Assessment of the potentials and limitations of cortical-based analysis for the integration of structure and function in normal and pathological brains using MRI

The software package Brainvisa (www.brainvisa.tnfo) offers a wide range of possibilities for cortical analysis using its automatic sulci recognition feature. Automated sulci identification is an attractive feature as the manual labelling of the cortical sulci is often challenging even for the experienced neuro-radiologists. This can also be of interest in fMRI studies of individual subjects where activated regions of the cortex can simply be identified using sulcal labels without the need for normalization to an atlas. As it will be explained later in this thesis, normalization to atlas can especially be problematic for pathologic brains. In addition, Brainvisa allows for sulcal morphometry from structural MR images by estimating a wide range of sulcal properties such as size, coordinates, direction, and pattern. Morphometry of abnormal brains has gained huge interest and has been widely used in finding the biomarkers of several neurological diseases or psychiatric disorders. However mainly because of its complexity, only a limited use of sulcal morphometry has been reported so far. With a wide range of possibilities for sulcal morphometry offered by Brainvisa, it is possible to thoroughly investigate the sulcal changes due to the abnormality. However, as any other automated method, Brainvisa can be susceptible to limitations associated with image quality. Factors such as noise, spatial resolution, and so on, can have an impact on the detection of the cortical folds and estimation of their attributes. Hence the robustness of Brainvisa needs to be assessed. This can be done by estimating the reliability and reproducibility of results as well as exploring the changes in results caused by other factors. This thesis is an attempt to investigate the possible benefits of sulci identification and sulcal morphometry for functional and structural MRI studies as well as the limitations of Brainvisa. In addition, the possibility of improvement of activation localization with functional MRI studies is further investigated. This investigation was motivated by a review of other cortical-based analysis methods, namely the cortical surface-based methods, which are discussed in the literature review chapter of this thesis. The application of these approaches in functional MRI data analysis and their potential benefits is used in this investigation

The effect of teaching conceptual and image metaphors to EFL learners

Foreign language learners encounter difficulties utilizing metaphorical expressions in everyday language, particularly because the use of metaphors in the discourse context is inescapable. In this study, efforts have been made to provide an effective way for the Iranian language learners to acquire and employ conceptual and image metaphors. The instruction took place on 60 junior students studying at the University of Petroleum Engineering at Ahvaz, a southern city in Iran, who were selected on the basis of their high marks on an English proficiency test. Forty metaphors of both types were presented to the participants during 10 sessions of instruction. To collect data on the learners\u27 performance, a 30- item sentence completion test requiring \u27word-given\u27 and \u27recognition\u27 type responses was prepared and administered. The results of a statistical t-test indicated no significant difference in the rate of acquiring conceptual and image metaphors (P&gt;.05). Therefore, both metaphors can be successfully taught concurrently with little difficulty.<br /

Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

Previous functional magnetic resonance imaging (fMRI) studies have shown that a subgroup of patients diagnosed as being in a vegetative state are aware and able to communicate by performing a motor imagery task in response to commands. Due to the fMRI\u27s cost and accessibility, there is a need for exploring different imaging modalities that can be used at the bedside. A promising technique is functional near infrared spectroscopy (fNIRS) that has been successfully applied to measure brain oxygenation in humans. Due to the limited depth sensitivity of continuous-wave NIRS, time-resolved (TR) detection has been proposed as a way of enhancing the sensitivity to the brain, since late arriving photons have a higher probability of reaching the brain. The goal of this study was to assess the feasibility and sensitivity of TR fNIRS in detecting brain activity during motor imagery. Fifteen healthy subjects were recruited in this study, and the fNIRS results were validated using fMRI. The change in the statistical moments of the distribution of times of flight (number of photons, mean time of flight and variance) were calculated for each channel to determine the presence of brain activity. The results indicate up to an 86% agreement between fMRI and TR-fNIRS and the sensitivity ranging from 64 to 93% with the highest value determined for the mean time of flight. These promising results highlight the potential of TR-fNIRS as a portable brain computer interface for patients with disorder of consciousness

Assessment of the impact of the scanner-related factors on brain morphometry analysis with Brainvisa.

BACKGROUND: Brain morphometry is extensively used in cross-sectional studies. However, the difference in the estimated values of the morphometric measures between patients and healthy subjects may be small and hence overshadowed by the scanner-related variability, especially with multicentre and longitudinal studies. It is important therefore to investigate the variability and reliability of morphometric measurements between different scanners and different sessions of the same scanner. METHODS: We assessed the variability and reliability for the grey matter, white matter, cerebrospinal fluid and cerebral hemisphere volumes as well as the global sulcal index, sulcal surface and mean geodesic depth using Brainvisa. We used datasets obtained across multiple MR scanners at 1.5 T and 3 T from the same groups of 13 and 11 healthy volunteers, respectively. For each morphometric measure, we conducted ANOVA analysis and verified whether the estimated values were significantly different across different scanners or different sessions of the same scanner. The between-centre and between-visit reliabilities were estimated from their contribution to the total variance, using a random-effects ANOVA model. To estimate the main processes responsible for low reliability, the results of brain segmentation were compared to those obtained using FAST within FSL. RESULTS: In a considerable number of cases, the main effects of both centre and visit factors were found to be significant. Moreover, both between-centre and between-visit reliabilities ranged from poor to excellent for most morphometric measures. A comparison between segmentation using Brainvisa and FAST revealed that FAST improved the reliabilities for most cases, suggesting that morphometry could benefit from improving the bias correction. However, the results were still significantly different across different scanners or different visits. CONCLUSIONS: Our results confirm that for morphometry analysis with the current version of Brainvisa using data from multicentre or longitudinal studies, the scanner-related variability must be taken into account and where possible should be corrected for. We also suggest providing some flexibility to Brainvisa for a step-by-step analysis of the robustness of this package in terms of reproducibility of the results by allowing the bias corrected images to be imported from other packages and bias correction step be skipped, for example.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Comparative Study of the Efficiency of Fiscal Regimes of the Buy Back and IPC

In this paper, utilizing a cash flow model in an Oil field as a case study, we compare the efficiency of fiscal regimes of buy back and Iranian Petroleum Contract (IPC). In order to implement the mentioned comparison, we have selected influential financial indices such as: internal rate of return (IRR), Net Present value (NPV), Payback period, Profit to investment ratio (PIR) and Government take (GT). Furthermore, considering three price scenarios, sensitivity analysis is performed for different oil prices. Subsequently, we model IPC comprising Enhanced Oil Recovery (EOR (/Improved Oil Recovery) IOR) operations and compare it with IPC without EOR/IOR in terms of the specified indices. Our results indicate that in addition to the more eligibility of IPC for contractors than buy back contracts, Government take is still adequate and noticeable enough in spite of the reduction it would confront in IPC. The paper concludes IPC comprising EOR/IOR is more beneficial to host government than E&P companies, therefore contractors do not have sufficient incentives to apply EOR/IOR operations in which the host government should lead the contractor toward by providing them with mutually acceptable options

Lower Functional Connectivity of the Periaqueductal Gray Is Related to Negative Affect and Clinical Manifestations of Fibromyalgia

Fibromyalgia (FM) syndrome is characterized by chronic widespread pain, muscle tenderness and emotional distress. Previous studies found reduced endogenous pain modulation in FM. This deficiency of pain modulation may be related to the attributes of chronic pain and other clinical symptoms experienced in patients with FM. Thus, we tested whether there is a link between the clinical symptoms of FM and functional connectivity (FC) of the periaqueductal gray (PAG), a key node of pain modulation. We acquired resting state 3T functional MRI (rsfMRI) data from 23 female patients with FM and 16 age- and sex- matched healthy controls (HC) and assessed FM symptoms with the Brief Pain Inventory (BPI), Fibromyalgia Impact Questionnaire (FIQ), Hospital Anxiety and Depression Scale (HADS) and Pain Catastrophizing Scale (PCS). We found that patients with FM exhibit statistically significant disruptions in PAG FC, particularly with brain regions implicated in negative affect, self-awareness and saliency. Specifically, we found that, compared to HCs, the FM patients had stronger PAG FC with the lingual gyrus and hippocampus but weaker PAG FC with regions associated with motor/executive functions, the salience (SN) and default mode networks (DMN). The attenuated PAG FC was also negatively correlated with FIQ scores, and positively correlated with the magnification subscale of the PCS. These alterations were correlated with emotional and behavioral symptoms of FM. Our study implicates the PAG as a site of dysfunction contributing to the clinical manifestations and pain in FM