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Diffusion Tensor Imaging Reveals Altered Centrality of Pain‐Related Regions in SCN9A‐Associated Small Fiber Neuropathy

by Clinical Neuropsychologist | Tuesday, November 11, 2025 | Neuroimaging

ABSTRACT Background and Purpose Small fiber neuropathy (SFN) is a neuropathic disorder that is associated with chronic pain. While most SFN cases are idiopathic, SFN can also have hereditary causes. For example, rare SCN9A gene mutations can impair the NaV1.7 sodium...

Distinguishing Myo‐Inositol From Glycine in Brain MRS at 3T: A Pitfall Using Intermediate Echo Times

by Clinical Neuropsychologist | Tuesday, November 11, 2025 | Neuroimaging

ABSTRACT Background and Purpose In in vivo magnetic resonance spectroscopy (MRS) of the brain, glycine (Gly) is traditionally separated from the overlapping signal of myo-inositol (mI) through the use of intermediate (e.g., 130–140 ms) or long (270–280 ms) echo times...

Assessing a Stimulator Modification for Simultaneous Noninvasive Auricular Vagus Nerve Stimulation and MRI

by Clinical Neuropsychologist | Friday, November 7, 2025 | Neuroimaging

ABSTRACT Background and Purpose The vagus nerve can be stimulated noninvasively at the ear using transcutaneous auricular vagus nerve stimulation (taVNS). Concurrent functional MRI (fMRI) permits study of taVNS-induced changes in brain dynamics, a key requisite for...

Diagnostic Accuracy of Neuromuscular Ultrasound for Carpal Tunnel Syndrome: A Real‐World Study

by Clinical Neuropsychologist | Tuesday, November 4, 2025 | Neuroimaging

ABSTRACT Background and Purpose To determine the diagnostic accuracy of median nerve ultrasound in suspected cases of carpal tunnel syndrome (CTS) in a prospective, real-world study. Methods This prospective study was carried out over one year at Roy Neuro Care...

Edge‐Guided Deep Learning Model to Predict Fetal Brain Age Using MRI

by Clinical Neuropsychologist | Tuesday, November 4, 2025 | Neuroimaging

ABSTRACT Background and Purpose Deep learning enables fast fetal brain age prediction from MRI. However, most models emphasize global features while ignoring local edge details. To improve accuracy, we propose a novel model incorporating global edge information,...
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