Connectome-based predictive modeling (CPM) based on the rs-FC data was used to predict the auditory verbal learning test-delayed recall (AVLT-DR) scores, which measured episodic memory in individuals. Pearson correlation between each brain connection in the connectivity matrices and AVLT-DR scores...
Using connectome-based predictive modeling to predict individual behavior from brain connectivity Xilin Shen Emily S Finn R Todd Constable Nature ProtocolsProtocol09 Feb 2017 Sections Figures References Abstract References Acknowledgements Author information ...
Connectome-Based Prediction Modeling Analysis was conducted using previously validated custom scripts for MATLAB release R2023b, version 23.2 (MathWorks).25 Edges positively and negatively associated with CAPS-5 total scores were selected using a threshold of P < .05, controlling for potential conf...
neuroimagingdata.Here,wepresentconnectome-basedpredictivemodeling(CPM),adata-driven protocolfordevelopingpredictivemodelsofbrain-behaviorrelationshipsfromconnectivitydata usingcross-validation.Thisprotocolincludesthefollowingsteps:1)featureselection,2)feature summarization,3)modelbuilding,and4)assessmentofpredictionsignifican...
NBS-Predict is a prediction-based extension of the Network-based Statistic (NBS) approach, which aims to alleviate the curse of dimensionality, lack of interpretability, and problem of generalizability when analyzing brain connectivity. NBS-Predict provi
Using the model developed based on the high depressive edges, the performance of the prediction achieved (r = 0.3965, MAE = 1.5984, R-squared = 0.1572,p = 0.002 (Fig.S4, Fig.4A). In addition, statistically significant prediction was obtained using the low depressive connect...
Fig. 6. Prediction of the three ADHD-RS sub-scale scores based on the average of ROI features corresponding to the 20% largest weights driven by Normconv and Edgeconv modules. (A) ADHD score, (B) inattention score, and (C) hyperactivity score. 3.3.3. Correlation between brain dysfunctions...
The human connectome refers to a comprehensive description of the brain’s structural and functional connections in terms of brain networks. As the field of brain connectomics has developed, data acquisition, subsequent processing and modeling, and ultimately the representation of the connectome have bec...
In the future, a better understanding of the roles of astrocytes and microglia in NMOSD may benefit from studies that directly associate the microscopic processes derived from animal models with neuroimaging-based features derived from human patients with the help of advanced computational modeling and ...
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