Oxytocin Affects the Connectivity of the Precuneus and the Amygdala: A Randomized, Double-Blinded, Placebo-Controlled Neuroimaging Trial

BACKGROUND: Although oxytocin is one of the most widely studied neuropeptides in recent times, the mechanistic process by which it modulates social-affective behavior in the brain is not yet clearly understood. Thus, to understand the neurophysiological basis of oxytocin effects, we used resting-state functional MRI to examine the effects of intranasal oxytocin on brain connectivity in healthy males. METHODS: Using a randomized, double-blinded, placebo-controlled, crossover design, 15 healthy male volunteers received 24 IU intranasal oxytocin or placebo prior to resting-state functional MRI acquisition at 3T. RESULTS: We found that oxytocin significantly reduced the degree centrality of the right precuneus (P<.05). Oxytocin also reduced connectivity between the bilateral amygdalae and between the right precuneus and the right and left amygdala (P<.05). Although there were no significant changes in regional homogeneity at the whole brain level, posthoc results showed a reduction involving the right precuneus (P<.05). CONCLUSIONS: These results show that oxytocin affects one of the key centers in the brain for social cognition and introspective processing, the precuneus, and enhances our understanding of how oxytocin can modulate brain networks at rest. An improved understanding of the neurophysiological effects of oxytocin can be important in terms of evaluating the mechanisms that are likely to underlie the clinical responses observed upon long-term oxytocin administration

Deviant cortical sulcation related to schizophrenia and cognitive deficits in the second trimester

Aberrant cortical development, inferred from cortical folding, is linked to the risk of schizophrenia. Cortical folds develop in a time-locked fashion during fetal growth. We leveraged this temporal specificity of sulcation to investigate the timing of the prenatal insult linked to schizophrenia and the cognitive impairment seen in this illness. Anatomical MRI scans from 68 patients with schizophrenia and 72 controls were used to evaluate the sulcal depth of five major invariable primary sulci representing lobar development (calcarine sulcus, superior temporal sulcus, superior frontal sulcus, intraparietal sulcus and inferior frontal sulcus) with formation representing the distinct developmental periods. A repeated-measure ANOVA with five sulci and two hemispheres as the within-subject factors and gender, age and intracranial volume as covariates revealed a significant effect of diagnosis (F[1,134] = 14.8, p = 0.0002). Control subjects had deeper bilateral superior temporal, right inferior frontal and left calcarine sulci. A deeper superior frontal sulcus predicted better cognitive scores among patients. Our results suggest that the gestational disruption underlying schizophrenia is likely to predate, if not coincide with the appearance of calcarine sulcus (early second trimester). Nevertheless, the burden of cognitive deficits may relate specifically to the aberrant superior frontal development apparent in late second trimester

Salience network in psychosis

This thesis explores the role of a large-scale brain network comprising of the insula and anterior cingulate cortex in the pathophysiology of psychosis using structural and functional neuroimaging. Primarily, anatomical changes affecting the grey matter structure and patterns of dysconnectivity involving the insula are investigated. Various meta-analytic studies have reported consistent reduction in insular grey matter across various psychotic disorders. Despite these robust observations, the role played by this brain region in the generation of psychotic symptoms remains unexplored. In this thesis, using a meta-analytic approach, the relevance of insula for the clinical expression of psychosis is highlighted. Further, significant reduction in the cortical folding of the insula was noted in patients with schizophrenia. Reduced gyrification is accompanied by reduced functional connectivity between the insula and the rest of the brain. Using an effective connectivity approach (Granger Causal Analysis), the primacy of insula in driving the dorsolateral prefrontal cortex is demonstrated in healthy controls; this relationship is significantly affected in schizophrenia amounting to aberrant connectivity within a putative salience-execution loop. Reduced primacy of the salience-execution loop relates to illness severity. It is argued that the insula, as a key region of the salience network, plays a crucial role in the generation of symptoms of psychosis. The evidence in support of this theory is discussed, together with its implications for clinical practice aimed at reducing the burden of psychosis

Statistical optimization of substrate, carbon and nitrogen source by response surface methodology for pectinase production using Aspergillus fumigatus MTCC 870 in submerged fermentation

Optimization procedure using response surface methodology (RSM) based on face centered central composite design (FCCCD) with three factors (concentrations of wheat flour, glucose and ammonium nitrate) was used in order to investigate the effect of these parameters on the production of pectinase from Aspergillus fumigatus MTCC 870. According to the results of RSM, concentrations of wheat flour, glucose and ammonium nitrate were significant (

Clinical Utility of Machine-Learning Approaches in Schizophrenia: Improving Diagnostic Confidence for Translational Neuroimaging

Machine-learning approaches are becoming commonplace in the neuroimaging literature as potential diagnostic and prognostic tools for the study of clinical populations. However, very few studies provide clinically informative measures to aid in decision-making and resource allocation. Head-to-head comparison of neuroimaging-based multivariate classifiers is an essential first step to promote translation of these tools to clinical practice. We systematically evaluated the classifier performance using back-to-back structural MRI in two field strengths (3- and 7-T) to discriminate patients with schizophrenia (n = 19) from healthy controls (n = 20). Gray matter (GM) and white matter images were used as inputs into a support vector machine to classify patients and control subjects. Seven Tesla classifiers outperformed the 3-T classifiers with accuracy reaching as high as 77% for the 7-T GM classifier compared to 66.6% for the 3-T GM classifier. Furthermore, diagnostic odds ratio (a measure that is not affected by variations in sample characteristics) and number needed to predict (a measure based on Bayesian certainty of a test result) indicated superior performance of the 7-T classifiers, whereby for each correct diagnosis made, the number of patients that need to be examined using the 7-T GM classifier was one less than the number that need to be examined if a different classifier was used. Using a hypothetical example, we highlight how these findings could have significant implications for clinical decision-making. We encourage the reporting of measures proposed here in future studies utilizing machine-learning approaches. This will not only promote the search for an optimum diagnostic tool but also aid in the translation of neuroimaging to clinical use