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Data-driven tensor independent component analysis for model-based connectivity neurofeedback

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Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

EPFL2024

Shared functional connectome fingerprints following ritualistic ayahuasca intake

Enrico Amico, Hanna Tolle, Pablo Mallaroni

The knowledge that brain functional connectomes are unique and reliable has enabled behaviourally relevant inferences at a subject level. However, whether such "fingerprints" persist under altered states of consciousness is unknown. Ayahuasca is a potent s ...

San Diego2023

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

Real-Time fMRI Neurofeedback: Methods and Application to Chronic Tinnitus

Nicolas Gninenko

In the last twenty years, advances in real-time functional magnetic resonance imaging (rt-fMRI) have offered exciting new tools to study the human brain. One of them, termed rt-fMRI neurofeedback (NF), has turned the MRI scanner environment into an interac ...

EPFL2022

Mind blanking is a distinct mental state linked to a recurrent brain profile of globally positive connectivity during ongoing mentation

Dimitri Nestor Alice Van De Ville, Sepehr Mortaheb

Mind blanking (MB) is a waking state during which we do not report any mental con-tent. The phenomenology of MB challenges the view of a constantly thinking mind. Here, we comprehensively characterize the MB's neurobehavioral profile with the aim to deline ...

NATL ACAD SCIENCES2022

Predictors of real-time fMRI neurofeedback performance and improvement-A machine learning mega-analysis

Dimitri Nestor Alice Van De Ville, Frank Scharnowski, Yury Koush, Kirsten Emmert

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinic ...

2021

Effective connectivity in brain networks estimated using EEG signals is altered in children with ADHD

Amir Hossein Omidvarnia

This study presents a methodology developed for estimating effective connectivity in brain networks (BNs) using multichannel scalp EEG recordings. The methodology uses transfer entropy as an information transfer measure to detect pair-wise directed informa ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Clinical connectome fingerprints of cognitive decline

Enrico Amico, Emahnuel Troisi Lopez

Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain d ...

2021

Can we predict real-timefMRIneurofeedback learning success from pretraining brain activity?

Dimitri Nestor Alice Van De Ville, Frank Scharnowski, Kirsten Emmert, Maria Laura Blefari

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report lar ...

2020

Dynamic analysis of fMRI activation during epileptic spikes can help identify the seizure origin

Amir Hossein Omidvarnia

Objective We use the dynamic electroencephalography-functional magnetic resonance imaging (EEG-fMRI) method to incorporate variability in the amplitude and field of the interictal epileptic discharges (IEDs) into the fMRI analysis. We ask whether IED varia ...

2020

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