BOLD Signal Research Articles

Correlation between P2-PCA volume flow rate and BOLD cerebrovascular reactivity in patients with symptomatic carotid artery occlusion.

Identifying and assessing hemodynamic and flow status in patients with symptomatic internal carotid artery (ICA) occlusion is crucial for evaluating recurrent stroke risk. The aim of this study was to analyze the correlation between two quantitative imaging modalities: (1) blood oxygenation level-dependent (BOLD) cerebrovascular reactivity (CVR) and (2) quantitative magnetic resonance angiography (qMRA) with non-invasive optimal vessel analysis (NOVA), measuring volume flow rate (VFR). Comparing these modalities is relevant for assessing collateral circulation and hemodynamic impairment. In this retrospective analysis of prospectively collected data, 37 symptomatic patients with unilateral ICA occlusion, who underwent both, NOVA-qMRA and BOLD-CVR investigation, were included. The correlation analysis between NOVAqMRA-derived second segment of the posterior cerebral artery (PCA-P2) VFR and BOLD-CVR (hemispheric and MCA territory CVR) was done by using a linear mixed-effects model. A moderate correlation was found between P2-VFR and BOLD-CVR values for the ipsilateral MCA territory (|r|=0.44, R2=0.2, p<0.001) and the ipsilateral hemisphere (|r| =0.39, R2=0.15, p<0.001), indicating that 20% of the variance in P2-VFR can be explained by the BOLD-CVR of the MCA territory and 15% by the BOLD-CVR of the affected hemisphere. This correlation suggests that impaired BOLD-CVR is partly linked to an increased PCA-P2 volume flow rate, potentially indicating the activation of leptomeningeal collaterals in severe hemodynamic conditions. Both imaging techniques could aid clinicians in in creating personalized treatment strategies for patients with symptomatic ICA occlusion. ACA = anterior cerebral artery; BOLD = blood oxygenation-level dependent; CVR = cerebrovascular reactivity; M1 = first segment of the middle cerebral artery; MCA =middle cerebral artery; NOVA = non-invasive optimal vessel analysis; P2 = second segment of the posterior cerebral artery; PCA = posterior cerebral artery; PCOM= posterior communicating artery; VFR = volume flow rate.

Efficacy of biomarkers and imaging techniques for the diagnosis of traumatic brain injury: challenges and opportunities.

Concussion is a pervasive health issue in the present day. Increased prevalence in recent years has indicated a need to improve the current understanding of minor traumatic brain injury (mTBI). Effort has been devoted to understanding the underlying pathophysiology of TBIs, but some mechanisms remain unknown. Potentially lethal secondary effects of concussion include second impact syndrome and chronic traumatic encephalopathy (CTE), introducing long-term considerations for the management of mTBI. Post-concussion syndrome is another long-term consequence of concussion and may be influenced by both neuroinflammation and hormonal imbalances resulting from head trauma. Genetically mutated apolipoprotein E may also contribute to the severity and persistence of concussion symptoms, perhaps even acting as a risk factor for CTE. As it stands, the diagnosis of concussion is nuanced, depending primarily on subjective diagnostic tools that incorporate patient-reported symptoms and neurocognitive tests. Diagnostic tools provide some assistance in concussion diagnosis, but still lack accuracy and inherently leave room for uncertainty. To mitigate some of this uncertainty, considerable research has been devoted to the development of methods to diagnose concussions objectively. Biomarkers such as S100 calcium binding protein B (S100B), glial fibrillary acidic protein (GFAP), neurofilament light protein (Nf-L), interleukin-6 (IL-6) and microRNAs (miRNAs) as well as imaging techniques including diffusion tensor imaging (DTI) and blood-oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) show great promise in this regard. This review aims to compile the relevant literature in these areas in the hopes of being used as a reference point for future research regarding concussions.

Value construction through sequential sampling explains serial dependencies in decision making.

Deciding between a pair of familiar items is thought to rely on a comparison of their subjective values. When the values are similar, decisions take longer, and the choice may be inconsistent with stated value. These regularities are thought to be explained by the same mechanism of noisy evidence accumulation that leads to perceptual errors under conditions of low signal to noise. However, unlike perceptual decisions, subjective values may vary with internal states (e.g. desires, priorities) that change over time. This raises the possibility that the apparent stochasticity of choice reflects changes in value rather than mere noise. We hypothesized that these changes would manifest in serial dependencies across decision sequences. We analyzed data from a task in which participants chose between snack items. We developed an algorithm, Reval, that revealed significant fluctuations of the subjective values of items within an experimental session. The dynamic values predicted choices and response times more accurately than stated values. The dynamic values also furnished a superior account of the BOLD signal in ventromedial prefrontal cortex. A novel bounded-evidence accumulation model with temporally correlated evidence samples supports the idea that revaluation reflects the dynamic construction of subjective value during deliberation, which in turn influences subsequent decisions.

Value construction through sequential sampling explains serial dependencies in decision making

Deciding between a pair of familiar items is thought to rely on a comparison of their subjective values. When the values are similar, decisions take longer, and the choice may be inconsistent with stated value. These regularities are thought to be explained by the same mechanism of noisy evidence accumulation that leads to perceptual errors under conditions of low signal to noise. However, unlike perceptual decisions, subjective values may vary with internal states (e.g. desires, priorities) that change over time. This raises the possibility that the apparent stochasticity of choice reflects changes in value rather than mere noise. We hypothesized that these changes would manifest in serial dependencies across decision sequences. We analyzed data from a task in which participants chose between snack items. We developed an algorithm, Reval, that revealed significant fluctuations of the subjective values of items within an experimental session. The dynamic values predicted choices and response times more accurately than stated values. The dynamic values also furnished a superior account of the BOLD signal in ventromedial prefrontal cortex. A novel bounded-evidence accumulation model with temporally correlated evidence samples supports the idea that revaluation reflects the dynamic construction of subjective value during deliberation, which in turn influences subsequent decisions.

Sensitivity of Functional Arterial Spin Labelling in Detecting Cerebral Blood Flow Changes

Aims/Background Arterial spin labelling (ASL) is a non-invasive magnetic resonance imaging (MRI) method. ASL techniques can quantitatively measure cerebral perfusion by fitting a kinetic model to the difference between labelled images (tag images) and ones which are acquired without labelling (control images). ASL functional MRI (fMRI) provides quantitative perfusion maps by using arterial water as an endogenous tracer instead of depending on vascular blood oxygenation level.This study aimed to assess the number of pulsed ASL blocks that were needed to provide accurate and reliable regional estimates of cerebral blood flow (CBF) changes when participants engaged in visually guided saccade and fixation task; evaluate the localization to cortical control saccade versus fixation; investigate the relationship between the sensitivity of ASL fMRI and the number of blocks; and compare the sensitivity of blood oxygen level-dependent (BOLD) fMRI and ASL fMRI. Methods The experiment was a block-design paradigm consisting of two conditions: fixation and saccade. No response other than the eye movements of the participants was recorded during the scans. ASL and BOLD fMRI scans were conducted on all participants during the same session. The fMRI study consisted of two functional experiments: a CBF contrast was provided using the ASL sequence, and an optimized BOLD contrast was provided using the BOLD sequence. Results From group analysis in all divided blocks of ASL sessions (4, 6, 8...... 14, 16, 18......26, 28, 30), ASL yielded significant activation clusters in the visual cortex of the bilateral hemisphere from block 4. There was no false activation from block 4. No activation cluster was found by reversing analysis of block 2. Robust and consistent activation in the visual cortex was observed in each of the 14 divided blocks group analysis, and no activation was found in the eye field of the brain. The sensitivity of 4-block was found to be better than that of 8-block. More significant activation clusters of the visual cortex were found in BOLD than in ASL. No activation cluster of parietal eye field (PEF), frontal eye field (FEF) and supplementary eye field (SEF) was detected in ASL. The voxel size of the activation cluster increased with the increasing number of blocks, and the percent signal change in the activation cluster decreased with the escalating block number. The voxel size was positively correlated with the number of blocks (correlation coefficient = 0.98, p &lt; 0.0001), and the percent signal change negatively correlated with the number of blocks (correlation coefficient = –0.90, p &lt; 0.0001). Conclusion The 4-block pulsed functional ASL (fASL) presents accurate and reliable activation, with minimal time-on-task effect and little adverse impact of time, in participants engaging in visually guided saccade and fixation tasks. Despite having lower sensitivity than BOLD fMRI, ASL can determine accurate activation location. Although the time-on-task effects affect the observation for the sensitivity of ASL over task time, it is suggested that ASL fMRI may provide a powerful method for pinpointing the time-on-task effect over a long period of time.

Context-dependent effects of morphosyntax processing in Turkish–Persian bilinguals: Electrophysiological and neuroanatomic correlates

Aims and objectives: Morphosyntax processing is related to the P600 event-related potentials (ERPs) component and blood-oxygen-level dependent (BOLD) activation of the Pars opercularis (PO). First, this paper aims to investigate the relation of these variables across individuals. Second, we consider the role of context in morphosyntactic processing. Design/methodology: Highly proficient Turkish–Persian bilinguals ( N = 33) made morphosyntactic judgments on sentences. In a monolingual context, only L2 sentences (Persian) were presented, and the electroencephalography (EEG) was recorded. In a bilingual context, Persian and Turkish sentences alternated, and functional magnetic resonance imaging (fMRI) was measured. Data and analysis: The EEG and fMRI data were taken from separately published experiments on the same participants. Here, we correlated amplitudes of EEG-derived ERP components and the number of activated voxels in fMRI in designated brain regions because both parameters are proportionally attuned to the number of activated neurons. Findings/conclusions: Morphosyntactic violations in a Persian monolingual context yielded a P600 component in the ERP. In L1, morphosyntactic violations increased BOLD activation in the left PO and in L2 they activated the posterior superior temporal gyrus (pSTG). The P600 amplitude correlated only with BOLD activity in the left PO for L1. These results first support a critical role of the PO in generating the P600; second, the findings are context-specific and are most pronounced for the presumed base languages in different contexts (i.e., L2 in monolingual and L1 in bilingual contexts). These results are consistent with predictions of the adaptive control theory. Originality: This study contributes to the rarely investigated interface between ERPs and fMRI in bilingual speakers during morphosyntactic processing. The results offer novel insights into language context effects. Significance/implications: Our findings highlight the importance of cross-modality neuroimaging in bilinguals and language processing in both monolingual and bilingual contexts.

A preliminary study of fMRI and the relationship with depression and anxiety in Meniere's patients

PurposeTo examine alterations in Blood Oxygen Level-Dependent (BOLD) resting-state functional magnetic resonance imaging (rs-fMRI) signals, utilizing regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF) metrics, within activated brain regions. Additionally, this study aims to explore the relationship between these neural changes and clinical characteristics, as well as emotional states, in patients diagnosed with unilateral Meniere's disease (MD). MethodThe study included 24 patients diagnosed with left Meniere's disease (L-MD), 25 patients diagnosed with right Meniere's disease (R-MD), and 23 healthy control subjects. Resting-state blood‑oxygen-level-dependent functional magnetic resonance imaging (rest-BOLD-fMRI) data were preprocessed. A two-sample t-test was employed to compare the regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF) between the patient groups and the control group. Brain regions exhibiting significant differences were further analyzed for correlations with disease duration, vertigo severity, vertigo duration, hearing loss grade, and levels of anxiety and depression. ResultsIn patients with L-MD, fALFF values were significantly decreased in the right cerebellar hemisphere, middle occipital gyrus, among other regions. In patients with right-sided Ménière's disease (R-MD), fractional amplitude of low-frequency fluctuation (fALFF) values were elevated in the right middle inferior temporal gyrus and fusiform gyrus. Regional homogeneity (ReHo) values exhibited both increases and decreases in the temporal gyrus, parahippocampal gyrus, occipital gyrus, superior marginal gyrus, anterior central gyrus, and fusiform gyrus. In studies examining relational aspects, the parahippocampal gyrus, inferior temporal gyrus, middle occipital gyrus, superior middle occipital gyrus, superior marginal gyrus, and occipital gyrus demonstrated positive or negative correlations with clinical characteristics and emotional states. ConclusionsPatients with unilateral Meniere's disease (MD) exhibited both increased and decreased activation in various brain regions when compared to control subjects. A correlation was identified between these neural activation patterns and clinical characteristics, as well as emotional state, which holds significant implications for clinical treatment, prognosis, and rehabilitation strategies for MD patients.

Combination of rs-fMRI, QSM, and ASL Reveals the Cerebral Neurovascular Coupling Dysfunction Is Associated With Cognitive Decline in Patients With Chronic Kidney Disease.

Neurovascular coupling (NVC) reflects the close connection between neural activity and cerebral blood flow (CBF) responses, providing new insights to explore the neuropathological mechanisms of various diseases. Non-dialysis patients with chronic kidney disease (CKD) exhibit cognitive decline, but the underlying pathological mechanisms are unclear. The prospective study involved 53 patients with stage 1-3a CKD (CKD1-3a), 78 patients with stage 3b-5 CKD (CKD3b-5), and 52 healthy controls (HC). Our investigation involved voxel-based assessments of both global and regional BOLD signal characteristics. Additionally, we explored the correlations between neuroimaging indices, Montreal Cognitive Assessment (MoCA) scores, and clinical laboratory findings. Compared to HC, the CKD3b-5 and CKD1-3a groups exhibited lower ALLF and ReHo in the default mode network (DMN), higher CBF in bilateral hippocampus (HIP), higher susceptibility values in bilateral caudate nucleus (CAU) and putamen (PUT), and lower susceptibility values in bilateral HIP. At the global level, the coupling coefficients were lower in CKD1-3a and CKD3b-5 groups than in HC. At the ROI level, the CBF-ALFF and CBF-ReHo coupling in HIP and basal ganglia regions were lower in CKD3b-5 groups than in the CKD1-3a group. Most importantly, susceptibility-ALFF in ANG.R may mediate the effects of phosphorus on cognitive decompensation in patients with CKD1-3a. Non-dialysis patients with CKD exhibit abnormal NCV, which is associated with the cognitive decline. Specifically, the susceptibility-ALFF may serve as a valuable biomarker for early assessment of cognitive decline in CKD, offering insights into the pathogenesis of cognitive decline in CKD.

Altered Blood Oxygen Level-Dependent Signal Stability in the Brain of Patients with Major Depressive Disorder Undergoing Resting-State Functional Magnetic Resonance Imaging

Introduction: Major depressive disorder (MDD) is a common, relapse-prone psychiatric disorder with unknown pathogenesis. Previous studies on resting-state functional magnetic resonance imaging of MDD have mostly focused on the spontaneous activity of blood oxygen level-dependent (BOLD) signals; however, a few studies have investigated BOLD signal stability. Methods: We conducted a resting-state functional study in 42 patients with MDD and 42 healthy controls (HC) matched for age and sex. This included the BOLD signal stability, resting-state functional connectivity (RSFC) analysis, correlation analysis, and support vector machine (SVM) analysis. Results: The BOLD signal stability of the left fusiform gyrus, right inferior temporal gyrus, right temporal pole superior temporal gyrus, and left thalamus was significantly lower in the MDD group compared to the HC group. Further RSFC analysis revealed that the connectivity between right inferior temporal gyrus and both left inferior temporal gyrus and left supramarginal gyrus was significantly reduced in the MDD group. Additionally, the RSFC levels of left thalamus and right thalamus were decreased. Combining BOLD signal stability and RSFC, the SVM-based classification model achieved an accuracy of 80.95% (sensitivity: 78.57%; specificity: 83.33%; receiver-operating characteristic area under the curve: 0.8793). Conclusion: The integration of the BOLD signal stability index and RSFC index demonstrates a robust capability to differentiate between individuals with MDD and HC subjects. We tentatively believe that a combination of the BOLD signal stability index and RSFC can be used to diagnose MDD.

Multi-parametric MRI: can we assess renal function differently?

Abstract We are lacking tools to evaluate renal performance. In this review, we presented the current knowledge and potential future applications in nephrology of new magnetic resonance imaging (MRI) techniques, focusing on Diffusion-weighted (DWI) MRI, Blood oxygen Level Dependent (BOLD) MRI, and magnetic resonance relaxometry (T1 and T2 mapping). These sequences are sensitive to early changes in biological processes such as perfusion, oxygenation, oedema or fibrosis without requiring contrast medium injection and avoids irradiation and nephrotoxicity. Combining these different sequences into the so-called ‘multiparametric MRI’ enables non-invasive, repeated exploration of renal performance on each kidney separately. DWI MRI, which evaluates the movement of water molecules, is a promising tool for non-invasive assessment of interstitial fibrosis and the cortical restricted diffusion has a prognostic value for the deterioration of renal function in diabetic nephropathy. BOLD MRI is sensitive to changes in renal tissue oxygenation based on the paramagnetic properties of deoxyhemoglobin and is of particular interest in the setting of renal artery stenosis to assess tissue oxygenation in the post-stenotic kidney. This sequence can be used for predicting degradation of renal function in CKD and might be useful in preclinical studies to assess nephroprotective and nephrotoxic effects of drugs in development. T1 and T2 relaxation times change with tissue water content and might help assessing renal fibrosis. A corticomedullary dedifferentiation in T1 has been observed in CKD and negatively correlates with glomerular filtration rate. Data on the significance of T2 values in renal imaging is more limited. Multiparametric MRI has the potential to provide a better understanding of renal physiology and pathophysiology, a better characterization of renal lesions, an earlier and more sensitive detection of renal disease, and an aid to personalized patient-centered therapeutic decision-making. Further data and clinical trials are needed to allow its routine application in clinical practice.

The intrinsic propagation directionality of fMRI infra-slow activity during visual tasks

The temporal order of propagation in the blood-oxygen-level-dependent (BOLD) infra-slow activity (ISA, 0.01–0.1 Hz) of functional magnetic resonance imaging (fMRI) can indicate the functional organization of the brain. While prior studies have revealed the temporal order of propagation of BOLD ISA during rest, how it emerges during cognitive tasks remains unclear. Furthermore, its differences between the gray and white matters at the whole-brain scale are unexplored. In this study, we probed the propagation of BOLD ISA using a publicly available fMRI dataset from participants performing visual detection and discrimination tasks (N = 46, 29 females). We examined the temporal order of propagation based on ISA oscillatory phase differences among brain parcels. During visual task performance, ISA in both the gray and white matters propagated in a direction from the visual cortex to the association cortex, including the default mode network (DMN). This result differs from the previously reported propagation direction during rest that traveled from the visual and somatosensory cortices to the DMN, suggesting that the functional organization may change when performing cognitive tasks. In addition, the propagation in the white matter represented more complex patterns than that in the gray matter, exhibiting that the cingulum preceded DMN. Our results may help the understanding of how task performance alters the sensory-DMN propagation according of ISA.

Functional localization of the human auditory and visual thalamus using a thalamic localizer functional magnetic resonance imaging task

Abstract Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due, in part, to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmarked their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

NIMG-26. GLIOBLASTOMA TISSUE INVASION MAPPING WITH NOVEL HYPOXIA-TARGETED BLOOD OXYGENATION-LEVEL DEPENDENT MRI

Abstract BACKGROUND Glioblastoma is a devastating incurable malignant primary brain tumor exhibiting an erratic growth pattern and brain tissue invasion exceeding the typically depicted contrast-enhancing lesion on MRI. This behaviour is strongly associated with the presence of aberrant vasculature. Advanced clinical neuroimaging techniques, however, have not provided convincing imaging markers to determine glioblastoma tissue infiltration and monitor treatment effects. We investigated a new imaging technique based on blood oxygenation-level dependent (BOLD) MRI contrast with precise hypoxic respiratory targeting in order to better determine tumor tissue invasion not restricted to the typically depicted focal glioblastoma lesion on contrast-enhanced MRI. METHODS A computer-controlled gas blender was used to induce transient and standardized hypoxic stimulus in isocapnic conditions during echo-planar-imaging acquisition in patients with brain tumors.8,9 Data were preprocessed using SPM and in-house written MATLAB scripts. The induced BOLD signal changes were used to calculate %BOLD signal change during hypoxic stimulus with respect to the baseline, contrast to noise (CNR) ratio and goodness-of-fit (Rsquared) for each voxel in the whole-brain and automatically segmented region of interest (contrast-enhancement, necrosis, edema) and overlayed using color-maps onto anatomical high resolution T1. RESULTS Hypoxic targeting during gas modulation could be performed with high reproducibility, caused no discomfort in patients with brain tumors and was able to induce strong signal change during hypoxic stimulus with high contrast-noise ratio and Rsquared. In particular, when compared with other tumors, BOLD hypoxia glioblastoma tissue invasion maps show very distinct hypoxic signal responses in some cases extending beyond the focal -contrast-enhancing- glioblastoma lesion. CONCLUSION The ability to map at voxel level BOLD hypoxia signal patterns may determine a novel therapeutic imaging marker based on structural vascular alterations in the tumour tissue infiltration zone before these become appreciable with standard neuroimaging. This may support a refinement and tailoring of tumor resection and improve follow-up after resection and during treatment i.e. chemoradiotherapy.

NIMG-23. A NOVEL APPROACH TO PERFUSION MRI STUDIES IN BRAIN TUMOR PATIENTS USING ENDOGENOUS DEOXYHEMOGLOBIN AS A CONTRAST AGENT: A PROOF-OF-CONCEPT STUDY

Abstract BACKGROUND Assessment of resting perfusion in brain tumors is clinically relevant and relies on dynamic susceptibility contrast magnetic resonance imaging using gadolinium contrast. Preliminary studies have introduced the use of controlled hemoglobin desaturation by means of a transient hypoxic stimulus during echo-planar imaging(EPI) as a surrogate for gadolinium for resting perfusion assessment in healthy subjects. In this proof of concept study, we investigated whether this approach is feasible in brain tumors and warrant further validation. METHODS A computer controlled gas blender was used to induce transient and standardized hypoxic stimulus in isocapnic conditions during EPI acquisition in a heterogenous cohort of tumor patients. The induced blood-oxygen-level-dependent(BOLD) signal changes determined by transit of a bolus of deoxygenated blood in the brain vasculature were used as a surrogate of gadolinium to calculate cerebral blood volume(CBV), cerebral blood flow(CBF) and mean transit time(MTT) using a global arterial input functions obtained through the BOLD signal measured over the middle cerebral artery as previously described by Poublanc et al. Perfusion parameters were calculated in the whole-brain voxel-by-voxel and in automatically segmented region of interest(ROI) using SPM, AFNI, Verbena softwares and MATLAB in-house written scripts. RESULTS Nine patients were included. MTT, rCBV, rCBF were calculated voxel-per-voxel. Obtained maps were overlayed on the co-registered T1 MRI scans and compared to T1CE and FLAIR to identify perfusion patterns in tumor ROIs (contrast enhancement, edema, necrosis). The deoxy-hemoglobin BOLD MRI perfusion were compared to clinical DSC-MRI when available and showed high qualitative agreement. CONCLUSION Transient and precise hemoglobin desaturation by controlled hypoxic gas modulation is safe and repeatable in brain tumor patients. The induced BOLD signal change allows measurement of resting perfusion, which qualitatively closely mimic gadolinium perfusion in different brain tumors. Deoxyhemoglobin-based perfusion warrant further quantitative validation against gadolinium in a larger cohort of heterogenous tumor patients.

The influence of alterations in the composition of intestinal microbiota on neurovascular coupling and cognitive dysfunction in individuals afflicted with CSVD

IntroductionAn expanding body of research has explored the crucial role of gut microbiota in cerebral small vessel disease (CSVD). The objective of this study is to investigate alterations in the gut microbiota structure among CSVD patients, to explore the correlation between differential taxonomic levels and the neurovascular coupling index as well as cognitive function and to elucidate the imaging and biomarkers of mild cognitive impairment (MCI) in CSVD. MethodsWe enrolled 104 patients with CSVD and 40 healthy controls (HC). Based on cognitive test scores, CSVD patients were categorized into a cognitively normal group (CSVD-NCI, n=61) and a mild cognitive impairment group (CSVD-MCI, n=43). Performing magnetic resonance imaging (MRI) scans, gut microbiota analysis, as well as clinical and neuropsychological assessments for all participants. Based on arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) imaging data, cerebral blood flow (CBF) and neural activity indices are computed. The coupling indices of CBF/mReHo, CBF/mfALFF, CBF/mALFF, and CBF/mDC are calculated to assess the whole-brain neurovascular coupling changes in patients with CSVD. ResultsSpecies annotation revealed differences in the composition at the phylum and genus levels among the HC, CSVD-NCI, and CSVD-MCI groups. Additionally, differential analysis using the Kruskal-Wallis test demonstrated specific dominant microbial communities in all three groups. The relative abundance of certain dominant microbial communities in CSVD patients exhibited correlations with neurovascular coupling and cognitive function. The combined assessment of Bacteroides genus and CBF/mDC proved effective in distinguishing between CSVD-NCI and CSVD-MCI, providing a novel non-invasive approach for the diagnosis of MCI in CSVD.

Efficient fully Bayesian approach to brain activity mapping with complex-valued fMRI data

Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals. In contrast, research suggests that analyzing both real and imaginary components of the complex-valued fMRI (cv-fMRI) signal provides a more holistic approach that can increase power to detect neuronal activation. We propose a fully Bayesian model for brain activity mapping with cv-fMRI data. Our model accommodates temporal and spatial dynamics. Additionally, we propose a computationally efficient sampling algorithm, which enhances processing speed through image partitioning. Our approach is shown to be computationally efficient via image partitioning and parallel computation while being competitive with state-of-the-art methods. We support these claims with both simulated numerical studies and an application to real cv-fMRI data obtained from a finger-tapping experiment.

Sensitivity assessment of QSM+qBOLD (or QQ) in detecting elevated oxygen extraction fraction (OEF) in physiological change.

The study investigated the sensitivity of a novel MRI-based OEF mapping, quantitative susceptibility mapping plus quantitative blood oxygen level-dependent imaging (QSM+qBOLD or QQ), to physiological changes, particularly increased oxygen extraction fraction (OEF) by using hyperventilation as a vasoconstrictive stimulus. While QQ's sensitivity to decreased OEF during hypercapnia has been demonstrated, its sensitivity to increased OEF levels, crucial for cerebrovascular disorders like vascular dementia and Parkinson's disease, remains unexplored. In comparison with a previous QSM-based OEF, we evaluated QQ's sensitivity to high OEF values. MRI data were obtained from 11 healthy subjects during resting state (RS) and hyperventilation state (HV) using a 3 T MRI with a three-dimensional multi-echo gradient echo sequence (mGRE) and arterial spin labeling (ASL). Region of interest (ROI) analysis and paired t-tests were used to compare OEF, CMRO2 and CBF between QQ and QSM. Similar to QSM, QQ showed higher OEF during HV compared to RS: in cortical gray matter, QQ-OEF and QSM-OEF was 36.44.7% and 35.312.5% at RS and 45.011.6% and 45.014.8% in HV, respectively. These findings demonstrate QQ's ability to detect physiological changes and suggest its potential in studying brain metabolism in neurological disorders.

Cerebrovascular reactivity and response times describe recent ischemic symptomatology in patients with moyamoya

Abstract Moyamoya is a non-atherosclerotic intracranial steno-occlusive condition that places patients at high risk for ischemic stroke. Randomized trials of surgical revascularization demonstrating efficacy in ischemic moyamoya have not been performed, and as such, biomarkers of parenchymal hemodynamic impairment are needed to assist with triage and evaluate post-surgical response. In this prospective study, we test the hypothesis that parenchymal cerebrovascular reactivity (CVR) metrics in response to a fixed-inspired 5% carbon dioxide challenge correlate with recent focal ischemic symptoms. Hypercapnic reactivity blood oxygenation level-dependent (BOLD) MRI (echo time=35ms; spatial resolution=3.5x3.5x3.5mm) and catheter angiography assessments of cortical reserve capacity and vascular patency, respectively, in moyamoya disease and syndromic participants (n=73) were performed in sequence. Cerebrovascular reactivity uncorrected for response time (CVRRAW) was quantified, and time regression analyses were applied to quantify maximum cerebrovascular reactivity (CVRMAX) and cerebrovascular reactivity response time (CVRDELAY). Symptomatology was categorized by a stroke neurologist by hemisphere: symptomatic (lateralizing ischemic symptoms &amp;lt; 6 months) or asymptomatic (no ischemic symptom history). Values are presented as median [interquartile range]; logistic regression assessed the association of cerebrovascular reactivity metrics with symptoms, controlling for age and sex. A total of 109 hemispheres, including 39 symptomatic and 70 asymptomatic hemispheres, met inclusion criteria. Symptomatic hemispheres displayed reduced CVRRAW (p&amp;lt;0.01) (symptomatic=0.45 [0.28-0.70] z-statistic/ΔEtCO2 vs. asymptomatic=0.67 [0.44-0.98] z-statistic/ΔEtCO2), lengthened CVRDELAY (p&amp;lt;0.001) (symptomatic=47.6 [37.7-57.0] seconds vs. asymptomatic=37.7 [30.4-46.4] seconds), and reduced CVRMAX (p=0.037) (symptomatic=1.31 [0.99-1.94] z-statistic/ΔEtCO2 vs. asymptomatic=1.64 [1.29-2.12] z-statistic/ΔEtCO2). CVRDELAY (p&amp;lt;0.001) was found to be significantly related to age in asymptomatic hemispheres (0.33-unit increase/year). Of assessed measures, the receiver operating characteristic curves suggest that CVRDELAY is associated most closely with recent ischemic symptoms (p&amp;lt;0.001). Findings support that cerebrovascular reactivity metrics are uniquely altered in hemispheres with recent ischemic symptoms, further motivating their utilization as biomarkers of ischemic symptomatology and potential treatment efficacy in moyamoya disease and syndrome.

Neonatal neural responses to novelty related to behavioral inhibition at 1 year.

Behavioral inhibition (BI), an early-life temperament characterized by vigilant responses to novelty, is a risk factor for anxiety disorders. In this study, we investigated whether differences in neonatal brain responses to infrequent auditory stimuli relate to children's BI at 1 year of age. Using functional magnetic resonance imaging (fMRI), we collected blood-oxygen-level-dependent (BOLD) data from N = 45 full-term, sleeping neonates during an adapted auditory oddball paradigm and measured BI from n = 27 of these children 1 year later using an observational assessment. Whole-brain analyses corrected for multiple comparisons identified 46 neonatal brain regions producing novelty-evoked BOLD responses associated with children's BI scores at 1 year of age. More than half of these regions (n = 24, 52%) were in prefrontal cortex, falling primarily within regions of the default mode or frontoparietal networks or in ventromedial/orbitofrontal regions without network assignments. Hierarchical clustering of the regions based on their patterns of association with BI resulted in two groups with distinct anatomical, network, and response-timing profiles. The first group, located primarily in subcortical and temporal regions, tended to produce larger early oddball responses among infants with lower subsequent BI. The second group, located primarily in prefrontal cortex, produced larger early oddball responses among infants with higher subsequent BI. These results provide preliminary insights into brain regions engaged by novelty in infants that may relate to later BI. The findings may inform understanding of anxiety disorders and guide future research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

BrainMass: Advancing Brain Network Analysis for Diagnosis With Large-Scale Self-Supervised Learning.

Foundation models pretrained on large-scale datasets via self-supervised learning demonstrate exceptional versatility across various tasks. Due to the heterogeneity and hard-to-collect medical data, this approach is especially beneficial for medical image analysis and neuroscience research, as it streamlines broad downstream tasks without the need for numerous costly annotations. However, there has been limited investigation into brain network foundation models, limiting their adaptability and generalizability for broad neuroscience studies. In this study, we aim to bridge this gap. In particular, 1) we curated a comprehensive dataset by collating images from 30 datasets, which comprises 70,781 samples of 46,686 participants. Moreover, we introduce pseudo-functional connectivity (pFC) to further generates millions of augmented brain networks by randomly dropping certain timepoints of the BOLD signal; 2) we propose the BrainMass framework for brain network self-supervised learning via mask modeling and feature alignment. BrainMass employs Mask-ROI Modeling (MRM) to bolster intra-network dependencies and regional specificity. Furthermore, Latent Representation Alignment (LRA) module is utilized to regularize augmented brain networks of the same participant with similar topological properties to yield similar latent representations by aligning their latent embeddings. Extensive experiments on eight internal tasks and seven external brain disorder diagnosis tasks show BrainMass's superior performance, highlighting its significant generalizability and adaptability. Nonetheless, BrainMass demonstrates powerful few/zero-shot learning abilities and exhibits meaningful interpretation to various diseases, showcasing its potential use for clinical applications.