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.

Reduced brain oxygen metabolism in patients with multiple sclerosis: Evidence from dual-calibrated functional MRI

Cerebral energy deficiency is increasingly recognised as an important feature of multiple sclerosis (MS). Until now, we have lacked non-invasive imaging methods to quantify energy utilisation and mitochondrial function in the human brain. Here, we used novel dual-calibrated functional magnetic resonance imaging (dc-fMRI) to map grey-matter (GM) deoxy-haemoglobin sensitive cerebral blood volume (CBVdHb), cerebral blood flow (CBF), oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen consumption (CMRO2) in patients with MS (PwMS) and age/sex matched controls. By integrating a flow-diffusion model of oxygen transport, we evaluated the effective oxygen diffusivity of the capillary network (DC) and the partial pressure of oxygen at the mitochondria (PmO2). Significant between-group differences were observed as decreased CBF (p = 0.010), CMRO2 (p < 0.001) and DC (p = 0.002), and increased PmO2 (p = 0.043) in patients compared to controls. No significant differences were observed for CBVdHb (p = 0.389), OEF (p = 0.358), or GM volume (p = 0.302). Regional analysis showed widespread reductions in CMRO2 and DC for PwMS. Our findings may be indicative of reduced oxygen demand or utilisation in the MS brain and mitochondrial dysfunction. Our results suggest changes in brain physiology may precede MRI-detectable GM loss and may contribute to disease progression and neurodegeneration.

Lag-Optimized Blood Oxygenation Level Dependent Cerebrovascular Reactivity Estimates Derived From Breathing Task Data Have a Stronger Relationship With Baseline Cerebral Blood Flow

Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve.

Verbal fluency difficulties in aphasia: A combination of lexical and executive control deficits

BACKGROUND

Verbal fluency tasks are routinely used in clinical assessment and research studies of aphasia. People with aphasia produce fewer items in verbal fluency tasks. It remains unclear if their output is limited solely by their lexical difficulties and/or has a basis in their executive control abilities. Recent research has illustrated that detailed characterization of verbal fluency performance using temporal characteristics of words retrieved, clustering and switching, and pause durations, along with separate measures of executive control stands to inform our understanding of the lexical and cognitive underpinnings of verbal fluency in aphasia.

AIMS

To determine the locus of the verbal fluency difficulties in aphasia, we compared semantic and letter fluency trials between people with aphasia and healthy control participants using a wide range of variables to capture the performance between the two groups. The groups were also tested on separate measures of executive control to determine the relationship amongst these tasks and fluency performance.

METHODS & PROCEDURES

Semantic (animal) and letter (F, A, S) fluency data for 60s trials were collected from 14 people with aphasia (PWA) and 24 healthy adult controls (HC). Variables, such as number of correct responses, clustering and switching analyses, were performed along with temporal measures of the retrieved words (response latencies) and pause durations. Participants performed executive control tasks to measure inhibitory control, mental-set shifting and memory span.

OUTCOMES & RESULTS

Compared with HC, PWA produced fewer correct responses, showed greater difficulty with the letter fluency condition, were slower in getting started with the trials, showed slower retrieval times as noted in within- and between-cluster pause durations, and switched less often. Despite these retrieval difficulties, PWA showed a similar decline in the rate of recall to HC, and had similar cluster size. Executive control measures correlated primarily with the letter fluency variables: mostly for PWA and in one instance for HC.

CONCLUSIONS & IMPLICATIONS

Poorer performance for PWA is a combination of difficulties in both the lexical and executive components of the verbal fluency task. Our findings highlight the importance of detailed characterization of fluency performance in deciphering the underlying mechanism of retrieval difficulties in aphasia, and illustrate the importance of using letter fluency trials to tap into executive control processes.

WHAT THIS PAPER ADDS

What is already known on the subject PWA typically show impaired performance in verbal fluency tasks. It is debated whether this impaired performance is a result of their lexical difficulties or executive control difficulties, or a combination of both. This debate continues because previous studies have mostly used semantic fluency condition without including letter fluency condition; used a limited range of variables (e.g., number of correct responses); and not included separate executive control measures to explain the performance pattern in aphasia. This research addresses these outstanding issues to determine the specific contribution of lexical and executive control processes in verbal fluency in aphasia by including: both semantic and letter fluency conditions; a wide range of variables to identify the relative contribution of lexical and executive control mechanisms; and independent measures of executive control. What this paper adds to existing knowledge Using the multidimensional analysis approach for verbal fluency performance from both semantic and letter fluency conditions, this is the first study to systematically demonstrate that PWA had difficulties in both lexical and executive control components of the task. At the individual level, PWA had greater difficulty on the letter fluency condition compared with semantic fluency. We observed significant correlations between the executive control measures and verbal fluency measures primarily for the letter fluency condition. This research makes a significant contribution to our understanding of lexical and executive control aspects in word production in aphasia. What are the potential or actual clinical implications of this work? From a clinical perspective, this research highlights the importance of using a full range of verbal fluency and executive control measures to tap into the lexical as well as executive control abilities of PWA, and also the utility of using letter fluency to tap into the executive control processes in PWA.

A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO₂ pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO₂ pressure: a breath-hold task to induce hypercapnia (CO₂ increase) and a cued deep breathing task to induce hypocapnia (CO₂ decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO₂ by systematically shifting the CO₂ regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO₂ and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.

ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI

Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

Voxelwise optimization of hemodynamic lags to improve regional CVR estimates in breath-hold fMRI

Cerebrovascular Reactivity (CVR), the responsiveness of blood vessels to a vasodilatory stimulus, is an important indicator of cerebrovascular health. Assessing CVR with fMRI, we can measure the change in the Blood Oxygen Level Dependent (BOLD) response induced by a change in CO2 pressure (%BOLD/mmHg). However, there exists a temporal offset between the recorded CO2 pressure and the local BOLD response, due to both measurement and physiological delays. If this offset is not corrected for, voxel-wise CVR values will not be accurate. In this paper, we propose a framework for mapping hemodynamic lag in breath-hold fMRI data. As breath-hold tasks drive task-correlated head motion artifacts in BOLD fMRI data, our framework for lag estimation fits a model that includes polynomial terms and head motion parameters, as well as a shifted variant of the CO2 regressor (±9 s in 0.3 s increments), and the hemodynamic lag at each voxel is the shift producing the maximum total model R2 within physiological constraints. This approach is evaluated in 8 subjects with multi-echo fMRI data, resulting in robust maps of hemodynamic delay that show consistent regional variation across subjects, and improved contrast-to-noise compared to methods where motion regression is ignored or performed earlier in preprocessing.Clinical Relevance- We map hemodynamic lag using breathhold fMRI, providing insight into vascular transit times and improving the regional accuracy of cerebrovascular reactivity measurements.

Dual-calibrated fMRI measurement of absolute cerebral metabolic rate of oxygen consumption and effective oxygen diffusivity

Dual-calibrated fMRI is a multi-parametric technique that allows for the quantification of the resting oxygen extraction fraction (OEF), the absolute rate of cerebral metabolic oxygen consumption (CMRO2), cerebral vascular reactivity (CVR) and baseline perfusion (CBF). It combines measurements of arterial spin labelling (ASL) and blood oxygenation level dependent (BOLD) signal changes during hypercapnic and hyperoxic gas challenges. Here we propose an extension to this methodology that permits the simultaneous quantification of the effective oxygen diffusivity of the capillary network (DC). The effective oxygen diffusivity has the scope to be an informative biomarker and useful adjunct to CMRO2, potentially providing a non-invasive metric of microvascular health, which is known to be disturbed in a range of neurological diseases. We demonstrate the new method in a cohort of healthy volunteers (n = 19) both at rest and during visual stimulation. The effective oxygen diffusivity was found to be highly correlated with CMRO2 during rest and activation, consistent with previous PET observations of a strong correlation between metabolic oxygen demand and effective diffusivity. The increase in effective diffusivity during functional activation was found to be consistent with previously reported increases in capillary blood volume, supporting the notion that measured oxygen diffusivity is sensitive to microvascular physiology.

FoxP1 marks medium spiny neurons from precursors to maturity and is required for their differentiation

Identifying the steps involved in striatal development is important both for understanding the striatum in health and disease, and for generating protocols to differentiate striatal neurons for regenerative medicine. The most prominent neuronal subtype in the adult striatum is the medium spiny projection neuron (MSN), which constitutes more than 85% of all striatal neurons and classically expresses DARPP-32. Through a microarray study of genes expressed in the whole ganglionic eminence (WGE: the developing striatum) in the mouse, we identified the gene encoding the transcription factor Forkhead box protein P1 (FoxP1) as the most highly up-regulated gene, thus providing unbiased evidence for the association of FoxP1 with MSN development. We also describe the expression of FoxP1 in the human fetal brain over equivalent gestational stages. FoxP1 expression persisted through into adulthood in the mouse brain, where it co-localised with all striatal DARPP-32 positive projection neurons and a small population of DARPP-32 negative cells. There was no co-localisation of FoxP1 with any interneuron markers. FoxP1 was detectable in primary fetal striatal cells following dissection, culture, and transplantation into the adult lesioned striatum, demonstrating its utility as an MSN marker for transplantation studies. Furthermore, DARPP-32 expression was absent from FoxP1 knock-out mouse WGE differentiated in vitro, suggesting that FoxP1 is important for the development of DARPP-32-positive MSNs. In summary, we show that FoxP1 labels MSN precursors prior to the expression of DARPP-32 during normal development, and in addition suggest that FoxP1 labels a sub-population of MSNs that are not co-labelled by DARPP-32. We demonstrate the utility of FoxP1 to label MSNs in vitro and following neural transplantation, and show that FoxP1 is required for DARPP-32 positive MSN differentiation in vitro.