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

Background Mood and anxiety disorders are ubiquitous but current treatment options are ineffective for large numbers of sufferers. Moreover, recent years have seen a number of promising pre-clinical interventions fail to translate into clinical efficacy in humans. Improved treatments are unlikely without better animal-human translational pipelines. Here, we directly adapt–i.e. back-translate - a rodent measure of negative affective bias into humans, and explore its relationship with a)pathological mood and anxiety symptoms (study one) and b)transient induced anxiety (study two). Method Participants who met criteria for mood or anxiety disorder symptomatology according to a face-to-face neuropsychiatric interview were included in the symptomatic group. N = 77(47 asymptomatic; Female = 21; 30 symptomatic; Female = 25) participants completed study one and N = 47 asymptomatic participants (25 female) completed study two. Outcome measures were choice ratios, reaction times and parameters recovered from a computational model of reaction time; the drift diffusion model (DDM). Results Symptomatic individuals demonstrated increased negative affective bias relative to asymptomatic individuals (proportion high reward = 0.42(SD = 0.14), and 0.53(SD = 0.17), respectively) as well as reduced DDM drift rate (p = 0.004). No significant effects were observed for the within-subjects anxiety-induction in study 2. Conclusion Humans with pathological anxiety symptoms directly mimic rodents undergoing anxiogenic manipulation. The lack of sensitivity to transient anxiety suggests the paradigm may, moreover, be primarily 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, and link it to a computational model of reaction time.