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Found 6 papers, 0 papers with code
Structural Brain Connectivity and Treatment Improvement in Mood Disorder
Compared with the not-improved, the improved displayed significantly reduced network integration and segregation, predominately in the default-mode regions, including the precuneus, middle temporal lobe and rostral anterior cingulate. Conclusions: This study highlights the involvement of regions belonging to the basal ganglia, the fronto-limbic network and the default mode network, leading to a better understanding of MD disease and its unfavorable outcome.
On the validity of fMRI studies with subject-level data processed through different pipelines
Here, we investigate the impact of combining subject-level data processed with different pipelines in between-group fMRI studies.
The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis
Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability including differences due to: the sampling of the participants, differences in acquisition protocols and material but also due to different analytical choices in the processing of the fMRI data.
Deep Recurrent Neural Networks for mapping winter vegetation quality coverage via multi-temporal SAR Sentinel-1
The objective of this paper is to provide a better understanding of the capabilities of radar Sentinel-1 and deep learning concerning about mapping winter vegetation quality coverage.
Land Cover Classification via Multi-temporal Spatial Data by Recurrent Neural Networks
Nowadays, modern earth observation programs produce huge volumes of satellite images time series (SITS) that can be useful to monitor geographical areas through time.
