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Primary central nervous system lymphoma (PCNSL) is an aggressive brain disease where lymphocytes invade along perivascular spaces of arteries and veins. The invasion markedly changes (peri)vascular structures but its effect on physiological brain pulsations has not been previously studied. Using physiological magnetic resonance encephalography (MREGBOLD) scanning, this study aims to quantify the extent to which (peri)vascular PCNSL involvement alters the stability of physiological brain pulsations mediated by cerebral vasculature. Clinical implications and relevance were explored. In this study, 21 PCNSL patients (median 67y; 38% females) and 30 healthy age-matched controls (median 63y; 73% females) were scanned for MREGBOLD signal during 2018–2021. Motion effects were removed. Voxel-by-voxel Coefficient of Variation (CV) maps of MREGBOLD signal was calculated to examine the stability of physiological brain pulsations. Group-level differences in CV were examined using nonparametric covariate-adjusted tests. Subject-level CV alterations were examined against control population Z-score maps wherein clusters of increased CV values were detected. Spatial distributions of clusters and findings from routine clinical neuroimaging were compared [contrast-enhanced, diffusion-weighted, fluid-attenuated inversion recovery (FLAIR) data]. Whole-brain mean CV was linked to short-term mortality with 100% sensitivity and 100% specificity, as all deceased patients revealed higher values (n = 5, median 0.055) than surviving patients (n = 16, median 0.028) (p < .0001). After adjusting for medication, head motion, and age, patients revealed higher CV values (group median 0.035) than healthy controls (group median 0.024) around arterial territories (p ≤ .001). Abnormal clusters (median 1.10 × 10₅mm₃) extended spatially beyond FLAIR lesions (median 0.62 × 10₅mm₃) with differences in volumes (p = .0055).

The physiological pulsations that drive tissue fluid homeostasis are not well characterized during brain activation. Therefore, we used fast magnetic resonance encephalography (MREG) fMRI to measure full band (0–5 Hz) blood oxygen level-dependent (BOLDFB) signals during a dynamic visual task in 23 subjects. This revealed brain activity in the very low frequency (BOLDVLF) as well as in cardiac and respiratory bands. The cardiovascular hemodynamic envelope (CHe) signal correlated significantly with the visual BOLDVLF response, considered as an independent signal source in the V1-V2 visual cortices. The CHe preceded the canonical BOLDVLF response by an average of 1.3 (± 2.2) s. Physiologically, the observed CHe signal could mark increased regional cardiovascular pulsatility following vasodilation.

Respiratory brain pulsations have recently been shown to drive electrophysiological brain activity in patients with epilepsy. Furthermore, functional neuroimaging indicates that respiratory brain pulsations have increased variability and amplitude in patients with epilepsy compared to healthy individuals. To determine whether the respiratory drive is altered in epilepsy, we compared respiratory brain pulsation synchronicity between healthy controls and patients. Whole brain fast functional magnetic resonance imaging was performed on 40 medicated patients with focal epilepsy, 20 drug-naïve patients and 102 healthy controls. Cerebrospinal fluid associated respiratory pulsations were used to generate individual whole brain respiratory synchronization maps, which were compared between groups. Finally, we analyzed the seizure frequency effect and diagnostic accuracy of the respiratory synchronization defect in epilepsy. Respiratory brain pulsations related to the verified fourth ventricle pulsations were significantly more synchronous in patients in frontal, periventricular and mid-temporal regions, while the seizure frequency correlated positively with synchronicity. The respiratory brain synchronicity had a good diagnostic accuracy (ROCAUC = 0.75) in discriminating controls from medicated patients. The elevated respiratory brain synchronicity in focal epilepsy suggests altered physiological effect of cerebrospinal fluid pulsations possibly linked to regional brain water dynamics involved with interictal brain physiology.

Background: Narcolepsy is a chronic neurological disease characterized by daytime sleep attacks, cataplexy, and fragmented sleep. The disease is hypothesized to arise from destruction or dysfunction of hypothalamic hypocretin-producing cells that innervate wake-promoting systems including the ascending arousal network (AAN), which regulates arousal via release of neurotransmitters like noradrenalin. Brain pulsations are thought to drive intracranial cerebrospinal fluid flow linked to brain metabolite transfer that sustains homeostasis. This flow increases in sleep and is suppressed by noradrenalin in the awake state. Here we tested the hypothesis that narcolepsy is associated with altered brain pulsations, and if these pulsations can differentiate narcolepsy type 1 from healthy controls. Methods: In this case-control study, 23 patients with narcolepsy type 1 (NT1) were imaged with ultrafast fMRI (MREG) along with 23 age- and sex-matched healthy controls (HC). The physiological brain pulsations were quantified as the frequency-wise signal variance. Clinical relevance of the pulsations was investigated with correlation and receiving operating characteristic analysis. Results: We find that variance and fractional variance in the very low frequency (MREGvlf) band are greater in NT1 compared to HC, while cardiac (MREGcard) and respiratory band variances are lower. Interestingly, these pulsations differences are prominent in the AAN region. We further find that fractional variance in MREGvlf shows promise as an effective bi-classification metric (AUC = 81.4%/78.5%), and that disease severity measured with narcolepsy severity score correlates with MREGcard variance (R = −0.48, p = 0.0249). Conclusions: We suggest that our novel results reflect impaired CSF dynamics that may be linked to altered glymphatic circulation in narcolepsy type 1.

The physiological underpinnings of the necessity of sleep remain uncertain. Recent evidence suggests that sleep increases the convection of cerebrospinal fluid (CSF) and promotes the export of interstitial solutes, thus providing a framework to explain why all vertebrate species require sleep. Cardiovascular, respiratory and vasomotor brain pulsations have each been shown to drive CSF flow along perivascular spaces, yet it is unknown how such pulsations may change during sleep in humans. To investigate these pulsation phenomena in relation to sleep, we simultaneously recorded fast fMRI, magnetic resonance encephalography (MREG), and electroencephalography (EEG) signals in a group of healthy volunteers. We quantified sleep-related changes in the signal frequency distributions by spectral entropy analysis and calculated the strength of the physiological (vasomotor, respiratory, and cardiac) brain pulsations by power sum analysis in 15 subjects (age 26.5 ± 4.2 years, 6 females). Finally, we identified spatial similarities between EEG slow oscillation (0.2–2 Hz) power and MREG pulsations. Compared with wakefulness, nonrapid eye movement (NREM) sleep was characterized by reduced spectral entropy and increased brain pulsation intensity. These effects were most pronounced in posterior brain areas for very low-frequency (≤0.1 Hz) vasomotor pulsations but were also evident brain-wide for respiratory pulsations, and to a lesser extent for cardiac brain pulsations. There was increased EEG slow oscillation power in brain regions spatially overlapping with those showing sleep-related MREG pulsation changes. We suggest that reduced spectral entropy and enhanced pulsation intensity are characteristic of NREM sleep. With our findings of increased power of slow oscillation, the present results support the proposition that sleep promotes fluid transport in human brain.

We review theoretical and numerical models of the glymphatic system, which circulates cerebrospinal fluid and interstitial fluid around the brain, facilitating solute transport. Models enable hypothesis development and predictions of transport, with clinical applications including drug delivery, stroke, cardiac arrest, and neurodegenerative disorders like Alzheimer’s disease. We sort existing models into broad categories by anatomical function: Perivascular flow, transport in brain parenchyma, interfaces to perivascular spaces, efflux routes, and links to neuronal activity. Needs and opportunities for future work are highlighted wherever possible; new models, expanded models, and novel experiments to inform models could all have tremendous value for advancing the field.

Introduction: There has been a growing effort to characterize the time-varying functional connectivity of resting state (RS) fMRI brain networks (RSNs). Although voxel-wise connectivity studies have examined different sliding window lengths, nonsequential volume-wise approaches have been less common. Methods: Inspired by earlier co-activation pattern (CAP) studies, we applied hierarchical clustering (HC) to classify the image volumes of the RS-fMRI data on 28 adolescents with autism spectrum disorder (ASD) and their 27 typically developing (TD) controls. We compared the distribution of the ASD and TD groups‘ volumes in CAPs as well as their voxel-wise means. For simplification purposes, we conducted a group independent component analysis to extract 14 major RSNs. The RSNs’ average z-scores enabled us to meaningfully regroup the RSNs and estimate the percentage of voxels within each RSN for which there was a significant group difference. These results were jointly interpreted to find global group-specific patterns. Results: We found similar brain state proportions in 58 CAPs (clustering interval from 2 to 30). However, in many CAPs, the voxel-wise means differed significantly within a matrix of 14 RSNs. The rest-activated default mode-positive and default mode-negative brain state properties vary considerably in both groups over time. This division was seen clearly when the volumes were partitioned into two CAPs and then further examined along the HC dendrogram of the diversifying brain CAPs. The ASD group network activations followed a more heterogeneous distribution and some networks maintained higher baselines; throughout the brain deactivation state, the ASD participants had reduced deactivation in 12/14 networks. During default mode-negative CAPs, the ASD group showed simultaneous visual network and either dorsal attention or default mode network overactivation. Conclusion: Nonsequential volume gathering into CAPs and the comparison of voxel-wise signal changes provide a complementary perspective to connectivity and an alternative to sliding window analysis.

Physiological pulsations have been shown to affect the global blood oxygen level dependent (BOLD) signal in human brain. While these pulsations have previously been regarded as noise, recent studies show their potential as biomarkers of brain pathology. We used the extended 5 Hz spectral range of magnetic resonance encephalography (MREG) data to investigate spatial and frequency distributions of physiological BOLD signal sources. Amplitude spectra of the global image signals revealed cardiorespiratory envelope modulation (CREM) peaks, in addition to the previously known very low frequency (VLF) and cardiorespiratory pulsations. We then proceeded to extend the amplitude of low frequency fluctuations (ALFF) method to each of these pulsations. The respiratory pulsations were spatially dominating over most brain structures. The VLF pulsations overcame the respiratory pulsations in frontal and parietal gray matter, whereas cardiac and CREM pulsations had this effect in central cerebrospinal fluid (CSF) spaces and major blood vessels. A quasi-periodic pattern (QPP) analysis showed that the CREM pulsations propagated as waves, with a spatiotemporal pattern differing from that of respiratory pulsations, indicating them to be distinct intracranial physiological phenomenon. In conclusion, the respiration has a dominant effect on the global BOLD signal and directly modulates cardiovascular brain pulsations.

Tiivistelmä Glymfaattinen (glia-lymfaattinen) järjestelmä eli glianestekierto on aivojen perivaskulaarinen puhdistusjärjestelmä, joka toimii syvän unen ja anestesian aikana ja mahdollistaa aivo-selkäydinnesteen virtauksen aivokudokseen huuhtomaan valveen aikana kertyneitä aineenvaihduntatuotteita. Aivo-selkäydinneste sukeltaa aivoihin valtimoita ympäröivissä perivaskulaaritiloissa ja pääsee aivokudokseen perivaskulaaritiloja ympäröivien astrosyyttien akvaporiini 4 (AQP4) -vesikanavien avustamana. Aivokudoksessa solunulkoinen neste ja sen sisältämät aineenvaihduntatuotteet, kuten beeta-amyloidi, sekoittuvat aivo-selkäydinnesteeseen. Tämä neste poistuu aivojen soluvälitilasta laskimoiden perivaskulaaritilojen kautta käyttämällä useita ulosvirtausreittejä, muun muassa aivokalvojen imusuonia. Glymfaattisen järjestelmän puutteellisen toiminnan arvellaan altistavan aivojen rappeumasairauksille sekä heikentävän toipumista aivoverenkiertohäiriöstä tai aivovammasta. Järjestelmän toimintaa tehostamalla voitaisiin puolestaan ehkäistä aivojen rappeumasairauksia tai edesauttaa esimerkiksi lääkkeiden pääsyä keskushermostoon. Glymfaattinen järjestelmä kuvattiin ensin koe-eläintutkimuksissa, ja ihmisen vastaavasta järjestelmästä tarvitaan vielä lisää tutkimusnäyttöä. Abstract The glymphatic (glial-lymphatic) system is mainly active during deep sleep and anesthesia, and allows the passage of cerebrospinal fluid into the brain parenchyma to wash the brain of harmful endogenous metabolic waste. Cerebrospinal fluid flows from the subarachnoid space to the periarterial spaces, and enters the brain parenchyma facilitated by astrocytic aquaporin 4 (AQP4) water channels. In the brain parenchyma, metabolic waste products in the interstitial fluid mix with the cerebrospinal fluid. This solute-containing fluid then flows to the perivenous spaces and is drained from the brain through several efflux routes, including the meningeal lymphatic vessels. Impaired glymphatic flow may contribute to the pathogenesis of several chronic neurodegenerative diseases and poor recovery from traumatic brain injury and ischemic stroke. On the other hand, enhancing glymphatic flow might help to prevent neurodegenerative diseases or facilitate drug delivery to the central nervous system. Although the glymphatic system was first described in rodents, recent studies suggest that a similar system functions in the human brain.

Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n = 102) and patients with epilepsy (n = 33) and furthermore to drug-naive seizure patients (n = 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11–0.51 Hz) were significantly (P

Enhancing brain fluid movement across blood brain barrier (BBB) has been recognized as a potential treatment of neurodegenerative diseases. Moreover, BBB opening is of high interest also in brain drug delivery in the treatment of brain tumors/cancers. However, efficient therapies which are based on BBB opening are still limited because of insufficient understanding of mechanisms and safety issues. Currently, there are few promising methodologically diverse BBB opening approaches. In this paper, we use functional near-infrared spectroscopy (fNIRS) for the first time for monitoring cerebral hemoglobin and water concentration changes during BBB opening in mouse brain by using two different techniques: intra-arterial mannitol infusion (IAM) and focused ultrasound (FUS). Both of these BBB opening techniques are already in clinical use but their hemo- and hydrodynamic implications have not been investigated from comparative aspect. Two fibre detectors were attached on both sides of the mouse brain and the source fibre was attached on middle of forehead. Further, by using a combination of three wavelengths 690nm, 830nm and 980nm, that have sufficient light penetration in the mouse brain, we can show average dynamics of hemoglobin and water in the whole brain, synchronized with BBB opening. To validate the level of BBB opening we used Evans blue dye and show its accumulation in the brain parenchyma tissue with the corresponding fNIRS responses.

Social and pragmatic difficulties in autism spectrum disorder (ASD) are widely recognized, although their underlying neural level processing is not well understood. The aim of this study was to examine the activity of the brain network components linked to social and pragmatic understanding in order to reveal whether complex socio-pragmatic events evoke differences in brain activity between the ASD and control groups. Nineteen young adults (mean age 23.6 years) with ASD and 19 controls (mean age 22.7 years) were recruited for the study. The stimulus data consisted of video clips showing complex social events that demanded processing of pragmatic communication. In the analysis, the functional magnetic resonance imaging signal responses of the selected brain network components linked to social and pragmatic information processing were compared. Although the processing of the young adults with ASD was similar to that of the control group during the majority of the social scenes, differences between the groups were found in the activity of the social brain network components when the participants were observing situations with concurrent verbal and non-verbal communication events. The results suggest that the ASD group had challenges in processing concurrent multimodal cues in complex pragmatic communication situations.

This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value

Development of schizophrenia relates to both genetic and environmental factors. Functional deficits in many cognitive domains, including the ability to communicate in social interactions and impaired recognition of facial expressions, are common for patients with schizophrenia and might also be present in individuals at risk of developing schizophrenia. Here we explore whether an individual’s polygenic risk score (PRS) for schizophrenia is associated with the degree of interregional similarities in blood oxygen level–dependent (BOLD) signal and gray matter volume of the face-processing network and whether the exposure to early adversity moderates this association. A total of 90 individuals (mean age 22 years, both functional and structural data available) were used for discovery analyses, and 211 individuals (mean age 26 years, structural data available) were used for replication of the structural findings. Both samples were drawn from the Northern Finland Birth Cohort 1986. We found that the degree of interregional similarities in BOLD signal and gray matter volume vary as a function of PRS; lowest interregional correlation (both measures) was observed in individuals with high PRS. We also replicated the gray matter volume finding. We did not find evidence for an interaction between early adversity and PRS on the interregional correlation of BOLD signal and gray matter volume. We speculate that the observed group differences in PRS-related correlations in both modalities may result from differences in the concurrent functional engagement of the face-processing regions over time, eg, via differences in exposure to social interaction with other people.

Ultra-fast functional magnetic resonance encephalography (MREG) enables separate assessment of cardiovascular, respiratory, and vasomotor waves from brain pulsations without temporal aliasing. We examined effects of breath hold- (BH) related changes on cardiovascular brain pulsations using MREG to study the physiological nature of cerebrovascular reactivity. We used alternating 32 s BH and 88 s resting normoventilation (NV) to change brain pulsations during MREG combined with simultaneously measured respiration, continuous non-invasive blood pressure, and cortical near-infrared spectroscopy (NIRS) in healthy volunteers. Changes in classical resting-state network BOLD-like signal and cortical blood oxygenation were reproduced based on MREG and NIRS signals. Cardiovascular pulsation amplitudes of MREG signal from anterior cerebral artery, oxygenated hemoglobin concentration in frontal cortex, and blood pressure decreased after BH. MREG cardiovascular pulse amplitudes in cortical areas and sagittal sinus increased, while cerebrospinal fluid and white matter remained unchanged. Respiratory centers in the brainstem — hypothalamus — thalamus — amygdala network showed strongest increases in cardiovascular pulsation amplitude. The spatial propagation of averaged cardiovascular impulses altered as a function of successive BH runs. The spread of cardiovascular pulse cycles exhibited a decreasing spatial similarity over time. MREG portrayed spatiotemporally accurate respiratory network activity and cardiovascular pulsation dynamics related to BH challenges at an unpreceded high temporal resolution.

Monitoring blood-brain barrier (BBB) opening is of great interest in terms of brain drug delivery in the treatment of brain lymphoma and maybe in the future in other diseases like dementia. A method involving BBB disruption (BBBD) by mannitol infusion has been developed in University of Portland, USA, and then exploited in Oulu University Hospital in treatment of primary CSN lymphoma. Proper opening of the BBB is crucial for the treatment, yet there are no methods available for its real-time clinical monitoring. Recently, we presented a combined method using direct-current electroencephalography (DC-EEG) and near-infrared spectroscopy (NIRS) for monitoring BBBD in human. Carotid artery mannitol infusion generated a strongly lateralized DC-EEG response and in NIRS a prolonged increase in the oxy/deoxyhemoglobin ratio. This study explores further BBBD, by focusing on monitoring its cardiovascular effects, when measured in human and mouse. For this, we used photoplethysmography (PPG) and opto-electro-mechanical sensors to gather the signals in human and mouse. Mannitol infusion in human causes strong fluctuations in blood pressure, heart rate and PPG signals, and here we discuss how the acquired signals in mouse model compares to human data. In addition, we present our scale-free monitoring concept that enables monitoring physiological signals similarly when performing experiments in mouse and human neuroimaging setups. By combining microscopic and macroscopic imaging in mouse setup enables us to study correlations between mechanistic cellular data and clinical functional data. Further, this allows us to validate and optimize macroscopic sensing and imaging techniques aimed to be used in human imaging.

Background and aims: Prepregnancy maternal obesity is a global health problem and has been associated with offspring metabolic and mental ill-health. However, there is a knowledge gap in understanding potential neurobiological factors related to these associations. This study explored the relation between maternal prepregnancy body mass index (BMI) and offspring brain white matter microstructure at the age of 6, 10, and 26 years in three independent cohorts. Subjects and methods: The study used data from three European birth cohorts (n = 116 children aged 6 years, n = 2466 children aged 10 years, and n = 437 young adults aged 26 years). Information on maternal prepregnancy BMI was obtained before or during pregnancy and offspring brain white matter microstructure was measured at age 6, 10, or 26 years. We used magnetic resonance imaging-derived fractional anisotropy (FA) and mean diffusivity (MD) as measures of white matter microstructure in the brainstem, callosal, limbic, association, and projection tracts. Linear regressions were fitted to examine the association of maternal BMI and offspring white matter microstructure, adjusting for several socioeconomic and lifestyle-related confounders, including education, smoking, and alcohol use. Results: Maternal BMI was associated with higher FA and lower MD in multiple brain tracts, for example, association and projection fibers, in offspring aged 10 and 26 years, but not at 6 years. In each cohort maternal BMI was related to different white matter tract and thus no common associations across the cohorts were found. Conclusions: Maternal BMI was associated with higher FA and lower MD in multiple brain tracts in offspring aged 10 and 26 years, but not at 6 years of age. Future studies should examine whether our observations can be replicated and explore the potential causal nature of the findings.

The symptoms of ADHD tend to have continuity to adulthood even though the diagnostic criteria were no longer fulfilled. The aim of our study was to find out possible differences in BOLD signal in the face-processing network between adults with previous ADHD (pADHD, n = 23) and controls (n = 29) from the same birth cohort when viewing dynamic facial expressions. The brain imaging was performed using a General Electric Signa 1.5 Tesla HDX. Dynamic facial expression stimuli included happy and fearful expressions. The pADHD group demonstrated elevated activity in the left parietal area during fearful facial expression. The Network Based Statistics including multiple areas demonstrated higher functional connectivity in attention related network during visual exposure to happy faces in the pADHD group. Conclusions: We found differences in brain responses to facial emotional expressions in individuals with previous ADHD compared to control group in a number of brain regions including areas linked to processing of facial emotional expressions and attention. This might indicate that although these individuals no longer fulfill the ADHD diagnosis, they exhibit overactive network properties affecting facial processing.

Highlights • Women lost more total brain volume than men during 8.5 years follow-up in midlife. • Women showed greater brain reduction in bilateral brain regions with and without co-varying for total brain volume loss. • Men exhibited greater brain reduction in mid-line brain regions after correcting for the total brain volume loss., Brain development during childhood and adolescence differs between boys and girls. Structural changes continue during adulthood and old age, particularly in terms of brain volume reductions that accelerate beyond age 35 years. We investigated whether brain structural change in mid-life differs between men and women. 43 men and 28 women from the Northern Finland 1966 Birth Cohort underwent MRI brain scans at age 33–35 (SD = 0.67) and then again at age 42–44 (SD = 0.41). We examined sex differences in total percentage brain volume change (PBVC) and regional brain change with FSL SIENA software. Women showed significant PBVC reduction compared with men between the ages of 33–35 and 42–44 years (Mean = −3.21% in men, Mean = −4.03% in women, F (1, 68) = 6.37, p

The aim of this paper was to investigate differences in brain structure volumes between schizophrenia and affective psychoses, and whether cumulative lifetime antipsychotic or benzodiazepine doses relate to brain morphology in these groups. We conducted two systematic reviews on the topic and investigated 44 schizophrenia cases and 19 with affective psychoses from the Northern Finland Birth Cohort 1966. The association between lifetime antipsychotic and benzodiazepine dose and brain MRI scans at the age of 43 was investigated using linear regression. Intracranial volume, sex, illness severity, and antipsychotic/benzodiazepine doses were used as covariates. There were no differences between the groups in brain structure volumes. In schizophrenia, after adjusting for benzodiazepine dose and symptoms, a negative association between lifetime antipsychotic dose and the nucleus accumbens volume remained. In affective psychoses, higher lifetime benzodiazepine dose associated with larger volumes of total gray matter and hippocampal volume after controlling for antipsychotic use and symptoms. It seems that in addition to antipsychotics, the severity of symptoms and benzodiazepine dose are also associated with brain structure volumes. These results suggest, that benzodiazepine effects should also be investigated also independently and not only as a confounder.

Introduction: Functional magnetic resonance imaging (fMRI) combined with simultaneous electroencephalography (EEG‐fMRI) has become a major tool in mapping epilepsy sources. In the absence of detectable epileptiform activity, the resting state fMRI may still detect changes in the blood oxygen level‐dependent signal, suggesting intrinsic alterations in the underlying brain physiology. Methods: In this study, we used coefficient of variation (CV) of critically sampled 10 Hz ultra‐fast fMRI (magnetoencephalography, MREG) signal to compare physiological variance between healthy controls (n = 10) and patients (n = 10) with drug‐resistant epilepsy (DRE). Results: We showed highly significant voxel‐level (p < 0.01, TFCE‐corrected) increase in the physiological variance in DRE patients. At individual level, the elevations range over three standard deviations (σ) above the control mean (μ) CVMREG values solely in DRE patients, enabling patient‐specific mapping of elevated physiological variance. The most apparent differences in group‐level analysis are found on white matter, brainstem, and cerebellum. Respiratory (0.12–0.4 Hz) and very‐low‐frequency (VLF = 0.009–0.1 Hz) signal variances were most affected. Conclusions: The CVMREG increase was not explained by head motion or physiological cardiorespiratory activity, that is, it seems to be linked to intrinsic physiological pulsations. We suggest that intrinsic brain pulsations play a role in DRE and that critically sampled fMRI may provide a powerful tool for their identification.

The lymph system is responsible for cleaning the tissues of metabolic waste products, soluble proteins and other harmful fluids etc. Lymph flow in the body is driven by body movements and muscle contractions. Moreover, it is indirectly dependent on the cardiovascular system, where the heart beat and blood pressure maintain force of pressure in lymphatic channels. Over the last few years, studies revealed that the brain contains the so-called glymphatic system, which is the counterpart of the systemic lymphatic system in the brain. Similarly, the flow in the glymphatic system is assumed to be mostly driven by physiological pulsations such as cardiovascular pulses. Thus, continuous measurement of blood pressure and heart function simultaneously with functional brain imaging is of great interest, particularly in studies of the glymphatic system. We present our MRI compatible optics based sensing system for continuous blood pressure measurement and show our current results on the effects of blood pressure variations on cerebral brain dynamics, with a focus on the glymphatic system. Blood pressure was measured simultaneously with near-infrared spectroscopy (NIRS) combined with an ultrafast functional brain imaging (fMRI) sequence magnetic resonance encephalography (MREG, 3D brain 10 Hz sampling rate).