Algorithm framework of this paper. by Xiaoqin Wu (470428)

“…<div><p>A brain tumor magnetic resonance image processing algorithm can help doctors to diagnose and treat the patient’s condition, which has important application significance in clinical medicine. …”

Penalty functions used in different methods. by Souvik Seal (12437166)

Data_Sheet_1_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).docx by Niklas Pallast (6796196)

“…Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). …”

Data_Sheet_2_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).pdf by Niklas Pallast (6796196)

“…Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). …”

Classification accuracy and information transfer rate (ITR) as a function of the measurement set-up and the number of combined trials. by Dovilė Kurmanavičiūtė (21072549)

Data_Sheet_1_A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks.docx by Maria Grazia Puxeddu (10211162)

“…Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. …”

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

Logistic kernel: Power and Type I error for cluster evaluation metric simulations. by Alexandria M. Jensen (6494957)

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ABIDE dataset subject demographics. by Alexandria M. Jensen (6494957)

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Linear kernel: Power and Type I error for cluster evaluation metric simulations. by Alexandria M. Jensen (6494957)

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Examples of between- and within-community Beta distributions. by Alexandria M. Jensen (6494957)

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P-values from analysis of ABIDE dataset for binary outcome of diagnostic group. by Alexandria M. Jensen (6494957)

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Examples of four simulated networks and adjacency matrices. by Alexandria M. Jensen (6494957)

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P-values from analysis of ABIDE dataset for continuous outcome of VIQ. by Alexandria M. Jensen (6494957)

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Analyses of Immune microenvironment and functions between gene clusters by Jiangli Zhao (2308330)

Summary of the five most indicative brain areas and networks in the classification of healthy (HC) and early mild cognitive impairment (EMCI). by Jafar Zamani (12902504)

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Consistency of model-derived predictive patterns as a function of sample diversity. by Oualid Benkarim (9707986)

Algorithm results based on experimental likelihood functions. by Nicolas Herzig (9230425)

Table_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.XLSX by Nadia Youssef (11586382)

“…<p>The oscillatory patterns of electroencephalography (EEG), during resting states, are informative and helpful in understanding the functional states of brain network and their contribution to behavioral performances. …”

Table_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.XLSX by Nadia Youssef (11586382)

“…<p>The oscillatory patterns of electroencephalography (EEG), during resting states, are informative and helpful in understanding the functional states of brain network and their contribution to behavioral performances. …”