Cognitive bias in the chick anxiety–depression model

Pharmacological reversal of cognitive bias in the chick anxiety-depression model

Cognitive bias presents in clinical populations where anxious individuals adopt a more pessimistic interpretation of ambiguous aversive stimuli and depressed individuals adopt both a more pessimistic interpretation of ambiguous aversive stimuli and a less optimistic interpretation of ambiguous appetitive stimuli. These biases have been reversed by anxiolytics and antidepressants. In the current study, chicks exposed to an isolation stressor of 5-min to induce an anxiety-like state or 60-min to induce a depressive-like state were tested in a straight alley maze to a series of morphed ambiguous appetitive (chick silhouette) to aversive (owl silhouette) cues. Chicks in the depression-like state displayed more pessimistic-like and less optimistic-like approach behavior to ambiguous aversive and appetitive cues, respectively. Both forms of cognitive bias were reversed by 15.0 mg/kg imipramine. Chicks in anxiety-like state displayed more pessimistic-like approach behavior under the ambiguous aversive stimulus cues. However, 0.10 mg/kg clonidine produced modest sedation and thus, was ineffective at reversing this bias. The observation that cognitive biases of more pessimism and less optimism can be reversed in the depression-like phase by imipramine adds to the validity of the chick anxiety-depression model as a neuropsychiatric simulation. This article is part of a Special Issue entitled 'Anxiety and Depression'.

Experimental models for anxiolytic drug discovery in the era of omes and omics

INTRODUCTION

Animal behavioral models have become an indispensable tool for studying anxiety disorders and testing anxiety-modulating drugs. However, significant methodological and conceptual challenges affect the translational validity and accurate behavioral dissection in such models. They are also often limited to individual behavioral domains and fail to target the disorder's real clinical picture (its spectrum or overlap with other disorders), which hinder screening and development of novel anxiolytic drugs.

AREAS COVERED

In this article, the authors discuss and emphasize the importance of high-throughput multi-domain neurophenotyping based on the latest developments in video-tracking and bioinformatics. Additionally, the authors also explain how bioinformatics can provide new insight into the neural substrates of brain disorders and its benefit for drug discovery.

EXPERT OPINION

The throughput and utility of animal models of anxiety and other brain disorders can be markedly increased by a number of ways: i) analyzing systems of several domains and their interplay in a wider spectrum of model species; ii) using a larger number of end points generated by video-tracking tools; iii) correlating behavioral data with genomic, proteomic and other physiologically relevant markers using online databases and iv) creating molecular network-based models of anxiety to identify new targets for drug design and discovery. Experimental models utilizing bioinformatics tools and online databases will not only improve our understanding of both gene-behavior interactions and complex trait interconnectivity but also highlight new targets for novel anxiolytic drugs.