Symptom comorbidity is present amongst neuropsychiatric disorders with repetitive behaviours, complicating clinical diagnosis and impeding appropriate treatments. This is of particular importance for obsessive-compulsive disorder (OCD) and Tourette syndrome. Here, we meticulously analysed the behaviour of Sapap3 knockout mice, the recent rodent model predominantly used to study compulsive-like behaviours, and found that its behaviour is more complex than originally and persistently described. Indeed, we detected previously unreported elements of distinct pathologically repetitive behaviours, which do not form part of rodent syntactic cephalo-caudal self-grooming. These repetitive behaviours include sudden, rapid body and head/body twitches, resembling tic-like movements. We also observed that another type of repetitive behaviour, aberrant hindpaw scratching, might be responsible for the flagship-like skin lesions of this mouse model. In order to characterise the symptomatological nature of observed repetitive behaviours, we pharmacologically challenged these phenotypes by systemic aripiprazole administration, a first-line treatment for tic-like symptoms in Tourette syndrome and trichotillomania. A single treatment of aripiprazole significantly reduced the number of head/body twitches, scratching, and single-phase grooming, but not syntactic grooming events. These observations are in line with the high comorbidity of tic- and compulsive-like symptoms in Tourette, OCD and trichotillomania patients.

The Fisher information metric provides a smooth family of probability measures with a Riemannian manifold structure, which is an object in information geometry. The information geometry of the gamma manifold associated with the family of gamma distributions has been well studied. However, only a few results are known for the generalized gamma family that adds an extra shape parameter. The present article gives some new results about the generalized gamma manifold. This paper also introduces an application in medical imaging that is the classification of Alzheimer's disease population. In the medical field, over the past two decades, a growing number of quantitative image analysis techniques have been developed, including histogram analysis, which is widely used to quantify the diffuse pathological changes of some neurological diseases. This method presents several drawbacks. Indeed, all the information included in the histogram is not used and the histogram is an overly simplistic estimate of a probability distribution. Thus, in this study, we present how using information geometry and the generalized gamma manifold improved the performance of the classification of Alzheimer's disease population.