FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308377053> ?p ?o ?g. }

• W4308377053 endingPage "119737" @default.
• W4308377053 startingPage "119737" @default.
• W4308377053 abstract "Brain network interactions are commonly assessed via functional (network) connectivity, captured as an undirected matrix of Pearson correlation coefficients. Functional connectivity can represent static and dynamic relations, but often these are modeled using a fixed choice for the data window Alternatively, deep learning models may flexibly learn various representations from the same data based on the model architecture and the training task. However, the representations produced by deep learning models are often difficult to interpret and require additional posthoc methods, e.g., saliency maps. In this work, we integrate the strengths of deep learning and functional connectivity methods while also mitigating their weaknesses. With interpretability in mind, we present a deep learning architecture that exposes a directed graph layer that represents what the model has learned about relevant brain connectivity. A surprising benefit of this architectural interpretability is significantly improved accuracy in discriminating controls and patients with schizophrenia, autism, and dementia, as well as age and gender prediction from functional MRI data. We also resolve the window size selection problem for dynamic directed connectivity estimation as we estimate windowing functions from the data, capturing what is needed to estimate the graph at each time-point. We demonstrate efficacy of our method in comparison with multiple existing models that focus on classification accuracy, unlike our interpretability-focused architecture. Using the same data but training different models on their own discriminative tasks we are able to estimate task-specific directed connectivity matrices for each subject. Results show that the proposed approach is also more robust to confounding factors compared to standard dynamic functional connectivity models. The dynamic patterns captured by our model are naturally interpretable since they highlight the intervals in the signal that are most important for the prediction. The proposed approach reveals that differences in connectivity among sensorimotor networks relative to default-mode networks are an important indicator of dementia and gender. Dysconnectivity between networks, specially sensorimotor and visual, is linked with schizophrenic patients, however schizophrenic patients show increased intra-network default-mode connectivity compared to healthy controls. Sensorimotor connectivity was important for both dementia and schizophrenia prediction, but schizophrenia is more related to dysconnectivity between networks whereas, dementia bio-markers were mostly intra-network connectivity." @default.
• W4308377053 created "2022-11-11" @default.
• W4308377053 creator A5019983016 @default.
• W4308377053 creator A5032850756 @default.
• W4308377053 creator A5051194003 @default.
• W4308377053 creator A5081150533 @default.
• W4308377053 creator A5082230429 @default.
• W4308377053 date "2022-12-01" @default.
• W4308377053 modified "2023-10-16" @default.
• W4308377053 title "Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI" @default.
• W4308377053 cites W1524326598 @default.
• W4308377053 cites W1552598564 @default.
• W4308377053 cites W1582928193 @default.
• W4308377053 cites W1943480391 @default.
• W4308377053 cites W1967699765 @default.
• W4308377053 cites W1968248619 @default.
• W4308377053 cites W1973741448 @default.
• W4308377053 cites W1975062332 @default.
• W4308377053 cites W1983208069 @default.
• W4308377053 cites W1990392898 @default.
• W4308377053 cites W1992974274 @default.
• W4308377053 cites W1997266223 @default.
• W4308377053 cites W1998855618 @default.
• W4308377053 cites W2000433175 @default.
• W4308377053 cites W2009872283 @default.
• W4308377053 cites W2013393341 @default.
• W4308377053 cites W2020245429 @default.
• W4308377053 cites W2024729467 @default.
• W4308377053 cites W2031677665 @default.
• W4308377053 cites W2041782669 @default.
• W4308377053 cites W2041951497 @default.
• W4308377053 cites W2050545476 @default.
• W4308377053 cites W2058187841 @default.
• W4308377053 cites W2058711140 @default.
• W4308377053 cites W2061564920 @default.
• W4308377053 cites W2089962878 @default.
• W4308377053 cites W2092872141 @default.
• W4308377053 cites W2095491050 @default.
• W4308377053 cites W2095921032 @default.
• W4308377053 cites W2101135654 @default.
• W4308377053 cites W2101839239 @default.
• W4308377053 cites W2106592748 @default.
• W4308377053 cites W2111893966 @default.
• W4308377053 cites W2113191728 @default.
• W4308377053 cites W2118366819 @default.
• W4308377053 cites W2120125896 @default.
• W4308377053 cites W2128428930 @default.
• W4308377053 cites W2130654277 @default.
• W4308377053 cites W2131774270 @default.
• W4308377053 cites W2133903921 @default.
• W4308377053 cites W2142858796 @default.
• W4308377053 cites W2143022451 @default.
• W4308377053 cites W2146784647 @default.
• W4308377053 cites W2148230634 @default.
• W4308377053 cites W2157106546 @default.
• W4308377053 cites W2157446241 @default.
• W4308377053 cites W2167868121 @default.
• W4308377053 cites W2170702893 @default.
• W4308377053 cites W2220283892 @default.
• W4308377053 cites W2522924024 @default.
• W4308377053 cites W2526511911 @default.
• W4308377053 cites W2528571485 @default.
• W4308377053 cites W2552618727 @default.
• W4308377053 cites W2560693837 @default.
• W4308377053 cites W2591711955 @default.
• W4308377053 cites W2604068292 @default.
• W4308377053 cites W2740893736 @default.
• W4308377053 cites W2755694539 @default.
• W4308377053 cites W2757639707 @default.
• W4308377053 cites W2779020697 @default.
• W4308377053 cites W2783059789 @default.
• W4308377053 cites W2784262759 @default.
• W4308377053 cites W2805985513 @default.
• W4308377053 cites W2806489700 @default.
• W4308377053 cites W2807312764 @default.
• W4308377053 cites W2885385898 @default.
• W4308377053 cites W2886913615 @default.
• W4308377053 cites W2892767141 @default.
• W4308377053 cites W2931005391 @default.
• W4308377053 cites W2941298255 @default.
• W4308377053 cites W2951617899 @default.
• W4308377053 cites W2952574438 @default.
• W4308377053 cites W2954019805 @default.
• W4308377053 cites W2955580176 @default.
• W4308377053 cites W2964913907 @default.
• W4308377053 cites W2966020520 @default.
• W4308377053 cites W2970726176 @default.
• W4308377053 cites W2977883299 @default.
• W4308377053 cites W2985741994 @default.
• W4308377053 cites W3016970897 @default.
• W4308377053 cites W3020975691 @default.
• W4308377053 cites W3033814985 @default.
• W4308377053 cites W3035456035 @default.
• W4308377053 cites W3039011740 @default.
• W4308377053 cites W3087237868 @default.
• W4308377053 cites W3088350896 @default.
• W4308377053 cites W3089503988 @default.
• W4308377053 cites W3091005297 @default.

• next