Biology subjects

Uji, M.

Publications and source records attributed to Uji, M..

11 recordsLinked to original sources

bioRxiv2026

Reducing the Risk of Gradient Induced EEG Hardware Heating During Simultaneous EEG-fMRI

Simultaneous electroencephalography (EEG) and functional MRI (fMRI) has the potential to provide a more complete characterisation of brain function. Acquiring these data simultaneously requires the EEG hardware to be MR safe, since the EEG cap, amplifiers and powerpacks must be located within the MR environment. Placing them in this environment exposes them to both static and varying (radiofrequency (RF) and gradient) magnetic fields, presenting a potential heating risk. Previous studies have typically positioned the amplifiers and powerpacks outside of the bore, meaning that this risk is largely limited to the EEG cap. However, current guidelines recommend positioning the amplifiers within the bore. This reduces the distance between the EEG electrodes and amplifier, improving EEG signal quality and reducing risks of RF heating at the electrodes, but presents a potential heating risk for the amplifiers and powerpacks from the varying magnetic field gradients. In this study, we demonstrate that placing the amplifiers and powerpacks in the bore presents a significant heating risk, both at 7T and 3T. At 7T, we show that EPI sequences with a slew rate of at least 88 T/m/s resulted in significant heating of the EEG amplifiers. This heating effect could be negated by reducing the slew rate to 61 T/m/s. At 3T, we replicate the EEG amplifier heating and show that an alternative approach to reducing the gradient slew rates experience by the hardware is to increase the distance between the EEG amplifier/powerpacks and the isocentre of the magnet. Increasing the distance between the EEG hardware and MR isocentre by 30 cm mitigates the heating risk to the amplifiers and powerpacks, regardless of sequence parameters (e.g., slew rate). Therefore, whilst reducing the distance between the electrodes and amplifiers may improve EEG signal quality and reduce the potential for electrode RF heating, we show that risk of heating of hardware by gradient switching is greatly increased. This is particularly important to consider with the faster gradient slew rates available on modern MRI scanners, desired to increase spatial resolution. Experimenters must make careful decisions about hardware placement to ensure that the EEG-fMRI setup they use is safe, taking account of the varying risks that are posed by different approaches.

neuroscience↗

bioRxiv2026

Memory transfer unfolds through rapid shifts in memory stability states during sleep in humans

Sleep benefits learning and memory. Fundamental questions remain regarding whether and how sleep transfers memories for adaptive behavior in humans. We demonstrate that declarative to procedural memory transfer occurs through rapid network reorganization and memory stability shifts in human participants. Following local processing in motor circuit during slow wave-spindle coupling in nonrapid eye movement (NREM) sleep, multiregional communication during phasic rapid-eye movement (REM) sleep enables transfer. By leveraging a newly developed time-resolved simultaneous ultrahigh-field magnetic resonance spectroscopy and polysomnography, we further reveal that memory state becomes instantaneously unstable during slow wave-spindle coupling then enters a hyperstable state during phasic-REM sleep. Thus, sleep bridges memory systems, utilizing increased instability in NREM sleep, and transferring memory through hyperstabilization in REM sleep for knowledge integration.

neuroscience↗

bioRxiv2025

Sleep deprivation constrains dynamic configurations of integrated and segregated brain states impacting cognitive performance

The breakdown of cognitive control following sleep deprivation is widely recognised, but the physiological mechanisms and brain signatures that produce this vulnerability have not been resolved. Effective cognition relies on large-scale brain networks flexibly reconfiguring between states of integration and segregation. Here we combined functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and electrocardiography (ECG) collected during cognitive tasks under rested wakefulness, after sleep deprivation, and following a recovery nap to test the hypothesis that sleep deprivation constrains this dynamical repertoire and disrupts its physiological regulation. Using time-resolved functional connectivity and graph theory, we show that sleep deprivation increases the distribution of connections across networks, while reducing the temporal variability of between-network connectivity. Furthermore, dynamic fluctuations between integrated and segregated modes of network topology were dampened, with brain regions spending more time in intermediate configurations and showing greater instability of mode transitions. These alterations were tightly linked to behavioural impairment: participants who exhibited greater contraction toward intermediate topologies also showed poorer task accuracy and slower responses. Under well-rested conditions, thalamic activity peaked prior to transitions into integrated states and was suppressed during transitions into segregated states, consistent with a coordinating role in cortical dynamics. Sleep deprivation weakened and delayed this thalamic coupling. Finally, global and regional fMRI fluctuations were elevated after sleep loss, becoming decoupled from cardiac physiology while more strongly coupled to EEG delta power, further linking reduced arousal to constrained network flexibility. Together, these findings show that sleep deprivation narrows the brains dynamical repertoire, due to disrupted thalamic regulation and changes to the physiological integration with cortical networks.

neuroscience↗

bioRxiv2024

Human deep sleep facilitates faster cerebrospinal fluid dynamics linked to brain oscillations for sleep homeostasis and memory

How sleep maintains our healthy brain function has remained one of the biggest mysteries in neuroscience, medical settings, and daily lives. While cerebrospinal fluid (CSF) during sleep have been implicated in metabolic waste reduction in animals, how CSF dynamics are driven in the healthy human brain during deep sleep remains elusive. A myriad of research has shown that crucial cognitive processing manifests in slow wave and rapid-eye movement (REM) sleep, suggesting that a key to maintaining brain functions lies in deep sleep. By leveraging a simultaneous sparse-fMRI and polysomnography method, we demonstrate that deep sleep-specific faster CSF dynamics are associated with spontaneous brain oscillations in healthy young human participants. Slow waves and sleep spindles during slow-wave sleep and rapid eye movements and sawtooth waves during rapid eye movement (REM) sleep are tightly linked to low-amplitude faster CSF fluctuations. In contrast, slow waves during light sleep and arousals produced large but slower CSF signal changes. Furthermore, CSF signals are significantly faster in frequency during deep than light sleep. These brain oscillations during light and deep sleep recruited essentially different brain networks, with deep sleep involving memory and homeostatic circuits. Thus, human deep sleep has a unique way of enabling faster CSF dynamics that are distinctive from arousal mechanisms. Significance StatementSleep is indispensable to our life, but its functions remain a significant mystery in the field of neuroscience. One of the most enigmatic issues in sleep is whether and how sleep regulates the CSF. The present study demonstrates deep sleep-specific faster CSF dynamics time locked to sleep brain oscillations in healthy young human participants. Slow waves and sleep spindles during slow-wave sleep and rapid eye movements and sawtooth waves during REM sleep are tightly linked to CSF fluctuations, contributing to faster CSF signals. Our results consistently demonstrate that human deep sleep has a unique way of enabling faster CSF dynamics that are distinctive from arousal mechanisms.

neuroscience↗

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.

neuroscience↗

bioRxiv2024

NREM sleep brain networks modulate cognitive recovery from sleep deprivation

Decrease in cognitive performance after sleep deprivation and its recovery following sleep suggests the key role of sleep, especially non-rapid eye movement (NREM) sleep, in maintaining cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during N2 and N3 sleep in a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we introduce a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. We found that network segregation increased in the posterior cingulate cortex during both N2 and N3 sleep compared to wakefulness. In contrast, increased segregation in the visual cortex and decreased segregation in the posterior ventromedial prefrontal cortex during N2 returned to levels comparable to wakefulness during N3. More segregation during N3 sleep was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. Sleep-related changes in network segregation emerged at different spatial scales, with regional- and voxel-level alterations being associated with different cognitive tasks. Finally, we demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

neuroscience↗

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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bioRxiv2020

Altered functional integration of brain activity is a marker of impaired cognitive performance following sleep deprivation

Sleep deprivation (SD) leads to impairments in cognitive function. Here, we tested the hypothesis that cognitive changes in the sleep-deprived brain can be explained by information processing within and between large-scale cortical networks. We acquired functional magnetic resonance imaging (fMRI) scans of 20 healthy volunteers during attention and executive tasks following a regular night of sleep, a night of sleep deprivation, and a recovery nap containing non-rapid eye movement (NREM) sleep. Overall, sleep deprivation was associated with increased cortex-wide functional integration, driven by a rise of integration within cortical networks. The ratio of within vs between network integration in the cortex increased further in the recovery nap, suggesting that prolonged wakefulness drives the cortex toward a state resembling sleep. This balance of integration and segregation in the sleep-deprived state was tightly associated with deficits in cognitive performance. This was a distinct and better marker of cognitive impairment than conventional indicators of homeostatic sleep pressure, as well as the pronounced thalamo-cortical connectivity changes that occurs towards falling asleep. Importantly, restoration of the balance between segregation and integration of cortical activity was also related to performance recovery after the nap, demonstrating a bi-directional effect. These results demonstrate that intra- and inter-individual differences in cortical network integration and segregation during task performance may play a critical role in vulnerability to cognitive impairment in the sleep deprived state. Significance StatementSleep deprivation has significant negative consequences for cognitive function. Understanding how changes in brain activity underpin changes in cognition is important not only to discover why performance declines following extended periods of wakefulness, but also for answering the fundamental question of why we require regular and recurrent sleep for optimal performance. Finding neural correlates that predict performance following sleep deprivation also has the potential to understand which individuals are particularly vulnerable to sleep deprivation, and what aspects of brain function may protect them from these negative consequences on performance. Finally, understanding how perturbations to regular (well-rested) brain functioning affect cognitive performance, will provide important insight into how underlying principles of information processing in the brain may support cognition generally.

neuroscience↗

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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bioRxiv2019

Identifying cortical substrates underlying the phenomenology of stereopsis and realness: A pilot fMRI study

Viewing a real scene or a stereoscopic image (e.g., 3D movies) with both eyes yields a vivid subjective impression of object solidity, tangibility, immersive negative space and sense of realness; something that is not experienced when viewing single pictures of 3D scenes normally with both eyes. This phenomenology, sometimes referred to as stereopsis, is conventionally ascribed to the derivation of depth from the differences in the two eyes images (binocular disparity). Here we report on a pilot study designed to explore if dissociable neural activity associated with the phenomenology of realness can be localised in the cortex. In order to dissociate subjective impression from disparity processing, we capitalised on the finding that the impression of realness associated with stereoscopic viewing can also be generated when viewing a single picture of a 3D scene with one eye through an aperture. Under a blocked fMRI design, subjects viewed intact and scrambled images of natural 3-D objects and scenes under three viewing conditions: (1) single pictures viewed normally with both eyes (binocular) (2) single pictures viewed with one eye through an aperture (monocular-aperture); (3) stereoscopic anaglyph images of the same scenes viewed with both eyes (binocular stereopsis). Fixed-effects GLM contrasts aimed at isolating the phenomenology of stereopsis demonstrated a selective recruitment of similar posterior parietal regions for both monocular and binocular stereopsis conditions. Our findings provide preliminary evidence that the cortical processing underlying the subjective impression of realness may be dissociable and distinct from the derivation of depth from disparity.

neuroscience↗

bioRxiv2019

Dissociating neural activity associated with the subjective phenomenology of monocular stereopsis: an EEG study

AbstractsThe subjective phenomenology associated with stereopsis, of solid tangible objects separated by a palpable negative space, is conventionally thought to be a by-product of the derivation of depth from binocular disparity. However, the same qualitative impression has been reported in the absence of disparity, e.g., when viewing pictorial images monocularly through an aperture. Here we aimed to explore if we could identify dissociable neural activity associated with the qualitative impression of stereopsis, in the absence of the processing of binocular disparities. We measured EEG activity while subjects viewed pictorial (non-stereoscopic) images of 2D and 3D geometric forms under four different viewing conditions (Binocular, Monocular, Binocular aperture, Monocular aperture). EEG activity was analysed by oscillatory source localization (beamformer technique) to examine power change in occipital and parietal regions across viewing and stimulus conditions in targeted frequency bands (alpha: 8-13Hz & gamma: 60-90Hz). We observed expected event-related gamma synchronization and alpha desynchronization in occipital cortex and predominant gamma synchronization in parietal cortex across viewing and stimulus conditions. However, only the viewing condition predicted to generate the strongest impression of stereopsis (monocular aperture) revealed significantly elevated gamma synchronization within the parietal cortex for the critical contrasts (3D vs. 2D form). These findings suggest dissociable neural processes specific to the qualitative impression of stereopsis as distinguished from disparity processing.

neuroscience↗