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For those new to the field of resting state fMRI, the large variety of approaches to functional connectivity analysis is highly confusing. This primer provides an introduction to the concepts and analysis decisions that need to be made at every step of the processing pipeline, starting from data acquisition through to interpretation of findings.
This accessible primer gives an introduction to the wide array of MRI-based neuroimaging methods that are used in research. It provides an overview of the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common 'pipelines'.
MRI has emerged as a powerful way of studying in-vivo brain structure and function in both healthy and disease states. Whilst new researchers may be able to call upon advice and support for acquisition from operators, radiologists and technicians, it is more challenging to obtain an understanding of the principles of analysing neuroimaging data. This is crucial for choosing acquisition parameters, designing and performing appropriate experiments, and correctly interpreting the results. This primer gives a general and accessible introduction to the wide array of MRI-based neuroimaging methods that are used in research. Supplemented with online datasets and examples to enable the reader to obt...
Advanced Neuro MR Techniques and Applications gives detailed knowledge of emerging neuro MR techniques and their specific clinical and neuroscience applications, showing their pros and cons over conventional and currently available advanced techniques. The book identifies the best available data acquisition, processing, reconstruction and analysis strategies and methods that can be utilized in clinical and neuroscience research. It is an ideal reference for MR scientists and engineers who develop MR technologies and/or support clinical and neuroscience research and for high-end users who utilize neuro MR techniques in their research, including clinicians, neuroscientists and psychologists. T...
Arterial Spin Labeling (ASL) is an increasingly popular tool to study the brain. What sets it apart from other neuroimaging methods is the combination of quantitative measurements of a physiologically well-defined process, namely perfusion, and a completely non-invasive acquisition methodology. Cerebral perfusion is a critical component to brain health, as it is the primary means to deliver nutrients to support brain function as well as clearing waste products. Hence it is a useful quantity to study in disease where changes in perfusion can indicate regions of the brain that are pathological. Likewise changes in perfusion can be indicative of greater demand for nutrients, such as might be re...
In this issue of Neuroimaging Clinics, guest editors Drs. Frederik Barkhof and Yaou Liu bring their considerable expertise to the topic of Multiple Sclerosis and Associated Demyelinating Disorders. Top experts in the field discuss advanced brain imaging in CNS demyelinating diseases; new imaging markers in MS and related disorders: smoldering inflammation and central vein sign; the use of AI in MS and white matter disease; optic nerve imaging in MS and related disorders; atypical demyelinating disorders; and more. Co-Editor Frederik Barkhof, MD, has received the National Multiple Sclerosis Society and the American Academy of Neurology's 2018 John Dystel Prize for Multiple Sclerosis Research ...
This book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions. The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications.
The huge volume of neuroscience data and the wide variety of data formats generated across different neuroscience communities has posed a challenge to traditional methods of data management, data sharing and data mining. Mandates on data sharing and the demand for using open data has driven the development of advanced methodologies and tools to effectively explore, mine and integrate data. However, the growing number of resources make it harder for researchers to navigate this landscape. Awareness of these tools and resources is vital for effective data mining and unlocking new discoveries. The goal of this research collection is to provide an overview of available resources, centred around making data findable, accessible, interoperable and reusable (FAIR).
Hysteria, a mysterious disease known since antiquity, is said to have ceased to exist. Challenging this commonly held view, this is the first cross-disciplinary study to examine the current functional neuroimaging research into hysteria and compare it to the nineteenth-century image-based research into the same disorder. Paula Muhr's central argument is that, both in the nineteenth-century and the current neurobiological research on hysteria, images have enabled researchers to generate new medical insights. Through detailed case studies, Muhr traces how different images, from photography to functional brain scans, have reshaped the historically situated medical understanding of this disorder that defies the mind-body dualism.