Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis
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Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...
IOP Publishing Ltd2023
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Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic netw ...
PERGAMON-ELSEVIER SCIENCE LTD2023
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The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics. It is an approach able to recognize individuals, based on the brain network. It showed its applicability providing network features used to predict the cog ...
WILEY2022
One of the most important goals in neuroscience research has always been to understand how animals control their behavior. However, the long focus on the role of brain neurons in behavioral control might be missing the full story. In fact, brain-wide fluct ...
Background: Modifications in brain function remain relatively unexplored in progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of the disease at this stage. Objectives: To characterize the dynamic ...
Pre-stimulus brain activity is thought to modulate visual perception. However, the underlying processes are strongly debated. Moreover, the role of pre-stimulus activity beyond tasks with single, simple stimuli is largely unknown. Here, we analyzed electro ...
2021
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Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite measuring different proxies of brain activity, both the measured blood-oxygenation ...
2021
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Measuring neural oscillatory synchrony facilitates our understanding of complex brain networks and the underlying pathological states. Altering the cross-regional synchrony-as a measure of brain network connectivity-via phase-locked deep brain stimulation ...
IEEE2022
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
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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 ...
