The Spatiotemporal Dynamics of Cerebral Autoregulation in Functional Magnetic Resonance Imaging.
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ABSTRACT:
SUBMITTER: Whittaker JR
PROVIDER: S-EPMC9304653 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Deviation of mean arterial blood pressure (MAP) from the range that optimizes cerebral autoregulatory vasoreactivity (optimal MAP) could increase neurological injury from hypoxic-ischemic encephalopathy (HIE). We tested whether a global magnetic resonance imaging (MRI) brain injury score and regional diffusion tensor imaging (DTI) are associated with optimal MAP in neonates with HIE. METHODS:Twenty-five neonates cooled for HIE were monitored with the hemoglobin volume index. In this observational study, we identified optimal MAP and measured brain injury by qualitative and quantitative MRIs with the Neonatal Research Network (NRN) score and DTI mean diffusivity scalars. Optimal MAP and blood pressure were compared with brain injury. RESULTS:Neonates with blood pressure measurements within optimal MAP during rewarming had less brain injury by NRN score (P = 0.040). Longer duration of MAP within optimal MAP during hypothermia correlated with higher mean diffusivity in the anterior centrum semiovale (P = 0.008) and pons (P = 0.002). Blood pressure deviation below optimal MAP was associated with lower mean diffusivity in cerebellar white matter (P = 0.033). Higher optimal MAP values related to lower mean diffusivity in the basal ganglia (P = 0.021), the thalamus (P = 0.006), the posterior limb of the internal capsule (P = 0.018), the posterior centrum semiovale (P = 0.035), and the cerebellar white matter (P = 0.008). Optimal MAP values were not associated with the NRN score. CONCLUSIONS:The NRN score and the regional mean diffusivity scalars detected injury with mean arterial blood pressure deviations from the optimal MAP. Higher optimal MAP and lower mean diffusivity may be related because of cytotoxic edema and limited vasodilatory reserve at low MAP in injured brain. DTI detected injury with elevated optimal MAP better than the NRN score.
| S-EPMC5960435 | biostudies-literature
Project description:The specificity of the hemodynamic response function (HRF) is determined spatially by the vascular architecture and temporally by the evolution of hemodynamic changes. The stimulus duration has additional influence on the spatiotemporal evolution of the HRF, as brief stimuli elicit responses that engage only the local vasculature, whereas long stimuli lead to the involvement of remote vascular supply and drainage. Here, we used functional magnetic resonance imaging to investigate the spatiotemporal evolution of the blood oxygenation level-dependent (BOLD), cerebral blood flow (CBF), and cerebral blood volume (CBV) HRF to ultrashort forelimb stimulation in an anesthetized rodent model. The HRFs to a single 333-?s-long stimulus were robustly detected and consisted of a rapid response in both CBF and CBV, with an onset time (OT) of 350 ms and a full width at half-maximum of 1 s. In contrast, longer stimuli elicited a dispersive transit of oxygenated blood across the cortical microvasculature that significantly prolonged the evolution of the CBV HRF, but not the CBF. The CBF and CBV OTs suggest that vasoactive messengers are synthesized, released, and effective within 350 ms. However, the difference between the BOLD and CBV OT (?100 ms) was significantly smaller than the arteriolar-venular transit time (?500 ms), indicating an arterial contribution to the BOLD HRF. Finally, the rapid rate of growth of the active region with stimulus elongation suggests that functional hyperemia is an integrative process that involves the entire functional cortical depth. These findings offer a new view into the spatiotemporal dynamics of functional hemodynamic regulation in the brain.
| S-EPMC3078723 | biostudies-literature
Project description:In addition to its role in hemorrhagic stroke, advanced cerebral amyloid angiopathy (CAA) is also associated with ischemic lesions and vascular cognitive impairment. We used functional magnetic resonance imaging (MRI) techniques to identify CAA-associated vascular dysfunction.Functional MRI was performed on 25 nondemented subjects with probable CAA (mean ± standard deviation age, 70.2 ± 7.8 years) and 12 healthy elderly controls (age, 75.3 ± 6.2 years). Parameters measured were reactivity to visual stimulation (quantified as blood oxygen level-dependent [BOLD] response amplitude, time to peak response, and time to return to baseline after stimulus cessation) and resting absolute cerebral blood flow in the visually activated region (measured by arterial spin labeling).CAA subjects demonstrated reduced response amplitude (percentage change in BOLD signal, 0.65 ± 0.28 vs 0.89 ± 0.14; p < 0.01), prolonged time to peak (11.1 ± 5.1 vs 6.4 ± 1.8 seconds; p < 0.001), and prolonged time to baseline (16.5 ± 6.7 vs 11.6 ± 3.1 seconds; p < 0.001) relative to controls. These differences were independent of age, sex, and hypertension in multivariable analysis and were also present in secondary analyses excluding nonresponsive voxels or voxels containing chronic blood products. Within the CAA group, longer time to peak correlated with overall volume of white matter T2 hyperintensity (Pearson correlation, 0.53; p = 0.007). Absolute resting blood flow in visual cortex, in contrast, was essentially identical between the groups (44.0 ± 12.6 vs 45.0 ± 10.0 ml/100 g/min, p = 0.8).Functional MRI identifies robust differences in both amplitude and timing of the response to visual stimulation in advanced CAA. These findings point to potentially powerful approaches for identifying the mechanistic links between vascular amyloid deposits, vascular dysfunction, and CAA-related brain injury.
| S-EPMC3408630 | biostudies-literature
Project description:Naturalistic stimuli, including movie, music, and speech, have been increasingly applied in the research of neuroimaging. Relative to a resting-state or single-task state, naturalistic stimuli can evoke more intense brain activities and have been proved to possess higher test–retest reliability, suggesting greater potential to study adaptive human brain function. In the current research, naturalistic functional magnetic resonance imaging (N-fMRI) has been a powerful tool to record brain states under naturalistic stimuli, and many efforts have been devoted to study the high-level semantic features from spatial or temporal representations via N-fMRI. However, integrating both spatial and temporal characteristics of brain activities for better interpreting the patterns under naturalistic stimuli is still underexplored. In this work, a novel hybrid learning framework that comprehensively investigates both the spatial (via Predictive Model) and the temporal [via convolutional neural network (CNN) model] characteristics of the brain is proposed. Specifically, to focus on certain relevant regions from the whole brain, regions of significance (ROS), which contain common spatial activation characteristics across individuals, are selected via the Predictive Model. Further, voxels of significance (VOS), whose signals contain significant temporal characteristics under naturalistic stimuli, are interpreted via one-dimensional CNN (1D-CNN) model. In this article, our proposed framework is applied onto the N-fMRI data during naturalistic classical/pop/speech audios stimuli. The promising performance is achieved via the Predictive Model to differentiate the different audio categories. Especially for distinguishing the classic and speech audios, the accuracy of classification is up to 92%. Moreover, spatial ROS and VOS are effectively obtained. Besides, temporal characteristics of the high-level semantic features are investigated on the frequency domain via convolution kernels of 1D-CNN model, and we effectively bridge the “semantic gap” between high-level semantic features of N-fMRI and low-level acoustic features of naturalistic audios in the frequency domain. Our results provide novel insights on characterizing spatiotemporal patterns of brain activities via N-fMRI and effectively explore the high-level semantic features under naturalistic stimuli, which will further benefit the understanding of the brain working mechanism and the advance of naturalistic stimuli clinical application.
| S-EPMC9563232 | biostudies-literature
Project description:BackgroundAccumulating studies have indicated a wide range of brain alterations with respect to the structure and function of classic trigeminal neuralgia (CTN). Given the dynamic nature of pain experience, the exploration of temporal fluctuations in interregional activity covariance may enhance the understanding of pain processes in the brain. The present study aimed to characterize the temporal features of functional connectivity (FC) states as well as topological alteration in CTN.MethodsResting-state functional magnetic resonance imaging and three-dimensional T1-weighted images were obtained from 41 CTN patients and 43 matched healthy controls (HCs). After group independent component analysis, sliding window based dynamic functional network connectivity (dFNC) analysis was applied to investigate specific FC states and related temporal properties. Then, the dynamics of the whole brain topological organization were estimated by calculating the coefficient of variation of graph-theoretical properties. Further correlation analyses were performed between all these measurements and clinical data.ResultsTwo distinct states were identified. Of these, the state 2, characterized by complicated coupling between default mode network (DMN) and cognitive control network (CC) and tight connections within DMN, was expressed more in CTN patients and presented as increased fractional windows and dwell time. Moreover, patients switched less frequently between states than HCs. Regarding the dynamic topological analysis, disruptions in global graph-theoretical properties (including network efficiency and small-worldness) were observed in patients, coupled with decreased variability in nodal efficiency of anterior cingulate cortex (ACC) in the salience network (SN) and the thalamus and caudate nucleus in the subcortical network (SC). The variation of topological properties showed negative correlation with disease duration and attack frequency.ConclusionsThe present study indicated disrupted flexibility of brain topological organization under persistent noxious stimulation and further highlighted the important role of "dynamic pain connectome" regions (including DMN/CC/SN) in the pathophysiology of CTN from the temporal fluctuation aspect. Additionally, the findings provided supplementary evidence for current knowledge about the aberrant cortical-subcortical interaction in pain development.
| S-EPMC8903588 | biostudies-literature
Project description:Genome wide DNA methylation profiling of normal and tumour prostate samples. The Illumina Infinium MethylationEPIC Human DNA methylation oligonucleotide beads was used to obtain DNA methylation profiles across approximately 850,000 CpGs. Comparative assessment was carried out.
2018-12-01 | GSE101908 | GEO
Project description:The General Linear Model (GLM) used in task-fMRI relates activated brain areas to extrinsic task conditions. The translation of resulting neural activation into a hemodynamic response is commonly approximated with a linear convolution model using a hemodynamic response function (HRF). There are two major limitations in GLM analysis. Firstly, the GLM assumes that neural activation is either on or off and matches the exact stimulus duration in the corresponding task timings. Secondly, brain networks observed in resting-state fMRI experiments present also during task experiments, but the GLM approach models these task-unrelated brain activity as noise. A novel kernel matrix factorization approach, called hemodynamic matrix factorization (HMF), is therefore proposed that addresses both limitations by assuming that task-related and task-unrelated brain activity can be modeled with the same convolution model as in GLM analysis. By contrast to the GLM, the proposed HMF is a blind source separation (BSS) technique, which decomposes fMRI data into modes. Each mode comprises of a neural activation time course and a spatial mapping. Two versions of HMF are proposed in which the neural activation time course of each mode is convolved with either the canonical HRF or predetermined subject-specific HRFs. Firstly, HMF with the canonical HRF is applied to two open-source cohorts. These cohorts comprise of several task experiments including motor, incidental memory, spatial coherence discrimination, verbal discrimination task and a very short localization task, engaging multiple parts of the eloquent cortex. HMF modes were obtained whose neural activation time course followed original task timings and whose corresponding spatial map matched cortical areas known to be involved in the respective task processing. Secondly, the alignment of these neural activation time courses to task timings were further improved by replacing the canonical HRF with subject-specific HRFs during HMF mode computation. In addition to task-related modes, HMF also produced seemingly task-unrelated modes whose spatial maps matched known resting-state networks. The validity of a fMRI task experiment relies on the assumption that the exposure to a stimulus for a given time causes an imminent increase in neural activation of equal duration. The proposed HMF is an attempt to falsify this assumption and allows to identify subject task participation that does not comply with the experiment instructions.
| S-EPMC8210649 | biostudies-literature
Project description:BackgroundPrevious functional magnetic resonance imaging (fMRI) sleep studies have been hampered by the difficulty of obtaining extended amounts of sleep in the sleep-adverse environment of the scanner and often have resorted to manipulations such as sleep depriving subjects before scanning. These manipulations limit the generalizability of the results.New methodThe current study is a methodological validation of procedures aimed at obtaining all-night fMRI data in sleeping subjects with minimal exposure to experimentally induced sleep deprivation. Specifically, subjects slept in the scanner on two consecutive nights, allowing the first night to serve as an adaptation night.Results/comparison with existing method(s)Sleep scoring results from simultaneously acquired electroencephalography data on Night 2 indicate that subjects (n = 12) reached the full spectrum of sleep stages including slow-wave (M = 52.1 min, SD = 26.5 min) and rapid eye movement (REM, M = 45.2 min, SD = 27.9 min) sleep and exhibited a mean of 2.1 (SD = 1.1) nonREM-REM sleep cycles.ConclusionsIt was found that by diligently applying fundamental principles and methodologies of sleep and neuroimaging science, performing all-night fMRI sleep studies is feasible. However, because the two nights of the study were performed consecutively, some sleep deprivation from Night 1 as a cause of the Night 2 results is likely, so consideration should be given to replicating the current study with a washout period. It is envisioned that other laboratories can adopt the core features of this protocol to obtain similar results.
| S-EPMC6524535 | biostudies-literature
Project description:Despite maximally-safe resection of the MRI-defined contrast-enhanced (CE) central tumor area and chemo-radiotherapy, most glioblastoma patients relapse within one year in peritumor FLAIR regions. Spectroscopic MRI (MRSI) can discriminate metabolic tumor areas with higher recurrence potential as CNI+ regions (Choline/N-acetyl-aspartate Index>2) can predict relapse sites. As relapses are mainly imputed to glioblastoma stem-like cells (GSC), CNI+ areas might be GSC-enriched. We conducted a prospective trial in 16 GBM patients subjected to preoperative MRSI/MRI and surgery/chemo-radiotherapy to investigate GSC content in CNI+ versus CNI- biopsies from CE/FLAIR. Biopsy characterization by RNAseq revealed that FLAIR/CNI+ areas were enriched in stem-related gene signature, but also in pathways related to DNA repair, adhesion/migration and mitochondrial bioenergetics.
2023-11-03 | GSE239379 | GEO
Project description:Large-scale brain dynamics are believed to lie in a latent, low-dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting-state data, ignoring a potentially large-and shared-portion of this space. Here, we establish that a shared, robust, and interpretable low-dimensional space of brain dynamics can be recovered from a rich repertoire of task-based functional magnetic resonance imaging (fMRI) data. This occurs when relying on nonlinear approaches as opposed to traditional linear methods. The embedding maintains proper temporal progression of the tasks, revealing brain states and the dynamics of network integration. We demonstrate that resting-state data embeds fully onto the same task embedding, indicating similar brain states are present in both task and resting-state data. Our findings suggest analysis of fMRI data from multiple cognitive tasks in a low-dimensional space is possible and desirable.
| S-EPMC8410525 | biostudies-literature