A framework for interpreting functional networks in schizophrenia

Some promising genetic correlates of schizophrenia have emerged in recent years but none explain more than a small fraction of cases. The challenge of our time is to characterize the neuronal networks underlying schizophrenia and other neuropsychiatric illnesses. Early models of schizophrenia have been limited by the ability to readily evaluate large-scale networks in living patients. With the development of resting state and advanced structural magnetic resonance imaging, it has become possible to do this. While we are at an early stage, a number of models of intrinsic brain networks have been developed to account for schizophrenia and other neuropsychiatric disorders. This paper reviews the recent voxel-based morphometry (VBM), diffusion tensor imaging (DTI), and resting functional magnetic resonance imaging literature in light of the proposed networks underlying these disorders. It is suggested that there is support for recently proposed models that suggest a pivotal role for the salience network. However, the interactions of this network with the default mode network and executive control networks are not sufficient to explain schizophrenic symptoms or distinguish them from other neuropsychiatric disorders. Alternatively, it is proposed that schizophrenia arises from a uniquely human brain network associated with directed effort including the dorsal anterior and posterior cingulate cortex (PCC), auditory cortex, and hippocampus while mood disorders arise from a different brain network associated with emotional encoding including the ventral anterior cingulate cortex (ACC), orbital frontal cortex, and amygdala. Both interact with the dorsolateral prefrontal cortex and a representation network including the frontal and temporal poles and the fronto-insular cortex, allowing the representation of the thoughts, feelings, and actions of self and others across time

Fast rates in statistical and online learning

The speed with which a learning algorithm converges as it is presented with more data is a central problem in machine learning --- a fast rate of convergence means less data is needed for the same level of performance. The pursuit of fast rates in online and statistical learning has led to the discovery of many conditions in learning theory under which fast learning is possible. We show that most of these conditions are special cases of a single, unifying condition, that comes in two forms: the central condition for 'proper' learning algorithms that always output a hypothesis in the given model, and stochastic mixability for online algorithms that may make predictions outside of the model. We show that under surprisingly weak assumptions both conditions are, in a certain sense, equivalent. The central condition has a re-interpretation in terms of convexity of a set of pseudoprobabilities, linking it to density estimation under misspecification. For bounded losses, we show how the central condition enables a direct proof of fast rates and we prove its equivalence to the Bernstein condition, itself a generalization of the Tsybakov margin condition, both of which have played a central role in obtaining fast rates in statistical learning. Yet, while the Bernstein condition is two-sided, the central condition is one-sided, making it more suitable to deal with unbounded losses. In its stochastic mixability form, our condition generalizes both a stochastic exp-concavity condition identified by Juditsky, Rigollet and Tsybakov and Vovk's notion of mixability. Our unifying conditions thus provide a substantial step towards a characterization of fast rates in statistical learning, similar to how classical mixability characterizes constant regret in the sequential prediction with expert advice setting.Comment: 69 pages, 3 figure

The neural correlates of regulating positive and negative emotions in medication-free major depression

Depressive cognitive schemas play an important role in the emergence and persistence of major depressive disorder (MDD). The current study adapted emotion regulation techniques to reflect elements of cognitive behavioural therapy (CBT) and related psychotherapies to delineate neurocognitive abnormalities associated with modulating the negative cognitive style in MDD. Nineteen non-medicated patients with MDD and 19 matched controls reduced negative or enhanced positive feelings elicited by emotional scenes while undergoing functional magnetic resonance imaging. Although both groups showed significant emotion regulation success as measured by subjective ratings of affect, the controls were significantly better at modulating both negative and positive emotion. Both groups recruited regions of dorsolateral prefrontal cortex and ventrolateral prefrontal cortex (VLPFC) when regulating negative emotions. Only in controls was this accompanied by reduced activity in sensory cortices and amygdala. Similarly, both groups showed enhanced activity in VLPFC and ventral striatum when enhancing positive affect; however, only in controls was ventral striatum activity correlated with regulation efficacy. The results suggest that depression is associated with both a reduced capacity to achieve relief from negative affect despite recruitment of ventral and dorsal prefrontal cortical regions implicated in emotion regulation, coupled with a disconnect between activity in reward-related regions and subjective positive affect

The PhoBR two-component system regulates antibiotic biosynthesis in Serratia in response to phosphate

<p>Abstract</p> <p>Background</p> <p>Secondary metabolism in <it>Serratia </it>sp. ATCC 39006 (<it>Serratia </it>39006) is controlled via a complex network of regulators, including a LuxIR-type (SmaIR) quorum sensing (QS) system. Here we investigate the molecular mechanism by which phosphate limitation controls biosynthesis of two antibiotic secondary metabolites, prodigiosin and carbapenem, in <it>Serratia </it>39006.</p> <p>Results</p> <p>We demonstrate that a mutation in the high affinity phosphate transporter <it>pstSCAB-phoU</it>, believed to mimic low phosphate conditions, causes upregulation of secondary metabolism and QS in <it>Serratia </it>39006, via the PhoBR two-component system. Phosphate limitation also activated secondary metabolism and QS in <it>Serratia </it>39006. In addition, a <it>pstS </it>mutation resulted in upregulation of <it>rap</it>. Rap, a putative SlyA/MarR-family transcriptional regulator, shares similarity with the global regulator RovA (regulator of virulence) from <it>Yersina </it>spp. and is an activator of secondary metabolism in <it>Serratia </it>39006. We demonstrate that expression of <it>rap</it>, <it>pigA-O </it>(encoding the prodigiosin biosynthetic operon) and <it>smaI </it>are controlled via PhoBR in <it>Serratia </it>39006.</p> <p>Conclusion</p> <p>Phosphate limitation regulates secondary metabolism in <it>Serratia </it>39006 via multiple inter-linked pathways, incorporating transcriptional control mediated by three important global regulators, PhoB, SmaR and Rap.</p

FIR Approximation of Fractional Sample Delay Systems

This paper examines the approximation of fractional delays by FIR systems using various techniques which have previously been reported in the literature. In particular, the equivalence of the time-domain Lagrangian interpolation, the frequency-domain maximally flat error criterion and the window method is shown, provided maximal flatness is specified at $\omega_0 = 0$ and the window used is a scaled binomial function. The first of these has been known before, the second equivalence is new

MEPicides: Potent antimalarial prodrugs targeting isoprenoid biosynthesis

AbstractThe emergence of Plasmodium falciparum resistant to frontline therapeutics has prompted efforts to identify and validate agents with novel mechanisms of action. MEPicides represent a new class of antimalarials that inhibit enzymes of the methylerythritol phosphate (MEP) pathway of isoprenoid biosynthesis, including the clinically validated target, deoxyxylulose phosphate reductoisomerase (Dxr). Here we describe RCB-185, a lipophilic prodrug with nanomolar activity against asexual parasites. Growth of P. falciparum treated with RCB-185 was rescued by isoprenoid precursor supplementation, and treatment substantially reduced metabolite levels downstream of the Dxr enzyme. In addition, parasites that produced higher levels of the Dxr substrate were resistant to RCB-185. Notably, environmental isolates resistant to current therapies remained sensitive to RCB-185, the compound effectively treated sexually-committed parasites, and was both safe and efficacious in malaria-infected mice. Collectively, our data demonstrate that RCB-185 potently and selectively inhibits Dxr in P. falciparum, and represents a promising lead compound for further drug development.</jats:p