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3dcnn4fmri

bgat

dnn_tl4fmri

dnnwsp

Deep neural network (DNN) with weight sparsity control (i.e., L1-norm regularization) improved the classification performance using whole-brain resting-state functional connectivity patterns of schizophrenia patient and healthy groups.

env

Eye-tracking based Naturalistic Viewing Paradigm (ENV)

extract-rsfc-pipeline

A surface-based rs-fMRI preprocessing script for extracting resting-state functional connectivity (RSFC) matrix from raw bold timeseries and T1w image.

fingerprintfcdnn

ig_pica_fmri_gene_sst

isl_rsa_digitobject_visual

khbm2019_summerschool

KHBM2019 SummerSchool: MVPA for whole brain

knu_2023_fc_classification

marp-core

The core of Marp converter

mema-cca

Mixed-effects multilevel analysis and Canonical correlation analysis in fMRI study

nbconvert

Jupyter Notebook Conversion

nimh_repro_2017

A workshop on open and reproducible neuroscience. These materials will cover 1) Using Python and Github to produce & share reproducible processing pipelines, 2) Structuring and reporting your data using community-recognized standards, 3) Accessing and contributing to share repositories, 4) Using pre-print servers

rtfmri-nf

sgnn

Official PyTorch code for "General Psychopathology Factor (p-factor) Prediction Using Resting-State Functional Connectivity and a Scanner-Generalization Neural Network"

sgnn_tl_snuh