Biology subjects

Lina, J.-M.

Publications and source records attributed to Lina, J.-M..

13 recordsLinked to original sources

bioRxiv2026

Modulating Sleep Oscillations Through Targeted Memory Reactivation: Linking Functional Dynamics to Brain Microstructure

Background: Sleep-dependent memory consolidation reputedly rely on the coordinated activity of sleep oscillations, which may facilitate the reactivation and redistribution of newly acquired memories. Targeted memory reactivation (TMR) during sleep can experimentally modulate these processes, although effects remain variable. Moreover, how learning-related microstructural plasticity relates to sleep oscillatory activity and spindle-related network dynamics remains poorly understood. We investigated whether auditory TMR modulates sleep spindles, slow oscillations (SOs) and their co-occurrence, whether these changes relate to motor memory consolidation and diffusion MRI (dMRI) measures of brain microstructure, and whether learning and TMR alter the evolution of cortico-cortical connectivity during spindle development. Methods: Sixty healthy young adults underwent five dMRI sessions before and after motor sequence learning (Day 1), after a post-training night of regular sleep (RS) or TMR (Day 2), and before and after relearning (Day 5). Baseline and experimental nights were recorded with 256-channel high-density EEG. Oscillation densities were analyzed using mixed-design ANOVAs and related to behavioral and dMRI changes using Pearson or Spearman correlations. Intra-spindle connectivity between 148 source-reconstructed cortical regions was compared between spindle onset and end, across nights and between groups using Network-Based Statistics. Results: Spindle density, SO density and SO-spindle co-occurrence remained stable across nights in the RS group but decreased after TMR. Higher spindle density and co-occurrence were associated with greater overnight performance gains, and all oscillatory measures were associated with learning-related dMRI changes in subcortical regions, notably striatum and thalamus. Connectivity increased from the beginning to the end of the spindle duration during the baseline night in both groups, but during the experimental night only in the RS group. Conclusions: Motor learning is associated with coordinated changes in sleep oscillatory activity, within-spindle cortical connectivity and brain microstructure, supporting a dynamic interaction between learning-induced plasticity and sleep-dependent network reorganization. Under the present stimulation conditions, TMR did not enhance these processes but instead reduced sleep oscillatory activity and attenuated spindle-related connectivity dynamics, underscoring the importance of precisely targeting endogenous sleep rhythms when using TMR.

neuroscience↗

bioRxiv2026

Sleep Spindle-Locked Targeted Memory Reactivation Enhances Declarative Memory Consolidation

Study ObjectivesSleep spindles are implicated in memory consolidation. Yet direct evidence linking spindle dynamics to declarative memory outcomes remains limited. We thus tested whether targeted memory reactivation (TMR) time-locked to sleep spindles enhances declarative memory, and whether the temporal organization of stimulated spindles-trains versus isolated events-is selectively associated with distinct memory outcomes. MethodsTwenty-eight healthy young adults learned image locations from two categories (animals, clothing) in a grid, each paired with a distinct auditory cue. During overnight NREM sleep, one cue was replayed time-locked to spindles detected in real-time using a closed-loop system (TMR condition); the other served as the non-reactivated control (No-TMR condition). Category-cue assignment was counterbalanced. Post-sleep recall, recognition accuracy, and movement time were assessed. ResultsRecall accuracy was significantly higher in the TMR than the No-TMR condition (93.96% vs. 90.61%, p = .024), whereas recognition accuracy (p = .139) and movement time (p = .651) did not differ. Stimulation intensity within spindle trains correlated with the TMR effect on recall (Spearman {rho} = .531, p = .004), whereas the proportion of isolated spindle stimulations correlated with the TMR effect on recognition ({rho} = .563, p = .002). Cross-associations were not significant. ConclusionsSpindle-locked TMR enhances recall-based declarative memory retention. The selective association between spindle temporal clustering and memory outcomes suggests that train-embedded and isolated spindles support different aspects of memory consolidation, highlighting spindle temporal context as a functionally relevant dimension of sleep-dependent memory processing.

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bioRxiv2025

Sex-dependent effects of Neuroligin-2 absence on wake/sleep architecture and electrocorticographic spectral and multifractal activities

Neuroligin-2 (NLGN2) regulates GABAergic neurotransmission and is linked to neurodevelopmental disorders. The absence of NLGN2 in male mice decreases time spent in slow wave sleep and alters electrocorticographic (ECoG) activity. We tested whether NLGN2 absence also impacts wake/sleep states in females and whether sleep phenotypes associate with specific omic signatures of the cerebral cortex. Nlgn2 knockout (KO) mice and wild-type (WT) littermates were implanted with ECoG electrodes, and ECoG signals were recorded for 48 hours. Other cohorts were submitted to motor cortex sampling followed by quantifications of the transcriptome or proteome. KO mice of both sexes spent less time in slow wave and paradoxical sleep, and KO males (but not females) showed more wake and slow wave sleep episodes during the light period. Mutant animals of both sexes showed widespread differences in wake/sleep ECoG spectral activity when compared to WT mice, including a slower theta peak frequency during paradoxical sleep. The most prominent Hurst exponent was significantly increased in Nlgn2 KO animals during all states, and Hurst exponents were less dispersed during paradoxical sleep only in KO females. Less than 31% of genes with expression changed in KO versus WT mice were shared between females and males (e.g., linked to MAPK/ERK pathway, protein regulation and neurotransmission), and it was less than 15% in the case of proteins (e.g., related to calcium signaling and excitatory synapse function). Moreover, KO males showed a higher number (> 2.5 fold) of genes with expression significantly increased and decreased compared to control mice than KO females, but only KO females presented significantly lower levels of a subset of core proteins regulating synapses (e.g., SYNGAP1, HOMER1). The findings indicate that effects of NLGN2 absence on wake/sleep phenotypes and omic landscapes depend on biological sex, and could help understanding the origin of sleep disturbances in neurodevelopmental disorders.

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bioRxiv2024

EEG source imaging technique to investigate sleep oscillations for simultaneous EEG-fMRI

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a widely used non-invasive neuroimaging technique in sleep studies. However, EEG data are strongly influenced by two types of MRI-related artefacts: gradient artefacts (GA) and ballistocardiogram artefacts (BCG). If artefacts correction is suboptimal, the BCG obscures the EEG signals below 20Hz and could make it difficult to investigate sleep oscillations, especially sleep spindles, sleep specific oscillations occurring within 11-16Hz frequency band. We previously demonstrated the utility of beamforming spatial filtering in correcting MRI-related artefacts on EEG. Here, we investigated the use of beamforming spatial filtering for improving the detection of EEG oscillations during sleep, in particular, 1) to accurately estimate single-event spindle EEG power changes, and 2) to demonstrate the potential improvement of fMRI general linear model (GLM) analysis when involving such additional EEG information. We analysed EEG-fMRI data acquired during a recovery nap after sleep deprivation in 20 young healthy participants (12 females, 8 males, age = 21.3 {+/-} 2.5 years). Based on spindle events (onset and duration) detected by trained sleep scorers on BCG corrected EEG signals through a conventional average artefact subtraction (AAS) method, we compared four different EEG processing steps: non-BCG corrected; AAS BCG corrected; beamforming BCG corrected; beamforming+AAS BCG corrected. These processing steps consist of non-BCG corrected and AAS BCG corrected considered either at the sensor level or at the source-level (after beamformer localization) to evaluate the impact of the BCG artefact on the detection of spindle activity. Then we further investigated four different fMRI GLM approaches using 1) the spindle onset and duration (GLM1), 2) spindle onset, duration, and parametric modulation of single-spindle power change from the Cz electrode of the AAS BCG corrected data (GLM2), 3) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming+AAS BCG corrected (GLM3) and 4) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming BCG corrected data (GLM4). We found that the beamforming approach did not only attenuate the BCG artefacts, but also recovered sleep spindle activity occurring during NREM sleep. Furthermore, this beamforming approach allowed us to accurately estimate single-event power change of each spindle in the source space when compared to the channel level analysis, and therefore to further improve the specificity of fMRI GLM analysis, better localizing the recruited brain regions during spindles. Our findings show the benefit of applying beamforming source imaging technique to EEG-fMRI acquired during sleep. We demonstrate that this approach would be beneficial especially for long EEG-fMRI data acquisitions (i.e., sleep, resting-state), when the BCG correction becomes problematic due to inherent dynamic changes of heart rates. Our findings extend previous work regarding the application of the source imaging to the sleep EEG-fMRI. Combining with this advanced methodology and analysis, sleep EEG-fMRI will help us better understand the functional roles of human sleep.

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bioRxiv2024

Electrocorticographic and Astrocytic Signatures of Stearoyl-CoA Desaturase Inhibition in the Triple Transgenic Mouse Model of Alzheimer's Disease

The symptomatology of Alzheimers disease (AD) includes cognitive deficits and sleep disturbances. Recent findings suggest the involvement of dysfunctions in lipid metabolism, such as oleic acid build-up, in the brain of AD patients and animal models. In addition, the inhibition of stearoyl-CoA desaturase (SCD), a lipid-converting enzyme, was shown to restore memory in triple transgenic (3xTg)-AD mice. In the brain, astrocytes regulate the synthesis of specific lipids. Alterations in astrocytes and their function were reported in AD patients and animal models, and astrocytes have been implicated in the regulation of sleep. However, the relationship between sleep disturbances, astrocytes and lipid metabolism remains to be explored in AD. This project thus aimed at assessing whether the inhibition of SCD restores sleep in 3xTg-AD mice, and whether this associated with modifications in astrocytic function. Wild-type (WT) and 3xTg-AD female mice (4-months old) received intracerebroventricular infusion of a SCD inhibitor (SCDi) or vehicle for 28 days, and a 24-hour electrocorticographic (ECoG) recording was conducted post-treatment. Post-mortem brain slices were stained for the astrocytic markers glial fibrillary acidic protein (GFAP) and 10-formyltetrahydrofolate dehydrogenase (ALDH1L1) to perform cell counting and/or morphological evaluation in the hippocampus, lateral hypothalamus and thalamus. The results indicate that the reduced time spent awake and increased time spent in slow wave sleep (SWS) in 3xTg-AD mice was not restored by the SCDi treatment. Similar observations were made concerning the increased number of wake and SWS bouts in 3xTg-AD mice. Rhythmic and scale-free ECoG activity were markedly altered in 3xTg-AD mice for all wake/sleep states, and SCDi significantly altered these phenotypes in a different manner in mutant mice in comparison to WT mice. GFAP- and ALDH1L1-positive cell densities were elevated in the hippocampus and lateral hypothalamus/thalamus of 3x-Tg-AD mice, respectively, and SCDi rescued the increase in the CA1 region in particular. Overall, these findings suggest that the multiple wake/sleep alterations in 3xTg-AD mice are not substantially restored by targeting lipid metabolism using SCD inhibition, at least for the targeted age window, but that this treatment can revert hippocampal changes in astrocytes. This work will benefit the understanding of the pathophysiology related to AD and associated sleep disturbances.

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bioRxiv2022

Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas

BackgroundMagnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation. MethodWe validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (IEEG) atlas (https://mni-open-ieegatlas.research.mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space, by applying a forward model to the MEG reconstructed source maps and estimated virtual IEEG (VIEEG) potentials on each IEEG channel location and quantitatively compared those with actual IEEG signals from the atlas for 38 regions of interest in the canonical frequency bands. ResultsThe MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the VIEEG than in the IEEG were more accurately recovered. In the deep regions, MEG estimated amplitudes were largely underestimated and the spectra were poorly recovered. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of IEEG but detected by MEG. Importantly, we found that MEG estimated spectra were more comparable to spectra from the IEEG atlas after the aperiodic components were removed. ConclusionThis study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies. HighlightsO_LIValidation of MEG source imaging with intracranial EEE atlas C_LIO_LIAssessment of resting state human brain oscillations from healthy brain C_LIO_LIAdapted source imaging method, wMEM, to localize resting state oscillations C_LIO_LIIdentified brain regions with oscillations accurately estimated by MEG C_LIO_LIMEG estimated spectra dominated by oscillations in the alpha band C_LI

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bioRxiv2022

Timely sleep coupling: spindle-slow wave synchrony is linked to early amyloid-β burden and predicts memory decline

Sleep alteration is a hallmark of ageing and emerges as a risk factor for Alzheimers disease (AD). While the fine-tuned coalescence of sleep microstructure elements may influence age-related cognitive trajectories, its association with AD processes is not fully established. Here, we investigated whether the coupling of spindles and slow waves is associated with early amyloid-beta (A{beta}) brain burden, a hallmark of AD neuropathology, and cognitive change over 2 years in 100 healthy individuals in late-midlife (50-70y; 68 women). We found that, in contrast to other sleep metrics, earlier occurrence of spindles on slow-depolarisation slow waves is associated with higher medial prefrontal cortex A{beta} burden (p=0.014, r2{beta}*=0.06), and is predictive of greater longitudinal memory decline (p=0.032, r2{beta}*=0.07). These findings unravel early links between sleep, AD-related processes and cognition and suggest that altered coupling of sleep microstructure elements, key to its mnesic function, contributes to poorer brain and cognitive trajectories in ageing.

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bioRxiv2021

Altered brain criticality in Schizophrenia: New insights from MEG

Schizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements towards a central biomarker are still lacking. One of the missing pieces is a better understanding of how non-linear neural dynamics are altered in this patient population. In this study, the resting-state neuromagnetic signals of schizophrenia patients and healthy controls were analyzed in the framework of criticality. When biological systems like the brain are in a state of criticality, they are thought to be functioning at maximum efficiency (e.g., optimal communication and storage of information) and with maximum adaptability to incoming information. Here, we assessed the self-similarity and multifractality of resting-state brain signals recorded with magnetoencephalography in patients with schizophrenia patients and in matched controls. Our analysis showed a clear ascending, rostral to caudal gradient of self-similarity values in healthy controls, and an opposite gradient for multifractality (descending values, rostral to caudal). Schizophrenia patients had similar, although attenuated, gradients of self-similarity and multifractality values. Statistical tests showed that patients had higher values of self-similarity than controls in fronto-temporal regions, indicative of more regularity and memory in the signal. In contrast, patients had less multifractality than controls in the parietal and occipital regions, indicative of less diverse singularities and reduced variability in the signal. In addition, supervised machine-learning, based on logistic regression, successfully discriminated the two groups using measures of self-similarity and multifractality as features. Our results provide new insights into the baseline cognitive functioning of schizophrenia patients by identifying key alterations of criticality properties in their resting-state brain data.

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bioRxiv2021

Hierarchical Bayesian Modeling of the Relationship between Task Related Hemodynamic Responses and Neuronal Excitability: a Simultaneous fNIRS/TMS Study

BackgroundInvestigating the relationship between task-related hemodynamic responses and cortical excitability is challenging because it requires simultaneous measurement of hemodynamic responses while applying non-invasive brain stimulation. Moreover, cortical excitability and task-related hemodynamic responses are both associated with inter-/intra-subject variability. To reliably assess such a relationship, we applied hierarchical Bayesian modeling. MethodsThis study involved 16 healthy subjects who underwent simultaneous Paired Associative Stimulation (PAS10, PAS25, Sham) while monitoring brain activity using functional Near-Infrared Spectroscopy (fNIRS), targeting the primary motor cortex (M1). Cortical excitability was measured by Motor Evoked Potentials (MEPs), and the motor task-related hemodynamic responses were measured using fNIRS 3D reconstructions. We constructed three models to investigate: 1) PAS effects on the M1 excitability; 2) PAS effects on fNIRS hemodynamic responses to a finger tapping task, and 3) the correlation between PAS effects on M1 excitability and PAS effects on task-related hemodynamic responses. ResultsSignificant increase in cortical excitability was found following PAS25, whereas a small reduction of the cortical excitability was shown after PAS10 and a subtle increase occurred after sham. Both HbO and HbR absolute amplitudes increased after PAS25 and decreased after PAS10. The probability of the positive correlation between modulation of cortical excitability and hemodynamic activity was 0.77 for HbO and 0.79 for HbR. ConclusionWe demonstrated that PAS stimulation modulates task-related cortical hemodynamic responses in addition to M1 excitability. Moreover, the positive correlation between PAS modulations of excitability and hemodynamics brought insight into understanding the fundamental properties of cortical function and cortical excitability.

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bioRxiv2021

Hemodynamic Correlates of Fluctuations in Neuronal Excitability: A Simultaneous Paired Associative Stimulation (PAS) and functional Near Infra-Red Spectroscopy (fNIRS) Study

BackgroundThe relationship between task-related hemodynamic activity and brain excitability is poorly understood in humans as it is technically challenging to combine simultaneously non-invasive brain stimulation and neuroimaging modalities. Cortical excitability corresponds to the readiness to become active and as such it may be linked to metabolic demand. HypothesesCortical excitability and hemodynamic activity are positively linked so that increases in hemodynamic activity correspond to increases in excitability and vice-versa. MethodsFluctuations of excitability and hemodynamic activity were investigated via simultaneous Transcranial Magnetic Stimulation (TMS) and functional Near Infrared Spectroscopy (fNIRS). Sixteen healthy subjects participated in a sham-controlled, pseudorandomized, counterbalanced study with PAS (PAS10/PAS25/Sham) on the right primary motor cortex (M1). The relationship between M1 excitability (Motor Evoked Potentials, MEP) and hemodynamic responses to finger tapping reconstructed via personalized fNIRS was assessed. ResultsHemodynamic activity exhibited a significant correlation with cortical excitability: increased HbO and HbR (absolute amplitude) corresponded to increased excitability and vice-versa (r=0.25; p=0.03 and r=0.16; p=0.17, respectively). The effect of PAS on excitability and hemodynamic activity showed a trend of positive correlation: correlation of MEP ratios (post-PAS/pre-PAS) with HbO and HbR ratios (r=0.19, p=0.29; r=0.18, p=0.30, respectively). ConclusionsTMS-fNIRS is a suitable technique for simultaneous investigation of excitability and hemodynamic responses and indicates a relationship between these two cortical properties. PAS effect is not limited to cortical excitability but also impacts hemodynamic processes. These findings have an impact on the application of neuromodulatory interventions in patients with neuropsychiatric disorders.

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bioRxiv2021

Diffuse optical reconstructions of NIRS data using Maximum Entropy on the Mean

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin (i.e., HbO/HbR) concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40cm2 along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE. HighlightsO_LIWe introduced a new fNIRS reconstruction method - Maximum Entropy on the Mean. C_LIO_LIWe implemented depth weighting strategy within the MEM framework. C_LIO_LIWe improved the temporal accuracy of the original MEM reconstruction. C_LIO_LIPerformances of MEM and MNE were evaluated with realistic simulations and real data. C_LIO_LIMEM provided more accurate and robust reconstructions than MNE. C_LI

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bioRxiv2021

Sleeping at the Switch

Sleep slow waves are studied for their role in brain plasticity, homeostatic regulation and their changes during aging. Here, we address the possibility that two types of slow waves co-exist in humans. Thirty young and 29 older adults underwent a night of polysomnographic recordings. Using the Transition frequency, slow waves with a slow transition (slow switchers) and with a fast transition (fast switchers) were discovered. Slow switchers had a high EEG connectivity along their depolarization transition while fast switchers had a lower connectivity dynamic and dissipated faster during the night. Aging was associated with lower temporal dissipation of sleep pressure in slow and fast switchers and lower EEG connectivity at the microscale of the oscillations, suggesting a decreased flexibility in the connectivity network of older individuals. Our findings show that two different types of slow waves with possible distinct underlying functions, coexist in the slow wave spectrum.

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bioRxiv2020

Data-driven beamforming techniques to attenuate ballistocardiogram (BCG) artefacts in EEG-fMRI without detecting cardiac pulses in electrocardiography (ECG) recordings

Simultaneous recording of EEG and fMRI is a very promising non-invasive neuroimaging technique, providing a wide range of complementary information to characterize underlying mechanisms associated with brain functions. However, EEG data obtained from the simultaneous EEG-fMRI recordings are strongly influenced by MRI related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. The GA is induced by temporally varying magnetic field gradients used for MR imaging, whereas the BCG artefacts are produced by cardiac pulse driven head motion in the strong magnetic field of the MRI scanner, so that this BCG artefact will be present when the subject is lying in the scanner, even when no fMRI data are acquired. When compared to corrections of the GA, the BCG artefact corrections are more challenging to remove due to its inherent variabilities and dynamic changes over time. Typically, the BCG artefacts obscure the EEG signals below 20Hz, and this remains problematic especially when the frequency of interest of EEG signals is below 20Hz, such as Alpha (8-13Hz) and Beta (13-30Hz) band EEG activity, or sleep spindle (11-16Hz) and slow-wave oscillations (<1 Hz) during sleep. The standard BCG artefact corrections, as for instance Average Artefact Subtraction method (AAS), require detecting cardiac pulse (R-peak) events from simultaneous electrocardiography (ECG) recordings. However, ECG signals in the MRI scanner are sometimes distorted and will become problematic for detecting reliable R-peaks. In this study, we focused on a beamforming technique, which is a spatial filtering technique to reject sources of signal variance that do not appear dipolar in the source space. This technique attenuates all unwanted source activities outside of a presumed region of interest without having to specify the location or the configuration of these underlying source signals. Specifically, in this study, we revisited the advantages of the beamforming technique to attenuate the BCG artefact in EEG-fMRI, and also to recover meaningful task-based induced neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond as accurately and quickly as possible. We analysed EEG-fMRI data in 20 healthy participants when they were performing the ANT, and compared four different BCG correction approaches (non-BCG corrected, AAS BCG corrected, beamforming+AAS BCG corrected, beamforming BCG corrected). We demonstrated that beamforming BCG corrected data did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task-based induced brain activity when compared to the standard AAS BCG corrections. Without detecting R-peak events from the ECG, this data-driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG-fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI related artefacts. HighlightsO_LIBeamforming spatial filtering technique attenuates ballistocardiogram (BCG) artefacts in EEG-fMRI without detecting cardiac pulses in electrocardiography (ECG) recordings. C_LIO_LIBeamforming BCG denoising technique recovers expected task-based induced visual alpha and motor beta event-related desynchronization (ERD). C_LIO_LIBeamforming technique improves signal-noise ratios (SNR) of neural activities as compared to sensor level signals. C_LIO_LIData-driven beamforming technique appears promising for longer data acquisition of sleep and resting EEG-fMRI without relying on ECG signals. C_LI

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