Behavioral flexibility in a mouse model for obsessive-compulsive disorder: Impaired Pavlovian reversal learning in SAPAP3 mutants.

Obsessive-compulsive disorder (OCD) is characterized by obsessive thinking, compulsive behavior and anxiety, and is often accompanied by cognitive deficits. The neuropathology of OCD involves dysregulation of cortical-striatal circuits. Similar to OCD patients, SAPAP3 knockout mice 3 (SAPAP3-/- ) exhibit compulsive behavior (grooming), anxiety and dysregulated cortical-striatal function. However, it is unknown whether SAPAP3-/- display cognitive deficits and how these different behavioral traits relate to one another. SAPAP3-/- and wild-type (WT) littermates were trained in a Pavlovian conditioning task pairing visual cues with the delivery of sucrose solution. After mice learned to discriminate between a reward-predicting conditioned stimulus (CS+) and a non-reward stimulus (CS-), contingencies were reversed (CS+ became CS- and vice versa). Additionally, we assessed grooming, anxiety and general activity. SAPAP3-/- acquired Pavlovian approach behavior similarly to WT, albeit less vigorously and with a different strategy. However, unlike WT, SAPAP3-/- were unable to adapt their behavior after contingency reversal, exemplified by a lack of re-establishing CS+ approach behavior (sign tracking). Surprisingly, such behavioral inflexibility, decreased vigor, compulsive grooming and anxiety were unrelated. This study shows that SAPAP3-/- are capable of Pavlovian learning, but lack flexibility to adapt associated conditioned approach behavior. Thus, SAPAP3-/- not only display compulsive-like behavior and anxiety, but also cognitive deficits, confirming and extending the validity of SAPAP3-/- as a suitable model for the study of OCD. The observation that compulsive-like behavior, anxiety and behavioral inflexibility were unrelated suggests a non-causal relationship between these traits and may be of clinical relevance for the treatment of OCD.

Automated classification of self-grooming in mice using open-source software.

BACKGROUND: Manual analysis of behavior is labor intensive and subject to inter-rater variability. Although considerable progress in automation of analysis has been made, complex behavior such as grooming still lacks satisfactory automated quantification. NEW METHOD: We trained a freely available, automated classifier, Janelia Automatic Animal Behavior Annotator (JAABA), to quantify self-grooming duration and number of bouts based on video recordings of SAPAP3 knockout mice (a mouse line that self-grooms excessively) and wild-type animals. RESULTS: We compared the JAABA classifier with human expert observers to test its ability to measure self-grooming in three scenarios: mice in an open field, mice on an elevated plus-maze, and tethered mice in an open field. In each scenario, the classifier identified both grooming and non-grooming with great accuracy and correlated highly with results obtained by human observers. Consistently, the JAABA classifier confirmed previous reports of excessive grooming in SAPAP3 knockout mice. COMPARISON WITH EXISTING METHODS: Thus far, manual analysis was regarded as the only valid quantification method for self-grooming. We demonstrate that the JAABA classifier is a valid and reliable scoring tool, more cost-efficient than manual scoring, easy to use, requires minimal effort, provides high throughput, and prevents inter-rater variability. CONCLUSION: We introduce the JAABA classifier as an efficient analysis tool for the assessment of rodent self-grooming with expert quality. In our "how-to" instructions, we provide all information necessary to implement behavioral classification with JAABA.