In this study, we verified that resting-state functional connectivity could be used to predict PS in 99 older adults by using connectome-based predictive modeling (CPM). We identified two distinct connectome pa
Main Outcomes and Measures Connectome-based predictive modeling (CPM), a whole-brain machine learning approach, was applied to resting-state and task-based fMRI data collected at 1 month post trauma. The primary outcome measure was PTSD symptom severity across the 3 time points, assessed with the...
Recently, we have developed connectome-based predictive modeling (CPM) with built-in cross validation, a method for extracting and summarizing the most relevant features from brain connectivity data in order to construct predictive models 4 . Using both resting-state functional magnetic resonance ...
(CPM) provides a powerful tool to predict behavior from functional connectivity35,36. Thus, we developed seed connectome-based predictive modeling (sCPM) to link stressor-modulated hippocampal connectivity to the complex, sustained state of subjective stress. Analyses reveal that distinct patterns of ...
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
The cpmr package is specifically designed for the analysis of the connectome predictive modeling (CPM) method in R. This package relies on Rfast to do row oriented calculation. Installation You can install the released version of cpmr from CRAN with: install.packages("cpmr") Or you can inst...
predictive networks of depression using the first dataset. This was performed using the connectome-based predictive modeling (CPM). Using the established model, external validation will be conducted using datasets 2 and 3. The CPM44is a recently developed method for identifying and modeling a brain...
Here, we performed connectome-based predictive modeling (CPM) to pursue a neural biomarker of global cognitive performance in PWH based on whole-brain resting-state functional connectivity. We built a CPM model that successfully predicted individual differences in global cognitive performance in the ...
Connectome-based predictive modeling (CPM)-a recently developed machine-learning approach-has been used to examine potential neural mechanisms in addictions and other psychiatric disorders. To identify the resting-state connections associated with IGD, we modified the CPM approach by replacing its core ...
Main Outcomes and Measures: Connectome-based predictive modeling (CPM), a whole-brain machine learning approach, was applied to resting-state and task-based fMRI data collected at 1 month post trauma. The primary outcome measure was PTSD symptom severity across the 3...