Laura Jett

ORCID: 0000-0001-9035-7385
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About
Contact & Profiles
Research Areas
  • Functional Brain Connectivity Studies
  • EEG and Brain-Computer Interfaces
  • Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Impact of Technology on Adolescents
  • Neural dynamics and brain function
  • Media Influence and Health
  • Child Development and Digital Technology
  • Advanced MRI Techniques and Applications
  • Mental Health Research Topics
  • Mind wandering and attention
  • Neuroscience and Music Perception

National Institute of Mental Health
2023-2025

University of Wisconsin–Madison
2023-2025

National Institutes of Health
2023

Willem B. Bruin Paul Zhutovsky Guido van Wingen Janna Marie Bas‐Hoogendam Nynke A. Groenewold and 95 more Kevin Hilbert Anderson M. Winkler André Zugman Federica Agosta Fredrik Åhs Carmen Andreescu Chase Antonacci Takeshi Asami Michal Assaf Jacques P. Barber Jochen Bauer Shreya Y. Bavdekar Katja Beesdo‐Baum Francesco Benedetti Rachel Bernstein Johannes Björkstrand James Blair Karina S. Blair Laura Blanco‐Hinojo Joscha Böhnlein Paolo Brambilla Rodrigo A. Bressan Fabian Breuer Marta Cano Elisa Canu Elise M. Cardinale Narcı́s Cardoner Camilla Cividini Henk Cremers Udo Dannlowski Gretchen J. Diefenbach Katharina Domschke Alex Doruyter Thomas Dresler Angelika Erhardt Massimo Filippi Gregory A. Fonzo Gabrielle F. Freitag Tomas Furmark Tian Ge Andrew J. Gerber Savannah N. Gosnell Hans J. Grabe Dominik Grotegerd Ruben C. Gur Raquel E. Gur Alfons O. Hamm Laura K. M. Han Jennifer C. Harper Anita Harrewijn Alexandre Heeren David Hofmann Andrea Parolin Jackowski Neda Jahanshad Laura Jett Antonia N. Kaczkurkin Parmis Khosravi Ellen Kingsley Tilo Kircher Milutin Kostić Bart Larsen Sang‐Hyuk Lee Elisabeth J. Leehr Ellen Leibenluft Christine Löchner Su Lui Eleonora Maggioni Gisele Gus Manfro Kristoffer Månsson Claire E. Marino Frances Meeten Barbara Milrod Ana Munjiza Benson Mwangi Michael J. Myers Susanne Neufang Jared A. Nielsen Patricia Ohrmann Cristina Ottaviani Martin P. Paulus Michael T. Perino K. Luan Phan Sara Poletti Daniel Porta‐Casteràs Jesùs Pujol Andrea Reinecke Grace Ringlein Pavel Rjabtsenkov Karin Roelofs Ramiro Salas Giovanni Abrahão Salum Theodore D. Satterthwaite Elisabeth Schrammen Lisa Sindermann Jordan W. Smoller

10.1038/s44220-023-00173-2 article EN Nature Mental Health 2024-01-10

Movie-watching fMRI has emerged as a theoretically viable platform for studying neurobiological substrates of affective states and emotional disorders such pathological anxiety. However, using anxiety-inducing movie clips to probe relevant impacted by psychopathology could risk exacerbating in-scanner movement, decreasing signal quality/quantity thus statistical power. This be especially problematic in target populations children who typically move more the scanner. Consequently, we...

10.1002/hbm.70163 article EN cc-by Human Brain Mapping 2025-03-01

Movie-watching fMRI has emerged as a theoretically viable platform for studying neurobiological substrates of affective states and emotional disorders such pathological anxiety. However, using anxiety-inducing movie clips to probe relevant impacted by psychopathology could risk exacerbating in-scanner movement, decreasing signal quality/quantity thus statistical power. This be especially problematic in target populations children who typically move more the scanner. Consequently, we...

10.31234/osf.io/8k9c4 preprint EN 2024-08-20

Movie-watching fMRI has emerged as a theoretically viable platform for studying neurobiological substrates of affective states and emotional disorders such pathological anxiety. However, using anxiety-inducing movie clips to probe relevant impacted by psychopathology could risk exacerbating in-scanner movement, decreasing signal quality/quantity thus statistical power. This be especially problematic in target populations children who typically move more the scanner. Consequently, we...

10.31234/osf.io/8k9c4_v1 preprint EN 2024-08-20
Willem B. Bruin Paul Zhutovsky Guido van Wingen Janna Marie Bas‐Hoogendam Nynke A. Groenewold and 95 more Kevin Hilbert Anderson M. Winkler André Zugman Federica Agosta Fredrik Åhs Carmen Andreescu Chase Antonacci Takeshi Asami Michal Assaf Jacques P. Barber Jochen Bauer Shreya Y. Bavdekar Katja Beesdo‐Baum Francesco Benedetti Rachel Bernstein Johannes Björkstrand Robert Blair Karina S. Blair Laura Blanco‐Hinojo Joscha Böhnlein Paolo Brambilla Rodrigo A. Bressan Fabian Breuer Marta Cano Elisa Canu Elise M. Cardinale Narcı́s Cardoner Camilla Cividini Henk Cremers Udo Dannlowski Gretchen J. Diefenbach Katharina Domschke Alex Doruyter Thomas Dresler Angelika Erhardt Massimo Filippi Gregory A. Fonzo Gabrielle F. Freitag Tomas Furmark Tian Ge Andrew J. Gerber Savannah N. Gosnell Hans J. Grabe Dominik Grotegerd Ruben C. Gur Raquel E. Gur Alfons O. Hamm Laura K. M. Han Jennifer L. Harper Anita Harrewijn Alexandre Heeren David Hoffman Andrea Parolin Jackowski Neda Jahanshad Laura Jett Antonia N. Kaczkurkin Parmis Khosravi Ellen Kingsley Tilo Kircher Milutin Kostić Bart Larsen Sang‐Hyuk Lee Elisabeth J. Leehr Ellen Leibenluft Christine Löchner Su Lui Eleonora Maggioni Gisele Gus Manfro Kristoffer Månsson Claire E. Marino Frances Meeten Barbara Milrod Ana Munjiza Benson Irungu Michael Myers Susanne Neufang Jared A. Nielsen Patricia Ohrmann Cristina Ottaviani Martin P. Paulus Michael T. Perino K Luan Phan Sara Poletti Daniel Porta‐Casteràs Jesùs Pujol Andrea Reinecke Grace Ringlein Pavel Rjabtsenkov Karin Roelofs Ramiro Salas Giovanni Abrahão Salum Theodore D. Satterthwaite Elisabeth Schrammen Lisa Sindermann Jordan W. Smoller

Neuroimaging studies point to neurostructural abnormalities in youth with anxiety disorders. Yet, findings are based on small-scale studies, often small effect sizes, and have limited generalizability clinical relevance. These issues prompted a paradigm shift the field towards highly powered (i.e., big data) individual-level inferences, which data-driven, transdiagnostic, neurobiologically informed. Here, we built validated machine learning (ML) models for inferences largest-ever multi-site...

10.31234/osf.io/exrm9 preprint EN 2022-11-23
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