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Neurobiology and the Hierarchical Taxonomy of Psychopathology: Progress toward ontogenetically informed and clinically useful nosology

  • Emily R. Perkins
  • , Keanan J. Joyner
  • , Christopher J. Patrick
  • , Bruce D. Bartholow
  • , Robert D. Latzman
  • , Colin G. DeYoung
  • , Roman Kotov
  • , Ulrich Reininghaus
  • , Samuel E. Cooper
  • , Mohammad H. Afzali
  • , Anna R. Docherty
  • , Michael N. Dretsch
  • , Nicholas R. Eaton
  • , Vina M. Goghari
  • , John D. Haltigan
  • , Robert F. Krueger
  • , Elizabeth A. Martin
  • , Giorgia Michelini
  • , Anthony C. Ruocco
  • , Jennifer L. Tackett
  • Noah C. Venables, Irwin D. Waldman, David H. Zald
  • Florida State University
  • University of Missouri
  • Georgia State University
  • University of Minnesota Twin Cities
  • Heidelberg University 
  • University of Texas at Austin
  • University of Montreal
  • University of Utah
  • Joint Base Lewis-McCord
  • University of Toronto
  • University of California at Irvine
  • Stony Brook University
  • Northwestern University
  • Minneapolis Veterans Affairs Health Care System
  • Emory University
  • Vanderbilt University

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical structural model of psychological symptoms formulated to improve the reliability and validity of clinical assessment. Neurobiology can inform assessments of early risk and intervention strategies, and the HiTOP model has greater potential to interface with neurobiological measures than traditional categorical diagnoses given its enhanced reliability. However, one complication is that observed biological correlates of clinical symptoms can reflect various factors, ranging from dispositional risk to consequences of psychopathology. In this paper, we argue that the HiTOP model provides an optimized framework for conducting research on the biological correlates of psychopathology from an ontogenetic perspective that distinguishes among indicators of liability, current symptoms, and consequences of illness. Through this approach, neurobiological research can contribute more effectively to identifying individuals at high dispositional risk, indexing treatment-related gains, and monitoring the consequences of mental illness, consistent with the aims of the HiTOP framework.

Original languageEnglish
Pages (from-to)51-63
Number of pages13
JournalDialogues in Clinical Neuroscience
Volume22
Issue number1
DOIs
StatePublished - Mar 2020

Keywords

  • Dimensional
  • Hierarchical Taxonomy of Psychopathology
  • Liability
  • Neurobiology
  • Ontogenetic
  • Psychopathology
  • RDoC

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