MLPB_output_median

A dataset containing summarized by calculating the median for dynamic functional connectivity estimates of pairwise region of interest (ROI) comparisions.

datasets

An implementation of multivariate linear process bootstrap (MLPB) method and sliding window technique to assess the dynamic functional connectivity (dFC) estimate by providing its confidence bands, based on Maria Kudela (2017) <doi: 10.1016/j.neuroimage.2017.01.056>.
It also integrates features to visualize non-zero coverage for selected a-priori regions of interest estimated by the dynamic functional connectivity model (dFCM) and dynamic functional connectivity (dFC) curves for reward-related a-priori regions of interest where the activation-based analysis reported.

Zikai Lin

dfConn

Dynamic Functional Connectivity Analysis

Maria Kudela

Jaroslaw Harezlak

Mario Dzemidzic

MLPB_output_median function

A list with 3 matrices, each matrix has 5 rows and 731 columns, where rows represent subjects-level multivariate linear process bootstrapping (MLPB) estimates and columns represent median of MLPB estimates at each window.<dl class="dl-horizontal"><dt>median_1_2</dt><dd>matrix with 5 rows and 731 columns, containing median of multivariate linear process bootstrapping results between region 1 and 2 in subject-level.</dd>
 <dt>median_1_3</dt><dd>matrix with 5 rows and 731 columns, containing median of multivariate linear process bootstrapping results between region 1 and 3 in subject-level.</dd>
 <dt>median_2_3</dt><dd>matrix with 5 rows and 731 columns, containing median of multivariate linear process bootstrapping results between region 2 and 3 in subject-level.</dd>
</dl>

Format

Sample median output of Multivariate Linear Process Bootstrap (MLPB) — MLPB_output_median

Sample median output of Multivariate Linear Process Bootstrap (MLPB)

MLPB_output_median: Sample median output of Multivariate Linear Process Bootstrap (MLPB)

Description

Usage

Arguments

Format