Translating a rodent measure of negative bias into humans: the impact of induced anxiety and unmedicated mood and anxiety disorders

Jessica Aylward, Claire Hales, Emma Robinson, Oliver Robinson

Research output: Contribution to journalArticle (Academic Journal)peer-review

7 Citations (Scopus)
305 Downloads (Pure)

Abstract

BackgroundMood and anxiety disorders are ubiquitous but current treatment options are ineffective for many sufferers. Moreover, a number of promising pre-clinical interventions have failed to translate into clinical efficacy in humans. Improved treatments are unlikely without better animal-human translational pipelines. Here, we translate a rodent measure of negative affective bias into humans, exploring its relationship with (1) pathological mood and anxiety symptoms and (2) transient induced anxiety.MethodsAdult participants (age = 29 ± 11) who met criteria for mood or anxiety disorder symptomatology according to a face-to-face neuropsychiatric interview were included in the symptomatic group. Study 1 included N = 77 (47 = asymptomatic [female = 21]; 30 = symptomatic [female = 25]), study 2 included N = 47 asymptomatic participants (25 = female). Outcome measures were choice ratios, reaction times and parameters recovered from a computational model of reaction time - the drift diffusion model (DDM) - from a two-alternative-forced-choice task in which ambiguous and unambiguous auditory stimuli were paired with high and low rewards.ResultsBoth groups showed over 93% accuracy on unambiguous tones indicating intact discrimination, but symptomatic individuals demonstrated increased negative affective bias on ambiguous tones [proportion high reward = 0.42 (s.d. = 0.14)] relative to asymptomatic individuals [0.53 (s.d. = 0.17)] as well as a significantly reduced DDM drift rate. No significant effects were observed for the within-subjects anxiety-induction.ConclusionsHumans with pathological anxiety symptoms directly mimic rodents undergoing anxiogenic manipulation. The lack of sensitivity to transient anxiety suggests the paradigm might be more sensitive to clinically relevant symptoms. Our results establish a direct translational pipeline (and candidate therapeutics screen) from negative affective bias in rodents to pathological mood and anxiety symptoms in humans.

Original languageEnglish
Number of pages10
JournalPsychological Medicine
Early online date26 Jan 2019
DOIs
Publication statusE-pub ahead of print - 26 Jan 2019

Keywords

  • Affective bias
  • anxiety
  • back-translation
  • computational psychiatry
  • depression
  • drift diffusion model

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