Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a region near the posterior inferior frontal sulcus of the right dorsolateral prefrontal cortex (piDLPFC) in migraine patients during acute pain and cognitive task performance. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this piDLPFC region, and diffusion weighted imaging verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

Simultaneous cortical, subcortical, and brainstem mapping of sensory activation

Non-painful tactile sensory stimuli are processed in the cortex, subcortex, and brainstem. Recent functional magnetic resonance imaging (fMRI) studies have highlighted the value of whole-brain, systems-level investigation for examining pain processing. However, whole-brain fMRI studies are uncommon, in part due to challenges with signal to noise when studying the brainstem. Furthermore, the differentiation of small sensory brainstem structures such as the cuneate and gracile nuclei necessitates high resolution imaging. To address this gap in systems-level sensory investigation, we employed a whole-brain, multi-echo fMRI acquisition at 3T with multi-echo independent component analysis (ME-ICA) denoising and brainstem-specific modeling to enable detection of activation across the entire sensory system. In healthy participants, we examined patterns of activity in response to non-painful brushing of the right hand, left hand, and right foot, and found the expected lateralization, with distinct cortical and subcortical responses for upper and lower limb stimulation. At the brainstem level, we were able to differentiate the small, adjacent cuneate and gracile nuclei, corresponding to hand and foot stimulation respectively. Our findings demonstrate that simultaneous cortical, subcortical, and brainstem mapping at 3T could be a key tool to understand the sensory system in both healthy individuals and clinical cohorts with sensory deficits.

Negative association between neurovascular coupling and cortical gray matter volume during the lifespan

Recent studies have established the moment-to-moment turnover of the blood-oxygen-level-dependent signal (TBOLD) at resting state as a key measure of local cortical brain function. Here, we sought to extend that line of research by evaluating TBOLD in 70 cortical areas with respect to corresponding brain volume, age, and sex across the lifespan in 1,344 healthy participants including 633 from the Human Connectome Project (HCP)-Development cohort (294 males and 339 females, age range 8-21 yr) and 711 healthy participants from HCP-Aging cohort (316 males and 395 females, 36-90 yr old). In both groups, we found that 1) TBOLD increased with age, 2) volume decreased with age, and 3) TBOLD and volume were highly significantly negatively correlated, independent of age. The inverse association between TBOLD and volume was documented in nearly all 70 brain areas and for both sexes, with slightly stronger associations documented for males. The strong correspondence between TBOLD and volume across age and sex suggests a common influence such as chronic neuroinflammation contributing to reduced cortical volume and increased TBOLD across the lifespan.NEW & NOTEWORTHY We report a significant negative association between resting functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent (BOLD) signal turnover (TBOLD) and cortical gray matter volume across the lifespan, such that TBOLD increased whereas volume decreased. We attribute this association to a hypothesized chronic, low-grade neuroinflammation, probably induced by various neurotropic pathogens, including human herpes viruses known to be dormant in the brain in a latent state and reactivated by stress, fever, and various environmental exposures, such as ultraviolet light.

Real-time Quantification of in vivo cerebrospinal fluid velocity using fMRI inflow effect

In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory gated approaches, such as 4D flow MRI, cannot capture CSF movement in real time due to limited temporal resolution and in addition deteriorate in accuracy at low fluid velocities. Other techniques like real-time PC-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional magnetic resonance imaging (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.

A selection and targeting framework of cortical locations for line-scanning fMRI

Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively.

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Detection and Mitigation of Neurovascular Uncoupling in Brain Gliomas

Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.

Detection and characterization of resting state functional networks in squirrel monkey brain

Resting-state fMRI based on analyzing BOLD signals is widely used to derive functional networks in the brain and how they alter during disease or injury conditions. Resting-state networks can also be used to study brain functional connectomes across species, which provides insights into brain evolution. The squirrel monkey (SM) is a non-human primate (NHP) that is widely used as a preclinical model for experimental manipulations to understand the organization and functioning of the brain. We derived resting-state networks from the whole brain of anesthetized SMs using Independent Component Analysis of BOLD acquisitions. We detected 15 anatomically constrained resting-state networks localized in the cortical and subcortical regions as well as in the white-matter. Networks encompassing visual, somatosensory, executive control, sensorimotor, salience and default mode regions, and subcortical networks including the Hippocampus-Amygdala, thalamus, basal-ganglia and brainstem region correspond well with previously detected networks in humans and NHPs. The connectivity pattern between the networks also agrees well with previously reported seed-based resting-state connectivity of SM brain. This study demonstrates that SMs share remarkable homologous network organization with humans and other NHPs, thereby providing strong support for their suitability as a translational animal model for research and additional insight into brain evolution across species.

The confound of hemodynamic response function variability in human resting-state functional MRI studies

Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.

Hemodynamic timing in resting-state and breathing-task BOLD fMRI

The blood flow response to a vasoactive stimulus demonstrates regional heterogeneity across both the healthy brain and in cerebrovascular pathology. The timing of a regional hemodynamic response is emerging as an important biomarker of cerebrovascular dysfunction, as well as a confound within fMRI analyses. Previous research demonstrated that hemodynamic timing is more robustly characterized when a larger systemic vascular response is evoked by a breathing challenge, compared to when only spontaneous fluctuations in vascular physiology are present (i.e., in resting-state data). However, it is not clear whether hemodynamic delays in these two conditions are physiologically interchangeable, and how methodological signal-to-noise factors may limit their agreement. To address this, we generated whole-brain maps of hemodynamic delays in nine healthy adults. We assessed the agreement of voxel-wise gray matter (GM) hemodynamic delays between two conditions: resting-state and breath-holding. We found that delay values demonstrated poor agreement when considering all GM voxels, but increasingly greater agreement when limiting analyses to voxels showing strong correlation with the GM mean time-series. Voxels showing the strongest agreement with the GM mean time-series were primarily located near large venous vessels, however these voxels explain some, but not all, of the observed agreement in timing. Increasing the degree of spatial smoothing of the fMRI data enhanced the correlation between individual voxel time-series and the GM mean time-series. These results suggest that signal-to-noise factors may be limiting the accuracy of voxel-wise timing estimates and hence their agreement between the two data segments. In conclusion, caution must be taken when using voxel-wise delay estimates from resting-state and breathing-task data interchangeably, and additional work is needed to evaluate their relative sensitivity and specificity to aspects of vascular physiology and pathology.

Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented method to map CVR involves using a breath-hold task during a BOLD fMRI scan. Recording end-tidal CO₂ (P_ETCO₂) changes during the breath-hold task is recommended to be used as a reference signal for modeling CVR amplitude in standard units (%BOLD/mmHg) and CVR delay in seconds. However, obtaining reliable P_ETCO₂ recordings requires equipment and task compliance that may not be achievable in all settings. To address this challenge, we investigated two alternative reference signals to map CVR amplitude and delay in a lagged general linear model (lagged-GLM) framework: respiration volume per time (RVT) and average gray matter BOLD response (GM-BOLD). In 8 healthy adults with multiple scan sessions, we compare spatial agreement of CVR maps from RVT and GM-BOLD to those generated with P_ETCO₂. We define a threshold to determine whether a P_ETCO₂ recording has "sufficient" quality for CVR mapping and perform these comparisons in 16 datasets with sufficient P_ETCO₂ and 6 datasets with insufficient P_ETCO₂. When P_ETCO₂ quality is sufficient, both RVT and GM-BOLD produce CVR amplitude maps that are nearly identical to those from P_ETCO₂ (after accounting for differences in scale), with the caveat they are not in standard units to facilitate between-group comparisons. CVR delays are comparable to P_ETCO₂ with an RVT regressor but may be underestimated with the average GM-BOLD regressor. Importantly, when P_ETCO₂ quality is insufficient, RVT and GM-BOLD CVR recover reasonable CVR amplitude and delay maps, provided the participant attempted the breath-hold task. Therefore, our framework offers a solution for achieving high quality CVR maps in both retrospective and prospective studies where sufficient P_ETCO₂ recordings are not available and especially in populations where obtaining reliable measurements is a known challenge (e.g., children). Our results have the potential to improve the accessibility of CVR mapping and to increase the prevalence of this promising metric of vascular health.

The Effect of Efavirenz on Reward Processing in Asymptomatic People Living with HIV: A Randomized Controlled Trial

Functional magnetic resonance imaging (fMRI) studies have demonstrated that HIV-infection affects the fronto-striatal network. It has not been examined what impact efavirenz (EFV), an antiretroviral drug notorious for its neurocognitive effects, has on the reward system: a key subcomponent involved in depressive and apathy symptoms. Therefore, this study aims to investigate the effect of EFV on reward processing using a monetary incentive delay (MID) task. In this multicenter randomized controlled trial, asymptomatic adult participants stable on emtricitabine/tenofovirdisoproxil fumarate (FTC/TDF)/EFV were randomly assigned in a 2:1 ratio to switch to FTC/TDF/rilpivirine (RPV) (n = 30) or continue taking FTC/TDF/EFV (n = 13). At baseline and 12 weeks after therapy switch, both groups performed an MID task. Behavior and functional brain activity related to reward anticipation and reward outcome were assessed with blood-oxygen-level-dependent fMRI. Both groups were matched for age, education level, and time since HIV diagnosis and on EFV. At the behavioral level, both groups had faster response times and better response accuracy during rewarding versus nonrewarding trials, with no improvement resulting from switching FTC/TDF/EFV to FTC/TDF/RPV. No significant change in activation related to reward anticipation in the ventral striatum was found after switching therapy. Both groups had significantly higher activation levels over time, consistent with a potential learning effect. Similar activity related to reward outcome in the orbitofrontal cortex was found. Discontinuing FTC/TDF/EFV was not found to improve activity related to reward anticipation in asymptomatic people living with HIV, with similar cortical functioning during reward outcome processing. It is therefore likely that EFV does not affect motivational control. Further research is needed to determine whether EFV affects motivational control in HIV populations with different characteristics.

BOLD fMRI and DTI fiber tracking for preoperative mapping of eloquent cerebral regions in brain tumor patients: impact on surgical approach and outcome

PURPOSE

Task-based BOLD fMRI and DTI-fiber tracking have become part of the routine presurgical work-up of brain tumor patients in many institutions. However, their potential impact on both surgical treatment and neurologic outcome remains unclear, in despite of the high costs and complex implementation.

METHODS

We retrospectively investigated whether performing fMRI and DTI-ft preoperatively substantially impacted surgical planning and patient outcome in a series of brain tumor patients. We assessed (i) the quality of fMRI and DTI-ft results, by using a scale of 0-2 (0 = failed mapping; 1 = intermediate confidence; 2 = good confidence), (ii) whether functional planning substantially contributed to defining the surgical strategy to be undertaken (i.e., no surgery, biopsy, or resection, with or without ESM), the surgical entry point and extent of resection, and (iii) the incidence of neurological deficits post-operatively.

RESULTS

Twenty-seven patients constituted the study population. The mean confidence rating was 1.9/2 for fMRI localization of the eloquent cortex and lateralization of the language function and 1.7/2 for DTI-ft results. Treatment strategy was altered in 33% (9/27) of cases. Surgical entry point was modified in 8% (2/25) of cases. The extent of resection was modified in 40% (10/25). One patient (1/25, 4%) developed one new functional deficit post-operatively.

CONCLUSION

Functional MR mapping - which must not be considered an alternative to ESM - has a critical role preoperatively, potentially modifying treatment strategy or increasing the neurosurgeons' confidence in the surgical approach hypothesized based on conventional imaging.

Masked features of task states found in individual brain networks

Completing complex tasks requires that we flexibly integrate information across brain areas. While studies have shown how functional networks are altered during different tasks, this work has generally focused on a cross-subject approach, emphasizing features that are common across people. Here we used extended sampling "precision" fMRI data to test the extent to which task states generalize across people or are individually specific. We trained classifiers to decode state using functional network data in single-person datasets across 5 diverse task states. Classifiers were then tested on either independent data from the same person or new individuals. Individualized classifiers were able to generalize to new participants. However, classification performance was significantly higher within a person, a pattern consistent across model types, people, tasks, feature subsets, and even for decoding very similar task conditions. Notably, these findings also replicated in a new independent dataset. These results suggest that individual-focused approaches can uncover robust features of brain states, including features obscured in cross-subject analyses. Individual-focused approaches have the potential to deepen our understanding of brain interactions during complex cognition.

Estimating and mitigating the effects of systemic low frequency oscillations (sLFO) on resting state networks in awake non-human primates using time lag dependent methodology

AIM

Resting-state fMRI (rs-fMRI) is often used to infer regional brain interactions from the degree of temporal correlation between spontaneous low-frequency fluctuations, thought to reflect local changes in the BOLD signal due to neuronal activity. One complication in the analysis and interpretation of rs-fMRI data is the existence of non-neuronal low frequency physiological noise (systemic low frequency oscillations; sLFOs) which occurs within the same low frequency band as the signal used to compute functional connectivity. Here, we demonstrate the use of a time lag mapping technique to estimate and mitigate the effects of the sLFO signal on resting state functional connectivity of awake squirrel monkeys.

METHODS

Twelve squirrel monkeys (6 male/6 female) were acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Rs-fMRI data was preprocessed using an in-house pipeline and sLFOs were detected using a seed regressor generated by averaging BOLD signal across all voxels in the brain, which was then refined recursively within a time window of -16-12 s. The refined regressor was then used to estimate the voxel-wise sLFOs; these regressors were subsequently included in the general linear model to remove these moving hemodynamic components from the rs-fMRI data using general linear model filtering. Group level independent component analysis (ICA) with dual regression was used to detect resting-state networks and compare networks before and after sLFO denoising.

RESULTS

Results show sLFOs constitute ~64% of the low frequency fMRI signal in squirrel monkey gray matter; they arrive earlier in regions in proximity to the middle cerebral arteries (e.g., somatosensory cortex) and later in regions close to draining vessels (e.g., cerebellum). Dual regression results showed that the physiological noise was significantly reduced after removing sLFOs and the extent of reduction was determined by the brain region contained in the resting-state network.

CONCLUSION

These results highlight the need to estimate and remove sLFOs from fMRI data before further analysis.

Robust high spatio-temporal line-scanning fMRI in humans at 7T using multi-echo readouts, denoising and prospective motion correction

BACKGROUND

Functional magnetic resonance imaging (fMRI), typically using blood oxygenation level-dependent (BOLD) contrast weighted imaging, allows the study of brain function with millimeter spatial resolution and temporal resolution of one to a few seconds. At a mesoscopic scale, neurons in the human brain are spatially organized in structures with dimensions of hundreds of micrometers, while they communicate at the millisecond timescale. For this reason, it is important to develop an fMRI method with simultaneous high spatial and temporal resolution. Line-scanning promises to reach this goal at the cost of volume coverage.

NEW METHOD

Here, we release a comprehensive update to human line-scanning fMRI. First, we investigated multi-echo line-scanning with five different protocols varying the number of echoes and readout bandwidth while keeping the TR constant. In these, we compared different echo combination approaches in terms of BOLD activation (sensitivity) and temporal signal-to-noise ratio. Second, we implemented an adaptation of NOise reduction with DIstribution Corrected principal component analysis (NORDIC) thermal noise removal for line-scanning fMRI data. Finally, we tested three image-based navigators for motion correction and investigated different ways of performing fMRI analysis on the timecourses which were influenced by the insertion of the navigators themselves.

RESULTS

The presented improvements are relatively straightforward to implement; multi-echo readout and NORDIC denoising together, significantly improve data quality in terms of tSNR and t-statistical values, while motion correction makes line-scanning fMRI more robust.

COMPARISON WITH EXISTING METHODS

Multi-echo acquisitions and denoising have previously been applied in 3D magnetic resonance imaging. Their combination and application to 1D line-scanning is novel. The current proposed method greatly outperforms the previous line-scanning acquisitions with single-echo acquisition, in terms of tSNR (4.0 for single-echo line-scanning and 36.2 for NORDIC-denoised multi-echo) and t-statistical values (3.8 for single-echo line-scanning and 25.1 for NORDIC-denoised multi-echo line-scanning).

CONCLUSIONS

Line-scanning fMRI was advanced compared to its previous implementation in order to improve sensitivity and reliability. The improved line-scanning acquisition could be used, in the future, for neuroscientific and clinical applications.

The impact of vasomotion on analysis of rodent fMRI data

Introduction

Small animal fMRI is an essential part of translational research in the cognitive neurosciences. Due to small dimensions and animal physiology preclinical fMRI is prone to artifacts that may lead to misinterpretation of the data. To reach unbiased translational conclusions, it is, therefore, crucial to identify potential sources of experimental noise and to develop correction methods for contributions that cannot be avoided such as physiological noise. Aim of this study was to assess origin and prevalence of hemodynamic oscillations (HDO) in preclinical fMRI in rat, as well as their impact on data analysis.

Methods

Following the development of algorithms for HDO detection and suppression, HDO prevalence in fMRI measurements was investigated for different anesthetic regimens, comprising isoflurane and medetomidine, and for both gradient echo and spin echo fMRI sequences. In addition to assessing the effect of vasodilation on HDO, it was studied if HDO have a direct neuronal correlate using local field potential (LFP) recordings. Finally, the impact of HDO on analysis of fMRI data was assessed, studying both the impact on calculation of activation maps as well as the impact on brain network analysis. Overall, 303 fMRI measurements and 32 LFP recordings were performed in 71 rats.

Results

In total, 62% of the fMRI measurements showed HDO with a frequency of (0.20 ± 0.02) Hz. This frequent occurrence indicated that HDO cannot be generally neglected in fMRI experiments. Using the developed algorithms, HDO were detected with a specificity of 95%, and removed efficiently from the signal time courses. HDO occurred brain-wide under vasoconstrictive conditions in both small and large blood vessels. Vasodilation immediately interrupted HDO, which, however, returned within 1 h under vasoconstrictive conditions. No direct neuronal correlate of HDO was observed in LFP recordings. HDO significantly impacted analysis of fMRI data, leading to altered cluster sizes and F-values for activated voxels, as well as altered brain networks, when comparing data with and without HDO.

Discussion

We therefore conclude that HDO are caused by vasomotion under certain anesthetic conditions and should be corrected during fMRI data analysis to avoid bias.

Dynamic Effective Connectivity using Physiologically informed Dynamic Causal Model with Recurrent Units: A functional Magnetic Resonance Imaging simulation study

Functional MRI (fMRI) is an indirect reflection of neuronal activity. Using generative biophysical model of fMRI data such as Dynamic Causal Model (DCM), the underlying neuronal activities of different brain areas and their causal interactions (i.e., effective connectivity) can be calculated. Most DCM studies typically consider the effective connectivity to be static for a cognitive task within an experimental run. However, changes in experimental conditions during complex tasks such as movie-watching might result in temporal variations in the connectivity strengths. In this fMRI simulation study, we leverage state-of-the-art Physiologically informed DCM (P-DCM) along with a recurrent window approach and discretization of the equations to infer the underlying neuronal dynamics and concurrently the dynamic (time-varying) effective connectivities between various brain regions for task-based fMRI. Results from simulation studies on 3- and 10-region models showed that functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) responses and effective connectivity time-courses can be accurately predicted and distinguished from faulty graphical connectivity models representing cognitive hypotheses. In summary, we propose and validate a novel approach to determine dynamic effective connectivity between brain areas during complex cognitive tasks by combining P-DCM with recurrent units.

Temporal stability of the hemodynamic response function across the majority of human cerebral cortex

The hemodynamic response function (HRF) measured with functional magnetic resonance imaging is generated by vascular and metabolic responses evoked by brief (<4 s) stimuli. It is known that the human HRF varies across cortex, between subjects, with stimulus paradigms, and even between different measurements in the same cortical location. However, our results demonstrate that strong HRFs are remarkably repeatable across sessions separated by time intervals up to 3 months. In this study, a multisensory stimulus was used to activate and measure the HRF across the majority of cortex (>70%, with lesser reliability observed in some areas of prefrontal cortex). HRFs were measured with high spatial resolution (2‐mm voxels) in central gray matter to minimize variations caused by partial‐volume effects. HRF amplitudes and temporal dynamics were highly repeatable across four sessions in 20 subjects. Positive and negative HRFs were consistently observed across sessions and subjects. Negative HRFs were generally weaker and, thus, more variable than positive HRFs. Statistical measurements showed that across‐session variability is highly correlated to the variability across events within a session; these measurements also indicated a normal distribution of variability across cortex. The overall repeatability of the HRFs over long time scales generally supports the long‐term use of event‐related functional magnetic resonance imaging protocols.

Toward an integrative neurovascular framework for studying brain networks

Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.

Multi-echo balanced SSFP with a sequential phase-encoding order for functional MR imaging at 7T

PURPOSE

To develop a 2D multi-echo passband balanced SSFP (bSSFP) sequence using an echo-train readout with a sequential phase-encoding order (sequential multi-echo bSSFP), and evaluate its performance in fast functional brain imaging at 7 T.

METHODS

As images of sequential multi-echo bSSFP exhibit multiple ghosts due to periodic k-space modulations, a GRAPPA-based reconstruction method was proposed to eliminate ghosting artifacts. MRI experiments were performed to compare the image quality of multi-echo bSSFP and conventional single-echo bSSFP. Submillimeter-resolution fMRI using a checkerboard visual stimulus was conducted to compare the activation characteristics of multi-echo bSSFP, conventional single-echo bSSFP and standard gradient-echo EPI (GE-EPI).

RESULTS

A higher mean structural similarity index was found between images of single-echo bSSFP and multi-echo bSSFP with a shorter echo train length (ETL). Multi-echo bSSFP (ETL = 3) showed higher temporal SNR (tSNR) values than GRAPPA-accelerated single-echo bSSFP (R = 2). In submillimeter-resolution fMRI experiments, multi-echo bSSFP (ETL = 3) approached the imaging speed of GRAPPA-accelerated single-echo bSSFP (R = 2), but without tSNR penalty and reduced activation due to acceleration. The median t-value and the number of significantly activated voxels were comparable between GE-EPI and multi-echo bSSFP (ETL = 3) that provides virtually distortion-free functional images and inherits the activation patterns of conventional bSSFP.

CONCLUSION

Sequential multi-echo bSSFP (ETL = 3) is suitable for fast fMRI with submillimeter in-plane resolution, and offers an option to accelerate bSSFP imaging without tSNR penalty like parallel imaging.

Where functional MRI stops, metabolism starts

Combining techniques that track blood oxygenation and biochemicals during neuronal activity reveals how the brain computes perceived and unperceived stimuli.

The relationship between cardiovascular risk and lifestyle activities on hippocampal volumes in normative aging

Background

Despite the life-course perspective of popular aging models, few studies on healthy aging to date have examined both younger and older adulthood. The current study examined how cumulative vascular risk factors and self-reported levels of physical, social, and cognitive activity are associated with differences in hippocampal volumes in healthy younger and older adults.

Methods

34 neurologically healthy participants were separated into two age cohorts: a younger adult group (age 25-35, n = 17) and an older adult group (age 65-82, n = 17). Participants underwent a 3 T T1 MRI and completed a series of questionnaires. Voxel-based morphometry examined whole-brain grey matter density differences between groups. Hippocampal volumes were computed. Analyses examined the association between hippocampal volumes, cumulative vascular risk, and self-reported levels of physical, social, and cognitive activity, both within and across groups.

Results

Between-group comparisons revealed greater cortical atrophy in older relative to young adults in regions including the left and right hippocampus and temporal fusiform cortex. Across-group analyses revealed a significant negative association between cardiovascular risk scores and bilateral hippocampal volumes across age groups. A significant negative association was identified between frequency of social activities and bilateral hippocampal volumes in older adults only. No significant associations were found between left or right hippocampal volumes and total, cognitive, or physical activities in both within- and across-group analyses.

Conclusion

Greater cumulative vascular risk is associated with smaller hippocampal volumes across age cohorts. Findings suggest that social activities with low cognitive load may not be beneficial to structural brain outcomes in older age.

Simultaneous fMRI and fast-scan cyclic voltammetry bridges evoked oxygen and neurotransmitter dynamics across spatiotemporal scales

The vascular contributions of neurotransmitters to the hemodynamic response are gaining more attention in neuroimaging studies, as many neurotransmitters are vasomodulatory. To date, well-established electrochemical techniques that detect neurotransmission in high magnetic field environments are limited. Here, we propose an experimental setting enabling simultaneous fast-scan cyclic voltammetry (FSCV) and blood oxygenation level-dependent functional magnetic imaging (BOLD fMRI) to measure both local tissue oxygen and dopamine responses, and global BOLD changes, respectively. By using MR-compatible materials and the proposed data acquisition schemes, FSCV detected physiological analyte concentrations with high temporal resolution and spatial specificity inside of a 9.4 T MRI bore. We found that tissue oxygen and BOLD correlate strongly, and brain regions that encode dopamine amplitude differences can be identified via modeling simultaneously acquired dopamine FSCV and BOLD fMRI time-courses. This technique provides complementary neurochemical and hemodynamic information and expands the scope of studying the influence of local neurotransmitter release over the entire brain.

Leptomeningeal collateral activation indicates severely impaired cerebrovascular reserve capacity in patients with symptomatic unilateral carotid artery occlusion

For patients with symptomatic unilateral internal carotid artery (ICA) occlusion, impaired cerebrovascular reactivity (CVR) indicates increased stroke risk. Here, the role of collateral activation remains a matter of debate, whereas angio-anatomical collateral abundancy does not necessarily imply sufficient compensatory flow provided. We aimed to further elucidate the role of collateral activation in the presence of impaired CVR. From a prospective database, 62 patients with symptomatic unilateral ICA occlusion underwent blood oxygenation-level dependent (BOLD) fMRI CVR imaging and a transcranial Doppler (TCD) investigation for primary and secondary collateral activation. Descriptive statistic and multivariate analysis were used to evaluate the relationship between BOLD-CVR values and collateral activation. Patients with activated secondary collaterals exhibited more impaired BOLD-CVR values of the ipsilateral hemisphere (p = 0.02). Specifically, activation of leptomeningeal collaterals showed severely impaired ipsilateral hemisphere BOLD-CVR values when compared to activation of ophthalmic collaterals (0.05 ± 0.09 vs. 0.12 ± 0.04, p = 0.005). Moreover, the prediction analysis showed leptomeningeal collateral activation as a strong independent predictor for ipsilateral hemispheric BOLD-CVR. In our study, ipsilateral leptomeningeal collateral activation is the sole collateral pathway associated with severely impaired BOLD-CVR in patients with symptomatic unilateral ICA occlusion.

Functional networks in non-human primate spinal cord and the effects of injury

Spontaneous fluctuations of Blood Oxygenation-Level Dependent (BOLD) MRI signal in a resting state have previously been detected and analyzed to describe intrinsic functional networks in the spinal cord of rodents, non-human primates and human subjects. In this study we combined high resolution imaging at high field with data-driven Independent Component Analysis (ICA) to i) delineate fine-scale functional networks within and between segments of the cervical spinal cord of monkeys, and also to ii) characterize the longitudinal effects of a unilateral dorsal column injury on these networks. Seven distinct functional hubs were revealed within each spinal segment, with new hubs detected at bilateral intermediate and gray commissure regions in addition to the bilateral dorsal and ventral horns previously reported. Pair-wise correlations revealed significantly stronger connections between hubs on the dominant hand side. Unilateral dorsal-column injuries disrupted predominantly inter-segmental rather than intra-segmental functional connectivities as revealed by correlation strengths and graph-theory based community structures. The effects of injury on inter-segmental connectivity were evident along the length of the cord both below and above the lesion region. Connectivity strengths recovered over time and there was revival of inter-segmental communities as animals recovered function. BOLD signals of frequency 0.01-0.033 Hz were found to be most affected by injury. The results in this study provide new insights into the intrinsic functional architecture of spinal cord and underscore the potential of functional connectivity measures to characterize changes in networks after an injury and during recovery.

Crossed Cerebellar Diaschisis in Patients with Diffuse Glioma Is Associated with Impaired Supratentorial Cerebrovascular Reactivity and Worse Clinical Outcome

Crossed cerebellar diaschisis (CCD) can be associated with impaired cerebrovascular reactivity (CVR) and poor clinical outcome, but whether this holds true for patients with diffuse glioma is unknown. With blood oxygenation level-dependent (BOLD)-CVR imaging, we determined the presence of CCD in patients with diffuse glioma and investigated its relationship with cerebrovascular reactivity and clinical outcome. For eighteen enrolled subjects (nineteen datasets) with diffuse glioma, CCD was deferred from BOLD-CVR using a predetermined cerebellar asymmetry index (CAI) cutoff value of 6.0%. A FET-PET study was done as a verification of the CCD diagnosis. BOLD-CVR values as well as clinical performance scores (i.e., Karnofsky performance score (KPS), disability rating scale (DRS), and modified Rankin scale (mRS)) by BOLD-CVR scan at 3-month clinical follow-up were assessed and compared for the CCD-positive and CCD-negative group. CCD was present in 26.3% of subjects and strongly associated with impaired BOLD-CVR of the affected (i.e., the hemisphere harboring the glioma) and unaffected supratentorial hemisphere (CCD(+) vs. CCD(-): 0.08 ± 0.11 vs. 0.18 ± 0.04; p = 0.007 and 0.08 ± 0.12 vs. 0.19 ± 0.04; p = 0.007, respectively). This finding was independent of tumor volume (p = 0.48). Furthermore, poorer initial (by scan) clinical performance scores at follow-up were found for the CCD(+) group. The presence of crossed cerebellar diaschisis in patients with diffuse glioma is associated with impaired supratentorial cerebrovascular reactivity and worse clinical outcome.

Fatigue following mild traumatic brain injury relates to visual processing and effort perception in the context of motor performance

INTRODUCTION

Following mild traumatic brain injury (mTBI), a substantial number of patients experience disabling fatigue for months after the initial injury. To date, the underlying mechanisms of fatigue remain unclear. Recently, it was shown that mTBI patients with persistent fatigue do not demonstrate increased performance fatigability (i.e., objective performance decline) during a sustained motor task. However, it is not known whether the neural activation required to sustain this performance is altered after mTBI.

METHODS

Blood oxygen level-dependent (BOLD) fMRI data were acquired from 19 mTBI patients (>3 months post-injury) and 19 control participants during two motor tasks. Force was recorded from the index finger abductors of both hands during submaximal contractions and a 2-minute maximal voluntary contraction (MVC) with the right hand. Voluntary muscle activation (i.e., CNS drive) was indexed during the sustained MVC using peripheral nerve stimulation. Fatigue was quantified using the Fatigue Severity Scale (FSS) and Modified Fatigue Impact Scale (MFIS). Questionnaire, task, and BOLD data were compared across groups, and linear regression was used to evaluate the relationship between BOLD-activity and fatigue in the mTBI group.

RESULTS

The mTBI patients reported significantly higher levels of fatigue (FSS: 5.3 vs. 2.6, p < 0.001). Both mTBI- and control groups demonstrated significant performance fatigability during the sustained MVC, but no significant differences in task performance or BOLD-activity were observed between groups. However, mTBI patients reporting higher FSS scores showed increased BOLD-activity in the bilateral visual cortices (mainly extrastriate) and the left midcingulate gyrus. Furthermore, across all participants mean voluntary muscle activation during the sustained MVC correlated with long lasting post-contraction BOLD-activation in the right insula and midcingulate cortex.

CONCLUSION

The fMRI findings suggest that self-reported fatigue in mTBI may relate to visual processing and effort perception. Long lasting activation associated with high levels of CNS drive might be related to changes in cortical homeostasis in the context of high effort.

Application of an integrated radio-frequency/shim coil technology for signal recovery in fMRI

PURPOSE

Gradient-echo echo-planar imaging (EPI), which is typically used for blood oxygenation level-dependent (BOLD) functional MRI (fMRI), suffers from distortions and signal loss caused by localized B₀ inhomogeneities. Such artifacts cannot be effectively corrected for with the low-order spherical harmonic (SH) shim coils available on most scanners. The integrated parallel reception, excitation, and shimming (iPRES) coil technology allows radiofrequency (RF) and direct currents to flow on each coil element, enabling imaging and localized B₀ shimming with one coil array. iPRES was previously used to correct for distortions in spin-echo EPI and is further developed here to also recover signal loss in gradient-echo EPI.

METHODS

The cost function in the shim optimization, which typically uses a single term representing the B₀ inhomogeneity, was modified to include a second term representing the signal loss, with an adjustable weight to optimize the trade-off between distortion correction and signal recovery. Simulations and experiments were performed to investigate the shimming performance.

RESULTS

Slice-optimized shimming with iPRES and the proposed cost function substantially reduced the signal loss in the inferior frontal and temporal brain regions compared to shimming with iPRES and the original cost function or 2^nd -order SH shimming with either cost function. In breath-holding fMRI experiments, the ΔB₀ and signal loss root-mean-square errors decreased by -34.3% and -56.2%, whereas the EPI signal intensity and number of activated voxels increased by 60.3% and 174.0% in the inferior frontal brain region.

CONCLUSION

iPRES can recover signal loss in gradient-echo EPI, which is expected to improve BOLD fMRI studies in brain regions suffering from signal loss.

Assessment of olfactory information in the human brain using 7-Tesla functional magnetic resonance imaging

Olfaction could prove to be an early marker of neurodegenerative diseases, including Alzheimer's and Parkinson's diseases. To use olfaction for disease diagnosis, elucidating the standard olfactory functions in healthy humans is necessary. However, the olfactory function in the human brain is less frequently assessed because of methodological difficulties associated with olfactory-related cerebral areas. Using ultra-high fields (UHF), functional magnetic resonance imaging (fMRI) with high spatial resolution and sensitivity may allow for the measurement of activation in the cerebral areas. This study aimed to apply 7-Tesla fMRI to assess olfactory function in the human brain by exposing individuals to four different odorants for 8 s. We found that olfactory stimulation mainly activated the piriform and orbitofrontal cortex in addition to the amygdala. Among these regions, univariate fMRI analysis indicated that subjective odor intensity significantly correlated with the averaged fMRI signals in the piriform cortex but not with subjective hedonic tone in any region. In contrast, multivariate fMRI analysis showed that subjective hedonic tone could be discriminated from the fMRI response patterns in the posterior orbitofrontal cortex. Thus, the piriform cortex is mainly associated with subjective odor intensity, whereas the posterior orbitofrontal cortex are involved in the discrimination of the subjective hedonic tone of the odorant. UHF-fMRI may be useful for assessing olfactory function in the human brain.

Different Functional Network Connectivity Patterns in Epilepsy: A Rest-State fMRI Study on Mesial Temporal Lobe Epilepsy and Benign Epilepsy With Centrotemporal Spike

The stark discrepancy in the prognosis of epilepsy is closely related to brain damage features and underlying mechanisms, which have not yet been unraveled. In this study, differences in the epileptic brain functional connectivity states were explored through a network-based connectivity analysis between intractable mesial temporal lobe epilepsy (MTLE) patients and benign epilepsy with centrotemporal spikes (BECT). Resting state fMRI imaging data were collected for 14 MTLE patients, 12 BECT patients and 16 healthy controls (HCs). Independent component analysis (ICA) was performed to identify the cortical functional networks. Subcortical nuclei of interest were extracted from the Harvard-Oxford probability atlas. Network-based statistics were used to detect functional connectivity (FC) alterations across intranetworks and internetworks, including the connectivity between cortical networks and subcortical nuclei. Compared with HCs, MTLE patients showed significant lower activity between the connectivity of cortical networks and subcortical nuclei (especially hippocampus) and lower internetwork FC involving the lateral temporal lobe; BECT patients showed normal cortical-subcortical FC with hyperconnectivity between cortical networks. Together, cortical-subcortical hypoconnectivity in MTLE suggested a low efficiency and collaborative network pattern, and this might be relevant to the final decompensatory state and the intractable prognosis. Conversely, cortical-subcortical region with normal connectivity remained well in global cooperativity, and compensatory internetwork hyperconnectivity caused by widespread cortical abnormal discharge, which might account for the self-limited clinical outcome in BECT. Based on the fMRI functional network study, different brain network patterns might provide a better explanation of mechanisms in different types of epilepsy.

Pneumatic artificial muscle-based stimulator for passive functional magnetic resonance imaging sensorimotor mapping in patients with brain tumours

BACKGROUND

Two concerns with respect to pre-operative task-based motor functional magnetic resonance imaging (fMRI) in patients with brain tumours are inadequate performance due to patients' impaired motor function and head motion artefacts.

NEW METHOD

In the present study we validate the use of a stimulator based on a pneumatic artificial muscle (PAM) for fMRI mapping of the primary sensorimotor (SM1) cortex in twenty patients with rolandic or perirolandic brain tumours. All patients underwent both active and passive motor block-design fMRI paradigms, performing comparable active and passive PAM-induced flexion-extensions of the icontralesional index finger.

RESULTS

PAM-induced movements resulted in a significant BOLD signal increase in contralateral primary motor (M1) and somatosensory (S1) cortices in 18/20 and 19/20 (p<.05 FWE corrected in 16/18 and 18/19) patients, versus 18/20 and 16/20 (p<.05 FWE corrected) during active movements. The two patients in whom the PAM-based stimulator failed to induce any significant BOLD signal change in the contralateral M1 cortex differed from the two in whom active motion was conversely ineffective. At the group level, no significant difference in contrast magnitude was observed within the contralateral SM1 cortex when comparing active with passive movements. During passive movements, head motion was significantly reduced. Comparison with existing method(s) As compared to the several robotic devices for passive motion that were introduced in the past decades, our PAM-based stimulator appears smaller, handier, and easier to use.

CONCLUSION

The use of PAM-based stimulators should be included in routine pre-operative fMRI protocols along with active paradigms in such patients' population.

Antiepileptic Efficacy and Network Connectivity Modulation of Repetitive Transcranial Magnetic Stimulation by Vertex Suppression

A core feature of drug-resistant epilepsy is hyperexcitability in the motor cortex, and low-frequency repetitive transcranial magnetic stimulation (rTMS) is a suitable treatment for seizures. However, the antiepileptic effect causing network reorganization has rarely been studied. Here, we assessed the impact of rTMS on functional network connectivity (FNC) in resting functional networks (RSNs) and their relation to treatment response. Fourteen patients with medically intractable epilepsy received inhibitive rTMS with a figure-of-eight coil over the vertex for 10 days spread across two weeks. We designed a 6-week follow-up phase divided into four time points to investigate FNC and rTMS-induced timing-dependent plasticity, such as seizure frequency and abnormal interictal discharges on electroencephalography (EEG). For psychiatric comorbidities, the Hamilton Depression Scale (HAM-D) and the Hamilton Anxiety Scale (HAM-A) were applied to measure depression and anxiety before and after rTMS. FNC was also compared to that of a cohort of 17 healthy control subjects. The after-effects of rTMS included all subjects that achieved the significant decrease rate of more than 50% in interictal epileptiform discharges and seizure frequency, 12 (14) patients with the reduction rate above 50% compared to the baseline, as well as emotional improvements in depression and anxiety (p < 0.05). In the analysis of RSNs, we found a higher synchronization between the sensorimotor network (SMN) and posterior default-mode network (pDMN) in epileptic patients than in healthy controls. In contrast to pre-rTMS, the results demonstrated a weaker FNC between the anterior DMN (aDMN) and SMN after rTMS, while the FNC between the aDMN and dorsal attention network (DAN) was greater (p < 0.05, FDR corrected). Importantly, the depressive score was anticorrelated with the FNC of the aDMN-SMN (r = −0.67, p = 0.0022), which was markedly different in the good and bad response groups treated with rTMS (p = 0.0115). Based on the vertex suppression by rTMS, it is possible to achieve temporary clinical efficacy by modulating network reorganization in the DMN and SMN for patients with refractory epilepsy.

Hypermetabolism and impaired cerebrovascular reactivity beyond the standard MRI-identified tumor border indicate diffuse glioma extended tissue infiltration

Background

Diffuse gliomas exhibit diffuse infiltrative growth, often beyond the magnetic resonance imaging (MRI)-detectable tumor lesion. Within this lesion, hypermetabolism and impaired cerebrovascular reactivity (CVR) are found, but its exact distribution pattern into the peritumoral environment is unknown. Our aim was to better characterize the extent of diffuse glioma tissue infiltration, beyond the visible lesion (ie, beyond the T1-contrast-enhancing lesion and/or T2/FLAIR-defined tumor border), with metabolic positron emission tomography (PET), and functional MRI CVR (blood oxygenation-level-dependent CVR [BOLD-CVR]) mapping.

Methods

From a prospective glioma database, 18 subjects (19 datasets) with diffuse glioma (n = 2 with anaplastic astrocytoma, n = 10 with anaplastic oligodendroglioma, and n = 7 with glioblastoma) underwent a BOLD-CVR and metabolic PET study between February 2016 and September 2019, 7 of them at primary diagnosis and 12 at tumor recurrence. In addition, 19 matched healthy controls underwent an identical BOLD-CVR study. The tumor lesion was defined using high-resolution anatomical MRI. Volumes of interest starting from the tumor lesion outward up to 30 mm were created for a detailed peritumoral PET and BOLD-CVR tissue analysis. Student’s t test was used for statistical analysis.

Results

Patients with diffuse glioma exhibit impaired BOLD-CVR 12 mm beyond the tumor lesion (P = .02) with normalization of BOLD-CVR values after 24 mm. Metabolic PET shows a difference between the affected and contralateral hemisphere of 6 mm (P = .05) with PET values normalization after 12 mm.

Conclusion

We demonstrate hypermetabolism and impaired CVR beyond the standard MRI-defined tumor border, suggesting active tumor infiltration in the peritumoral environment.

High-resolution fMRI at 7 Tesla: challenges, promises and recent developments for individual-focused fMRI studies

Limited detection power has been a bottleneck for subject-specific functional MRI (fMRI) studies, however the higher signal-to-noise ratio afforded by ultra-high magnetic fields (≥ 7 Tesla) provides levels of sensitivity and resolution needed to study individual subjects. What may be surprising is that higher imaging resolution may provide both higher specificity and sensitivity due to reductions in partial volume effects and reduced physiological noise. However, challenges remain to ensure high data quality and to reduce variability in ultra-high field fMRI. We discuss session-specific biases including those caused by factors related to instrumentation, anatomy, and physiology-which can translate into variability across sessions-and how to minimize these to help ultra-high field fMRI reach its full potential for individual-focused studies.

Blood oxygen level dependent fMRI and perfusion MRI in the sheep brain

The ovine model could be an effective translational model but remains underexplored. Here, Blood Oxygen Level dependent functional MRI during visual stimulation and resting-state perfusion MRI were explored. We aimed at investigating the impact of isoflurane anesthesia during visual stimulation and evaluate resting cerebral blood flow and cerebral blood volume parameters in the lamb and adult sheep brain. BOLD fMRI and perfusion MRI after a bolus of DOTAREM were conducted in 4 lambs and 6 adult ewes at 3 T. A visual stimulation paradigm was delivered during fMRI at increasing isoflurane doses (1-3%). Robust but weak BOLD responses (0.21 ± 0.08%) were found in the lateral geniculate nucleus (LGN) up to 3% isoflurane anaesthesia. No significant differences were found beween BOLD responses in the range 1 to 3% ISO (p > 0.05). However, LGN cluster size decreased and functional localization became less reliable at high ISO doses (2.5-3% ISO). BOLD responses were weaker in adult sheep than in lambs (4.6 ± 1.5 versus 13.6 ± 8.5; p = 0.08). Relative cerebral blood volumes (rCBV) and relative cerebral blood flows (rCBF) were significantly higher (p < 0.0001) in lambs than in adult sheep for both gray and white matter. The impact of volatile anesthesia was explored for the first time on BOLD responses demonstrating increased reliability of functional localization of brain activity at low doses. Perfusion MRI was conducted for the first time in both lambs and adult ewes. Assessment of baseline cerebrovascular values are of interest for future studies of brain diseases allowing an improved interpretation of BOLD responses.

Estimation of laminar BOLD activation profiles using deconvolution with a physiological point spread function

BACKGROUND

The specificity of gradient echo (GE)-BOLD laminar fMRI activation profiles is degraded by intracortical veins that drain blood from lower to upper cortical layers, propagating activation signal in the same direction. This work describes an approach to obtain layer specific profiles by deconvolving the measured profiles with a physiological Point Spread Function (PSF).

NEW METHOD

It is shown that the PSF can be characterised by a TE-dependent peak to tail (p2t) value that is independent of cortical depth and can be estimated by simulation. An experimental estimation of individual p2t values and the sensitivity of the deconvolved profiles to variations in p2t is obtained using laminar data measured with a multi-echo 3D-FLASH sequence. These profiles are echo time dependent, but the underlying neuronal response is the same, allowing a data-based estimation of the PSF.

RESULTS

The deconvolved profiles are highly similar to the gold-standard obtained from extremely high resolution 3D-EPI data, for a range of p2t values of 5-9, which covers both the empirically determined value (6.8) and the value obtained by simulation (6.3). -Comparison with Existing Method(s) Corrected profiles show a flatter shape across the cortex and a high level of similarity with the gold-standard, defined as a subset of profiles that are unaffected by intracortical veins.

CONCLUSIONS

We conclude that deconvolution is a robust approach for removing the effect of signal propagation through intracortical veins. This makes it possible to obtain profiles with high laminar specificity while benefitting from the higher efficiency of GE-BOLD sequences.

Resting-State Cerebello-Cortical Dysfunction in Parkinson's Disease

Purpose: Recently, the cerebellum's role in Parkinson's disease (PD) has been highlighted. Therefore, this study sought to test the hypothesis that functional connectivity (FC) between cerebellar and cortical nodes of the resting-state networks differentiates PD patients from controls by scanning participants at rest using functional magnetic resonance imaging (fMRI) and investigating connectivity of the cerebellar nodes of the resting-state networks.

Materials and Methods: Sixty-two PD participants off medication for at least 12 h and 33 normal controls (NCs) were scanned at rest using blood oxygenation level-dependent fMRI scans. Motor and cognitive functions were assessed with the Movement Disorder Society's Revision of the Unified Parkinson's Disease Rating Scale III and Montreal Cognitive Assessment, respectively. Connectivity was investigated with cerebellar seeds defined by Buckner's 7-network atlas.

Results: PD participants had significant differences in FC when compared to NC participants. Most notably, PD patients had higher FC between cerebellar nodes of the somatomotor network (SMN) and the corresponding cortical nodes. Cognitive functioning was differentially associated with connectivity of the cerebellar SMN and dorsal attention network. Further, cerebellar connectivity of frontoparietal and default mode networks correlated with the severity of motor function.

Conclusion: Our study demonstrates altered cerebello-cortical FC in PD, as well as an association of this FC with PD-related motor and cognitive disruptions, thus providing additional evidence for the cerebellum's role in PD.

FMRI based on transition-band balanced SSFP in comparison with EPI on a high-performance 0.55 T scanner

PURPOSE

Low-field (<1 tesla) MRI scanners allow more widespread diagnostic use for a range of cardiac, musculoskeletal, and neurological applications. However, the feasibility of performing robust fMRI at low field has yet to be fully demonstrated. To address this gap, we investigated task-based fMRI using a highly sensitive transition-band balanced steady-state free precession approach and standard EPI on a 0.55 tesla scanner equipped with modern high-performance gradient coils and a receive array.

METHODS

TR and flip-angle of transition-band steady-state free precession were optimized for 0.55 tesla by simulations. Static shimming was employed to compensate for concomitant field effects. Visual task-based fMRI data were acquired from 8 healthy volunteers. For comparison, standard EPI data were also acquired with TE = T 2 ∗ . Retrospective image-based correction for physiological effects (RETROICOR) was used to quantify physiological noise effects.

RESULTS

Activation was robustly detected using both methods in a 4-min scan time. Transition-band steady-state free precession was found to be sensitive to interference from subtle spatial and temporal (field drift, respiration) variations in the magnetic field, counteracting potential advantages of the reduced magnetic susceptibility effects compared to its utilization at high field. These adverse effects could be partially remedied with static shimming and postprocessing approaches. Standard EPI proved more robust against the sources of interference.

CONCLUSION

BOLD contrast is sufficiently large at 0.55 tesla for robust detection of brain activation and may be employed to broaden the spectrum of applications of low-field MRI. Standard EPI outperforms transition-band steady-state free precession in terms of signal stability.

Systematic Review: Anesthetic Protocols and Management as Confounders in Rodent Blood Oxygen Level Dependent Functional Magnetic Resonance Imaging (BOLD fMRI)-Part B: Effects of Anesthetic Agents, Doses and Timing

Simple Summary

To understand brain function in rats and mice functional magnetic resonance imaging of the brain is used. With this type of “brain scan” regional changes in blood flow and oxygen consumption are measured as an indirect surrogate for activity of brain regions. Animals are often anesthetized for the experiments to prevent stress and blurred images due to movement. However, anesthesia may alter the measurements, as blood flow within the brain is differently affected by different anesthetics, and anesthetics also directly affect brain function. Consequently, results obtained under one anesthetic protocol may not be comparable with those obtained under another, and/or not representative for awake animals and humans. We have systematically searched the existing literature for studies analyzing the effects of different anesthesia methods or studies that compared anesthetized and awake animals. Most studies reported that anesthetic agents, doses and timing had an effect on functional magnetic resonance imaging results. To obtain results which promote our understanding of brain function, it is therefore essential that a standard for anesthetic protocols for functional magnetic resonance is defined and their impact is well characterized.

Abstract

In rodent models the use of functional magnetic resonance imaging (fMRI) under anesthesia is common. The anesthetic protocol might influence fMRI readouts either directly or via changes in physiological parameters. As long as those factors cannot be objectively quantified, the scientific validity of fMRI in rodents is impaired. In the present systematic review, literature analyzing in rats and mice the influence of anesthesia regimes and concurrent physiological functions on blood oxygen level dependent (BOLD) fMRI results was investigated. Studies from four databases that were searched were selected following pre-defined criteria. Two separate articles publish the results; the herewith presented article includes the analyses of 83 studies. Most studies found differences in BOLD fMRI readouts with different anesthesia drugs and dose rates, time points of imaging or when awake status was compared to anesthetized animals. To obtain scientifically valid, reproducible results from rodent fMRI studies, stable levels of anesthesia with agents suitable for the model under investigation as well as known and objectively quantifiable effects on readouts are, thus, mandatory. Further studies should establish dose ranges for standardized anesthetic protocols and determine time windows for imaging during which influence of anesthesia on readout is objectively quantifiable.

More than just summed neuronal activity: how multiple cell types shape the BOLD response

Functional neuroimaging techniques are widely applied to investigations of human cognition and disease. The most commonly used among these is blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. The BOLD signal occurs because neural activity induces an increase in local blood supply to support the increased metabolism that occurs during activity. This supply usually outmatches demand, resulting in an increase in oxygenated blood in an active brain region, and a corresponding decrease in deoxygenated blood, which generates the BOLD signal. Hence, the BOLD response is shaped by an integration of local oxygen use, through metabolism, and supply, in the blood. To understand what information is carried in BOLD signals, we must understand how several cell types in the brain-local excitatory neurons, inhibitory neurons, astrocytes and vascular cells (pericytes, vascular smooth muscle and endothelial cells), and their modulation by ascending projection neurons-contribute to both metabolism and haemodynamic changes. Here, we review the contributions of each cell type to the regulation of cerebral blood flow and metabolism, and discuss situations where a simplified interpretation of the BOLD response as reporting local excitatory activity may misrepresent important biological phenomena, for example with regards to arousal states, ageing and neurological disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Perinidal Angiogenesis Is a Predictor for Neurovascular Uncoupling in the Periphery of Brain Arteriovenous Malformations: A Task-Based and Resting-State fMRI Study

BACKGROUND

Potential neurovascular uncoupling (NVU) related to perinidal angiogenesis (PA) of brain arteriovenous malformations (AVMs) may cause inappropriate presurgical mapping using functional magnetic resonance imaging (fMRI), resulting in overconfident resection and postoperative morbidity.

PURPOSE

To evaluate the potential impact of PA upon fMRI blood oxygen level-dependent signal in the periphery of AVMs.

STUDY TYPE

Prospective.

POPULATION

Twenty-one patients with AVMs located in the primary sensorimotor cortex (SM1) undergoing task-based fMRI (hand motor), and 19 patients with supratentorial AVMs undergoing resting-state fMRI.

FIELD STRENGTH/SEQUENCE

3.0T, echo-planar, time-of-flight, and magnetization-prepared rapid gradient-echo.

ASSESSMENT

The presence of PA was determined by three observers (Y.C., J.W., and X.C.) according to digital subtraction angiography and MR angiography. Interhemispheric asymmetry of fMRI activations contralateral to hand movements was evaluated with the interhemispheric ratio of the average t-value within ipsilesional SM1 to contralesional SM1. Regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) were extracted from ring-shaped perinidal regions and contralateral homologous regions, and the corresponding interhemispheric ratios were calculated. The effect of PA on the interhemispheric asymmetry of motor activations, ReHo, and fALFF was estimated.

STATISTICAL TESTS

Pearson analysis, paired and independent t-test, multiple linear regression, Friedman test, and factorial analysis of variance were used.

RESULTS

Motor activations were significantly reduced in ipsilesional SM1 compared to contralesional SM1 (P < 0.05). The presence of PA was the independent predictor of activation loss in ipsilateral SM1(P < 0.05). Furthermore, perinidal regions exhibited reduced ReHo compared to the homologous regions (P < 0.05). PA was significantly associated with the decline of ReHo and fALFF in perinidal regions (P < 0.05, for both).

DATA CONCLUSION

The presence of PA can predict perinidal NVU that may confound the interpretation of both task-based and resting-state fMRI, highlighting the importance of alternative approaches of brain functional localization in improving treatment of AVMs.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Origin of the Time Lag Phenomenon and the Global Signal in Resting-State fMRI

The global mean signal of resting-state fMRI (rs-fMRI) shows a characteristic spatiotemporal pattern that is closely related to the pattern of vascular perfusion. Although being increasingly adopted in the mapping of the flow of neural activity, the mechanism that gives rise to the BOLD signal time lag remains controversial. In the present study, we compared the time lag of the global mean signal with those of the local network components obtained by applying temporal independent component analysis to the resting-state fMRI data, as well as by using simultaneous wide-field visual stimulation, and demonstrated that the time lag patterns are highly similar across all types of data. These results suggest that the time lag of the rs-fMRI signal reflects the local variance of the hemodynamic responses rather than the arrival or transit time of the stimulus, whether the trigger is neuronal or non-neuronal in origin as long as it is mediated by local hemodynamic responses. Examinations of the internal carotid artery signal further confirmed that the arterial signal is tightly inversely coupled with the global mean signal in accordance with previous studies, presumably reflecting the blood flow or blood pressure changes that are occurring almost simultaneously in the internal carotid artery and the cerebral pial/capillary arteries, within the low-frequency component in human rs-fMRI.

Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity

Functional neuroimaging using MRI relies on measurements of blood oxygen level-dependent (BOLD) signals from which inferences are made about the underlying neuronal activity. This is possible because neuronal activity elicits increases in blood flow via neurovascular coupling, which gives rise to the BOLD signal. Hence, an accurate interpretation of what BOLD signals mean in terms of neural activity depends on a full understanding of the mechanisms that underlie the measured signal, including neurovascular and neurometabolic coupling, the contribution of different cell types to local signalling, and regional differences in these mechanisms. Furthermore, the contributions of systemic functions to cerebral blood flow may vary with ageing, disease and arousal states, with regard to both neuronal and vascular function. In addition, recent developments in non-invasive imaging technology, such as high-field fMRI, and comparative inter-species analysis, allow connections between non-invasive data and mechanistic knowledge gained from invasive cellular-level studies. Considered together, these factors have immense potential to improve BOLD signal interpretation and bring us closer to the ultimate purpose of decoding the mechanisms of human cognition. This theme issue covers a range of recent advances in these topics, providing a multidisciplinary scientific and technical framework for future work in the neurovascular and cognitive sciences. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Systematic Review: Anaesthetic Protocols and Management as Confounders in Rodent Blood Oxygen Level Dependent Functional Magnetic Resonance Imaging (BOLD fMRI)-Part A: Effects of Changes in Physiological Parameters

Background: To understand brain function in health and disease, functional magnetic resonance imaging (fMRI) is widely used in rodent models. Because animals need to be immobilised for image acquisition, fMRI is commonly performed under anaesthesia. The choice of anaesthetic protocols and may affect fMRI readouts, either directly or via changing physiological balance, and thereby threaten the scientific validity of fMRI in rodents. Methods: The present study systematically reviewed the literature investigating the influence of different anaesthesia regimes and changes in physiological parameters as confounders of blood oxygen level dependent (BOLD) fMRI in rats and mice. Four databases were searched, studies selected according to pre-defined criteria, and risk of bias assessed for each study. Results are reported in two separate articles; this part of the review focuses on effects of changes in physiological parameters. Results: A total of 121 publications was included, of which 49 addressed effects of changes in physiological parameters. Risk of bias was high in all included studies. Blood oxygenation [arterial partial pressure of oxygen (paO2)], ventilation [arterial partial pressure of carbon dioxide (paCO2)] and arterial blood pressure affected BOLD fMRI readouts across various experimental paradigms. Conclusions: Blood oxygenation, ventilation and arterial blood pressure should be monitored and maintained at stable physiological levels throughout experiments. Appropriate anaesthetic management and monitoring are crucial to obtain scientifically valid, reproducible results from fMRI studies in rodent models.

Spontaneously emerging patterns in human visual cortex and their functional connectivity are linked to the patterns evoked by visual stimuli

The function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli. We compared in human visual cortex multivertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g., phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g., extrastriate body area for bodies), measured multivertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multivertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, positive and negative, was significantly greater for the preferred stimulus category of an ROI. The relationship between spontaneous and stimulus-evoked multivertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting multivertex patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and fluctuations of the pattern for a category (e.g., body) within its preferred ROIs were largely uncorrelated with fluctuations of the pattern for a disparate category (e.g., scene) within its preferred ROIs. These results support the proposal that spontaneous multivertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.NEW & NOTEWORTHY Spontaneous brain activity was once thought to reflect only noise, but evidence of strong spatiotemporal regularities has motivated a search for functional explanations. Here we show that the spatial pattern of spontaneous activity in human high-level and early visual cortex is related to the spatial patterns evoked by stimuli. Moreover, these patterns partly govern spontaneous spatiotemporal interactions between regions, so-called functional connectivity. These results support the hypothesis that spontaneous activity serves a representational function.

Cerebrovascular Reactivity After Sport Concussion: From Acute Injury to 1 Year After Medical Clearance

Neuroimaging has identified significant disturbances in cerebrovascular reactivity (CVR) in the early symptomatic phase of sport-related concussion. However, less is known about how whole-brain alterations in CVR evolve after concussion and whether they remain present beyond medical clearance to return to play (RTP). In the present study, CVR was evaluated using blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) during a respiratory challenge. Imaging data were collected for 110 university-level athletes, including 39 concussed athletes and 71 athletic controls. The concussed athletes were imaged at the acute phase of injury (1–7 days post-injury), the subacute phase (8-14 days post-injury), medical clearance to RTP, 1 month post-RTP, and 1 year post-RTP. Enhanced negative BOLD response to controlled breathing was seen at acute injury, with attenuation of the effect mainly occurring by 1 year post-RTP. Secondary analyses showed that greater symptom severity and prolonged recovery were associated with enhanced BOLD response in the acute phase of injury, but a more attenuated BOLD response in the subacute phase. This study provides novel information characterizing the CVR response after concussion and shows CVR to be a sensitive technique for evaluating long-term brain recovery.