Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives DOI Creative Commons

Giulia Salvatici,

Giovanni Pellegrino, Marco Perulli

et al.

NeuroImage Clinical, Journal Year: 2024, Volume and Issue: 44, P. 103703 - 103703

Published: Jan. 1, 2024

Epilepsy is one of the most diffused neurological disorders, affecting 50 million people worldwide. Around 30% patients have drug-resistant epilepsy (DRE), defined as failure at least two tolerated antiseizure medications (ASMs) to achieve sustained seizure freedom. Brain surgery an effective therapeutic approach in this group, hinging on accurate localization epileptic focus. The latter task complex and requires multimodal investigation methods. also a network disorder represents best application scenarios methods leveraging brain functional organization large scales. Connectivity analysis promising tool for improving surgical assessment, enabling better identification candidates who could benefit from surgery. scalp electroencephalography (EEG) relevant characterize activity. EEG has benefited significantly technological advancement across last decades. Firstly, electrical source imaging (ESI) allows reconstruction activity detected by cortex level; secondly, connectivity (FC) assessment dependencies areas. therefore expanded potential applications characterization epileptogenic planning. As translation these clinical practice little discussed literature, we reviewed investigations using EEG-derived FC. We showed that FC-informed networks improves precision focal epilepsy. heterogeneity results methodology preventing prompt research-to-clinic translation. finally provided practical suggestions promoting applicability FC-based research real practice, looking future research.

Language: Английский

Excitation/Inhibition balance relates to cognitive function and gene expression in temporal lobe epilepsy: a high density EEG assessment with aperiodic exponent DOI Creative Commons
Gian Marco Duma, Simone Cuozzo, Luc Wilson

et al.

Brain Communications, Journal Year: 2024, Volume and Issue: 6(4)

Published: Jan. 1, 2024

Patients with epilepsy are characterized by a dysregulation of excitation/inhibition balance (E/I). The assessment E/I may inform clinicians during the diagnosis and therapy management, even though it is rarely performed. An accessible measure brain represents clinically relevant feature. Here, we exploited exponent aperiodic component power spectrum electroencephalography (EEG) signal, as non-invasive cost-effective proxy balance. We recorded resting-state activity high-density EEG from 67 patients temporal lobe 35 controls. extracted fit source-reconstructed tested differences between Spearman's correlation was performed clinical variables (age onset, duration neuropsychology) cortical expression epilepsy-related genes derived Allen Human Brain Atlas. showed significantly larger exponent, corresponding to inhibition-directed balance, in bilateral frontal regions. Lower left entorhinal dorsolateral prefrontal cortices corresponded lower performance short-term verbal memory. Limited epilepsy, detected significant

Language: Английский

Citations

9
Linking structural and functional changes during aging using multilayer brain network analysis DOI Creative Commons
Gwendolyn Jauny, Mite Mijalkov, Anna Canal‐Garcia

et al.

Communications Biology, Journal Year: 2024, Volume and Issue: 7(1)

Published: Feb. 28, 2024

Abstract Brain structure and function are intimately linked, however this association remains poorly understood the complexity of relationship has remained understudied. Healthy aging is characterised by heterogenous levels structural integrity changes that influence functional network dynamics. Here, we use multilayer brain analysis on (diffusion weighted imaging) (magnetoencephalography) data from Cam-CAN database. We found level similarity connectivity patterns between in parietal temporal regions (alpha frequency band) associated with cognitive performance healthy older individuals. These results highlight impact reorganisation preservation function, provide a mechanistic understanding concepts maintenance compensation aging. Investigation link could thus represent new marker individual variability, pathological changes.

Language: Английский

Citations

7
Human Auditory–Motor Networks Show Frequency‐Specific Phase‐Based Coupling in Resting‐State MEG DOI Creative Commons
Oscar Bedford,

Alix Noly‐Gandon,

Alberto Ara

et al.

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(1)

Published: Jan. 1, 2025

ABSTRACT Perception and production of music speech rely on auditory–motor coupling, a mechanism which has been linked to temporally precise oscillatory coupling between auditory motor regions the human brain, particularly in beta frequency band. Recently, brain imaging studies using magnetoencephalography (MEG) have also shown that accurate temporal predictions specifically depend phase coherence cortical regions. However, it is not yet clear whether this tight an intrinsic feature loop, or only elicited by task demands. Further, we do know if synchrony uniquely enhanced system compared other sensorimotor modalities, degree amplified musical training. In order resolve these questions, measured locking visual areas musicians non‐musicians resting‐state MEG. We derived values (PLVs) transfer entropy (PTE) from 90 healthy young participants. observed significantly higher PLVs across all pairings visuomotor bands. The pairing with highest was right primary cortex ventral premotor cortex, connection highlighted previous literature coupling. Additionally, were structures hemisphere, found differences theta, alpha, Last, theta bands exhibited preference for motor‐to‐auditory PTE direction alpha gamma opposite auditory‐to‐motor direction. Taken together, findings confirm our hypotheses at rest, are theta‐beta spectrum frequencies, there exist alternating information flow loops as function frequency. view, supports existence intrinsic, time‐based low‐latency integration sounds movements involves synchronized phasic activity areas.

Language: Английский

Citations

0
Cortical parcellation optimized for magnetoencephalography with a clustering technique DOI Creative Commons
Sara Sommariva, Narayan Puthanmadam Subramaniyam, Lauri Parkkonen

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 21, 2025

A typical approach to estimate connectivity from magnetoencephalographic (MEG) data consists of 1) computing a cortically-constrained, distributed source estimate, 2) dividing the cortex into parcels according an anatomical atlas, 3) combining time courses within each parcel, and 4) metric between these combined courses. However, MEG signals spatial mean activities anatomically-defined often leads cancellation crosstalk parcels. We present method that divides whose activity can be faithfully represented by single dipolar while minimizing inter-parcel crosstalk. The relies on unsupervised clustering leadfields, also accounting for distances cortically-constrained sources promote spatially contiguous cluster point belongs is determined its k nearest-neighbour memberships. Inter-parcel was minimized assigning $$k=20-30$$ weight 20%-40% distances, leading 60–120 Our approach, available through Python package "megicparc", enables compact yet anatomically-informed source-level representation with similar dimensionality as in original sensor-level data. Such should enable significant improvements source-space visualization features or estimating functional connectivity.

Language: Английский

Citations

0
Validating MEG estimated resting state connectome with intracranial EEG DOI Creative Commons
Jawata Afnan, Zhengchen Cai, Jean‐Marc Lina

et al.

Network Neuroscience, Journal Year: 2025, Volume and Issue: 9(1), P. 421 - 446

Published: Jan. 1, 2025

Magnetoencephalography (MEG) is widely used for studying resting-state brain connectivity. However, MEG source imaging ill posed and has limited spatial resolution. This introduces source-leakage issues, making it challenging to interpret MEG-derived connectivity in resting states. To address this, we validated from 45 healthy participants using a normative intracranial EEG (iEEG) atlas. The inverse problem was solved the wavelet-maximum entropy on mean method. We computed four metrics: amplitude envelope correlation (AEC), orthogonalized AEC (OAEC), phase locking value (PLV), weighted-phase lag index (wPLI). compared between iEEG connectomes across standard canonical frequency bands. found moderate correlations PLV. when considering metrics that correct/remove zero-lag (OAEC/wPLI), decreased. exhibited higher with iEEG. suggest relevant patterns can be recovered MEG. since these are moderate/low, results should interpreted caution. Metrics correct show decreased correlations, highlighting trade-off; while may capture more due source-leakage, removing eliminate true connections.

Language: Английский

Citations

0
How do the resting EEG preprocessing states affect the outcomes of postprocessing? DOI Creative Commons
Shiang Hu,

Jie Ruan,

Pedro A. Valdés‐Sosa

et al.

NeuroImage, Journal Year: 2025, Volume and Issue: unknown, P. 121122 - 121122

Published: March 1, 2025

Plenty of artifact removal tools and pipelines have been developed to correct the resting EEG waves discover scientific values behind. Without expertised visual inspection, it is susceptible derive improper preprocessing, resulting in either insufficient preprocessed (IPE) or excessive (EPE). However, little known about impacts IPE EPE on postprocessing temporal, frequency, spatial domains, particularly as spectra functional connectivity analysis. Here, clean (CE) with linear quasi-stationary assumption was synthesized ground truth based New-York head model multivariate autoregressive model. Later, were simulated by injecting Gaussian noise losing brain components, respectively. Spectral homogeneities all EEGs evaluated proposed Parallel LOg Spectra index (PaLOSi). Then, quantified IPE/EPE deviation from CE temporal statistics, multichannel power, cross spectra, scalp network properties, source dispersion. Lastly, association between PaLOSi varying trends outcomes analyzed evolutionary preprocessing states. We found that compared CE: 1) (EPE) statistics deviated more greatly injected (brain activities discarded); 2) power higher (lower), almost parallel across frequencies, while decreased frequencies; than EPE, except for β band; 3) derived 7 coupling measures, had lower (higher) transmission efficiency worse (better) integration ability; 4) sources distributed dispersedly greater strength activated focally amplitudes; 5) consistently correlated investigated both real data. This study shed light how are affected states a promising quality control metric creating normative databases.

Language: Английский

Citations

0
The strength of anticipated distractors shapes EEG alpha and theta oscillations in a Working Memory task DOI Creative Commons
Elisa Magosso, Davide Borra

NeuroImage, Journal Year: 2024, Volume and Issue: 300, P. 120835 - 120835

Published: Sept. 7, 2024

Working Memory (WM) requires maintenance of task-relevant information and suppression task-irrelevant/distracting information. Alpha theta oscillations have been extensively investigated in relation to WM. However, studies that examine both alpha bands distractors, encompassing not only power modulation but also connectivity modulation, remain scarce. Here, we depicted, at the EEG-source level, increase induced by strong relative weak distractors during a visual Sternberg-like WM task involving encoding verbal items. During retention, or distractor was presented, predictable time nature. Analysis focused on retention phases before presentation. Theta were computed cortical regions interest, networks estimated via spectral Granger causality synthetized using in/out degree indices. The following modulations observed for vs. distractors. In band encoding, frontal increased, together with frontal-to-frontal bottom-up occipital-to-temporal-to-frontal connectivity; even increased. temporal-occipital top-down frontal-to-occipital temporal-to-occipital connectivity. From our results, postulate proactive cooperation between mechanisms: first would mediate enhancement target representation second increased inhibition sensory areas only, suppress processing imminent without interfering ongoing stimulus encoding.

Language: Английский

Citations

3
Excitation/Inhibition balance relates to cognitive function and gene expression in Temporal Lobe Epilepsy: an hdEEG assessment with aperiodic exponent DOI Creative Commons
Gian Marco Duma, Simone Cuozzo, Luc Wilson

et al.

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

Published: Feb. 4, 2024

Abstract Patients with epilepsy are characterized by a dysregulation of excitation-inhibition balance (E/I). The assessment E/I may inform clinicians during the diagnosis and therapy management, even though it is rarely performed. An accessible measure brain represents clinically relevant feature. Here we exploited exponent aperiodic component power spectrum EEG signal as noninvasive cost-effective proxy balance. We recorded resting-state activity high-density from 65 patients temporal lobe (TLE) 35 controls. extracted fit source-reconstructed tested differences between TLE Spearman’s correlation was performed clinical variables (age onset, duration neuropsychology) cortical expression epilepsy-related genes derived Human Allen Brain Atlas. showed significantly larger exponent, corresponding to an inhibition directed balance, in bilateral frontal regions. Lower left entorhinal, dorsolateral prefrontal cortices corresponded lower performance short term verbal memory. Limited TLE, detected significant GABRA1, GRIN2A, GABRD, GABRG2, KCNA2and PDYN. maps non-invasively reveals tight relationship altered patterns, cognition genetics.

Language: Английский

Citations

0
Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives DOI Creative Commons

Giulia Salvatici,

Giovanni Pellegrino, Marco Perulli

et al.

NeuroImage Clinical, Journal Year: 2024, Volume and Issue: 44, P. 103703 - 103703

Published: Jan. 1, 2024

Epilepsy is one of the most diffused neurological disorders, affecting 50 million people worldwide. Around 30% patients have drug-resistant epilepsy (DRE), defined as failure at least two tolerated antiseizure medications (ASMs) to achieve sustained seizure freedom. Brain surgery an effective therapeutic approach in this group, hinging on accurate localization epileptic focus. The latter task complex and requires multimodal investigation methods. also a network disorder represents best application scenarios methods leveraging brain functional organization large scales. Connectivity analysis promising tool for improving surgical assessment, enabling better identification candidates who could benefit from surgery. scalp electroencephalography (EEG) relevant characterize activity. EEG has benefited significantly technological advancement across last decades. Firstly, electrical source imaging (ESI) allows reconstruction activity detected by cortex level; secondly, connectivity (FC) assessment dependencies areas. therefore expanded potential applications characterization epileptogenic planning. As translation these clinical practice little discussed literature, we reviewed investigations using EEG-derived FC. We showed that FC-informed networks improves precision focal epilepsy. heterogeneity results methodology preventing prompt research-to-clinic translation. finally provided practical suggestions promoting applicability FC-based research real practice, looking future research.

Language: Английский

Citations

0