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Functional magnetic resonance imaging (fMRI) has dramatically advanced non-invasive human brain mapping and decoding. Functional near-infrared spectroscopy (fNIRS) and high-density diffuse optical tomography (HD-DOT) non-invasively measure blood oxygen fluctuations related to brain activity, like fMRI, at the brain surface, using more-lightweight equipment that circumvents ergonomic and logistical limitations of fMRI. HD-DOT grids have smaller inter-optode spacing (~ 13 mm) than sparse fNIRS (~ 30 mm) and therefore provide higher image quality, with spatial resolution ~ 1/2 that of fMRI, when using the several source-detector distances (13–40 mm) afforded by the HD-DOT grid. Herein, simulations indicated reducing inter-optode spacing to 6.5 mm, creating a higher-density grid with more source-detector distances, would further improve image quality and noise-resolution tradeoff, with diminishing returns below 6.5 mm. We then constructed an ultra-high-density DOT system (6.5-mm spacing) with 140 dB dynamic range that imaged stimulus-evoked activations with 30–50% higher spatial resolution and repeatable multi-focal activity with excellent agreement with participant-matched fMRI. Further, this system decoded visual stimulus position with 19–35% lower error than previous HD-DOT, throughout occipital cortex. [ABSTRACT FROM AUTHOR]

The use of submillimeter resolution functional magnetic resonance imaging (fMRI) is increasing in popularity due to the prospect of studying human brain activation non-invasively at the scale of cortical layers and columns. This method, known as laminar fMRI, is inherently signal-to-noise ratio (SNR)-limited, especially at lower field strengths, with the dominant noise source being of thermal origin. Furthermore, laminar fMRI is challenged with signal displacements due to draining vein effects in conventional gradient-echo blood oxygen level-dependent (BOLD) imaging contrasts. fMRI contrasts such as cerebral blood volume (CBV)-sensitive vascular space occupancy (VASO) sequences have the potential to mitigate draining vein effects. However, VASO comes along with another reduction in detection sensitivity. NOise Reduction with DIstribution Corrected (NORDIC) PCA (principal component analysis) is a denoising technique specifically aimed at suppressing thermal noise, which has proven useful for increasing the SNR of high-resolution functional data. While NORDIC has been examined for BOLD acquisitions, its application to VASO data has been limited, which was the focus of the present study. We present a preliminary analysis to evaluate NORDIC's capability to suppress thermal noise while preserving the VASO signal across a wide parameter space at 3T. For the data presented here, with a proper set of parameters, NORDIC reduced thermal noise with minimal bias on the underlying signal and preserved spatial resolution. Denoising performance was found to vary with different implementation strategies and parameter choices, for which we provide recommendations. We conclude that when applied properly, NORDIC has the potential to overcome the sensitivity limitations of laminar-specific VASO fMRI. Since very few groups currently have 3T VASO data, by sharing our analysis and code, we can compile and compare the effects of NORDIC across a broader range of acquisition parameters and study designs. Such a communal effort will help develop robust recommendations that will increase the utility of laminar fMRI at lower field strengths. [ABSTRACT FROM AUTHOR]

High-resolution awake mouse functional magnetic resonance imaging (fMRI) remains challenging despite extensive efforts to address motion-induced artifacts and stress. This study introduces an implantable radio frequency (RF) surface coil design that minimizes image distortion caused by the air/tissue interface of mouse brains while simultaneously serving as a headpost for fixation during scanning. Furthermore, this study provides a thorough acclimation method used to accustom animals to the MRI environment minimizing motion-induced artifacts. Using a 14 T scanner, high-resolution fMRI enabled brain-wide functional mapping of visual and vibrissa stimulation at 100 μm×100 μm×200 μm resolution with a 2 s per frame sampling rate. Besides activated ascending visual and vibrissa pathways, robust blood oxygen level-dependent (BOLD) responses were detected in the anterior cingulate cortex upon visual stimulation and spread through the ventral retrosplenial area (VRA) with vibrissa air-puff stimulation, demonstrating higher-order sensory processing in association cortices of awake mice. In particular, the rapid hemodynamic responses in VRA upon vibrissa stimulation showed a strong correlation with the hippocampus, thalamus, and prefrontal cortical areas. Cross-correlation analysis with designated VRA responses revealed early positive BOLD signals at the contralateral barrel cortex (BC) occurring 2 s prior to the air-puff in awake mice with repetitive stimulation, which was not detected using a randomized stimulation paradigm. This early BC activation indicated a learned anticipation through the vibrissa system and association cortices in awake mice under continuous exposure of repetitive air-puff stimulation. This work establishes a high-resolution awake mouse fMRI platform, enabling brain-wide functional mapping of sensory signal processing in higher association cortical areas. [ABSTRACT FROM AUTHOR]

Rather than a passive reflection of nociception, pain is shaped by the interplay between one's experiences, current cognitive-affective states, and expectations. The placebo response, a paradoxical yet reliable phenomenon, is postulated to reduce pain by engaging mechanisms shared with active therapies. It has been assumed that mindfulness meditation, practiced by sustaining nonjudgmental awareness of arising sensory events, merely reflects mechanisms evoked by placebo. Recently, brain-based multivariate pattern analysis has been validated to successfully disentangle nociceptive-specific, negative affective, and placebo-based dimensions of the subjective pain experience. To determine whether mindfulness meditation engages distinct brain mechanisms from placebo and sham mindfulness to reduce pain, multivariate pattern analysis pain signatures were applied across 2 randomized clinical trials that employed overlapping psychophysical pain testing procedures (49 °C noxious heat; visual analog pain scales) and distinct functional magnetic resonance imaging techniques (blood oxygen level–dependent; perfusion based). After baseline pain testing, 115 healthy participants were randomized into a 4-session mindfulness meditation (n = 37), placebo-cream conditioning (n = 19), sham mindfulness meditation (n = 20), or book-listening control (n = 39) intervention. After each intervention, noxious heat was administered during functional magnetic resonance imaging and each manipulation. A double dissociation in the multivariate pattern analysis signatures supporting pain regulation was revealed by mindfulness meditation compared with placebo cream. Mindfulness meditation produced significantly greater reductions in pain intensity and pain unpleasantness ratings and nociceptive-specific and negative affective pain signatures than placebo cream, sham mindfulness meditation, and control interventions. The placebo-cream group significantly lowered the placebo-based signature. Mindfulness meditation and placebo engaged distinct and granular neural pain signatures to reduce pain. [ABSTRACT FROM AUTHOR]

Developmental dyslexia (DD) is one of the most common learning disorders, affecting millions of children and adults worldwide. To date, scientific research has attempted to explain DD primarily based on pathophysiological alterations in the cerebral cortex. In contrast, several decades ago, pioneering research on five post-mortem human brains suggested that a core characteristic of DD might be morphological alterations in a specific subdivision of the visual thalamus—the magnocellular lateral geniculate nucleus (M-LGN). However, due to considerable technical challenges in investigating LGN subdivisions non-invasively in humans, this finding was never confirmed in vivo , and its relevance for DD pathology remained highly controversial. Here, we leveraged recent advances in high resolution MRI at high field strength (7 T) to investigate the M-LGN in DD in vivo. Using a case-control design, we acquired data from a large sample of young adults with DD (n = 26; age 28 ± 7 years; 13 females) and matched control participants (n = 28; age 27 ± 6 years; 15 females). Each participant completed a comprehensive diagnostic behavioural test battery and participated in two MRI sessions, including three functional MRI experiments and one structural MRI acquisition. We measured blood oxygen level-dependent responses and longitudinal relaxation rates to compare both groups on LGN subdivision function and myelination. Based on previous research, we hypothesized that the M-LGN is altered in DD and that these alterations are associated with a key DD diagnostic score, i.e. rapid letter and number naming. The results showed aberrant responses of the M-LGN in DD compared to controls, which was reflected in a different functional lateralization of this subdivision between groups. These alterations were associated with rapid letter and number naming performance, specifically in male DD. We also found lateralization differences in the longitudinal relaxation rates of the M-LGN in DD relative to controls. Conversely, the other main subdivision of the LGN, the parvocellular LGN (P-LGN), showed comparable blood oxygen level-dependent responses and longitudinal relaxation rates between groups. The present study is the first to unequivocally show that M-LGN alterations are a hallmark of DD, affecting both the function and microstructure of this subdivision. It further provides a first functional interpretation of M-LGN alterations and a basis for a better understanding of sex-specific differences in DD with implications for prospective diagnostic and treatment strategies. [ABSTRACT FROM AUTHOR]

Spin‐lock (SL) pulses have been proposed to directly detect neuronal activity otherwise inaccessible through standard functional magnetic resonance imaging. However, the practical limits of this technique remain unexplored. Key challenges in SL‐based detection include ultra‐weak signal variations, sensitivity to magnetic field inhomogeneities, and potential contamination from blood oxygen level‐dependent effects, all of which hinder the reliable isolation of neuronal signals. This pilot study evaluates the performance of the stimulus‐induced rotary saturation (SIRS) technique to map visual stimulation response in the human cortex. A rotary echo spin‐lock (RESL) preparation followed by a 2D echo planar imaging readout was used to investigate 12 healthy subjects at rest and during continuous exposure to 8 Hz flickering light. The SL amplitude was fixed to the target neuroelectric oscillations at that frequency. The signal variance was used as contrast metric, and two alternative post‐processing pipelines (regression‐filtering‐rectification and normalized subtraction) were statistically evaluated. Higher variance in the SL signal was detected in four of the 12 subjects. Although group‐level analysis indicated activation in the occipital pole, analysis of variance revealed that this difference was not statistically significant, highlighting the need for comparable control measures and more robust preparations. Further optimization in sensitivity and robustness is required to noninvasively detect physiological neuroelectric activity in the human brain. [ABSTRACT FROM AUTHOR]

Within-individual blood oxygen level-dependent (BOLD) signal variability, intrinsic moment-to-moment signal fluctuations within a single individual in specific voxels across a given time course, is a relatively new metric recognized in the neuroimaging literature. Within-individual BOLD signal variability has been postulated to provide information beyond that provided by mean-based analysis. Synthesis of the literature using within-individual BOLD signal variability methodology to examine various cognitive domains is needed to understand how intrinsic signal fluctuations contribute to optimal performance. This systematic review summarizes and integrates this literature to assess task-based cognitive performance in healthy groups and few clinical groups. Included papers were published through October 17, 2022. Searches were conducted on PubMed and APA PsycInfo. Studies eligible for inclusion used within-individual BOLD signal variability methodology to examine BOLD signal fluctuations during task-based functional magnetic resonance imaging (fMRI) and/or examined relationships between task-based BOLD signal variability and out-of-scanner behavioral measure performance, were in English, and were empirical research studies. Data from each of the included 19 studies were extracted and study quality was systematically assessed. Results suggest that variability patterns for different cognitive domains across the lifespan (ages 7–85) may depend on task demands, measures, variability quantification method used, and age. As neuroimaging methods explore individual-level contributions to cognition, within-individual BOLD signal variability may be a meaningful metric that can inform understanding of neurocognitive performance. Further research in understudied domains/populations, and with consistent quantification methods/cognitive measures, will help conceptualize how intrinsic BOLD variability impacts cognitive abilities in healthy and clinical groups. [ABSTRACT FROM AUTHOR]

Background: Renal hypoxia plays a key role in the progression of chronic kidney disease (CKD). Shen Shuai II Recipe (SSR) has shown good results in the treatment of CKD as a common herbal formula. This study aimed to explore the effect of SSR on renal hypoxia and injury in CKD rats. Methods: Twenty-five Wistar rats underwent 5/6 renal ablation/infarction (A/I) surgery were randomly divided into three groups: 5/6 (A/I), 5/6 (A/I) + losartan (LOS), and 5/6 (A/I) + SSR groups. Another eight normal rats were used as the Sham group. After 8-week corresponding interventions, blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) was performed to evaluate renal oxygenation in all rats, and biochemical indicators were used to measure kidney and liver function, hemoglobin, and proteinuria. The expression of fibrosis and hypoxia-related proteins was analyzed using immunoblotting examination. Results: Renal oxygenation, evaluated by BOLD-fMRI as cortical and medullary T2* values (COT2* and MET2*), was decreased in 5/6 (A/I) rats, but increased after SSR treatment. SSR also downregulated the expression of hypoxia-inducible factor-1α (HIF-1α) in 5/6 (A/I) kidneys. With the improvement of renal hypoxia, renal function and fibrosis were improved in 5/6 (A/I) rats, accompanied by reduced proteinuria. Furthermore, the COT2* and MET2* were significantly positively correlated with the levels of creatinine clearance rate (Ccr) and hemoglobin, but negatively associated with the levels of serum creatinine (SCr), blood urea nitrogen (BUN), serum cystatin C (CysC), serum uric acid (UA), 24-h urinary protein (24-h Upr), and urinary albumin:creatinine ratio (UACR). Conclusion: The degree of renal oxygenation reduction is correlated with the severity of renal injury in CKD. SSR can improve renal hypoxia to attenuate renal injury in 5/6 (A/I) rats of CKD. [ABSTRACT FROM AUTHOR]

Various subjective and objective methods have been proposed to identify which interictal epileptiform discharge (IED)-related EEG-functional MRI (fMRI) results are more likely to delineate seizure-generating tissue in patients with drug-resistant focal epilepsy for the purposes of surgical planning. In this intracranial EEG-fMRI study, we evaluated the utility of these methods to localize clinically relevant regions preoperatively and compared the extent of resection of these areas to postoperative outcome. Seventy patients admitted for intracranial video-EEG monitoring were recruited for a simultaneous intracranial EEG-fMRI study. For all analyses of blood oxygen level-dependent responses associated with IEDs, an experienced epileptologist identified the most clinically relevant brain activation cluster using available clinical information. The maximum cluster (the cluster with the highest z -score) was also identified for all analyses and assigned to one of three confidence levels (low, medium or high) based on the difference of the peak z -scores between the maximum and second maximum cluster (the cluster with the second highest peak z -value). The distance was measured and compared between the peak voxel of the aforementioned clusters and the electrode contacts where the interictal discharge and seizure onset were recorded. In patients who subsequently underwent epilepsy surgery, the spatial concordance between the aforementioned clusters and the area of resection was determined and compared to postoperative outcome. We evaluated 106 different IEDs in 70 patients. Both subjective (identification of the clinically relevant cluster) and objective (maximum cluster much more significant than the second maximum cluster) methods of culling non-localizing EEG-fMRI activation maps increased the spatial concordance between these clusters and the corresponding IED or seizure onset zone contacts. However, only the objective methods of identifying medium and high confidence maps resulted in a significant association between resection of the peak voxel of the maximum cluster and postoperative outcome. Resection of this area was associated with good postoperative outcomes but was not sufficient for seizure freedom. On the other hand, we found that failure to resect the medium and high confidence maximum clusters was associated with a poor post-surgical outcome (negative predictive value = 1.0, sensitivity = 1.0). Methods to identify higher confidence EEG-fMRI results are needed to localize areas necessary for good postoperative outcomes. However, resection of the peak voxel within higher confidence maximum clusters is not sufficient for good outcomes. Conversely, failure to resect the peak voxel in these clusters is associated with a poor post-surgical outcome. [ABSTRACT FROM AUTHOR]

Blood oxygen level‐dependent functional magnetic resonance imaging (BOLD fMRI) arises from a physiological and physical cascade of events taking place at the level of the cortical microvasculature which constitutes a medium with complex geometry. Several analytical models of the BOLD contrast have been developed, but these have not been compared directly against detailed bottom‐up modeling methods. Using a 3D modeling method based on experimentally measured images of mice microvasculature and Monte Carlo simulations, we quantified the accuracy of two analytical models to predict the amplitude of the BOLD response from 1.5 to 7 T, for different echo time (TE) and for both gradient echo and spin echo acquisition protocols. We also showed that accounting for the tridimensional structure of the microvasculature results in more accurate prediction of the BOLD amplitude, even if the values for SO2 were averaged across individual vascular compartments. A secondary finding is that modeling the venous compartment as two individual compartments results in more accurate prediction of the BOLD amplitude compared with standard homogenous venous modeling, arising from the bimodal distribution of venous SO2 across the microvasculature in our data. [ABSTRACT FROM AUTHOR]

Objective Resting-state functional MRI (rs-fMRI) was used to study the cerebral regional homogeneity (ReHo) in high-altitude population to explore the neural mechanism of brain activity in people with chronic environmental hypoxia. Methods Thirty subjects from the high-altitude and low-altitude (control group) populations underwent Mini-Mental State Examination (MMSE), conventional non-contrast, high-resolution 3-D T1-weighted and blood oxygen level dependent MRI. Based on the Matlab mathematical platform, the DPABI software was used for image processing, and the two-sample t-test was used to compare the two groups of brain regions with local consistency differences. The correlations between ReHo value and blood hemoglobin, oxygen saturation, partial pressure of carbon dioxide, partial pressure of oxygen (PaO2) and platelets were analyzed. Results The MMSE values of the two groups were >29. The results of t-test were corrected by Alphasim and showed that the ReHo values of the Supp_Motor_Area_R (SMA_R, Brodmann area 6) and Supp_Motor_Area_L (SMA_L, Brodmann area 8) brain regions in the high-altitude group were significantly higher than those in the control group (P<0.001). In addition, the ReHo values of Precuneus_R (Brodmann area 29) were significantly lower than that of the control group (P<0.05). The change of SMA_L function was positively correlated with PaO2 (r=0.373, P=0.043). Conclusion The increase of ReHo in bilateral supplementary motor areas and the decrease in the spontaneous activity consistency of the right precuneus neurons may be one of the neural mechanisms for the increase of exercise capacity and the impairment of visual organs and functions after hypoxia in high-altitude populations. [ABSTRACT FROM AUTHOR]

Functional magnetic resonance imaging (fMRI) is currently one of the most popular technologies for measuring brain activity in both research and clinical contexts. However, clinical constraints often result in short fMRI scan durations, limiting the diagnostic performance for brain disorders. To address this limitation, we developed an end‐to‐end frequency‐specific dual‐attention‐based adversarial network (FDAA‐Net) to extend the time series of existing blood oxygen level‐dependent (BOLD) data, enhancing their diagnostic utility. Our approach leverages the frequency‐dependent nature of fMRI signals using variational mode decomposition (VMD), which adaptively tracks brain activity across different frequency bands. We integrated the generative adversarial network (GAN) with a spatial–temporal attention mechanism to fully capture relationships among spatially distributed brain regions and temporally continuous time windows. We also introduced a novel loss function to estimate the upward and downward trends of each frequency component. We validated FDAA‐Net on the Human Connectome Project (HCP) database by comparing the original and predicted time series of brain regions in the default mode network (DMN), a key network activated during rest. FDAA‐Net effectively overcame linear frequency‐specific challenges and outperformed other popular prediction models. Test–retest reliability experiments demonstrated high consistency between the functional connectivity of predicted outcomes and targets. Furthermore, we examined the clinical applicability of FDAA‐Net using short‐term fMRI data from individuals with autism spectrum disorder (ASD) and major depressive disorder (MDD). The model achieved a maximum predicted sequence length of 40% of the original scan durations. The prolonged time series improved diagnostic performance by 8.0% for ASD and 11.3% for MDD compared with the original sequences. These findings highlight the potential of fMRI time series prediction to enhance diagnostic power of brain disorders in short fMRI scans. [ABSTRACT FROM AUTHOR]

BOLD signal variability (SDBOLD) has emerged as a unique measure of the adaptive properties of neural systems that facilitate fast, stable responding, based on claims that SDBOLD is independent of mean BOLD signal (meanBOLD) and is a powerful predictor of behavioral performance. We challenge these two claims. First, the apparent independence of SDBOLD and meanBOLD may reflect the presence of deactivations; we hypothesize that although SDBOLD may not be related to raw meanBOLD, it will be linearly related to "absolute" meanBOLD. Second, the observed relationship between SDBOLD and performance may be an artifact of using fixed-length trials longer than RTs. Such designs provide opportunities to toggle between on- and off-task states, and fast responders likely engage in more frequent state-switching, thereby artificially elevating SDBOLD. We hypothesize that SDBOLD will be higher and more strongly related to performance when using such fixed-length trials relative to self-paced trials that terminate upon a response. We test these two hypotheses in an fMRI study using blocks of fixed-length or self-paced trials. Results confirmed both hypotheses: (1) SDBOLD was robustly related with absolute meanBOLD, and (2) toggling between on- and off-task states during fixed-length trials reliably contributed to SDBOLD. Together, these findings suggest that a reappraisal of the functional significance of SDBOLD as a unique marker of cognitive performance is warranted. [ABSTRACT FROM AUTHOR]

Advances in neuroimaging acquisition protocols and denoising techniques, along with increasing magnetic field strengths, have dramatically improved the temporal signal‐to‐noise ratio (tSNR) in functional magnetic resonance imaging (fMRI). This permits spatial resolution with submillimeter voxel sizes and ultrahigh temporal resolution and opens a route toward performing precision fMRI in the brains of individuals. Yet ultrahigh spatial and temporal resolution comes at a cost: it reduces tSNR and, therefore, the sensitivity to the blood oxygen level‐dependent (BOLD) effect and other functional contrasts across the brain. Here we investigate the potential of various smoothing filters to improve BOLD sensitivity while preserving the spatial accuracy of activated clusters in single‐subject analysis. We introduce adaptive‐weight smoothing with optimized metrics (AWSOM), which addresses this challenge extremely well. AWSOM employs a local inference approach that is as sensitive as cluster‐corrected inference of data smoothed with large Gaussian kernels, but it preserves spatial details across multiple tSNR levels. This is essential for examining whole‐brain fMRI data because tSNR varies across the entire brain, depending on the distance of a brain region from the receiver coil, the type of setup, acquisition protocol, preprocessing, and resolution. We found that cluster correction in single subjects results in inflated family‐wise error and false positive rates. AWSOM effectively suppresses false positives while remaining sensitive even to small clusters of activated voxels. Furthermore, it preserves signal integrity, that is, the relative activation strength of significant voxels, making it a valuable asset for a wide range of fMRI applications. Here we demonstrate these features and make AWSOM freely available to the research community for download. [ABSTRACT FROM AUTHOR]

Entropy measures are increasingly being used to analyze the structure of neural activity observed by functional magnetic resonance imaging (fMRI), with resting‐state networks (RSNs) being of interest for their reproducible descriptions of the brain's functional architecture. Temporal correlations have shown a dichotomy among these networks: those that engage with the environment, known as extrinsic, which include the visual and sensorimotor networks; and those associated with executive control and self‐referencing, known as intrinsic, which include the default mode network and the frontoparietal control network. While these inter‐voxel temporal correlations enable the assessment of synchrony among the components of individual networks, entropic measures introduce an intra‐voxel assessment that quantifies signal features encoded within each blood oxygen level‐dependent (BOLD) time series. As a result, this framework offers insights into comprehending the representation and processing of information within fMRI signals. Multiscale entropy (MSE) has been proposed as a useful measure for characterizing the entropy of neural activity across different temporal scales. This measure of temporal entropy in BOLD data is dependent on the length of the time series; thus, high‐quality data with fine‐grained temporal resolution and a sufficient number of time frames is needed to improve entropy precision. We apply MSE to the Midnight Scan Club, a highly sampled and well‐characterized publicly available dataset, to analyze the entropy distribution of RSNs and evaluate its ability to distinguish between different functional networks. Entropy profiles are compared across temporal scales and RSNs. Our results have shown that the spatial distribution of entropy at infra‐slow frequencies (0.005–0.1 Hz) reproduces known parcellations of RSNs. We found a complexity hierarchy between intrinsic and extrinsic RSNs, with intrinsic networks robustly exhibiting higher entropy than extrinsic networks. Finally, we found new evidence that the topography of entropy in the posterior cerebellum exhibits high levels of entropy comparable to that of intrinsic RSNs. [ABSTRACT FROM AUTHOR]

Introduction: This study aims to examine brain activity during dierent swallowing actions in patients with dysphagia caused by medullary infarction (MI) before and after treatment using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Methods: Fifteen patients were enrolled in this study. Brain activation during saliva swallowing and eortful saliva swallowing was observed using BOLD imaging in the acute phase of stroke and after 4 weeks of rehabilitation training. Dierences in the activation of brain regions during saliva swallowing before and after treatment, during eortful saliva swallowing before and after treatment, and between the two swallowing actions before and after treatment were compared. Results: In the acute phase of stroke, only the bilateral precentral and left lingual gyrus were partially activated during saliva swallowing, and there was no obvious activation in the insula. Eortful saliva swallowing activated more brain regions than saliva swallowing before treatment, including the bilateral supplementary motor area (SMA), postcentral gyrus, and right insular cortex. The number of brain regions activated during saliva swallowing increased after treatment, including the bilateral precentral gyrus, postcentral gyrus, insula, thalamus, and SMA. Discussion: Cortical activation increases after recovery from dysphagia, and the increased activation of the postcentral gyrus might play a functional compensatory role. Eortful saliva swallowing is a more eective rehabilitation training method for patients with dysphagia caused [ABSTRACT FROM AUTHOR]

Introduction: Exploring gender differences in cognitive abilities offers vital insights into human brain functioning. Methods: Our study utilized advanced techniques like magnetic resonance thermometry, standard working memory n-back tasks, and functional MRI to investigate if gender-based variations in brain temperature correlate with distinct neuronal responses and working memory capabilities. Results: We observed a significant decrease in average brain temperature in males during working memory tasks, a phenomenon not seen in females. Although changes in female brain temperature were significantly lower than in males, we found an inverse relationship between the absolute temperature change (ATC) and cognitive performance, alongside a correlation with blood oxygen level dependent (BOLD) signal change induced by neural activity. This suggests that in females, ATC is a crucial determinant for the link between cognitive performance and BOLD responses, a linkage not evident in males. However, we also observed additional female specific BOLD responses aligned with comparable task performance to that of males. Discussion: Our results suggest that females compensate for their brain's heightened temperature sensitivity by activating additional neuronal networks to support working memory. This study not only underscores the complexity of gender differences in cognitive processing but also opens new avenues for understanding how temperature fluctuations influence brain functionality. [ABSTRACT FROM AUTHOR]

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub‐bundles of a prototypical visual WM tract—the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub‐bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub‐bundles, and the consistency of the pRF properties of sub‐bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub‐bundles, along with LGN and V1 subfields, during 0‐back and 2‐back tasks. We then evaluate differences in 2bk‐0bk contrast between foveal and peripheral sub‐bundles (or subfields), and further examine potential relationships between 2bk‐0bk contrast and 2‐back task d‐prime. The results show that the pRF properties of OR sub‐bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2‐back task consistently surpass those under the 0‐back task across foveal and peripheral OR sub‐bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk‐0bk contrast than peripheral V1. The 2‐back task d‐prime shows strong correlations with 2bk‐0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level‐dependent (BOLD) signals of OR sub‐bundles encode high‐fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub‐bundle level. Additionally, the study highlights the role of OR in the top‐down processes of visual working memory beyond the bottom‐up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub‐bundle level and expands understanding of OR function. [ABSTRACT FROM AUTHOR]

(1) Background: Functional magnetic resonance imaging (fMRI) utilizing multi-echo gradient echo-planar imaging (ME-GE-EPI) has demonstrated higher sensitivity and stability compared to utilizing single-echo gradient echo-planar imaging (SE-GE-EPI). The direct derivation of T2* maps from fitting multi-echo data enables accurate recording of dynamic functional changes in the brain, exhibiting higher sensitivity than echo combination maps. However, the widely employed voxel-wise log-linear fitting is susceptible to inevitable noise accumulation during image acquisition. (2) Methods: This work introduced a synthetic data-driven deep learning (SD-DL) method to obtain T2* maps for multi-echo (ME) fMRI analysis. (3) Results: The experimental results showed the efficient enhancement of the temporal signal-to-noise ratio (tSNR), improved task-based blood oxygen level-dependent (BOLD) percentage signal change, and enhanced performance in multi-echo independent component analysis (MEICA) using the proposed method. (4) Conclusion: T2* maps derived from ME-fMRI data using the proposed SD-DL method exhibit enhanced BOLD sensitivity in comparison to T2* maps derived from the LLF method. [ABSTRACT FROM AUTHOR]

Background: Moyamoya is a progressive, non-atherosclerotic cerebral arteriopathy that may present in childhood and currently has no cure. Early diagnosis is critical to prevent a lifelong risk of neurological morbidity. Blood-oxygen-level-dependent (BOLD) MRI cerebrovascular reactivity (CVR) imaging provides a non-invasive, in vivo measure of autoregulatory capacity and cerebrovascular reserve. However, non-compliant or younger children require general anesthesia to achieve BOLD-CVR imaging. Objective: To determine the same-day repeatability of BOLD-CVR imaging under general anesthesia in children with moyamoya. Materials and methods: Twenty-eight examination pairs were included (mean patient age = 7.3 ± 4.0 years). Positive and negatively reacting voxels were averaged over signals and counted over brain tissue and vascular territory. The intraclass correlation coefficient (ICC), Wilcoxon signed-rank test, and Bland–Altman plots were used to assess the variability between the scans. Results: There was excellent-to-good (≥ 0.59) within-day repeatability in 18 out of 28 paired studies (64.3%). Wilcoxon signed-rank tests demonstrated no significant difference in the grey and white matter CVR estimates, between repeat scans (all p-values > 0.05). Bland–Altman plots of differences in mean magnitude of positive and negative and fractional positive and negative CVR estimates illustrated a reasonable degree of agreement between repeat scans and no systematic bias. Conclusion: BOLD-CVR imaging provides repeatable assessment of cerebrovascular reserve in children with moyamoya imaged under general anesthesia. [ABSTRACT FROM AUTHOR]

Objective: Functional magnetic resonance imaging (fMRI) has been applied to assess the microstructure of the kidney. However, it is not clear whether fMRI could be used in the field of kidney injury in patients with Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Methods: This study included 20 patients with AAV. Diffusion kurtosis imaging (DKI) and blood oxygen level-dependent (BOLD) scanning of the kidneys were performed in AAV patients and healthy controls. The mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) parameters of DKI, the R2* parameter of BOLD, and clinical data were further analyzed. Results: In AAV patients, the cortex exhibited lower MD but higher R2* values compared to the healthy controls. Medullary MK values were elevated in AAV patients. Renal medullary MK values showed a positive correlation with serum creatinine levels and negative correlations with hemoglobin levels and estimated glomerular filtration rate. To assess renal injury in AAV patients, AUC values for MK, MD, FA, and R2* in the cortex were 0.66, 0.67, 0.57, and 0.55, respectively, and those in the medulla were 0.81, 0.77, 0.61, and 0.53, respectively. Conclusions: Significant differences in DKI and BOLD MRI parameters were observed between AAV patients with kidney injuries and the healthy controls. The medullary MK value in DKI may be a noninvasive marker for assessing the severity of kidney injury in AAV patients. [ABSTRACT FROM AUTHOR]

Resting‐state functional magnetic resonance imaging (rs‐fMRI) is increasingly being used to infer the functional organization of the brain. Blood oxygen level‐dependent (BOLD) features related to spontaneous neuronal activity, are yet to be clearly understood. Prior studies have hypothesized that rs‐fMRI is spontaneous event‐related and these events convey crucial information about the neuronal activity in estimating resting state functional connectivity (FC). Attempts have been made to extract these temporal events using a predetermined threshold. However, the thresholding methods in addition to being very sensitive to noise, may consider redundant events or exclude the low‐valued inflection points. Here, we extract the event‐related temporal onsets from the rs‐fMRI time courses using a zero‐frequency resonator (ZFR). The ZFR reflects the transient behavior of the BOLD events at its output. The conditional rate (CR) of the BOLD events occurring in a time course with respect to a seed time course is used to derive static FC. The temporal activity around the estimated events called high signal‐to‐noise ratio (SNR) segments are also obtained in the rs‐fMRI time course and are then used to compute static and dynamic FCs during rest. Coactivation pattern (CAP) is the dynamic FC obtained using the high SNR segments driven by the ZFR. The static FC demonstrates that the ZFR‐based CR distinguishes the coactivation and non‐coactivation scores well in the distribution. CAP analysis demonstrated the stable and longer dwell time dominant resting state functional networks with high SNR segments driven by the ZFR. Static and dynamic FC analysis underpins that the ZFR‐driven temporal onsets of BOLD events derive reliable and consistent FCs in the resting brain using a subset of the time points. [ABSTRACT FROM AUTHOR]

Background: Blood oxygen level dependent-magnetic resonance imaging (BOLD-MRI) is a non-invasive functional imaging technique that can be used to assess renal allograft dysfunction. Purpose: To evaluate the diagnostic performance of BOLD-MRI using a 3-T scanner in discriminating causes of renal allograft dysfunction in the post-transplant period. Material and Methods: This prospective study was conducted on 112 live donor-renal allograft recipients: 53 with normal graft function, as controls; 18 with biopsy-proven acute rejection (AR); and 41 with biopsy-proven acute tubular necrosis (ATN). Multiple fast-field echo sequences were performed to obtain T2*-weighted images. Cortical R2* (CR2*) level, medullary R2* (MR2*) level, and medullary over cortical R2* ratio (MCR) were measured in all participants. Results: The mean MR2* level was significantly lower in the AR group (20.8 ± 2.8/s) compared to the normal group (24 ± 2.4/s, P <0.001) and ATN group (27.4 ± 1.7/s, P <0.001). The MCR was higher in ATN group (1.47 ± 0.18) compared to the AR group (1.18 ± 0.17) and normal functioning group (1.34 ± 0.2). Both MR2* (area under the curve [AUC] = 0.837, P <0.001) and MCR (AUC = 0.727, P = 0.003) can accurately discriminate ATN from AR, however CR2* (AUC = 0.590, P = 0.237) showed no significant difference between both groups. Conclusion: In early post-transplant renal dysfunction, BOLD-MRI is a valuable non-invasive diagnostic technique that can differentiate between AR and ATN by measuring changes in intra-renal tissue oxygenation. [ABSTRACT FROM AUTHOR]

Purpose: Static and dynamic B0$$ {\mathrm{B}}_0 $$ field imperfections are detrimental to functional MRI (fMRI) applications, especially at ultra‐high magnetic fields (UHF). In this work, a field camera is used to assess the benefits of retrospectively correcting B0$$ {\mathrm{B}}_0 $$ field perturbations on Blood Oxygen Level Dependent (BOLD) sensitivity in non‐Cartesian three‐dimensional (3D)‐SPARKLING fMRI acquisitions. Methods: fMRI data were acquired at 1 mm3$$ {}^3 $$ and for a 2.4s‐TR while concurrently monitoring in real‐time field perturbations using a Skope Clip‐on field camera in a novel experimental setting involving a shorter TR than the required minimal TR of the field probes. Measurements of the dynamic field deviations were used along with a static ΔB0$$ \Delta {\mathrm{B}}_0 $$ map to retrospectively correct static and dynamic field imperfections, respectively. In order to evaluate the impact of such a correction on fMRI volumes, a comparative study was conducted on healthy volunteers. Results: Correction of B0$$ {\mathrm{B}}_0 $$ deviations improved image quality and yielded between 20% and 30% increase in median temporal signal‐to‐noise ratio (tSNR).Using fMRI data collected during a retinotopic mapping experiment, we demonstrated a significant increase in sensitivity to the BOLD contrast and improved accuracy of the BOLD phase maps: 44% (resp., 159%) more activated voxels were retrieved when using a significance control level based on a p‐value of 0.001 without correcting for multiple comparisons (resp., 0.05 with a false discovery rate correction). Conclusion: 3D‐SPARKLING fMRI hugely benefits from static and dynamic B0$$ {\mathrm{B}}_0 $$ imperfections correction. However, the proposed experimental protocol is flexible enough to be deployed on a large spectrum of encoding schemes, including arbitrary non‐Cartesian readouts. [ABSTRACT FROM AUTHOR]

Direct imaging of neuronal activity (DIANA) by functional magnetic resonance imaging (fMRI) could be a revolutionary approach for advancing systems neuroscience research. To independently replicate this observation, we performed fMRI experiments in anesthetized mice. The blood oxygenation level-dependent (BOLD) response to whisker stimulation was reliably detected in the primary barrel cortex before and after DIANA experiments; however, no DIANA-like fMRI peak was observed in individual animals' data with the 50 to 300 trials. Extensively averaged data involving 1050 trials in six mice showed a flat baseline and no detectable neuronal activity-like fMRI peak. However, spurious, nonreplicable peaks were found when using a small number of trials, and artifactual peaks were detected when some outlier-like trials were excluded. Further, no detectable DIANA peak was observed in the BOLD-responding thalamus from the selected trials with the neuronal activity-like reference function in the barrel cortex. Thus, we were unable to replicate the previously reported results without data preselection. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the changes in the Blood Oxygen Level Dependent signal of Primary somatosensory area (S1) and Brodmann area 3 (BA3) per finger and phalanx in comparison to the activation voxel when 250 Hz vibratory stimulation with high sensitivity for the Pacinian corpuscle was given to the four fingers and three phalanges. The result of analyzing the activation voxel showed a significant difference for S1 per finger and phalanx, but for BA3, no significant difference was observed despite a similar trend to S1. In contrast, the activation intensity (BOLD) displayed a significant difference for S1 per finger and phalanx and for BA3, where the activation voxel had no significant variation. In addition, while the result of S1 did not indicate whether the index or the little fingers had the highest sensitivity based on the BOLD signal per finger, the result of BA3 marked the strongest BOLD signal for the little finger as a response to 250 Hz vibratory stimulation. The activation intensity per phalanx was the highest for the intermediate phalanx for S1 and BA3, which was in line with a previous study comparing the activation voxel. The method based on the intensity of the nerve activation is presumed to have high sensitivity as the signal intensity is monitored within a specific, defined area. Thus, for the extraction of brain activation patterns of micro-domains, such as BA3, monitoring the BOLD signal that reflects the nerve activation intensity more sensitively is likely to be advantageous. [ABSTRACT FROM AUTHOR]

A recurring issue in functional neuroimaging is how to link task‐driven haemodynamic blood oxygen level dependent functional MRI (BOLD‐fMRI) responses to underlying neurochemistry at the synaptic level. Glutamate and γ‐aminobutyric acid (GABA), the major excitatory and inhibitory neurotransmitters respectively, are typically measured with MRS sequences separately from fMRI, in the absence of a task. The present study aims to resolve this disconnect, developing acquisition and processing techniques to simultaneously assess GABA, glutamate and glutamine (Glx) and BOLD in relation to a cognitive task, at 3 T. Healthy subjects (N = 81) performed a cognitive task (Eriksen flanker), which was presented visually in a task‐OFF, task‐ON block design, with individual event onset timing jittered with respect to the MRS readout. fMRS data were acquired from the medial anterior cingulate cortex during task performance, using an adapted MEGA‐PRESS implementation incorporating unsuppressed water‐reference signals at a regular interval. These allowed for continuous assessment of BOLD activation, through T2*‐related changes in water linewidth. BOLD‐fMRI data were additionally acquired. A novel linear model was used to extract modelled metabolite spectra associated with discrete functional stimuli, building on well established processing and quantification tools. Behavioural outcomes from the flanker task, and activation patterns from the BOLD‐fMRI sequence, were as expected from the literature. BOLD response assessed through fMRS showed a significant correlation with fMRI, specific to the fMRS‐targeted region of interest; fMRS‐assessed BOLD additionally correlated with lengthening of response time in the incongruent flanker condition. While no significant task‐related changes were observed for GABA+, a significant increase in measured Glx levels (~8.8%) was found between task‐OFF and task‐ON periods. These findings verify the efficacy of our protocol and analysis pipelines for the simultaneous assessment of metabolite dynamics and BOLD. As well as establishing a robust basis for further work using these techniques, we also identify a number of clear directions for further refinement in future studies. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is a major public health concern worldwide, with a high incidence and a significant impact on morbidity and mortality. The alteration of cerebrospinal fluid (CSF) dynamics after TBI is a well‐known phenomenon; however, the underlying mechanisms and their implications for cognitive function are not fully understood. In this study, we propose a new approach to studying the alteration of CSF dynamics in TBI patients. Our approach involves using conventional echo‐planar imaging‐based functional MRI with no additional scan, allowing for simultaneous assessment of functional CSF dynamics and blood oxygen level‐dependent–based functional brain activities. We utilized two previously suggested indices of (i) CSFpulse, and (ii) correlation between global brain activity and CSF inflow. Using CSFpulse, we demonstrated a significant decrease in CSF pulsation following TBI (p < 0.05), which was consistent with previous studies. Furthermore, we confirmed that the decrease in CSF pulsation was most prominent in the early months after TBI, which could be explained by ependymal ciliary loss, intracranial pressure increment, or aquaporin‐4 dysregulation. We also observed a decreasing trend in the correlation between global brain activity and CSF inflow in TBI patients (p < 0.05). Our findings suggest that the decreased CSF pulsation after TBI could lead to the accumulation of toxic substances in the brain and an adverse effect on brain function. Further longitudinal studies with larger sample sizes, TBI biomarker data, and various demographic information are needed to investigate the association between cognitive decline and CSF dynamics after TBI. Overall, this study sheds light on the potential role of altered CSF dynamics in TBI‐induced neurologic symptoms and may contribute to the development of novel therapeutic interventions. [ABSTRACT FROM AUTHOR]

Objective: We aimed to evaluate the contribution of simultaneous recording of electroencephalography–functional magnetic resonance imaging (EEG‐fMRI) in the diagnosis of epilepsy syndrome, localization of the epileptogenic zone (EZ), and decision‐making regarding surgical treatment. Methods: We performed a retrospective study to evaluate patients with focal epilepsy who underwent EEG‐fMRI. Two evaluators assessed epilepsy syndrome, presumed focus, and surgical candidacy and defined confidence levels. They assessed these clinical characteristics first without EEG‐fMRI and then including EEG‐fMRI to assess how the results of EEG‐fMRI changed the evaluations. We also determined how the clinical evaluation was affected by the concordance level between the blood oxygen level‐dependent (BOLD) response and the presumed focus location, and by the confidence level of the BOLD response itself based on the t‐value of the primary and secondary clusters. Results: Fifty‐one scans from 48 patients were included. The BOLD map affected 66.7% of the evaluations by altering evaluation items (epilepsy syndrome, presumed focus, or surgical candidacy) or their confidence levels. EEG‐fMRI results increased the confidence levels of epilepsy syndrome, presumed focus, or surgical candidacy in 47.1% of patients but reduced clinical confidence in these features in 11.8%. More specifically, the confidence levels increased for epilepsy syndrome in 28.5%, identification of presumed focus in 33.9%, and determination of surgical candidacy in 29.4%. The BOLD signal confidence level, whether high or low, did not influence these clinical factors. Significance: Previous studies have emphasized the utility of EEG‐fMRI for the localization of the epileptogenic zone. This study demonstrated the potential of EEG‐fMRI to influence clinical confidence when determining epilepsy syndrome, the presumed epileptic focus, and surgical candidacy. [ABSTRACT FROM AUTHOR]

Objective: To find a possible quantitative relation between activation-induced fast (< 10 s) changes in the γ-aminobutyric acid (GABA) level and the amplitude of a blood oxygen level-dependent contrast (BOLD) response (according to magnetic resonance spectroscopy [MRS] and functional magnetic resonance imaging [fMRI]). Materials and methods: fMRI data and MEGA-PRESS magnetic resonance spectra [echo time (TE)/repetition time (TR) = 68 ms/1500 ms] of an activated area in the visual cortex of 33 subjects were acquired using a 3 T MR scanner. Stimulation was performed by presenting an image of a flickering checkerboard for 3 s, repeated with an interval of 13.5 s. The time course of GABA and creatine (Cr) concentrations and the width and height of resonance lines were obtained with a nominal time resolution of 1.5 s. Changes in the linewidth and height of n-acetylaspartate (NAA) and Cr signals were used to determine the BOLD effect. Results: In response to the activation, the BOLD-corrected GABA + /Cr ratio increased by 5.0% (q = 0.027) and 3.8% (q = 0.048) at 1.6 and 3.1 s, respectively, after the start of the stimulus. Time courses of Cr and NAA signal width and height reached a maximum change at the 6th second (~ 1.2–1.5%, q < 0.05). Conclusion: The quick response of the observed GABA concentration to the short stimulus is most likely due to a release of GABA from vesicles followed by its packaging back into vesicles. [ABSTRACT FROM AUTHOR]

The eye possesses a paravascular solute transport pathway that is driven by physiological pulsations, resembling the brain glymphatic pathway. We developed synchronous multimodal imaging tools aimed at measuring the driving pulsations of the human eye, using an eye-tracking functional eye camera (FEC) compatible with magnetic resonance imaging (MRI) for measuring eye surface pulsations. Special optics enabled integration of the FEC with MRI-compatible video ophthalmoscopy (MRcVO) for simultaneous retinal imaging along with functional eye MRI imaging (fMREye) of the BOLD (blood oxygen level dependent) contrast. Upon optimizing the fMREye parameters, we measured the power of the physiological (vasomotor, respiratory, and cardiac) eye and brain pulsations by fast Fourier transform (FFT) power analysis. The human eye pulsated in all three physiological pulse bands, most prominently in the respiratory band. The FFT power means of physiological pulsation for two adjacent slices was significantly higher than in one-slice scans (RESP1 vs. RESP2; df = 5, p = 0.045). FEC and MRcVO confirmed the respiratory pulsations at the eye surface and retina. We conclude that in addition to the known cardiovascular pulsation, the human eye also has respiratory and vasomotor pulsation mechanisms, which are now amenable to study using non-invasive multimodal imaging of eye fluidics. [ABSTRACT FROM AUTHOR]

Functional magnetic resonance imaging (fMRI) based on the Blood Oxygen Level Dependent (BOLD) contrast has been extensively used to map brain activity and connectivity in health and disease. Standard fMRI preprocessing includes different steps to remove confounds unrelated to neuronal activity. First, this narrative review explores how signal fluctuations due to cardiac and respiratory activity, usually considered as "physiological noise" and regressed out from fMRI time series. However, these signal components bear useful information about some mechanisms of brain functioning (e.g., glymphatic clearance) or cerebrovascular compliance in response to arterial pressure waves. Aging and chronic diseases can cause stiffening of the aorta and other main arteries, with a reduced dampening effect resulting in greater transmission of pressure impulses to the brain. Importantly, the continuous hammering of cardiac pulsations can produce local alterations of the mechanical properties of the small cerebral vessels, with a progressive deterioration that ultimately affects neuronal functionality. Second, the review emphasizes how fMRI can study the brain patterns most affected by cardiac pulsations in health and disease with high spatiotemporal resolution, offering the opportunity to identify much more specific risk markers than systemic factors based on measurements of the vascular compliance of large arteries or other global risk factors. In this regard, modern fast fMRI acquisition techniques allow a better characterization of these pulsatile signal components due to reduced aliasing effects, turning what has been traditionally considered as noise in a signal of interest that can be used to develop novel non-invasive biomarkers in different clinical contexts. [ABSTRACT FROM AUTHOR]

Functional magnetic resonance imaging (fMRI) in awake small animals such as pigeons or songbirds opens a new window into the neural fundaments of cognitive behavior. However, high‐field fMRI in the avian brain is challenging due to strong local magnetic field inhomogeneities caused by air cavities in the skull. A spoiled gradient‐echo fMRI sequence has already been used to map the auditory network in songbirds, but due to susceptibility artifacts only 50% of the whole brain could be recorded. Since whole‐brain fMRI coverage is vital to reveal whole‐brain networks, an MRI sequence that is less susceptible to these artifacts was required. This was recently achieved in various bird species by using a rapid acquisition with relaxation enhancement (RARE) sequence. Weak blood oxygen level‐dependent (BOLD) sensitivity, low temporal resolution, and heat caused by the long train of RF refocusing pulses are the main limits of RARE fMRI at high magnetic fields. To go beyond some of these limitations, we here describe the implementation of a two‐segmented spin‐echo echo‐planar imaging (SE‐EPI). The proposed sequence covers the whole brain of awake pigeons. The sequence was applied to investigate the auditory network in awake pigeons and assessed the relative merits of this method in comparison with the single‐shot RARE sequence. At the same imaging resolution but with a volume acquisition of 3 s versus 4 s for RARE, the two‐segmented SE‐EPI provided twice the strength of BOLD activity compared with the single‐shot RARE sequence, while the image signal‐to‐noise ratio (SNR) and in particular the temporal SNR were very similar for the two sequences. In addition, the activation patterns in two‐segmented SE‐EPI data are more symmetric and larger than single‐shot RARE results. Two‐segmented SE‐EPI represents a valid alternative to the RARE sequence in avian fMRI research since it yields more than twice the BOLD sensitivity per unit of time with much less energy deposition and better temporal resolution, particularly for event‐related experiments. [ABSTRACT FROM AUTHOR]

Systemic physiological dynamics, such as heart rate variability (HRV) and respiration volume per time (RVT), are known to account for significant variance in the blood oxygen level dependent (BOLD) signal of resting‐state functional magnetic resonance imaging (rsfMRI). However, synchrony between these cardiorespiratory changes and the BOLD signal could be due to neuronal (i.e., autonomic activity inducing changes in heart rate and respiration) or vascular (i.e., cardiorespiratory activity facilitating hemodynamic changes and thus the BOLD signal) effects and the contributions of these effects may differ spatially, temporally, and spectrally. In this study, we characterize these brain–body dynamics using a wavelet analysis in rapidly sampled rsfMRI data with simultaneous pulse oximetry and respiratory monitoring of the Human Connectome Project. Our time–frequency analysis across resting‐state networks (RSNs) revealed differences in the coherence of the BOLD signal and heartbeat interval (HBI)/RVT dynamics across frequencies, with unique profiles per network. Somatomotor (SMN), visual (VN), and salience (VAN) networks demonstrated the greatest synchrony with both systemic physiological signals when compared to other networks; however, significant coherence was observed in all RSNs regardless of direct autonomic involvement. Our phase analysis revealed distinct frequency profiles of percentage of time with significant coherence between BOLD and systemic physiological signals for different phase offsets across RSNs, suggesting that the phase offset and temporal order of signals varies by frequency. Lastly, our analysis of temporal variability of coherence provides insight on potential influence of autonomic state on brain–body communication. Overall, the novel wavelet analysis enables an efficient characterization of the dynamic relationship between cardiorespiratory activity and the BOLD signal in spatial, temporal, and spectral dimensions to inform our understanding of autonomic states and improve our interpretation of the BOLD signal. [ABSTRACT FROM AUTHOR]

Background: Sodium-dependent glucose transporter 2 inhibitor (SGLT2i) has the advantages of effectively lowering blood glucose levels and improving renal outcomes in diabetic patients. This study evaluated the effect of canagliflozin on intrarenal lipid content and oxygenation in newly diagnosed type 2 diabetes mellitus (T2DM) patients. Methods: A total of 64 newly diagnosed T2DM patients with normal renal function were randomly divided into canagliflozin (n = 33) and glimepiride control (n = 31) groups. All patients underwent functional magnetic resonance imaging (fMRI) scanning to assay patients' intrarenal lipid content and oxygenation level before and after 24 weeks of treatment. Furthermore, the relationship between body mass index and intrarenal lipid content in T2DM patients was analyzed and the correlation between changes in intrarenal lipid content and improvements in renal hypoxia was further assessed. Results: The canagliflozin group had a greater decrease in body weight and blood uric acid level than the glimepiride group (all P < 0.05). The intrarenal lipid content could be significantly reduced after canagliflozin treatment for 24 weeks. The R2* values, a parameter for quantifying the oxygen content in tissues and is inversely related to the oxygen content, of the renal cortex and medulla in the canagliflozin group decreased from the baseline by 6.40% (P < 0.01) and 12.09% (P = 0.000007), respectively. In addition, the degree of reduction of fat fraction (ΔFF) in the kidneys of the canagliflozin group was correlated with the degree of improvement of oxygenation level (ΔR2*) in the renal cortex (r = 0.422, P = 0.014). Conclusions: The early renal protective effect of SGLT2i in newly diagnosed T2DM patients may be partly attributed to the amelioration of renal hypoxia via the alleviation of ectopic lipid deposition in the kidneys. Trial Registration: Chu Hsien-I Memorial Hospital of Tianjin Medical University (ChiCTR2000037951). [ABSTRACT FROM AUTHOR]

Simultaneous electroencephalography–functional MRI (EEG‐fMRI) is a unique and noninvasive method for epilepsy presurgical evaluation. When selecting voxels by null‐hypothesis tests, the conventional analysis may overestimate fMRI response amplitudes related to interictal epileptic discharges (IEDs), especially when IEDs are rare. We aimed to estimate fMRI response amplitudes represented by blood oxygen level dependent (BOLD) percentage changes related to IEDs using a hierarchical model. It involves the local and distributed hemodynamic response homogeneity to regularize estimations. Bayesian inference was applied to fit the model. Eighty‐two epilepsy patients who underwent EEG‐fMRI and subsequent surgery were included in this study. A conventional voxel‐wise general linear model was compared to the hierarchical model on estimated fMRI response amplitudes and on the concordance between the highest response cluster and the surgical cavity. The voxel‐wise model overestimated fMRI responses compared to the hierarchical model, evidenced by a practically and statistically significant difference between the estimated BOLD percentage changes. Only the hierarchical model differentiated brief and long‐lasting IEDs with significantly different BOLD percentage changes. Overall, the hierarchical model outperformed the voxel‐wise model on presurgical evaluation, measured by higher prediction performance. When compared with a previous study, the hierarchical model showed higher performance metric values, but the same or lower sensitivity. Our results demonstrated the capability of the hierarchical model of providing more physiologically reasonable and more accurate estimations of fMRI response amplitudes induced by IEDs. To enhance the sensitivity of EEG‐fMRI for presurgical evaluation, it may be necessary to incorporate more appropriate spatial priors and bespoke decision strategies. [ABSTRACT FROM AUTHOR]

Blood oxygenation level‐dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three‐dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two‐photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes—cerebral blood flow, cerebral blood volume, and blood oxygen saturation—induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes. [ABSTRACT FROM AUTHOR]

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics. [ABSTRACT FROM AUTHOR]

Primary headache is a very common and burdensome functional headache worldwide, which can be classified as migraine, tension-type headache (TTH), trigeminal autonomic cephalalgia (TAC), and other primary headaches. Managing and treating these different categories require distinct approaches, and accurate diagnosis is crucial. Functional magnetic resonance imaging (fMRI) has become a research hotspot to explore primary headache. By examining the interrelationships between activated brain regions and improving temporal and spatial resolution, fMRI can distinguish between primary headaches and their subtypes. Currently the most commonly used is the cortical brain mapping technique, which is based on blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI). This review sheds light on the state-of-the-art advancements in data analysis based on fMRI technology for primary headaches along with their subtypes. It encompasses not only the conventional analysis methodologies employed to unravel pathophysiological mechanisms, but also deep-learning approaches that integrate these techniques with advanced statistical modeling and machine learning. The aim is to highlight cutting-edge fMRI technologies and provide new insights into the diagnosis of primary headaches. [ABSTRACT FROM AUTHOR]

In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23–51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals. [ABSTRACT FROM AUTHOR]

Objective: Functional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases. Yet, mapping the blood oxygen level dependent (BOLD) response to distinct neuronal processes continues to be challenging. Here, we investigated the characteristics of 7 T-fMRI compared to 3 T-fMRI in the human brain beyond the effect of increased SNR and verified the benefits of 7 T-fMRI in the detection of tiny, highly specific modulations of functional connectivity in the resting state following a motor task. Methods: 18 healthy volunteers underwent two resting state and a stimulus driven measurement using a finger tapping motor task at 3 and 7 T, respectively. The SNR for each field strength was adjusted by targeted voxel size variation to minimize the effect of SNR on the field strength specific outcome. Spatial and temporal characteristics of resting state ICA, network graphs, and motor task related activated areas were compared. Finally, a graph theoretical approach was used to detect resting state modulation subsequent to a simple motor task. Results: Spatial extensions of resting state ICA and motor task related activated areas were consistent between field strengths, but temporal characteristics varied, indicating that 7 T achieved a higher functional specificity of the BOLD response than 3 T-fMRI. Following the motor task, only 7 T-fMRI enabled the detection of highly specific connectivity modulations representing an "offline replay" of previous motor activation. Modulated connections of the motor cortex were directly linked to brain regions associated with memory consolidation. Conclusion: These findings reveal how memory processing is initiated even after simple motor tasks, and that it begins earlier than previously shown. Thus, the superior capability of 7 T-fMRI to detect subtle functional dynamics promises to improve diagnostics and therapeutic assessment of neurological diseases. [ABSTRACT FROM AUTHOR]

Thanks to technical advances in the field of medical imaging, it is now possible to study key features of renal anatomy and physiology, but so far poorly explored due to the inherent difficulties in studying both the metabolism and vasculature of the human kidney. In this narrative review, we provide an overview of recent research findings on renal perfusion, oxygenation, and substrate uptake. Most studies evaluating renal perfusion with positron emission tomography (PET) have been performed in healthy controls, and specific target populations like obese individuals or patients with renovascular disease and chronic kidney disease (CKD) have rarely been assessed. Functional magnetic resonance (fMRI) has also been used to study renal perfusion in CKD patients, and recent studies have addressed the kidney hemodynamic effects of therapeutic agents such as glucagon-like receptor agonists (GLP-1RA) and sodium-glucose co-transporter 2 inhibitors (SGLT2-i) in an attempt to characterise the mechanisms leading to their nephroprotective effects. The few available studies on renal substrate uptake are discussed. In the near future, these imaging modalities will hopefully become widely available with researchers more acquainted with them, gaining insights into the complex renal pathophysiology in acute and chronic diseases. [ABSTRACT FROM AUTHOR]

Previous research has suggested that familiarity can enhance associative memory after unitization, but the cognitive mechanisms underlying unitization remain debated. To explore the neural mechanisms of associative memory after unitization in the absence of semantic relations, we used Chinese characters as stimuli and recorded participants' blood oxygen level‐dependent signals during recognition. Behavioral results showed that after Chinese character unitization, not only the associative performance of recognition (Pr, hit rate minus false alarm rate) and general Pr but also the hit rate and correct rejection rate increased. Neuroimaging results revealed activation of the hippocampus and parahippocampal gyrus during associative recognition in both the unitized and the non‐unitized condition, and hippocampal activation increased after unitization. However, activation of the perirhinal cortex was not observed in either condition. These findings, in contrast to those from previous studies on unitization, suggest that Chinese character unitization enhances recollection‐based, rather than familiarity‐based, associative recognition. This suggests that the encoding of semantic relations during unitization is critical for subsequent familiarity‐based associative recognition. [ABSTRACT FROM AUTHOR]

Objective: In preclinical models, insulin resistance in the dorsal striatum (DS) contributes to overeating. Although human studies support the concept of central insulin resistance, they have not investigated its effect on consummatory reward‐induced brain activity. Methods: Taste‐induced activation was assessed in the caudate and putamen of the DS with blood oxygen level‐dependent (BOLD) functional magnetic resonance imaging. Three phenotypically distinct groups were studied: metabolically healthy lean, metabolically healthy obesity, and metabolically unhealthy obesity (MUO; presumed to have central insulin resistance). Participants with MUO also completed a weight loss intervention followed by a second functional magnetic resonance imaging session. Results: The three groups were significantly different at baseline consistent with the design. The metabolically healthy lean group had a primarily positive BOLD response, the MUO group had a primarily negative BOLD response, and the metabolically healthy obesity group had a response in between the two other groups. Food craving was predicted by taste‐induced activation. After weight loss in the MUO group, taste‐induced activation increased in the DS. Conclusions: These data support the hypothesis that insulin resistance and obesity contribute to aberrant responses to taste in the DS, which is only partially attenuated by weight loss. Aberrant responses to food exposure may be a barrier to weight loss. [ABSTRACT FROM AUTHOR]

Background: The diversity of clinical trajectories in diabetic kidney disease (DKD) has made blood and biochemical urine markers less precise, while renal puncture, the gold standard, is almost impossible in the assessment of diabetic kidney disease, and the value of functional magnetic resonance imaging in the evaluation of diabetic pathological alterations is increasingly recognized. Methods: The literature on functional magnetic resonance imaging (fMRI) for the assessment of renal alterations in diabetic kidney disease was searched in PubMed, Web of Science, Cochrane Library, and Embase databases. The search time limit is from database creation to March 10, 2023. RevMan was used to perform a meta-analysis of the main parameters of fMRIs extracted from DKD patients and healthy volunteers (HV). Results: 24 publications (1550 subjects) were included in this study, using five functional MRIs with seven different parameters. The renal blood flow (RBF) values on Arterial spin labeling magnetic resonance imaging (ASL-MRI) was significantly lower in the DKD group than in the HV group. The [WMD=-99.03, 95% CI (-135.8,-62.27), P<0.00001]; Diffusion tensor imaging magnetic resonance imaging (DTIMRI) showed that the fractional anisotropy (FA) values in the DKD group were significantly lower than that in HV group [WMD=-0.02, 95%CI (-0.03,-0.01), P<0.0001]. And there were no statistically significant differences in the relevant parameters in Blood oxygen level-dependent magnetic resonance imaging (BOLDMRI) or Intro-voxel incoherent movement magnetic resonance imaging (IVIM-DWI). Discussion: ASL and DWI can identify the differences between DKD and HV. DTI has a significant advantage in assessing renal cortical changes; IVIM has some value in determining early diabetic kidney disease from the cortex or medulla. We recommend combining multiple fMRI parameters to assess structural or functional changes in the kidney to make the assessment more comprehensive. We did not observe a significant risk of bias in the present study. [ABSTRACT FROM AUTHOR]

Introduction: To examine the effect of botulinum toxin A (BoNT-A) on neural mechanisms underlying pain and photophobia using functional magnetic resonance imaging (fMRI) in individuals with chronic ocular pain. Methods: Twelve subjects with chronic ocular pain and light sensitivity were recruited from the Miami Veterans Affairs eye clinic. Inclusion criteria were: (1) chronic ocular pain; (2) presence of ocular pain over 1 week recall; and (3) presence of photophobia. All individuals underwent an ocular surface examination to capture tear parameters before and 4-6 weeks after BoNT-A injections. Using an event-related fMRI design, subjects were presented with light stimuli during two fMRI scans, once before and 4-6 weeks after BoNT-A injection. Light evoked unpleasantness ratings were reported by subjects after each scan. Whole brain blood oxygen level dependent (BOLD) responses to light stimuli were analyzed. Results: At baseline, all subjects reported unpleasantness with light stimulation (average: 70.8 ± 32.0). Four to six weeks after BoNT-A injection, unpleasantness scores decreased (48.1 ± 33.6), but the change was not significant. On an individual level, 50% of subjects had decreased unpleasantness ratings in response to light stimulation compared to baseline ("responders," n = 6), while 50% had equivalent (n = 3) or increased (n = 3) unpleasantness ("non-responders"). At baseline, several differences were noted between responders and non-responders; responders had higher baseline unpleasantness ratings to light, higher symptoms of depression, and more frequent use of antidepressants and anxiolytics, compared to nonresponders. Group analysis at baseline displayed light-evoked BOLD responses in bilateral primary somatosensory (S1), bilateral secondary somatosensory (S2), bilateral anterior insula, paracingulate gyrus, midcingulate cortex (MCC), bilateral frontal pole, bilateral cerebellar hemispheric lobule VI, vermis, bilateral cerebellar crus I and II, and visual cortices. BoNT-A injections significantly decreased light evoked BOLD responses in bilateral S1, S2 cortices, cerebellar hemispheric lobule VI, cerebellar crus I, and left cerebellar crus II. BoNT-A responders displayed activation of the spinal trigeminal nucleus at baseline where non-responders did not. Discussion: BoNT-A injections modulate light-evoked activation of pain-related brain systems and photophobia symptoms in some individuals with chronic ocular pain. These effects are associated with decreased activation in areas responsible for processing the sensory-discriminative, affective, dimensions, and motor responses to pain. [ABSTRACT FROM AUTHOR]

Cerebral vascular reactivity quantified using blood oxygen level‐dependent functional MRI in conjuncture with a visual stimulus has been proven to be a potent and early marker for cerebral amyloid angiopathy. This work investigates the influence of different postprocessing methods on the outcome of such vascular reactivity measurements. Three methods for defining the region of interest (ROI) over which the reactivity is measured are investigated: structural (transformed V1), functional (template based on the activation of a subset of subjects), and percentile (11.5 cm3 most responding voxels). Evaluation is performed both in a test–retest experiment in healthy volunteers (N = 12), as well as in 27 Dutch‐type cerebral amyloid angiopathy patients and 33 age‐ and sex‐matched control subjects. The results show that the three methods select a different subset of voxels, although all three lead to similar outcome measures in healthy subjects. However, in (severe) pathology, the percentile method leads to higher reactivity measures than the other two, due to circular analysis or "double dipping" by defining a subject‐specific ROI based on the strongest responses within each subject. Furthermore, while different voxels are included in the presence of lesions, this does not necessarily result in different outcome measures. In conclusion, to avoid bias created by the method, either a structural or a functional method is recommended. Both of these methods provide similar reactivity measures, although the functional ROI appears to be less reproducible between studies, because slightly different subsets of voxels were found to be included. On the other hand, the functional method did include fewer lesion voxels than the structural method. [ABSTRACT FROM AUTHOR]

Based on the fluctuations ensembled over neighbouring neurons, blood oxygen leveldependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain-wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain-wide manner. [ABSTRACT FROM AUTHOR]

Most fMRI inferences are based on analyzing the scans of a cohort. Thus, the individual variability of a subject is often overlooked in these studies. Recently, there has been a growing interest in individual differences in brain connectivity also known as individual connectome. Various studies have demonstrated the individual specific component of functional connectivity (FC), which has enormous potential to identify participants across consecutive testing sessions. Many machine learning and dictionary learning‐based approaches have been used to extract these subject‐specific components either from the blood oxygen level dependent (BOLD) signal or from the FC. In addition, several studies have reported that some resting‐state networks have more individual‐specific information than others. This study compares four different dictionary‐learning algorithms that compute the individual variability from the network‐specific FC computed from resting‐state functional Magnetic Resonance Imaging (rs‐fMRI) data having 10 scans per subject. The study also compares the effect of two FC normalization techniques, namely, Fisher Z normalization and degree normalization on the extracted subject‐specific components. To quantitatively evaluate the extracted subject‐specific component, a metric named Overlap is proposed, and it is used in combination with the existing differential identifiability Idiff metric. It is based on the hypothesis that the subject‐specific FC vectors should be similar within the same subject and different across different subjects. Results indicate that Fisher Z transformed subject‐specific fronto‐parietal and default mode network extracted using Common Orthogonal Basis Extraction (COBE) dictionary learning have the best features to identify a participant. [ABSTRACT FROM AUTHOR]

Background Focal cortical dysplasias (FCD) are a frequent cause of drug-resistant epilepsy in children but are often undetected on structural magnetic resonance imaging (MRI). We aimed to measure and validate the variation of resting state functional MRI (rs-fMRI) blood oxygenation level dependent (BOLD) metrics in surgically proven FCDs in children, to assess the potential yield for detecting and understanding these lesions. Methods We prospectively included pediatric patients with surgically proven FCD with inconclusive structural MRI and healthy controls, who underwent a ten-minute rs-fMRI acquired at 3T. Rs-fMRI data was pre-processed and maps of values of regional homogeneity (ReHo), degree centrality (DC), amplitude of low frequency fluctuations (ALFF) and fractional ALFF (fALFF) were calculated. The variations of BOLD metrics within the to-be-resected areas were analyzed visually, and quantitatively using lateralization indices. BOLD metrics variations were also analyzed in fluorodeoxyglucose-positron emission tomography (FDG-PET) hypometabolic areas. Results We included 7 patients (range: 3–15 years) and 6 aged-matched controls (range: 6–17 years). ReHo lateralization indices were positive in the to-be-resected areas in 4/7 patients, and in 6/7 patients in the additional PET hypometabolic areas. These indices were significantly higher compared to controls in 3/7 and 4/7 patients, respectively. Visual analysis revealed a good spatial correlation between high ReHo areas and MRI structural abnormalities (when present) or PET hypometabolic areas. No consistent variation was seen using DC, ALFF, or fALFF. Conclusion Resting-state fMRI metrics, noticeably increase in ReHo, may have potential to help detect MRI-negative FCDs in combination with other morphological and functional techniques, used in clinical practice and epilepsy-surgery screening. [ABSTRACT FROM AUTHOR]