Publications de Enrico Amico | EPFL Graph Search

TR(Acking) Individuals Down: Exploring the Effect of Temporal Resolution in Resting-State Functional MRI Fingerprinting

Dimitri Nestor Alice Van De Ville, Enrico Amico, Francesca Saviola

Functional brain fingerprinting has emerged as an influential tool to quantify reliability in neuroimaging studies and to identify cognitive biomarkers in both healthy and clinical populations. Recent studies have revealed that brain fingerprints reside in ...

Wiley2025

Homological Landscape of Human Brain Functional Sub-Circuits

Enrico Amico

Human whole-brain functional connectivity networks have been shown to exhibit both local/quasilocal (e.g., a set of functional sub-circuits induced by node or edge attributes) and non-local (e.g., higher-order functional coordination patterns) properties. ...

2024

Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior

Enrico Amico, Andrea Santoro

Traditional models of human brain activity often represent it as a network of pairwise interactions between brain regions. Going beyond this limitation, recent approaches have been proposed to infer higher-order interactions from temporal brain signals inv ...

Nature Portfolio2024

Connectome embedding in multidimensional graph spaces

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

Nodal properties are of particular importance when investigating patterns in brain networks. Nodal information is usually studied by comparing a few nodal measurements (up to three), resulting in analyses in three-dimensional spaces, at maximum. We offer a ...

MIT PRESS2024

The unique neural signature of your trip: Functional connectome fingerprints of subjective psilocybin experience

Enrico Amico, Juan Carlos Farah

The emerging neuroscientific frontier of brain fingerprinting has recently established that human functional connectomes (FCs) exhibit fingerprint-like idiosyncratic features, which map onto heterogeneously distributed behavioral traits. Here, we harness b ...

Mit Press2024

Fingerprints of brain disease: connectome identifiability in Alzheimer’s disease

Dimitri Nestor Alice Van De Ville, Olaf Blanke, Enrico Amico, Maria Giulia Preti

Functional connectivity patterns in the human brain, like the friction ridges of a fingerprint, can uniquely identify individuals. Does this “brain fingerprint” remain distinct even during Alzheimer’s disease (AD)? Using fMRI data from healthy and patholog ...

Springer Science and Business Media LLC2024

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 ...

Academic Press Inc Elsevier Science2023

The arrow-of-time in neuroimaging time series identifies causal triggers of brain function

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Enrico Amico, Maria Giulia Preti, Raphaël Pierre Liégeois

Moving from association to causal analysis of neuroimaging data is crucial to advance our understanding of brain function. The arrow-of-time (AoT), that is, the known asymmetric nature of the passage of time, is the bedrock of causal structures shaping phy ...

Wiley2023

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states

Alessandra Griffa, Enrico Amico, Ekansh Sareen

The discovery that human brain connectivity data can be used as a "fingerprint " to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have iden-tified the possibility to extract t ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Higher-order organization of multivariate time series

Enrico Amico, Andrea Santoro

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...

NATURE PORTFOLIO2023

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

Mingkui Wang, Enrico Amico

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, Emahnuel Troisi Lopez, Antonella Romano

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, Enrico Amico, Maria Giulia Preti, 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, Amir Hossein Omidvarnia, Enrico Amico, Maria Giulia Preti, Raphaël Pierre Liégeois

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