A principled method to identify individual differences and behavioral shifts in signaled active avoidance

A.M. Krypotos, J.M. Moscarello, R.M. Sears, J.E. LeDoux, I. Galatzer-Levy

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Signaled active avoidance (SigAA) is the key experimental procedure for studying theacquisition of instrumental responses towards conditioned threat cues. Traditional analyticapproaches (e.g. general linear model) often obfuscate important individual differences. However,individual differences models (e.g. latent growth curve modeling) typically require large samplesand onerous computational methods. Here, we present an analytic methodology that enables thedetection of individual differences in SigAA performance at a high accuracy based at the n=1level. We further show an online software that enables the easy application of our method to anySigAA data set.
Original languageEnglish
Pages (from-to)564-568
JournalLearning and Memory
Volume25
Issue number11
DOIs
Publication statusPublished - 2018

Keywords

  • anxiety disorders
  • psychopathology
  • fear
  • defensive behaviors

Fingerprint

Dive into the research topics of 'A principled method to identify individual differences and behavioral shifts in signaled active avoidance'. Together they form a unique fingerprint.

Cite this