Pharmacological characterization of BDNF promoters I, II and IV reveals that serotonin and norepinephrine input is sufficient for transcription activation.

Compelling evidence has shown that the effects of antidepressants, increasing extracellular serotonin and noradrenaline as a primary mechanism of action, involve neuroplastic and neurotrophic mechanisms. Brain-derived neurotrophic factor (BDNF) has been shown to play a key role in neuroplasticity and synaptic function, as well as in the pathophysiology of neuropsychiatric disorders and the mechanism of action of antidepressants. The expression of BDNF is mediated by the transcription of different mRNAs derived by the splicing of one of the eight 5' non-coding exons with the 3' coding exon (in rats).

Voxel scale complex networks of functional connectivity in the rat brain: neurochemical state dependence of global and local topological properties.

Network analysis of functional imaging data reveals emergent features of the brain as a function of its topological properties. However, the brain is not a homogeneous network, and the dependence of functional connectivity parameters on neuroanatomical substrate and parcellation scale is a key issue. Moreover, the extent to which these topological properties depend on underlying neurochemical changes remains unclear.

Plasma protein biomarkers for depression and schizophrenia by multi analyte profiling of case-control collections.

Despite significant research efforts aimed at understanding the neurobiological underpinnings of psychiatric disorders, the diagnosis and the evaluation of treatment of these disorders are still based solely on relatively subjective assessment of symptoms. Therefore, biological markers which could improve the current classification of psychiatry disorders, and in perspective stratify patients on a biological basis into more homogeneous clinically distinct subgroups, are highly needed. In order to identify novel candidate biological markers for major depression and schizophrenia, we have applied a focused proteomic approach using plasma samples from a large case-control collection.

Community structure in networks of functional connectivity: resolving functional organization in the rat brain with pharmacological MRI.

In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline).