@article{MouraoMirandaHardoonHahnetal.2011, author = {Mour{\~a}o-Miranda, Janaina and Hardoon, David R. and Hahn, Tim and Marquand, Andre F. and Williams, Steve C.R. and Shawe-Taylor, John and Brammer, Michael}, title = {Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine}, series = {NeuroImage}, volume = {58}, journal = {NeuroImage}, number = {3}, doi = {10.1016/j.neuroimage.2011.06.042}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-141412}, pages = {793-804}, year = {2011}, abstract = {Pattern recognition approaches, such as the Support Vector Machine (SVM), have been successfully used to classify groups of individuals based on their patterns of brain activity or structure. However these approaches focus on finding group differences and are not applicable to situations where one is interested in accessing deviations from a specific class or population. In the present work we propose an application of the one-class SVM (OC-SVM) to investigate if patterns of fMRI response to sad facial expressions in depressed patients would be classified as outliers in relation to patterns of healthy control subjects. We defined features based on whole brain voxels and anatomical regions. In both cases we found a significant correlation between the OC-SVM predictions and the patients' Hamilton Rating Scale for Depression (HRSD), i.e. the more depressed the patients were the more of an outlier they were. In addition the OC-SVM split the patient groups into two subgroups whose membership was associated with future response to treatment. When applied to region-based features the OC-SVM classified 52\% of patients as outliers. However among the patients classified as outliers 70\% did not respond to treatment and among those classified as non-outliers 89\% responded to treatment. In addition 89\% of the healthy controls were classified as non-outliers.}, language = {en} } @article{RantamaekiVesaAntilaetal.2011, author = {Rantam{\"a}ki, Tomi and Vesa, Liisa and Antila, Hanna and Di Lieto, Antonio and Tammela, P{\"a}ivi and Schmitt, Angelika and Lesch, Klaus-Peter and Rios, Maribel and Castr{\´e}n, Eero}, title = {Antidepressant Drugs Transactivate TrkB Neurotrophin Receptors in the Adult Rodent Brain Independently of BDNF and Monoamine Transporter Blockade}, series = {PLoS ONE}, volume = {6}, journal = {PLoS ONE}, number = {6}, doi = {10.1371/journal.pone.0020567}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-133746}, pages = {e20567}, year = {2011}, abstract = {Background: Antidepressant drugs (ADs) have been shown to activate BDNF (brain-derived neurotrophic factor) receptor TrkB in the rodent brain but the mechanism underlying this phenomenon remains unclear. ADs act as monoamine reuptake inhibitors and after prolonged treatments regulate brain bdnf mRNA levels indicating that monoamine-BDNF signaling regulate AD-induced TrkB activation in vivo. However, recent findings demonstrate that Trk receptors can be transactivated independently of their neurotrophin ligands. Methodology: In this study we examined the role of BDNF, TrkB kinase activity and monoamine reuptake in the AD-induced TrkB activation in vivo and in vitro by employing several transgenic mouse models, cultured neurons and TrkB-expressing cell lines. Principal Findings: Using a chemical-genetic TrkB(F616A) mutant and TrkB overexpressing mice, we demonstrate that ADs specifically activate both the maturely and immaturely glycosylated forms of TrkB receptors in the brain in a TrkB kinase dependent manner. However, the tricyclic AD imipramine readily induced the phosphorylation of TrkB receptors in conditional bdnf(-/-) knock-out mice (132.4+/-8.5\% of control; P = 0.01), indicating that BDNF is not required for the TrkB activation. Moreover, using serotonin transporter (SERT) deficient mice and chemical lesions of monoaminergic neurons we show that neither a functional SERT nor monoamines are required for the TrkB phosphorylation response induced by the serotonin selective reuptake inhibitors fluoxetine or citalopram, or norepinephrine selective reuptake inhibitor reboxetine. However, neither ADs nor monoamine transmitters activated TrkB in cultured neurons or cell lines expressing TrkB receptors, arguing that ADs do not directly bind to TrkB. Conclusions: The present findings suggest that ADs transactivate brain TrkB receptors independently of BDNF and monoamine reuptake blockade and emphasize the need of an intact tissue context for the ability of ADs to induce TrkB activity in brain.}, language = {en} }