Work

Author response: Computational modeling of threat learning reveals links with anxiety and neuroanatomy in humans

Year: 2021

Type: peer-review

Abstract: Applying computational modeling to quantify threat learning processes uncovers how variations in these conserved learning processes relate to anxiety severity and the neuroanatomical substrates moderating these associations.

DOI: 10.7554/elife.66169.sa2

Authors: Rany Abend, Diana Burk, Sonia G Ruiz, Andrea L Gold, Julia L Napoli, Jennifer C Britton, Kalina J Michalska, Tomer Shechner, Anderson M Winkler, Ellen Leibenluft, Daniel S Pine, Bruno B Averbeck

Institutions: National Institutes of Health, National Institute of Mental Health, Brown University, University of Miami, University of California, Riverside, University of Haifa

Language: English

Topic: Memory and Neural Mechanisms

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

OpenAlex ID: W4285314704

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