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Contains fulltext : 151733.pdf (Publisher’s version ) (Open Access) An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow. 10 p.

During the past decade, it has been shown that circadian clock genes have more than a simple circadian time-keeping role. Clock genes also modulate motivational processes and have been implicated in the development of psychiatric disorders such as drug addiction. Recent studies indicate that casein-kinase 1ɛ/δ (CK1ɛ/δ)—one of the components of the circadian molecular clockwork—might be involved in the etiology of addictive behavior. The present study was initiated to study the specific role of CK1ɛ/δ in alcohol relapse-like drinking using the ‘Alcohol Deprivation Effect’ model. The effect of CK1ɛ/δ inhibition was tested on alcohol consumption in long-term alcohol-drinking rats upon re-exposure to alcohol after deprivation using a four-bottle free-choice paradigm with water, 5%, 10%, and 20% ethanol solutions, as well as on saccharin preference in alcohol-naive rats. The inhibition of CK1ɛ/δ with systemic PF-670462 (0, 10, and 30 mg/kg) injections dose-dependently decreased, and at a higher dosage prevented the alcohol deprivation effect, as compared with vehicle-treated rats. The impact of the treatment was further characterized using nonlinear regression analyses on the daily profiles of drinking and locomotor activity. We reveal that CK1ɛ/δ inhibition blunted the high daytime alcohol intake typically observed upon alcohol re-exposure, and induced a phase shift of locomotor activity toward daytime. Only the highest dose of PF-670462 shifted the saccharin intake daily rhythm toward daytime during treatment, and decreased saccharin preference after treatment. Our data suggest that CK1 inhibitors may be candidates for drug treatment development for alcoholism.