Enrico Amico

Publications associées (30)

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Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Enrico Amico

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain's computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to ...

Nature Portfolio2023

Tangent functional connectomes uncover more unique phenotypic traits

Enrico Amico, Mingkui Wang

Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projecti ...

CELL PRESS2023

Fading of brain network fingerprint in Parkinson's disease predicts motor clinical impairment

Enrico Amico, Antonella Romano

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 ...

Wiley2023

The kinectome: A comprehensive kinematic map of human motion in health and disease

Enrico Amico, Antonella Romano, Emahnuel Troisi Lopez

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

WILEY2022

Brain structure-function coupling provides signatures for task decoding and individual fingerprinting

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Maria Giulia Preti, Enrico Amico, Raphaël Pierre Liégeois

Brain signatures of functional activity have shown promising results in both decoding brain states, meaning distinguishing between different tasks, and fingerprinting, that is identifying individuals within a large group. Importantly, these brain signature ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Enrico Amico, Antonella Romano

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to ...

ELSEVIER SCI LTD2022

On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Enrico Amico, Raphaël Pierre Liégeois, Amir Hossein Omidvarnia

Measuring the temporal complexity of functional MRI (fMRI) time series is one approach to assess how brain activity changes over time. In fact, hemodynamic response of the brain is known to exhibit critical behaviour at the edge between order and disorder. ...

MDPI2022

Functional brain connectomes reflect acute and chronic cannabis use

Enrico Amico

Resting state fMRI has been employed to identify alterations in functional connectivity within or between brain regions following acute and chronic exposure to Delta 9-tetrahydrocannabinol (THC), the psychoactive component in cannabis. Most studies focused ...

Nature Research2022

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

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