Author

Laura A. Berner

Icahn School of Medicine at Mount SinaiORCID 0000-0002-1430-8028Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:cell type annotation· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Daniela SchilleriD· 2 shared Kaustubh R. KulkarniiD· 2 shared Vincenzo G. FioreiD· 2 shared Xiaosi GuiD· 2 shared Elizabeth Martin· 1 shared Francesca Mapua FilbeyiD· 1 shared Gaurav Shankar PandeyiD· 1 shared Kent E. HutchisoniD· 1 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersNeuroscience

Daniela SchillerORCID

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3 papers

Recent·Most cited

NeurosciencebioRxivPreprintDec 11, 2025

Altered Brain Network Topology during Successful Response Inhibition in Children with Binge Eating

Elizabeth Martin, Kurt P. Schulz, Tom Hildebrandt…·Xiaobo Li

This study examines neural network differences in children with binge eating compared to controls, finding altered efficiency and connectivity in inhibitory control brain regions.

DOI 10.64898/2025.12.09.693025

humanimaging

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NeurosciencebioRxivPreprintApr 24, 2023

A generalizable computational mechanism underlying the interaction between momentary craving and decision-making

Kaustubh R. Kulkarni, Laura A. Berner, Shawn A Rhoads…·Xiaosi Gu

This study identifies a computational mechanism linking momentary craving and decision-making in substance use disorders, showing differential effects between alcohol and cannabis users.

2 citations

humanstatistical model

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NeurosciencebioRxivPreprintMay 4, 2021

An interpretable connectivity-based decoding model for classification of chronic marijuana use

Kaustubh R. Kulkarni, Matthew Schafer, Laura A. Berner…·Xiaosi Gu

This paper develops an interpretable decoding model using functional connectivity to classify chronic marijuana users and non-users with high accuracy.

1 citation

humanimaging

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