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High-resolution diffusion-weighted imaging (DWI) has great potential to provide unique information about tissue microstructure in-vivo. Although single-shot echo-planar imaging (EPI) is a most popular tool for DWI, its application for high-resolution DWI is limited due to T2* blurring and susceptibility- and eddy-current-induced geometric distortions, especially at ultra-high field (UHF) such as 7T. In this study, we adapt a hybrid spin-warp and echo-planar encoding strategy inspired by point spread function (PSF) mapping and optimize it for high-resolution and distortion-free diffusion imaging applications. More specifically, a 2D navigator echo is added into the original sequence for shot-to-shot motion-induced phase error estimation and correction. The spatial encoding is shared between the PSF and the EPI phase encoding dimension allowing short echo trains to preserve the diffusion and navigator signals efficiently at UHF, where T2 decay is relatively fast. In addition, variable k-space spacing was applied in the PSF dimension and combined with parallel imaging in the EPI-PE dimension to further accelerate the PSF acquisition. The results demonstrate that this method can yield isotropic submillimeter resolution without T2* blurring and geometric distortions at 7T and enables a clear and detailed delineation of human brain structures in-vivo with the diffusion contrasts. In addition, results of the proposed approach for high-resolution diffusion imaging at 3T are presented. [Display omitted] •A new variant of multi-shot EPI for high-resolution diffusion-weighted MRI is presented.•The method allows distortion-free imaging without T2* blurring.•A clear delineation of brain structures with diffusion contrast at 7T is shown.•High-resolution diffusion imaging is possible also at 3T.

Functional imaging with sub-millimeter spatial resolution is a basic requirement for assessing functional MRI (fMRI) responses across different cortical depths and is used extensively in the emerging field of laminar fMRI. Such studies seek to investigate the detailed functional organization of the brain and may develop to a new powerful tool for human neuroscience. However, several studies have shown that measurement of laminar fMRI responses can be biased by the image acquisition and data processing strategies. In this work, measurements with three different gradient-echo EPI BOLD fMRI protocols with a voxel size down to 650 ​μm isotropic were performed at 9.4 ​T. We estimated how prospective motion correction can help to improve spatial accuracy by reducing the number of spatial resampling steps in postprocessing. In addition, we demonstrate key requirements for accurate geometric distortion correction to ensure that distortion correction maps are properly aligned to the functional data and that strong variations of distortions near large veins can lead to signal overlays which cannot be corrected for during postprocessing. Furthermore, this study illustrates the spatial extent of bias induced by pial and other larger veins in laminar BOLD experiments. Since these issues under investigation affect studies performed with more conventional spatial resolutions, the methods applied in this work may also help to improve the understanding of the BOLD signal more broadly. •Prospective motion correction can help to reduce the number of processing steps affecting spatial accuracy of laminar fMRI.•Magnitude PSF distortion correction leads to resolution losses.•Signal of voxels close to large veins may be displaced by several millimeters.•Laminar GE-BOLD signal is 60% lower at distances above 1 ​mm from large veins.•The GE-BOLD signal increases towards the surface even distant from large veins.

•Cardiorespiratory dynamics significantly impact brain hemodynamics.•Heart rate variability (HRV) and respiratory sinus arrhythmia (RSA) reflect vital physiological states in the brain.•CO2 and O2 levels modulate cerebral blood flow and BOLD signal.•Glymphatic system dynamics influenced by CSF flow can be indirectly detected in fMRI.•Recognizing physiological signals can enhance insights into brain function and health. Cardiorespiratory signals have long been treated as \"noise\" in functional magnetic resonance imaging (fMRI) research, with the goal of minimizing their impact to isolate neural activity. However, there is a growing recognition that these signals, once seen as confounding variables, provide valuable insights into brain function and overall health. This shift reflects the dynamic interaction between the cardiovascular, respiratory, and neural systems, which together support brain activity. In this review, we explore the role of cardiorespiratory dynamics—such as heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and changes in blood flow, oxygenation, and carbon dioxide levels—embedded within fMRI signals. These physiological signals reflect critical aspects of neurovascular coupling and are influenced by factors such as physiological stress, breathing patterns, and age-related changes. We also discuss the complexities of distinguishing these signals from neuronal activity in fMRI data, given their significant contribution to signal variability and interactions with cerebrospinal fluid (CSF). Recognizing the influence of these cardiorespiratory dynamics is crucial for improving the interpretation of fMRI data, shedding light on heart-brain and respiratory-brain connections, and enhancing our understanding of circulation, oxygen delivery, and waste elimination within the brain.

•Hypoxia impairs inhibitory control and sustained attention during the Go/No-Go task.•A modified Davis model for normoxia-hypoxia differences estimates CMRO2 changes.•Regional CMRO2 reductions reveal significant heterogeneity across brain networks.•Attention and executive frontoparietal networks exhibited the largest CMRO2 reductions.•Adaptive prioritization of brain networks explains cognitive impairments in hypoxia. Acute exposure to severe hypoxia impairs cognitive performance, yet the integrated brain mechanisms underlying this temporary decline remain unclear. This study examined regional variations in cerebral oxygen metabolism during acute hypoxia and their relationship to cognitive impairment. Eleven young, healthy participants (26.5 ± 4.5 years old) performed the Go/No-Go task during two sessions, each of which includes three minutes of hypoxia (FiO2 = 7.7 %). Cerebral blood flow (CBF) was assessed using pCASL MRI in one session, while blood-oxygen-level-dependent (BOLD) signals were acquired in another. Fractional changes in CBF (δCBF) and BOLD (δBOLD) were combined using a modified Davis model, adjusted for physiological differences between normoxia and acute and severe hypoxia, to calculate the fractional change in cerebral metabolic rate of oxygen (δCMRO2). Group-level z-normalized δCMRO2 maps revealed significant regional heterogeneity, with most pronounced reductions in areas associated with the dorsal and ventral attention networks and executive frontoparietal networks. These regions exhibited δCMRO2 reductions exceeding the hemispheric average (-9.6 ± 7.9 %) and were associated with increased commission errors during the Go/No-Go task, reflecting impaired inhibitory control and sustained attention. This study highlights the brain's adaptive prioritization of certain networks under oxygen deprivation, providing insights into the physiological mechanisms underlying hypoxia-induced cognitive impairments. These findings enhance our understanding of how acute hypoxia affects brain function, emphasizing the importance of network-specific adaptations in maintaining cognitive performance during oxygen deprivation.

Cerebrospinal fluid dynamics play a crucial role in maintaining brain homeostasis by delivering nutrients, transmitting immune signals, and clearing waste products. While cardiac activity primarily drives the pulsatile movement of cerebrospinal fluid, respiration has been shown to facilitate low-frequency oscillations and contribute to bulk flow. Recent studies suggest that enhancing respiratory function may be an effective intervention to modulate cerebrospinal fluid dynamics. This study included 20 individuals with long-term formal training in Seokmun Hoheup, a lower belly–centered breathing practice (mea n  ± SD age, 58.1 ± 17.3 years; 8 females), and 25 controls with no formal long-term breathing practice (mea n  ± SD age, 49.2 ± 20.2 years; 12 females). All underwent real-time velocity-encoding magnetic resonance imaging to assess cerebrospinal fluid movement at the foramen magnum and lateral ventricle during both regular breathing and deep breathing. Deep breathing enhances cerebrospinal fluid dynamics in both groups, increasing displacement and net flow, particularly at the foramen magnum. Seokmun Hoheup trained participants show greater cerebrospinal fluid movement than controls at both the foramen magnum and lateral ventricle. Even during regular breathing, trained participants show higher cerebrospinal fluid mean speed, displacement, and net flow. Among respiratory factors, inhale length and diaphragm displacement show the strongest correlations with cerebrospinal fluid movement. Respiration modulated cerebrospinal fluid dynamics through both mechanical enhancement of venous outflow and autonomic modulation of the heart, with mechanical effects predominating in the lateral ventricle and both pathways contributing to the foramen magnum. Our findings identify respiration in the awake state as a modifiable, noninvasive mechanism that influences involuntary functions such as cerebrospinal fluid dynamics and may have implications for cerebrospinal fluid-mediated brain homeostasis. Respiration enhances cerebrospinal fluid flow through mechanical and autonomic pathways. Inhale length and diaphragm motion influence its displacement and net flow, identifying a modifiable, noninvasive mechanism relevant to brain homeostasis.

Functional magnetic resonance imaging (fMRI) is an emerging tool for investigating brain activation associated with, or modulated by, deep brain stimulation (DBS). However, DBS-fMRI generally suffers from severe susceptibility to artifacts in regions near the metallic stimulation electrodes, as well as near tissue/air boundaries of the brain. These result in strong intensity and geometric distortions along the phase-encoding (PE) (i.e., blipped) direction in gradient-echo echo-planar imaging (GE-EPI). Distortion presents a major challenge to conducting reliable data analysis and in interpreting the findings. A recent study showed that the point spread function (PSF) mapping-based reverse gradient approach has a potential to correct for distortions not only in spin-echo EPI, but also in GE-EPI acquired in both the forward and reverse PE directions. In this study, we adapted that approach in order to minimize severe metal-induced susceptibility artifacts for DBS-fMRI, and to evaluate the performance of the approach in a phantom study and a large animal DBS-fMRI study. The method combines the distortion-corrected GE-EPI pair with geometrically different intensity distortions due to the opposing encoding directions. The results demonstrate that the approach can minimize susceptibility artifacts that appear around the metallic electrodes, as well as in the regions near the tissue/air boundaries in the brain. We also demonstrated that an accurate geometric correction is important in improving BOLD contrast in the group dataset, especially in regions where strong susceptibility artifacts appear. •PSF mapping-based reverse gradient approach can be adapted to minimize susceptibility artifacts in fMRI.•This approach can minimize susceptibility artifacts that appear around the metallic electrodes.•Susceptibility artifacts near the tissue/air boundaries in the brain can also be resolved.•With the distortions minimized, local BOLD contrast in DBS-fMRI can be improved.

In echo-planar imaging (EPI), such as commonly used for functional MRI (fMRI) and diffusion-tensor imaging (DTI), compressed distortion is a more difficult challenge than local stretching as spatial information can be lost in strongly compressed areas. In addition, the effects are more severe at ultra-high field (UHF) such as 7T due to increased field inhomogeneity. To resolve this problem, two EPIs with opposite phase-encoding (PE) polarity were acquired and combined after distortion correction. For distortion correction, a point spread function (PSF) mapping method was chosen due to its high correction accuracy and extended to perform distortion correction of both EPIs with opposite PE polarity thus reducing the PSF reference scan time. Because the amount of spatial information differs between the opposite PE datasets, the method was further extended to incorporate a weighted combination of the two distortion-corrected images to maximize the spatial information content of a final corrected image. The correction accuracy of the proposed method was evaluated in distortion-corrected data using both forward and reverse phase-encoded PSF reference data and compared with the reversed gradient approaches suggested previously. Further we demonstrate that the extended PSF method with an improved weighted combination can recover local distortions and spatial information loss and be applied successfully not only to spin-echo EPI, but also to gradient-echo EPIs acquired with both PE directions to perform geometrically accurate image reconstruction.

Deep brain stimulation (DBS) has been shown to be an effective treatment for movement disorders and it is now being extended to the treatment of psychiatric disorders. Functional magnetic resonance imaging (fMRI) studies indicate that DBS stimulation targets dependent brain network effects, in networks that respond to stimulation. Characterizing these patterns is crucial for linking DBS-induced therapeutic and adverse effects. Conventional DBS-fMRI, however, lacks the sensitivity needed for decoding multidimensional information such as spatially diffuse patterns. We report here on the use of a multivariate pattern analysis (MVPA) to demonstrate that stimulation of three DBS targets (STN, subthalamic nucleus; GPi, globus pallidus internus; NAc, nucleus accumbens) evoked a sufficiently distinctive blood-oxygen-level-dependent (BOLD) activation in swine brain. The findings indicate that STN and GPi evoke a similar motor network pattern, while NAc shows a districted associative and limbic pattern. The findings show that MVPA could be effectively applied to overlapping or sparse BOLD patterns which are often found in DBS. Future applications are expected employ MVPA fMRI to identify the proper stimulation target dependent brain circuitry for a DBS outcome.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

Introduction While the clinical efficacy of deep brain stimulation (DBS) the treatment of motor‐related symptoms is well established, the mechanism of action of the resulting cognitive and behavioral effects has been elusive. Methods By combining functional magnetic resonance imaging (fMRI) and DBS, we investigated the pattern of blood‐oxygenation‐level‐dependent (BOLD) signal changes induced by stimulating the nucleus accumbens in a large animal model. Results We found that diffused BOLD activation across multiple functional networks, including the prefrontal, limbic, and thalamic regions during the stimulation, resulted in a significant change in inter‐regional functional connectivity. More importantly, the magnitude of the modulation was closely related to the strength of the inter‐regional resting‐state functional connectivity. Conclusions Nucleus accumbens stimulation affects the functional activity in networks that underlie cognition and behavior. Our study provides an insight into the nature of the functional connectivity, which mediates activation effect via brain networks. Deep brain stimulation on nucleus accumbens of eight healthy swine evoked blood‐oxygenated‐level‐dependent (BOLD) activation in multiple cortical and subcortical brain regions.