Chronic Unpredictable Stress Protocol

The chronic unpredictable stress (CUS) protocol, also known as chronic mild stress (CMS) or chronic unpredictable mild stress (CUMS), is the most widely used animal model for inducing a depression-like phenotype through prolonged exposure to a rotating battery of mild stressors over 3-6 weeks. Originally developed by Willner (1987), the model produces anhedonia, behavioral despair, anxiety, cognitive deficits, HPA axis dysregulation, reduced hippocampal neurogenesis, and neuroinflammatory changes that parallel core features of human major depressive disorder. The unpredictable nature of the stressor schedule prevents habituation and models the cumulative toll of chronic psychosocial stress. Neural circuit adaptations span the prefrontal cortex (dendritic retraction), hippocampus (reduced BDNF, impaired neurogenesis), amygdala (dendritic hypertrophy), and mesolimbic dopamine system (reduced reward sensitivity).

The CUS battery typically includes 8-12 different stressors applied in a pseudo-random sequence: restraint stress, wet bedding, cage tilt, social isolation, crowded housing, food or water deprivation, reversed light-dark cycle, continuous illumination, cold exposure, white noise, and stroboscopic lighting. No single stressor is repeated on consecutive days, and the schedule is unpredictable to the animal. Dependent variables are not measured during CUS itself but rather through periodic behavioral readouts including the sucrose preference test (anhedonia), forced swim test (despair), open field (anxiety-locomotion), elevated plus maze (anxiety), novelty-suppressed feeding (conflict), and coat state scoring (self-care). Body weight and corticosterone levels provide physiological markers.

ConductMaze manages the entire CUS protocol as an automated scheduling system: it generates pseudo-random stressor sequences, sends daily alerts to experimenters with stressor assignments, tracks compliance with protocol timing, schedules periodic behavioral assessments at defined intervals, and compiles longitudinal data across all readout measures. The software ensures no two consecutive days share the same stressor, manages light-cycle disruption timing, and generates publication-ready timeline figures showing stressor exposure and behavioral readout trajectories.