

...

2024

Topological cluster statistic (tcs): Towards structural-connectivity-guided fmri cluster enhancement

L SM

C Seguin

A Winkler

S Noble

A Zalesky

2022/9/15

Test-Retest Reliability of Functional Connectivity in Adolescents With Depression

Dan Jin

Kaibin Xu

Bing Liu

Tianzi Jiang

Yong Liu

2018/7/18

The tip of the iceberg: a call to embrace anti-localizationism in human neuroscience research

Imaging Neuroscience

Stephanie Noble

Joshua Curtiss

Luiz Pessoa

Dustin Scheinost

2024/4/2

Data leakage inflates prediction performance in connectome-based machine learning models

Nature Communications

Matthew Rosenblatt

Link Tejavibulya

Rongtao Jiang

Stephanie Noble

Dustin Scheinost

2024/2/28

156. Association Between Physical Frailty and Incident Depression

Biological Psychiatry

Rongtao Jiang

Stephanie Noble

Matthew Rosenblatt

Jean Ye

Vince Calhoun

...

2024/5/15

Creating Diverse and Inclusive Scientific Practices for Research Datasets and Dissemination

Julia Kam

AmanPreet Badhwar

Valentina Borghesani

Kangjoo Lee

Stephanie Noble

...

2024/1/27

432. Success and Failure of Connectome-Based Prediction of Cognitive Functioning in Early Psychosis

Biological Psychiatry

Alexandra O'Neill

Melissa Pax

Jorge Sepulcre

Joan Camprodon

Daphne Holt

...

2024/5/15

Connectome caricatures: removing large-amplitude co-activation patterns in resting-state fMRI emphasizes individual differences

bioRxiv

Raimundo Xavier Rodriguez

Stephanie Noble

Chris C Camp

Dustin Scheinost

2024

Psychiatric Neuroimaging Designs for Individualised, Cohort, and Population Studies

Martin Gell

Stephanie Noble

Timothy O Laumann

Steven M Nelson

Brenden Tervo-Clemmens

2024/4/22

Connectome-based machine learning models are vulnerable to subtle data manipulations

Patterns

Matthew Rosenblatt

Raimundo X Rodriguez

Margaret L Westwater

Wei Dai

Corey Horien

...

2023/7/14

Machine learning and prediction in fetal, infant, and toddler neuroimaging: A review and primer

Dustin Scheinost

Angeliki Pollatou

Alexander J Dufford

Rongtao Jiang

Michael C Farruggia

...

2023/5/15

Power and reproducibility in the external validation of brain-phenotype predictions

bioRxiv

Matthew Rosenblatt

Link Tejavibulya

Chris C Camp

Rongtao Jiang

Margaret L Westwater

...

2023/10/30

The effects of data leakage on connectome-based machine learning models

bioRxiv

Matthew Rosenblatt

Link Tejavibulya

Rongtao Jiang

Stephanie Noble

Dustin Scheinost

2023/6/11

6. Altered Brain Dynamics Across Bipolar Disorder and Schizophrenia During Rest and Task-Switching Revealed by Overlapping Brain States

Biological Psychiatry

Jean Ye

Huili Sun

Siyuan Gao

Javid Dadashkarimi

Matthew Rosenblatt

...

2023/5/1

The effects of data leakage on neuroimaging predictive models

Matthew Rosenblatt

Link Tejavibulya

Rongtao Jiang

Stephanie Noble

Dustin Scheinost

2023/6/11

Functional brain networks reflect spatial and temporal autocorrelation

Nature neuroscience

Maxwell Shinn

Amber Hu

Laurel Turner

Stephanie Noble

Katrin H Preller

...

2023/5

Altered brain dynamics across bipolar disorder and schizophrenia during rest and task switching revealed by overlapping brain states

Biological Psychiatry

Jean Ye

Huili Sun

Siyuan Gao

Javid Dadashkarimi

Matthew Rosenblatt

...

2023/10/1

A functional connectome signature of blood pressure in> 30 000 participants from the UK biobank

Cardiovascular Research

Rongtao Jiang

Vince D Calhoun

Stephanie Noble

Jing Sui

Qinghao Liang

...

2023/5

Network controllability of structural connectomes in the neonatal brain

Nature Communications

Huili Sun

Rongtao Jiang

Wei Dai

Alexander J Dufford

Stephanie Noble

...

2023/9/19

See List of Professors in Stephanie Noble University(Yale University)

Co-Authors

H-index: 168
John Krystal

John Krystal

Yale University

H-index: 125
R. Todd Constable

R. Todd Constable

Yale University

H-index: 87
Lawrence Hirsch

Lawrence Hirsch

Yale University

H-index: 86
Marvin M. Chun

Marvin M. Chun

Yale University

H-index: 59
Dustin Scheinost

Dustin Scheinost

Yale University

H-index: 37
Monica D. Rosenberg

Monica D. Rosenberg

University of Chicago

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