Entropy is an important trait of brain function and high entropy indicates high information processing capacity. We recently demonstrated that brain entropy (BEN) is stable across time and differs between controls and patients with various brain disorders. The purpose of this study was to examine whether BEN is sensitive to pharmaceutical modulations with caffeine. Both cerebral blood flow (CBF) and resting fMRI were collected from sixty caffeine-naïve healthy subjects before and after taking a 200 mg caffeine pill. Our data showed that caffeine reduced CBF in the whole brain but increased BEN across the cerebral cortex with the highest increase in lateral prefrontal cortex, the default mode network (DMN), visual cortex, and motor network, consistent with the beneficial effects of caffeine (such as vigilance and attention) on these areas. BEN increase was correlated to CBF reduction only in several regions (-0.5 < r < -0.4), indicating a neuronal nature for most of the observed BEN alterations. In summary, we showed the first evidence of BEN alterations due to caffeine ingestion, suggesting BEN as a biomarker sensitive to pharmaceutical brain function modulations.
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http://dx.doi.org/10.1038/s41598-018-21008-6 | DOI Listing |
Eur J Neurosci
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Case Western Reserve University, Cleveland, Ohio, USA.
Movement disorders such as Parkinson's disease (PD) and cervical dystonia (CD) are associated with abnormal neuronal activity in the globus pallidus internus (GPi). Reduced firing rate and presence of spiking bursts are typical for CD, whereas PD is characterized by high frequency tonic activity. This research aims to identify the most important pallidal spiking parameters to classify these conditions.
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Department of Information Science, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China. Electronic address:
Accurate prediction of brain age is crucial for identifying deviations between typical individual brain development trajectories and neuropsychiatric disease progression. Although current research has made progress, the effective application of brain age prediction models to multi-center datasets, particularly those with small-sample sizes, remains a significant challenge that is yet to be addressed. To this end, we propose a multi-center data correction method, which employs a domain adaptation correction strategy with Wasserstein distance of optimal transport, along with maximum mean discrepancy to improve the generalizability of brain-age prediction models on small-sample datasets.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam.
The field of medical image segmentation powered by deep learning has recently received substantial attention, with a significant focus on developing novel architectures and designing effective loss functions. Traditional loss functions, such as Dice loss and Cross-Entropy loss, predominantly rely on global metrics to compare predictions with labels. However, these global measures often struggle to address challenges such as occlusion and nonuni-form intensity.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Sport & Health, Exercise Science & Neuroscience Unit Universität Paderborn, Warburger Straße 100, 33098, Paderborn, Germany.
Anterior cruciate ligament injuries (ACLi) impact football players substantially leading to performance declines and premature career endings. Emerging evidence suggests that ACLi should be viewed not merely as peripheral injuries but as complex conditions with neurophysiological aspects. The objective of the present study was to compare kicking performance and associated cortical activity between injured and healthy players.
View Article and Find Full Text PDFMol Psychiatry
January 2025
Siena Brain Investigation and Neuromodulation Lab, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Ketamine, a dissociative compound, shows promise in treating mood disorders, including treatment-resistant depression (TRD) and bipolar disorder (BD). Despite its therapeutic potential, the neurophysiological mechanisms underlying ketamine's effects are not fully understood. This study explored acute neurophysiological changes induced by subanesthetic doses of ketamine in BD patients with depression using electroencephalography (EEG) biomarkers.
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