Brain disorders? Precisely

By Thomas R. Insel, B. Cuthbert. Science, 2015

669 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Pharmacology, Psychiatry and Mental health

View Paper: https://www.semanticscholar.org/paper/767272e61ba417ee0db5f491f8a756089e008a11

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Zening Fu
2. Yuhui Du
3. Vince D. Calhoun
4. Martin P. Paulus
5. Sarah Graham
6. Ho-Cheol Kim
7. Ralph Adolphs
8. J. Dubois

In Pharmacology

1. Vince D. Calhoun

In Psychiatry and Mental health

1. Vince D. Calhoun
2. Martin P. Paulus
3. M. de Choudhury
4. Ralph Adolphs
5. J. Dubois
6. Dilip Jeste

Citations in the corpus

• Coping, Emotion Regulation and Psychopathology in Childhood and Adolescence: A Meta-Analysis and Narrative Review (2017, background): “Further, the National Institute of Mental Health Research Domain Criteria (RDoC; Casey, Oliveri, & Insel, 2014; Insel & Cuthbert, 2015) represents a dimensional framework that conceptualizes mechanisms underlying psychopathology in five domains (negative valence systems, positive valence systems,…”
• Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging (2018, background): “…ultimate goal of identifying biomarkers and diagnosing brain disorders using neuroimagebased measures is promising but challenging, due to the fact that the current diagnostic categorization itself used as prior guidance could be inaccurate and need further refinement (Insel and Cuthbert, 2015).”
• Artificial Intelligence for Mental Healthcare: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom (2021, background): “AI may further complement clinical intuition by enhancing diagnostic accuracy by supporting the clinical reasoning process (13) and advancing the mechanistic understanding of mental illnesses (14,15).”
• Building a Science of Individual Differences from fMRI. (2016, background): “In the future, we may be able to interpret the fMRI-derived statistic of an individual subject in light of its distribution in a normative sample, provided that absolute reliability is achieved; this approach could lead, for clinical imaging, to a more biologically informed science of human neuropsy”