The DOI matches its Crossref record; 129 of the 129 references it cites were found in a registry or an index.
Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders
Open accessAbstract
Neuroimaging has revolutionized our understanding of brain function and has become an essential tool for researchers studying neurological disorders. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two widely used neuroimaging techniques to review changes in brain activity. fMRI is a noninvasive technique that uses magnetic fields and radio waves to produce detailed brain images. An EEG is a noninvasive technique that records the brain’s electrical activity through electrodes placed on the scalp. This review overviews recent developments in noninvasive functional neuroimaging methods, including fMRI and EEG. Recent advances in fMRI technology, its application to studying brain function, and the impact of neuroimaging techniques on neuroscience research are discussed. Advances in EEG technology and its applications to analyzing brain function and neural oscillations are also highlighted. In addition, advanced courses in neuroimaging, such as diffusion tensor imaging (DTI) and transcranial electrical stimulation (TES), are described, along with their role in studying brain connectivity, white matter tracts, and potential treatments for schizophrenia and chronic pain. Application. The review concludes by examining neuroimaging studies of neurodevelopmental and neurological disorders such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer’s disease (AD), and Parkinson’s disease (PD). We also described the role of transcranial direct current stimulation (tDCS) in ASD, ADHD, AD, and PD. Neuroimaging techniques have significantly advanced our understanding of brain function and provided essential insights into neurological disorders. However, further research into noninvasive treatments such as EEG, MRI, and TES is necessary to continue to develop new diagnostic and therapeutic strategies for neurological disorders.
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Cites
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Cited by
Catd: unified representation learning for eeg-to-fmri cross-modal generation
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Metadata
- Authors
- Yen, C., Lin, C.-L., & Chiang, M.-C.
- Venue
- Life
- Publisher
- MDPI AG
- Published
- 2023-06-29
- Volume
- 13
- Issue
- 7
- Pages
- 1472
- ISSN
- 2075-1729 (ISSN-L)
- OpenAlex
- W4382699420
- Cited by
- 281
- References
- 129
- FWCI
- 41.48
- Type
- journal article
- Language
- en
- Open access
- gold
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