Human Connectome Project
PulseAugur coverage of Human Connectome Project — every cluster mentioning Human Connectome Project across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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fMRI transfer learning reveals multi-source cognitive task relations
Researchers have developed a novel method to analyze the relationships between cognitive tasks using fMRI data, extending previous single-source transfer learning models to a multi-source framework. This new approach, w…
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TensorLDM: Diffusion model enhances DTI reconstruction accuracy
Researchers have developed TensorLDM, a novel component-wise latent diffusion model designed for volumetric Diffusion Tensor Imaging (DTI) reconstruction from sparse Diffusion Weighted Images (DWIs). This model addresse…
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New framework Artemis tackles demographic confounders in neuroimaging
Researchers have developed Artemis, a novel region-level causal framework designed to eliminate demographic confounders in multimodal neuroimaging data. This framework integrates functional magnetic resonance imaging (f…
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Krakencoder analysis reveals subtle sex differences in brain connectomes
A new study published on arXiv analyzes sex-based differences in brain connectomes using the Krakencoder framework. Researchers examined structural and functional connectomes from 702 participants in the Human Connectom…
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AI enhances MRI diagnostics with motion correction and feature disentanglement
Researchers have developed new deep learning frameworks to address motion artifacts and improve diagnostic accuracy in MRI scans. One approach, ScanCLIP, uses parameter-informed contrast disentanglement and adaptive exp…
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New FM-fMRI Model Synthesizes Task fMRI from Rest Data
Researchers have developed FM-fMRI, a novel flow-matching model designed to synthesize task-based fMRI time series from resting-state fMRI data. This method conditions the synthesis on specific task events, enabling the…
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Deep learning MRI super-resolution quality depends on feature loss layer selection
Researchers have explored how different layers in feature-based loss functions impact the quality of deep learning-based super-resolution for brain diffusion MRI. They found that using deeper layers in VGG16 networks in…
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New UBD method creates universal space for brain dynamics analysis
Researchers have developed a new method called Universal Brain Dynamics (UBD) to create a universal space for analyzing human brain activity. This approach integrates both spatial and temporal properties of brain signal…