Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics.

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a canonical HRF shape at baseline. For individuals with canonical baseline HRFs, substantial gain in the index is overwhelmingly predicted by decreases in HRF amplitude. For individuals with non-canonical baseline HRFs, substantial gain in the index is predicted by congruent changes in both HRF amplitude and dispersion. Our results illustrate that neuroimaging measures can track cognitive indices in healthy states, and that machine learning approaches using novel metrics take important steps toward precision brain health.

Altered linear coupling between stimulus-evoked blood flow and oxygen metabolism in the aging human brain.

Neural-vascular coupling (NVC) is the process by which oxygen and nutrients are delivered to metabolically active neurons by blood vessels. Murine models of NVC disruption have revealed its critical role in healthy neural function. We hypothesized that, in humans, aging exerts detrimental effects upon the integrity of the neural-glial-vascular system that underlies NVC. To test this hypothesis, calibrated functional magnetic resonance imaging (cfMRI) was used to characterize age-related changes in cerebral blood flow (CBF) and oxygen metabolism during visual cortex stimulation. Thirty-three younger and 27 older participants underwent cfMRI scanning during both an attention-controlled visual stimulation task and a hypercapnia paradigm used to calibrate the blood-oxygen-level-dependent signal. Measurement of stimulus-evoked blood flow and oxygen metabolism permitted calculation of the NVC ratio to assess the integrity of neural-vascular communication. Consistent with our hypothesis, we observed monotonic NVC ratio increases with increasing visual stimulation frequency in younger adults but not in older adults. Age-related changes in stimulus-evoked cerebrovascular and neurometabolic signal could not fully explain this disruption; increases in stimulus-evoked neurometabolic activity elicited corresponding increases in stimulus-evoked CBF in younger but not in older adults. These results implicate age-related, demand-dependent failures of the neural-glial-vascular structures that comprise the NVC system.

Resting cerebral oxygen metabolism exhibits archetypal network features.

Standard magnetic resonance imaging approaches offer high-resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low-frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2 ). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual-echo, pseudocontinuous arterial spin labeling, and blood-oxygen-level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain-wide, CMRO2 low-frequency fluctuations were subjected to graph-based and voxel-wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO2 fluctuations exhibited complex, small-world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel-wise CMRO2 connectivity also exhibited spatial patterns consistent with four targeted resting-state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital-visual). These are the first findings to support the use of calibration-derived CMRO2 low-frequency fluctuations for detecting brain-wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration-derived oxygen metabolism signals for examining the intrinsic organization of the human brain.

Age-differential relationships among dopamine D1 binding potential, fusiform BOLD signal, and face-recognition performance.

Facial recognition ability declines in adult aging, but the neural basis for this decline remains unknown. Cortical areas involved in face recognition exhibit lower dopamine (DA) receptor availability and lower blood-oxygen-level-dependent (BOLD) signal during task performance with advancing adult age. We hypothesized that changes in the relationship between these two neural systems are related to age differences in face-recognition ability. To test this hypothesis, we leveraged positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) to measure D1 receptor binding potential (BPND) and BOLD signal during face-recognition performance. Twenty younger and 20 older participants performed a face-recognition task during fMRI scanning. Face recognition accuracy was lower in older than in younger adults, as were D1 BPND and BOLD signal across the brain. Using linear regression, significant relationships between DA and BOLD were found in both age-groups in face-processing regions. Interestingly, although the relationship was positive in younger adults, it was negative in older adults (i.e., as D1 BPND decreased, BOLD signal increased). Ratios of BOLD:D1 BPND were calculated and relationships to face-recognition performance were tested. Multiple linear regression revealed a significant Group × BOLD:D1 BPND Ratio interaction. These results suggest that, in the healthy system, synchrony between neurotransmitter (DA) and hemodynamic (BOLD) systems optimizes the level of BOLD activation evoked for a given DA input (i.e., the gain parameter of the DA input-neural activation function), facilitating task performance. In the aged system, however, desynchronization between these brain systems would reduce the gain parameter of this function, adversely impacting task performance and contributing to reduced face recognition in older adults.

The neurovascular basis of processing speed differences in humans: A model-systems approach using multiple sclerosis.

Behavioral studies investigating fundamental cognitive abilities provide evidence that processing speed accounts for large proportions of performance variability between individuals. Processing speed decline is a hallmark feature of the cognitive disruption observed in healthy aging and in demyelinating diseases such as multiple sclerosis (MS), neuromyelitis optica, and Wilson's disease. Despite the wealth of evidence suggesting a central role for processing speed in cognitive decline, the neural mechanisms of this fundamental ability remain unknown. Intact neurovascular coupling, acute localized blood flow increases following neural activity, is essential for optimal neural function. We hypothesized that efficient coupling forms the neural basis of processing speed. Because MS features neural-glial-vascular system disruption, we used it as a model to test this hypothesis. To assess the integrity of the coupling system, we measured blood-oxygen-level-dependent (BOLD) signal in healthy controls (HCs) and MS patients using a 3T MRI scanner while they viewed radial checkerboards that flickered periodically at 8 â€‹Hz. To assess processing speed and cognitive function, we administered a battery of neuropsychological tests. While MS patients exhibited reduced ΔBOLD with reductions in processing speed, no such relationships were observed in HCs. To further investigate the mechanisms that underlie ΔBOLD-processing speed relationships, we assessed the physiologic components that constitute ΔBOLD signal (i.e., cerebral blood flow, ΔCBF; cerebral metabolic rate of oxygen, ΔCMRO2; neurovascular coupling ratio) in speed-preserved and -impaired MS patients. While ΔCBF and ΔCMRO2 showed no group-differences, the neurovascular coupling ratio was significantly reduced in speed-impaired MS patients compared to speed-preserved MS patients. Together, these results suggest that neurovascular uncoupling might underlie cognitive slowing in MS and might be the central pathogenic mechanism governing processing speed decline.

Reduced arterial compliance along the cerebrovascular tree predicts cognitive slowing in multiple sclerosis: Evidence for a neurovascular uncoupling hypothesis.

BACKGROUND: Cognitive slowing occurs in ~70% of multiple sclerosis (MS) patients. The pathophysiology of this slowing is unknown. Neurovascular coupling, acute localized blood flow increases following neural activity, is essential for efficient cognition. Loss of vascular compliance along the cerebrovascular tree would result in suboptimal vasodilation, neurovascular uncoupling, and cognitive slowing. OBJECTIVE: To assess vascular compliance along the cerebrovascular tree and its relationship to MS-related cognition. METHODS: We tested vascular compliance along the cerebrovascular tree by dividing cerebral cortex into nested layers. MS patients and healthy controls were scanned using a dual-echo functional magnetic resonance imaging (fMRI) sequence while they periodically inhaled room air and hypercapnic gas mixture. Cerebrovascular reactivity was calculated from both cerebral blood flow (arterial) and blood-oxygen-level-dependent signal (venous) increases per unit increase in end-tidal CO2. RESULTS: Arterial cerebrovascular reactivity changes along the cerebrovascular tree were reduced in cognitively slow MS compared to cognitively normal MS and healthy controls. These changes were fit to exponential functions, the decay constant (arterial compliance index; ACI) of which was associated with individual subjects' reaction time and predicted reaction time after controlling for disease processes. CONCLUSION: Such associations suggest prospects for utility of ACI in predicting future cognitive disturbances, monitoring cognitive deficiencies and therapeutic responses, and implicates neurovascular uncoupling as a mechanism of cognitive slowing in MS.

BOLD hemodynamic response function changes significantly with healthy aging.

Functional magnetic resonance imaging (fMRI) has been used to infer age-differences in neural activity from the hemodynamic response function (HRF) that characterizes the blood-oxygen-level-dependent (BOLD) signal over time. BOLD literature in healthy aging lacks consensus in age-related HRF changes, the nature of those changes, and their implications for measurement of age differences in brain function. Between-study discrepancies could be due to small sample sizes, analysis techniques, and/or physiologic mechanisms. We hypothesize that, with large sample sizes and minimal analysis assumptions, age-related changes in HRF parameters could reflect alterations in one or more components of the neural-vascular coupling system. To assess HRF changes in healthy aging, we analyzed the large population-derived dataset from the Cambridge Center for Aging and Neuroscience (CamCAN) study (Shafto et al., 2014). During scanning, 74 younger (18-30 years of age) and 173 older participants (54-74 years of age) viewed two checkerboards to the left and right of a central fixation point, simultaneously heard a binaural tone, and responded via right index finger button-press. To assess differences in the shape of the HRF between younger and older groups, HRFs were estimated using FMRIB's Linear Optimal Basis Sets (FLOBS) to minimize a priori shape assumptions. Group mean HRFs were different between younger and older groups in auditory, visual, and motor cortices. Specifically, we observed increased time-to-peak and decreased peak amplitude in older compared to younger adults in auditory, visual, and motor cortices. Changes in the shape and timing of the HRF in healthy aging, in the absence of performance differences, support our hypothesis of age-related changes in the neural-vascular coupling system beyond neural activity alone. More precise interpretations of HRF age-differences can be formulated once these physiologic factors are disentangled and measured separately.

Preserved canonicality of the BOLD hemodynamic response reflects healthy cognition: Insights into the healthy brain through the window of Multiple Sclerosis.

The hemodynamic response function (HRF), a model of brain blood-flow changes in response to neural activity, reflects communication between neurons and the vasculature that supplies these neurons in part by means of glial cell intermediaries (e.g., astrocytes). Intact neural-vascular communication might play a central role in optimal cognitive performance. This hypothesis can be tested by comparing healthy individuals to those with known white-matter damage and impaired performance, as seen in Multiple Sclerosis (MS). Glial cell intermediaries facilitate the ability of neurons to adequately convey metabolic needs to cerebral vasculature for sufficient oxygen and nutrient perfusion. In this study, we isolated measurements of the HRF that could quantify the extent to which white-matter affects neural-vascular coupling and cognitive performance. HRFs were modeled from multiple brain regions during multiple cognitive tasks using piecewise cubic spline functions, an approach that minimized assumptions regarding HRF shape that may not be valid for diseased populations, and were characterized using two shape metrics (peak amplitude and time-to-peak). Peak amplitude was reduced, and time-to-peak was longer, in MS patients relative to healthy controls. Faster time-to-peak was predicted by faster reaction time, suggesting an important role for vasodilatory speed in the physiology underlying processing speed. These results support the hypothesis that intact neural-glial-vascular communication underlies optimal neural and cognitive functioning.

Re-examination of "release-from-PI" phenomena: recall accuracy does not recover after a semantic switch.

Recall accuracy decreases over successive memory trials using similar memoranda. This effect reflects proactive interference (PI) - the tendency for previously studied information to reduce recall of new information. However, recall improves if memoranda for a subsequent trial are semantically dissimilar from the previous trials. This improvement is thought to reflect a release from PI. We tested whether PI is reduced or released from the semantic category for which it had been induced by employing paradigms which featured inducement, semantic switch, and then return-to-original category epochs. Two experiments confirmed that PI was not released after various semantic switch trials (effects from d = -0.93 to -1.6). Combined analyses from both studies demonstrated that the number of intervening new category trials did not reduce or release PI. In fact, in all conditions recall accuracy decreased, demonstrating that PI is maintained and can increase after the new category trials. The release-from-PI account cannot accommodate these broader dynamics of PI. This account is also incongruent with evidence and theory from cognitive psychology, linguistics, and neuroscience. We propose a reintroduction-of-PI account which explains these broader PI dynamics and is consistent with the wider psychological and neurosciences.

Calibrated imaging reveals altered grey matter metabolism related to white matter microstructure and symptom severity in multiple sclerosis.

Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically-nonspecific neuroimaging indices (i.e., blood-oxygen-level dependent signal [BOLD]). Here, we used calibrated functional magnetic resonance imaging and diffusion tensor imaging to examine the extent to which specific, evoked grey matter physiological processes were associated with white matter diffusion in MS. Evoked changes in BOLD, cerebral blood flow (CBF), and oxygen metabolism (CMRO2 ) were measured in visual cortex. Individual differences in the diffusion tensor measure, radial diffusivity, within occipital tracts were strongly associated with MS patients' BOLD and CMRO2 . However, these relationships were in opposite directions, complicating the interpretation of the relationship between BOLD and white matter microstructural damage in MS. CMRO2 was strongly associated with individual differences in patients' fatigue and neurological disability, suggesting that alterations to evoked oxygen metabolic processes may be taken as a marker for primary symptoms of MS. This work demonstrates the first application of calibrated and diffusion imaging together and details the first application of calibrated functional MRI in a neurological population. Results lend support for neuroenergetic hypotheses of MS pathophysiology and provide an initial demonstration of the utility of evoked oxygen metabolism signals for neurology research. Hum Brain Mapp 38:5375-5390, 2017. © 2017 Wiley Periodicals, Inc.

Ear Advantage for Musical Location and Relative Pitch: Effects of Musical Training and Attention.

Trained musicians have been found to exhibit a right-ear advantage for high tones and a left-ear advantage for low tones. We investigated whether this right/high, left/low pattern of musical processing advantage exists in listeners who had varying levels of musical experience, and whether such a pattern might be modulated by attentional strategy. A dichotic listening paradigm was used in which different melodic sequences were presented to each ear, and listeners attended to (a) the left ear or the right ear or (b) the higher pitched tones or the lower pitched tones. Listeners judged whether tone-to-tone transitions within each melodic sequence moved upward or downward in pitch. Only musically experienced listeners could adequately judge the direction of successive pitch transitions when attending to a specific ear; however, all listeners could judge the direction of successive pitch transitions within a high-tone stream or a low-tone stream. Overall, listeners exhibited greater accuracy when attending to relatively higher pitches, but there was no evidence to support a right/high, left/low bias. Results were consistent with effects of attentional strategy rather than an ear advantage for high or low tones. Implications for a potential performer/audience paradox in listening space are considered.

Dopamine D1 Binding Potential Predicts Fusiform BOLD Activity during Face-Recognition Performance.

The importance of face memory in humans and primates is well established, but little is known about the neurotransmitter systems involved in face recognition. We tested the hypothesis that face recognition is linked to dopamine (DA) activity in fusiform gyrus (FFG). DA availability was assessed by measuring D1 binding potential (BP) during rest using PET. We further assessed blood-oxygen-level-dependent (BOLD) signal change while subjects performed a face-recognition task during fMRI scanning. There was a strong association between D1 BP and BOLD activity in FFG, whereas D1 BP in striatal and other extrastriatal regions were unrelated to neural activity in FFG. These results suggest that D1 BP locally modulates FFG function during face recognition. Observed relationships among D1 BP, BOLD activity, and face-recognition performance further suggest that D1 receptors place constraints on the responsiveness of FFG neurons. SIGNIFICANCE STATEMENT: The importance of face memory in humans and primates is well established, but little is known about the neurotransmitter systems involved in face recognition. Our work shows a role for a specific neurotransmitter system in face memory.

Depressive thoughts limit working memory capacity in dysphoria.

Dysphoria is associated with persistence of attention on mood-congruent information. Longer time attending to mood-congruent information for dysphoric individuals (DIs) detracts from goal-relevant information processing and should reduce working memory (WM) capacity. Study 1 showed that DIs and non-DIs have similar WM capacities. Study 2 embedded depressive information into a WM task. Compared to non-DIs, DIs showed significantly reduced WM capacity for goal-relevant information in this task. Study 3 replicated results from Studies 1 and 2, and further showed that DIs had a significantly greater association between processing speed and recall on the depressively modified WM task compared to non-DIs. The presence of inter-task depressive information leads to DI-related decreased WM capacity. Results suggest dysphoria-related WM capacity deficits when depressive thoughts are present. WM capacity deficits in the presence of depressive thoughts are a plausible mechanism to explain day-to-day memory and concentration difficulties associated with depressed mood.

Neural mechanisms of age-related slowing: the ΔCBF/ΔCMRO2 ratio mediates age-differences in BOLD signal and human performance.

The precise mechanisms that give rise to the blood-oxygen-level-dependent (BOLD) activation differences that accompany age-related cognitive slowing remain fundamentally unknown. We sought to isolate the origin of age-related BOLD changes by comparing blood-flow and oxygen-metabolic constituents of the BOLD response using dual-echo arterial spin labeling during visual stimulation and CO2 ingestion. We hypothesized, and our results confirmed, that age-related changes in the ratio of fractional cerebral blood flow to fractional cerebral metabolic rate of oxygen consumption (ΔCBF/ΔCMRO2) lead to the BOLD changes that are observed in older adults. ΔCBF/ΔCMRO2 was also significantly related to performance, suggesting that age-related cognitive slowing results from neural cell assemblies that operate less efficiently, requiring greater oxygen metabolism that is not matched by blood-flow changes relative to younger adults. Age-related changes in ΔCBF/ΔCMRO2 are sufficient to explain variations in BOLD responding and performance cited throughout the literature, assuming no bias based on physiological baseline CMRO2.

Calibrating BOLD fMRI activations with neurovascular and anatomical constraints.

Functional magnetic resonance imaging signals, in addition to reflecting neuronal response, also contain physiological variances. These factors may introduce variability into blood oxygen level-dependent (BOLD) activation results, particularly in different population groups. In this study, we hypothesized that the amplitude as well as the spatial extent of BOLD activation could be improved after minimizing the variance caused by the neurovascular and anatomical factors. Subjects were scanned while they performed finger tapping and digit-symbol substitution tasks (DSSTs). Partial volume and neurovascular effects were estimated on a voxelwise basis using subjects' own gray matter volume (GMV), breath holding (BH), and amplitude of low-frequency fluctuation (ALFF). The results showed that all individual's GMV, BH, and ALFF could significantly predict motor and DSST activations in a voxelwise manner. Whole-brain analyses were conducted to regress out the anatomical and neurovascular information. Differential maps (obtained using t-test) indicated that the adjustment tended to suppress activation in regions that were near vessels such as midline cingulate gyrus, bilateral anterior insula, and posterior cerebellum. These results suggest that voxelwise adjustment using GMV and neurovascular parameters can minimize structural and physiological variances among individuals and be used for quantitative comparisons.

Isolating age-group differences in working memory load-related neural activity: assessing the contribution of working memory capacity using a partial-trial fMRI method.

Previous studies examining age-group differences in working memory load-related neural activity have yielded mixed results. When present, age-group differences in working memory capacity are frequently proposed to underlie these neural effects. However, direct relationships between working memory capacity and working memory load-related activity have only been observed in younger adults. These relationships remain untested in healthy aging. Therefore, the present study examined patterns of working memory load-related activity in 22 younger and 20 older adults and assessed the contribution of working memory capacity to these load-related effects. Participants performed a partial-trial delayed response item recognition task during functional magnetic resonance imaging. In this task, participants encoded either 2 or 6 letters, maintained them during a delay, and then indicated whether a probe was present in the memory set. Behavioral results revealed faster and more accurate responses to load 2 versus 6, with age-group differences in this load condition effect for the accuracy measure. Neuroimaging results revealed one region (medial superior frontal gyrus) that showed age-group differences in load-related activity during the retrieval period, with less (greater) neural activity for the low versus high load condition in younger (older) adults. Furthermore, for older adults, load-related activity did not vary as a function of working memory capacity. Thus, working memory-related activity varies with healthy aging, but these patterns are not due solely to working memory capacity. Neurocognitive aging theories that feature capacity will need to account for these results.

Toward discovery science of human brain function.

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.

Interaction Between Memory Load and Experimental Design on Brain Connectivity and Network Topology.

The conventional approach to investigating functional connectivity in the block-designed study usually concatenates task blocks or employs residuals of task activation. While providing many insights into brain functions, the block design adds more manipulation in functional network analysis that may reduce the purity of the blood oxygenation level-dependent signal. Recent studies utilized one single long run for task trials of the same condition, the so-called continuous design, to investigate functional connectivity based on task functional magnetic resonance imaging. Continuous brain activities associated with the single-task condition can be directly utilized for task-related functional connectivity assessment, which has been examined for working memory, sensory, motor, and semantic task experiments in previous research. But it remains unclear how the block and continuous design influence the assessment of task-related functional connectivity networks. This study aimed to disentangle the separable effects of block/continuous design and working memory load on task-related functional connectivity networks, by using repeated-measures analysis of variance. Across 50 young healthy adults, behavioral results of accuracy and reaction time showed a significant main effect of design as well as interaction between design and load. Imaging results revealed that the cingulo-opercular, fronto-parietal, and default model networks were associated with not only task activation, but significant main effects of design and load as well as their interaction on intra- and inter-network functional connectivity and global network topology. Moreover, a significant behavior-brain association was identified for the continuous design. This work has extended the evidence that continuous design can be used to study task-related functional connectivity and subtle brain-behavioral relationships.

Investigating the link between regional oxygen metabolism and cognitive speed in multiple sclerosis: Implications for fatigue.

BACKGROUND: Most multiple sclerosis (MS) patients experience fatigue and cognitive decline but the underlying mechanisms remain unknown. Previous work has shown whole brain resting cerebral metabolic rate of oxygen (CMRO2) is associated with the extent of these symptoms. However, it is not known if the association between global CMRO2 and MS-related cognitive speed and fatigue can be localized to specific brain regions. Based upon previous research suggesting prefrontal involvement in MS-related changes in cognitive speed and fatigue, we hypothesized that oxygen metabolic changes within prefrontal cortex (PFC) might form the pathophysiologic basis of cognitive performance and fatigue in MS patients. OBJECTIVE: Investigate whether PFC ΔCMRO2 is associated with cognitive speed and fatigue in MS. METHODS: MS and healthy control (HC) participants were scanned using a dual--echo fMRI sequence and underwent a hypercapnia calibration experiment that permitted estimation of ΔCMRO2 while performing a scanner version of symbol-digit modalities task, a measure of information processing speed and utilized in the clinic as a reliable sentinel biomarker for global cognitive impairment in MS. Participants then completed the Modified Fatigue Impact Scale (MFIS) to measure fatigue. RESULTS: MS patients exhibited significant reductions in cognitive performance relative to HCs (p < 0.04). Prefrontal ΔCMRO2 explained significant variability (ΔR2 = 0.11) in cognitive speed, over and above disease and demographic variables, for the MS group only. Prefrontal ΔCMRO2 was not associated with fatigue across groups. ΔCMRO2 in visual and motor areas were not associated with cognitive performance or fatigue for either group. CONCLUSION: Prefrontal oxygen metabolism may be a sensitive measure of MS-related cognitive decline.

Effect of surgical mask on fMRI signals during task and rest.

Wearing a face mask has become essential to contain the spread of COVID-19 and has become mandatory when collecting fMRI data at most research institutions. Here, we investigate the effects of wearing a surgical mask on fMRI data in n = 37 healthy participants. Activations during finger tapping, emotional face matching, working memory tasks, and rest were examined. Preliminary fMRI analyses show that despite the different mask states, resting-state signals and task activations were relatively similar. Resting-state functional connectivity showed negligible attenuation patterns in mask-on compared with mask-off. Task-based ROI analysis also demonstrated no significant difference between the two mask states under each contrast investigated. Notwithstanding the overall insignificant effects, these results indicate that wearing a face mask during fMRI has little to no significant effect on resting-state and task activations.