Results 61 to 70 of about 111,880 (318)
, 2014 Resting state functional magnetic resonance imaging (fMRI) was used to measure whole brain functional connectivity within specific networks hypothesised to be more affected in dementia with Lewy bodies (DLB) (a disease characterised by prominent ...
Blamire, Andrew M +3 more
core +2 more sources
Advanced Science, EarlyView.BrainFusion is a low‐code software framework for multimodal brain–computer interface (BCI) and brain–body interaction research. It supports electroencephalography (EEG), functional near‐infrared spectroscopy (fNIRS), electromyography (EMG), and electrocardiography (ECG) integration with standardized preprocessing, feature fusion, and model ...
Wenhao Li +10 more
wiley +1 more source
On the generalizability of resting-state fMRI machine learning classifiers [PDF]
Frontiers in Human Neuroscience, 2014 Machine learning classifiers have become increasingly popular tools to generate single-subject inferences from fMRI data. With this transition from the traditional group level difference investigations to single-subject inference, the application of machine learning methods can be seen as a considerable step forward.
Wolfgang eHuf +15 more
openaire +3 more sources
Monkey in the middle: why non-human primates are needed to bridge the gap in resting-state investigations [PDF]
, 2012 Resting-state investigations based on the evaluation of intrinsic low-frequency fluctuations of the BOLD fMRI signal have been extensively utilized to map the structure and dynamics of large-scale functional network organization in humans. In addition to
R. Matthew Hutchison, Stefan Everling
core +1 more source
Aging and the Spectral Properties of Brain Hemodynamics
Advanced Science, EarlyView.As the brain ages, its metabolic demands decline—but not uniformly. Here, spectral slope flattening of resting‐state fMRI signals is proposed as a potential biomarker of pathologic brain aging. A subset of older adults diverges from youthful spectral and metabolic patterns, with changes linked to frontal white matter pathology and regional loss of ...
Ki Yun Park +9 more
wiley +1 more source
Machine learning in resting-state fMRI analysis
Magnetic Resonance Imaging, 2019 51 pages, 6 ...
Meenakshi Khosla +4 more
openaire +4 more sources
An open database of resting-state fMRI in awake rats [PDF]
NeuroImage, 2019 AbstractRodent models are essential to translational research in health and disease. Investigation in rodent brain function and organization at the systems level using resting-state functional magnetic resonance imaging (rsfMRI) has become increasingly popular, owing to its high spatial resolution and whole-brain coverage.
Liu, Yikang +7 more
openaire +4 more sources
Statistical power and prediction accuracy in multisite resting-state fMRI connectivity
, 2017 Connectivity studies using resting-state functional magnetic resonance imaging are increasingly pooling data acquired at multiple sites. While this may allow investigators to speed up recruitment or increase sample size, multisite studies also ...
Arnold, Douglas +6 more
core +1 more source
The State of High‐Resolution Imaging of the Human Inner Ear: A Look Into the Black Box
Advanced Science, Volume 12, Issue 28, July 24, 2025.High‐resolution imaging of the cochlea is challenged by numerous unique aspects of this organ, where sensorineural cells, crucial for hearing, are too small for conventional modalities like magnetic resonance imaging and computed tomography. This article reviews current imaging techniques, emerging technologies, and innovations aimed at improving ...
Shelley Batts +3 more
wiley +1 more source
Optimization of scan time for resting ⁃state fMRI in clinical application
Chinese Journal of Contemporary Neurology and Neurosurgery, 2011 Objective To study the optimization of scan time for resting⁃state functional magnetic resonance imaging (fMRI) in clinical application. Methods Fractional amplitude of low ⁃ frequency fluctuation (fALFF) was performed to analyse the resting ⁃ state fMRI
Cheng ZHAO +5 more
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