Publications related to Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence

Brain connectome correlates of short-term motor learning in healthy older subjects

Friedhelm Christoph Hummel, Takuya Morishita, Manon Chloé Durand-Ruel, Chang-Hyun Park, Maeva Moyne

The motor learning process entails plastic changes in the brain, especially in brain network reconfigurations. In the current study, we sought to characterize motor learning by determining changes in the coupling behaviour between the brain functional and ...

Paris2023

Differential Impact of Brain Network Efficiency on Poststroke Motor and Attentional Deficits

Dimitri Nestor Alice Van De Ville, Friedhelm Christoph Hummel, Gabriel Girard, Takuya Morishita, Elena Beanato, Lisa Aïcha Mireille Julie Fleury, Maximilian Jonas Wessel, Philipp Johannes Koch, Philip Egger, Andéol Geoffroy Cadic-Melchior

Background:Most studies on stroke have been designed to examine one deficit in isolation; yet, survivors often have multiple deficits in different domains. While the mechanisms underlying multiple-domain deficits remain poorly understood, network-theoretic ...

2023

Improving Functional Connectome Fingerprinting with Degree-Normalization

Enrico Amico

Background: Functional connectivity quantifies the statistical dependencies between the activity of brain regions, measured using neuroimaging data such as functional magnetic resonance imaging (fMRI) blood-oxygenation-level dependent time series. The netw ...

MARY ANN LIEBERT, INC2022

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022

Multiple testing with test statistics following heavy-tailed distributions

Zhiwen Jiang

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

EPFL2021

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence

Tom Hilbert, Sébastien Bacher

Objectives To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple r ...

SPRINGER2021

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

Anjali Bagunu Tarun

The synchronized firing of distant neuronal populations gives rise to a wide array of functional brain networks that underlie human brain function. Given the enormous perception, learning, and cognition potential of the human brain, it is not surprising th ...

EPFL2020

Learning and Adaptive Data Analysis via Maximal Leakage

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

There has been growing interest in studying connections between generalization error of learning algorithms and information measures. In this work, we generalize a result that employs the maximal leakage, a measure of leakage of information, and explore ho ...

IEEE2019

A Brief History of Simulation Neuroscience

Henry Markram, Xue Fan

Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of ...

FRONTIERS MEDIA SA2019

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Meritxell Bach Cuadra, Tobias Kober, Cristina Granziera, Mario Joao Fartaria de Oliveira

Purpose: The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-conventional MR se ...

2019

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence

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Brain connectome correlates of short-term motor learning in healthy older subjects

Differential Impact of Brain Network Efficiency on Poststroke Motor and Attentional Deficits

Improving Functional Connectome Fingerprinting with Degree-Normalization

Investigating cognitive ability using action-based models of structural brain networks

Multiple testing with test statistics following heavy-tailed distributions

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

Learning and Adaptive Data Analysis via Maximal Leakage

A Brief History of Simulation Neuroscience

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Differential Impact of Brain Network Efficiency on Poststroke Motor and Attentional Deficits

Brain connectome correlates of short-term motor learning in healthy older subjects

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

A Brief History of Simulation Neuroscience

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence

Learning and Adaptive Data Analysis via Maximal Leakage

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Improving Functional Connectome Fingerprinting with Degree-Normalization

Investigating cognitive ability using action-based models of structural brain networks

Multiple testing with test statistics following heavy-tailed distributions