Jelle R. Dalenberg, Debora E. Peretti, Lenny R. Marapin, A. M. Madelein van der Stouwe, Remco J. Renken, Marina A. J. Tijssen
{"title":"运动障碍的下一步:超运动障碍的神经成像方案","authors":"Jelle R. Dalenberg, Debora E. Peretti, Lenny R. Marapin, A. M. Madelein van der Stouwe, Remco J. Renken, Marina A. J. Tijssen","doi":"10.3389/fnhum.2024.1406786","DOIUrl":null,"url":null,"abstract":"IntroductionThe Next Move in Movement Disorders (NEMO) study is an initiative aimed at advancing our understanding and the classification of hyperkinetic movement disorders, including tremor, myoclonus, dystonia, and myoclonus-dystonia. The study has two main objectives: (a) to develop a computer-aided tool for precise and consistent classification of these movement disorder phenotypes, and (b) to deepen our understanding of brain pathophysiology through advanced neuroimaging techniques. This protocol review details the neuroimaging data acquisition and preprocessing procedures employed by the NEMO team to achieve these goals.Methods and analysisTo meet the study’s objectives, NEMO utilizes multiple imaging techniques, including T1-weighted structural MRI, resting-state fMRI, motor task fMRI, and 18F-FDG PET scans. We will outline our efforts over the past 4 years to enhance the quality of our collected data, and address challenges such as head movements during image acquisition, choosing acquisition parameters and constructing data preprocessing pipelines. This study is the first to employ these neuroimaging modalities in a standardized approach contributing to more uniformity in the analyses of future studies comparing these patient groups. The data collected will contribute to the development of a machine learning-based classification tool and improve our understanding of disorder-specific neurobiological factors.Ethics and disseminationEthical approval has been obtained from the relevant local ethics committee. The NEMO study is designed to pioneer the application of machine learning of movement disorders. We expect to publish articles in multiple related fields of research and patients will be informed of important results via patient associations and press releases.","PeriodicalId":12536,"journal":{"name":"Frontiers in Human Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Next move in movement disorders: neuroimaging protocols for hyperkinetic movement disorders\",\"authors\":\"Jelle R. Dalenberg, Debora E. Peretti, Lenny R. Marapin, A. M. Madelein van der Stouwe, Remco J. Renken, Marina A. J. Tijssen\",\"doi\":\"10.3389/fnhum.2024.1406786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"IntroductionThe Next Move in Movement Disorders (NEMO) study is an initiative aimed at advancing our understanding and the classification of hyperkinetic movement disorders, including tremor, myoclonus, dystonia, and myoclonus-dystonia. The study has two main objectives: (a) to develop a computer-aided tool for precise and consistent classification of these movement disorder phenotypes, and (b) to deepen our understanding of brain pathophysiology through advanced neuroimaging techniques. This protocol review details the neuroimaging data acquisition and preprocessing procedures employed by the NEMO team to achieve these goals.Methods and analysisTo meet the study’s objectives, NEMO utilizes multiple imaging techniques, including T1-weighted structural MRI, resting-state fMRI, motor task fMRI, and 18F-FDG PET scans. We will outline our efforts over the past 4 years to enhance the quality of our collected data, and address challenges such as head movements during image acquisition, choosing acquisition parameters and constructing data preprocessing pipelines. This study is the first to employ these neuroimaging modalities in a standardized approach contributing to more uniformity in the analyses of future studies comparing these patient groups. The data collected will contribute to the development of a machine learning-based classification tool and improve our understanding of disorder-specific neurobiological factors.Ethics and disseminationEthical approval has been obtained from the relevant local ethics committee. The NEMO study is designed to pioneer the application of machine learning of movement disorders. 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Next move in movement disorders: neuroimaging protocols for hyperkinetic movement disorders
IntroductionThe Next Move in Movement Disorders (NEMO) study is an initiative aimed at advancing our understanding and the classification of hyperkinetic movement disorders, including tremor, myoclonus, dystonia, and myoclonus-dystonia. The study has two main objectives: (a) to develop a computer-aided tool for precise and consistent classification of these movement disorder phenotypes, and (b) to deepen our understanding of brain pathophysiology through advanced neuroimaging techniques. This protocol review details the neuroimaging data acquisition and preprocessing procedures employed by the NEMO team to achieve these goals.Methods and analysisTo meet the study’s objectives, NEMO utilizes multiple imaging techniques, including T1-weighted structural MRI, resting-state fMRI, motor task fMRI, and 18F-FDG PET scans. We will outline our efforts over the past 4 years to enhance the quality of our collected data, and address challenges such as head movements during image acquisition, choosing acquisition parameters and constructing data preprocessing pipelines. This study is the first to employ these neuroimaging modalities in a standardized approach contributing to more uniformity in the analyses of future studies comparing these patient groups. The data collected will contribute to the development of a machine learning-based classification tool and improve our understanding of disorder-specific neurobiological factors.Ethics and disseminationEthical approval has been obtained from the relevant local ethics committee. The NEMO study is designed to pioneer the application of machine learning of movement disorders. We expect to publish articles in multiple related fields of research and patients will be informed of important results via patient associations and press releases.
期刊介绍:
Frontiers in Human Neuroscience is a first-tier electronic journal devoted to understanding the brain mechanisms supporting cognitive and social behavior in humans, and how these mechanisms might be altered in disease states. The last 25 years have seen an explosive growth in both the methods and the theoretical constructs available to study the human brain. Advances in electrophysiological, neuroimaging, neuropsychological, psychophysical, neuropharmacological and computational approaches have provided key insights into the mechanisms of a broad range of human behaviors in both health and disease. Work in human neuroscience ranges from the cognitive domain, including areas such as memory, attention, language and perception to the social domain, with this last subject addressing topics, such as interpersonal interactions, social discourse and emotional regulation. How these processes unfold during development, mature in adulthood and often decline in aging, and how they are altered in a host of developmental, neurological and psychiatric disorders, has become increasingly amenable to human neuroscience research approaches. Work in human neuroscience has influenced many areas of inquiry ranging from social and cognitive psychology to economics, law and public policy. Accordingly, our journal will provide a forum for human research spanning all areas of human cognitive, social, developmental and translational neuroscience using any research approach.