BROADband brain Network Estimation via Source Separation (BROAD-NESS) DOI Creative Commons
Leonardo Bonetti, Gemma Fernández-Rubio, Mads Hald Andersen

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 31, 2024

ABSTRACT This study presents BROADband brain Network Estimation via Source Separation (BROAD- NESS), a novel method tailored for event-related designs, leveraging magnetoencephalography’s (MEG) high temporal and spatial resolution to identify dynamic networks without predefined regions. By applying principal component analysis (PCA) source-reconstructed MEG data from 83 participants in long-term musical sequence recognition task, BROAD-NESS captured more effectively than traditional approaches, revealing two main that explained 88% of the variance. The first network, involving auditory cortices medial cingulate gyrus, was associated with continuous processing. second encompassing prefrontal hippocampal regions, inferior cortex, insula, linked memory, confirmed predictions prediction error With limited computational demands minimal assumptions, offers powerful tool studying dynamics, enhancing understanding memory-related sequences.

Language: Английский

Multilevel irreversibility reveals higher-order organization of nonequilibrium interactions in human brain dynamics DOI Creative Commons
Ramón Nartallo-Kaluarachchi, Leonardo Bonetti, Gemma Fernández-Rubio

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(10)

Published: March 7, 2025

Information processing in the human brain can be modeled as a complex dynamical system operating out of equilibrium with multiple regions interacting nonlinearly. Yet, despite extensive study global level nonequilibrium brain, quantifying irreversibility interactions among at levels remains an unresolved challenge. Here, we present Directed Multiplex Visibility Graph Irreversibility framework, method for analyzing neural recordings using network analysis time-series. Our approach constructs directed multilayer graphs from multivariate time-series where information about decoded marginal degree distributions across layers, which each represents variable. This framework is able to quantify every interaction system. Applying magnetoencephalography during long-term memory recognition task, between and identify combinations showed higher their interactions. For individual regions, find cognitive versus sensorial while pairs, strong relationships are uncovered pairs same hemisphere. triplets quadruplets, most cognitive-sensorial alongside medial regions. Combining these results, show that multilevel offers unique insights into higher-order, hierarchical organization dynamics perspective dynamics.

Language: Английский

Citations

0
Working Memory Predicts Long‐Term Recognition of Auditory Sequences: Dissociation Between Confirmed Predictions and Prediction Errors DOI Creative Commons
Leonardo Bonetti,

Emma Risgaard Olsen,

F. Carlomagno

et al.

Scandinavian Journal of Psychology, Journal Year: 2025, Volume and Issue: unknown

Published: May 21, 2025

ABSTRACT Memory is a crucial cognitive process involving several subsystems: sensory memory (SM), short‐term (STM), working (WM), and long‐term (LTM). While each has been extensively studied, the interaction between subsystems, particularly in relation to predicting temporal sequences, remains largely unexplored. This study investigates association WM LTM, how these relate aging musical training. Using three datasets with total of 243 healthy volunteers across various age groups, we examined impact WM, age, training on LTM recognition novel previously memorized sequences. Our results show that abilities are positively associated identification but not Additionally, similar positive while increasing reduced performance. Different processes involved handling prediction errors compared confirmatory predictions, contributes differently. Future research should extend our investigation populations impairments explore underlying neural substrates.

Language: Английский

Citations

0
Multilevel irreversibility reveals higher-order organisation of non-equilibrium interactions in human brain dynamics DOI Creative Commons
Ramón Nartallo-Kaluarachchi, Leonardo Bonetti, Gemma Fernández-Rubio

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 5, 2024

Information processing in the human brain can be modelled as a complex dynamical system operating out of equilibrium with multiple regions interacting nonlinearly. Yet, despite extensive study global level non-equilibrium brain, quantifying irreversibility interactions among at levels remains an unresolved challenge. Here, we present Directed Multiplex Visibility Graph Irreversibility framework, method for analysing neural recordings using network analysis time-series. Our approach constructs directed multi-layer graphs from multivariate time-series where information about decoded marginal degree distributions across layers, which each represents variable. This framework is able to quantify every interaction system. Applying magnetoencephalography during long-term memory recognition task, between and identify combinations showed higher their interactions. For individual regions, find cognitive versus sensorial whilst pairs, strong relationships are uncovered pairs same hemisphere. triplets quadruplets, most cognitive-sensorial alongside medial regions. Finally, quintuplets, our finds when prefrontal cortex included interaction. Combining these results, show that multilevel offers unique insights into higher-order, hierarchical organisation dynamics presents new perspective on dynamics.

Language: Английский

Citations

1
The neurophysiology of healthy and pathological aging: A comprehensive systematic review DOI Creative Commons
Gemma Fernández-Rubio, Peter Vuust, Morten L. Kringelbach

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 7, 2024

Abstract As the population of older adults grows, so does prevalence neurocognitive disorders such as mild cognitive impairment (MCI) and dementia. While biochemical, genetic, neuroimaging biomarkers have accelerated early detection diagnosis, neurophysiological measures are absent from daily medical use. Electroencephalography (EEG) magnetoencephalography (MEG) two non-invasive techniques that measure signals in brain convey information about signal strength at different frequency bands, event-related activity, complexity, temporal correlation between spatially remote regions. Here we conducted a pre-registered, comprehensive systematic review 942 studies using EEG, MEG, combined MEG EEG to characterise neurophysiology healthy aging, MCI, dementia under resting-state task conditions. To complement our search, also reviewed 51 past reviews field. Relevant features these papers were extracted present detailed overview current state evidence. Overall, show great promise diagnostic tools could prove invaluable predicting pathological aging trajectories. However, reach this potential clinical practice, it is crucial adopt longitudinal designs, standardise methodologies, identify individual rather than group level.

Language: Английский

Citations

1
BROADband brain Network Estimation via Source Separation (BROAD-NESS) DOI Creative Commons
Leonardo Bonetti, Gemma Fernández-Rubio, Mads Hald Andersen

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 31, 2024

ABSTRACT This study presents BROADband brain Network Estimation via Source Separation (BROAD- NESS), a novel method tailored for event-related designs, leveraging magnetoencephalography’s (MEG) high temporal and spatial resolution to identify dynamic networks without predefined regions. By applying principal component analysis (PCA) source-reconstructed MEG data from 83 participants in long-term musical sequence recognition task, BROAD-NESS captured more effectively than traditional approaches, revealing two main that explained 88% of the variance. The first network, involving auditory cortices medial cingulate gyrus, was associated with continuous processing. second encompassing prefrontal hippocampal regions, inferior cortex, insula, linked memory, confirmed predictions prediction error With limited computational demands minimal assumptions, offers powerful tool studying dynamics, enhancing understanding memory-related sequences.

Language: Английский

Citations

1