Functional brain imaging with fMRI and MEG

The work described in this thesis was performed by the author, except where indicated. All the studies were accomplished on the 3 Tesla system within the Magnetic Resonance Centre at the University of Nottingham, and the Wellcome Trust MEG Laboratory at the Aston University during the period between October 1999 and June 2005. Functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG) are two promising brain function research modalities, sensitive to the hemodynamic and electrophysiological responses respectively during brain activites. The feasibility of joint employment of both modalities was examined in both spatial and temporal domains. A somatosensory tactile stimulus was adopted to induce simple functional reaction. It was shown that a reasonable spatial correspondence between fMRI and MEG can be established. Attempts were made on MEG recordings to extract suitable aspects for temporal features matching fMRI with a method reflecting the physical principles. It was shown that the this method is capable of exposing the nature of neural electric activities, although further development is required to perfect the strategy

Dietary nitrate reduces skeletal muscle oxygenation response to physical exercise : a quantitative muscle functional MRI study

© 2014 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.Peer reviewedPublisher PD

Functional brain imaging with fMRI and MEG

The work described in this thesis was performed by the author, except where indicated. All the studies were accomplished on the 3 Tesla system within the Magnetic Resonance Centre at the University of Nottingham, and the Wellcome Trust MEG Laboratory at the Aston University during the period between October 1999 and June 2005. Functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG) are two promising brain function research modalities, sensitive to the hemodynamic and electrophysiological responses respectively during brain activites. The feasibility of joint employment of both modalities was examined in both spatial and temporal domains. A somatosensory tactile stimulus was adopted to induce simple functional reaction. It was shown that a reasonable spatial correspondence between fMRI and MEG can be established. Attempts were made on MEG recordings to extract suitable aspects for temporal features matching fMRI with a method reflecting the physical principles. It was shown that the this method is capable of exposing the nature of neural electric activities, although further development is required to perfect the strategy

Grey and white matter differences in Chronic Fatigue Syndrome : A voxel-based morphometry study

Conflicts of interest and source of funding The authors declare no conflicts of interest. This research was funded by the Medical Research Council (MR/J002712/1). AF is supported by Research Capability Funding from the Newcastle upon Tyne Hospitals NHS Foundation Trust and the Northumberland, Tyne and Wear NHS Foundation Trust.Peer reviewedPublisher PD

Disease activity and cognition in rheumatoid arthritis : an open label pilot study

Acknowledgements This work was supported in part by NIHR Newcastle Biomedical Research Centre. Funding for this study was provided by Abbott Laboratories. Abbott Laboratories were not involved in study design; in the collection, analysis and interpretation of data; or in the writing of the report.Peer reviewedPublisher PD

A Survey of Explainable Knowledge Tracing

With the long term accumulation of high quality educational data, artificial intelligence has shown excellent performance in knowledge tracing. However, due to the lack of interpretability and transparency of some algorithms, this approach will result in reduced stakeholder trust and a decreased acceptance of intelligent decisions. Therefore, algorithms need to achieve high accuracy, and users need to understand the internal operating mechanism and provide reliable explanations for decisions. This paper thoroughly analyzes the interpretability of KT algorithms. First, the concepts and common methods of explainable artificial intelligence and knowledge tracing are introduced. Next, explainable knowledge tracing models are classified into two categories: transparent models and black box models. Then, the interpretable methods used are reviewed from three stages: ante hoc interpretable methods, post hoc interpretable methods, and other dimensions. It is worth noting that current evaluation methods for explainable knowledge tracing are lacking. Hence, contrast and deletion experiments are conducted to explain the prediction results of the deep knowledge tracing model on the ASSISTment2009 by using three XAI methods. Moreover, this paper offers some insights into evaluation methods from the perspective of educational stakeholders. This paper provides a detailed and comprehensive review of the research on explainable knowledge tracing, aiming to offer some basis and inspiration for researchers interested in the interpretability of knowledge tracing

Cerebral vascular control is associated with skeletal muscle pH in chronic fatigue syndrome patients both at rest and during dynamic stimulation

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Effects of Community Exercise Therapy on Metabolic, Brain, Physical, and Cognitive Function Following Stroke : A Randomized Controlled Pilot Trial

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FairBench: A Four-Stage Automatic Framework for Detecting Stereotypes and Biases in Large Language Models

Detecting stereotypes and biases in Large Language Models (LLMs) can enhance fairness and reduce adverse impacts on individuals or groups when these LLMs are applied. However, the majority of existing methods focus on measuring the model's preference towards sentences containing biases and stereotypes within datasets, which lacks interpretability and cannot detect implicit biases and stereotypes in the real world. To address this gap, this paper introduces a four-stage framework to directly evaluate stereotypes and biases in the generated content of LLMs, including direct inquiry testing, serial or adapted story testing, implicit association testing, and unknown situation testing. Additionally, the paper proposes multi-dimensional evaluation metrics and explainable zero-shot prompts for automated evaluation. Using the education sector as a case study, we constructed the Edu-FairBench based on the four-stage framework, which encompasses 12,632 open-ended questions covering nine sensitive factors and 26 educational scenarios. Experimental results reveal varying degrees of stereotypes and biases in five LLMs evaluated on Edu-FairBench. Moreover, the results of our proposed automated evaluation method have shown a high correlation with human annotations

q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T : A Pilot Study with Freshly Excised Whole-Breast Tumors

N.S. supported by Biotechnology and Biological Sciences Research Council (1654748, BB/M010996/1). Study supported by the National Health Service Grampian Endowment Fund (15/1/052).Peer reviewedPublisher PD