Cocaine use severity and cerebellar gray matter are associated with reversal learning deficits in cocaine-dependent individuals

Cocaine addiction involves persistent deficits to unlearn previously rewarded response options, potentially due to neuroadaptations in learning-sensitive regions. Cocaine-targeted prefrontal systems have been consistently associated with reinforcement learning and reversal deficits, but more recent interspecies research has raised awareness about the contribution of the cerebellum to cocaine addiction and reversal. We aimed at investigating the link between cocaine use, reversal learning and prefrontal, insula and cerebellar gray matter in cocaine-dependent individuals (CDIs) varying on levels of cocaine exposure in comparison with healthy controls (HCs). Twenty CDIs and 21 HCs performed a probabilistic reversal learning task (PRLT) and were subsequently scanned in a 3-Tesla magnetic resonance imaging scanner. In the PRLT, subjects progressively learn to respond to one predominantly reinforced stimulus, and thenmust learn to respond according to the opposite, previously irrelevant, stimulus-reward pairing. Performance measureswere errors after reversal (reversal cost), and probability of maintaining response after errors. Voxel-based morphometry was conducted to investigate the association between gray matter volume in the regions of interest and cocaine use and PRLT performance. Severity of cocaine use correlated with gray matter volume reduction in the left cerebellum (lobule VIII), while greater reversal cost was correlated with gray matter volume reduction in a partially overlapping cluster (lobules VIIb and VIII). Right insula/inferior frontal gyrus correlated with probability of maintaining response after errors. Severity of cocaine use detrimentally impacted reversal learning and cerebellar gray matter.

Segmentation of gray scale image based on intuitionistic fuzzy sets constructed from several membership functions

Segmentation is the process of extraction of objects from an image. This paper proposes a new algorithm to construct intuitionistic fuzzy set (IFS) from multiple fuzzy sets as an application to image segmentation. Hesitation degree in IFS is formulated as the degree of ignorance (due to the lack of knowledge) to determine whether the chosen membership function is best for image segmentation. By minimizing entropy of IFS generated from various fuzzy sets, an image is thresholded. Experimental results are provided to show the effectiveness of the proposed method.

An integrative approach to characterize Malagasy bats of the subfamily Vespertilioninae Gray, 1821, with the description of a new species of Hypsugo

© 2015 The Linnean Society of London. Although important advances have been made in recent years in the taxonomy of different families and subfamilies of Malagasy bats, those belonging to the Vespertilioninae remain partially unresolved. Herein using a mitochondrial marker (cytochrome b) as the point of departure for 76 specimens of Malagasy vespers and appropriate African taxa, we diagnose the six taxa of this subfamily on the island by overlaying different morphological and bioacoustic characters on the clade structure of sequenced animals. The species include: endemic Neoromicia matroka, which is sister to African N. capensis; endemics N. malagasyensis and N. robertsi, which form sister species; a member of the genus Hypsugo, which is sister to African H. anchietae and described herein as new to science; Pipistrellus hesperidus for which Madagascar animals are genetically close but distinct from African populations of the same species; and endemic P. raceyi, which shows segregation of eastern (mesic) and western (dry) populations and its sister species relationships are unresolved. While the external and craniodental measurements, as well as bioacoustic variables, allow only partial differentiation of these six species of Vespertilioninae, molecular characters provide definitive separation of the taxa, as do male bacular morphology.