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.

The neural-vascular basis of age-related processing speed decline.

Most studies examining neurocognitive aging are based on the blood-oxygen level-dependent signal obtained during functional magnetic resonance imaging (fMRI). The physiological basis of this signal is neural-vascular coupling, the process by which neurons signal cerebrovasculature to dilate in response to an increase in active neural metabolism due to stimulation. These fMRI studies of aging rely on the hemodynamic equivalence assumption that this process is not disrupted by physiologic deterioration associated with aging. Studies of neural-vascular coupling challenge this assumption and show that neural-vascular coupling is closely related to cognition. In this review, we put forward a theory of processing speed decline in aging and how it is related to age-related neural-vascular coupling changes based on the results of studies elucidating the relationships between cognition, cerebrovascular dynamics, and aging.

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.

Altered task-induced cerebral blood flow and oxygen metabolism underlies motor impairment in multiple sclerosis.

The neural mechanisms underlying motor impairment in multiple sclerosis (MS) remain unknown. Motor cortex dysfunction is implicated in blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies, but the role of neural-vascular coupling underlying BOLD changes remains unknown. We sought to independently measure the physiologic factors (i.e., cerebral blood flow (ΔCBF), cerebral metabolic rate of oxygen (ΔCMRO2), and flow-metabolism coupling (ΔCBF/ΔCMRO2), utilizing dual-echo calibrated fMRI (cfMRI) during a bilateral finger-tapping task. We utilized cfMRI to measure physiologic responses in 17 healthy volunteers and 32 MS patients (MSP) with and without motor impairment during a thumb-button-press task in thumb-related (task-central) and surrounding primary motor cortex (task-surround) regions of interest (ROIs). We observed significant ΔCBF and ΔCMRO2 increases in all MSP compared to healthy volunteers in the task-central ROI and increased flow-metabolism coupling (ΔCBF/ΔCMRO2) in the MSP without motor impairment. In the task-surround ROI, we observed decreases in ΔCBF and ΔCMRO2 in MSP with motor impairment. Additionally, ΔCBF and ΔCMRO2 responses in the task-surround ROI were associated with motor function and white matter damage in MSP. These results suggest an important role for task-surround recruitment in the primary motor cortex to maintain motor dexterity and its dependence on intact white matter microstructure and neural-vascular coupling.

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.

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.

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.

A neural-vascular complex of age-related changes in the human brain: Anatomy, physiology, and implications for neurocognitive aging.

Theories of neurocognitive aging rely heavily on functional magnetic resonance imaging (fMRI) to test hypotheses regarding the brain basis of age-differences in cognition. This technique is based on the blood-oxygen level dependent signal (BOLD) that arises from the coordinated neural-vascular coupling that leads to increased blood flow following an increase in neural activity. Here we review the literature and current controversies regarding the mechanisms by which blood flow and neural activity are coupled, and how they change in the aging process. This literature suggests that neural-vascular coupling is a complex of processes, involving dynamic signaling between neurons, glia, and blood vessels. Nearly every component of this process is affected in aging leading to changes in BOLD and pervasive age-related cognitive changes.

Three-Dimensional Lesion Phenotyping and Physiologic Characterization Inform Remyelination Ability in Multiple Sclerosis.

BACKGROUND AND PURPOSE: Multiple sclerosis (MS) clinical management is based upon lesion characterization from 2-dimensional (2D) magnetic resonance imaging (MRI) views. Such views fail to convey the lesion-phenotype (ie, shape and surface texture) complexity, underlying metabolic alterations, and remyelination potential. We utilized a 3-dimensional (3D) lesion phenotyping approach coupled with imaging to study physiologic profiles within and around MS lesions and their impacts on lesion phenotypes. METHODS: Lesions were identified in 3T T2 -FLAIR images and segmented using geodesic active contouring. A calibrated fMRI sequence permitted measurement of cerebral blood flow (CBF), blood-oxygen-level-dependent signal (BOLD), and cerebral metabolic rate of oxygen (CMRO2 ). These metrics were measured within lesions and surrounding tissue in concentric layers exact to the 3D-lesion shape. BOLD slope was calculated as BOLD changes from a lesion to its surrounding perimeters. White matter integrity was measured using diffusion kurtosis imaging. Associations between these metrics and 3D-lesion phenotypes were studied. RESULTS: One hundred nine lesions from 23 MS patients were analyzed. We identified a noninvasive biomarker, BOLD slope, to metabolically characterize lesions. Positive BOLD slope lesions were metabolically active with higher CMRO2 and CBF compared to negative BOLD slope or inactive lesions. Metabolically active lesions with more intact white matter integrity had more symmetrical shapes and more complex surface textures compared to inactive lesions with less intact white matter integrity. CONCLUSION: The association of lesion phenotypes with their metabolic signatures suggests the prospect for translation of such data to clinical management by providing information related to metabolic activity, lesion age, and risk for disease reactivation and self-repair. Our findings also provide a platform for disease surveillance and outcome quantification involving myelin repair therapeutics.

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.

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.

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.

Evaluation of Visual-Evoked Cerebral Metabolic Rate of Oxygen as a Diagnostic Marker in Multiple Sclerosis.

A multiple sclerosis (MS) diagnosis often relies upon clinical presentation and qualitative analysis of standard, magnetic resonance brain images. However, the accuracy of MS diagnoses can be improved by utilizing advanced brain imaging methods. We assessed the accuracy of a new neuroimaging marker, visual-evoked cerebral metabolic rate of oxygen (veCMRO2), in classifying MS patients and closely age- and sex-matched healthy control (HC) participants. MS patients and HCs underwent calibrated functional magnetic resonance imaging (cfMRI) during a visual stimulation task, diffusion tensor imaging, T1- and T2-weighted imaging, neuropsychological testing, and completed self-report questionnaires. Using resampling techniques to avoid bias and increase the generalizability of the results, we assessed the accuracy of veCMRO2 in classifying MS patients and HCs. veCMRO2 classification accuracy was also examined in the context of other evoked visuofunctional measures, white matter microstructural integrity, lesion-based measures from T2-weighted imaging, atrophy measures from T1-weighted imaging, neuropsychological tests, and self-report assays of clinical symptomology. veCMRO2 was significant and within the top 16% of measures (43 total) in classifying MS status using both within-sample (82% accuracy) and out-of-sample (77% accuracy) observations. High accuracy of veCMRO2 in classifying MS demonstrated an encouraging first step toward establishing veCMRO2 as a neurodiagnostic marker of MS.

Cognitive Slowing in Gulf War Illness Predicts Executive Network Hyperconnectivity: Study in a Population-Representative Sample.

Cognitive slowing is a prevalent symptom observed in Gulf War Illness (GWI). The present study assessed the extent to which functional connectivity between dorsolateral prefrontal cortex (DLPFC) and other task-relevant brain regions was predictive of GWI-related cognitive slowing. GWI patients (n = 54) and healthy veteran controls (n = 29) were assessed on performance of a processing speed task (the Digit Symbol Substitution Task; DSST) while undergoing functional magnetic resonance imaging (fMRI). GWI patients were slower on the DSST relative to controls. Bilateral DLPFC connectivity with task-relevant nodes was altered in GWI patients compared to healthy controls during DSST performance. Moreover, hyperconnectivity in these networks predicted GWI-related increases in reaction time on the DSST, whereas hypoconnectivity did not. These results suggest that GWI-related cognitive slowing reflects reduced efficiency in cortical networks.

Asynchrony in executive networks predicts cognitive slowing in multiple sclerosis.

OBJECTIVE: Cognitive slowing is a core neuropsychological symptom of Multiple Sclerosis (MS). We aimed to assess the extent to which cognitive slowing in MS was predicted by changes in dorsolateral prefrontal networks. METHOD: We assessed patients with relapsing-remitting MS and healthy controls (HCs) on measures of processing speed. Participants underwent a functional MRI while performing a processing speed task to allow assessment of task-based connectivity. RESULTS: Patients were slower than HCs on the processing speed tasks. Patients showed attenuated connectivity between right and left dorsolateral prefrontal cortex (DLPFC) and task-relevant brain regions compared to HCs during processing speed task performance. Patients' connectivity with DLPFC in these group-disparate networks accounted for significant variability in their performance on processing speed measures administered both in and out of the imaging environment. Specifically, patients who had stronger functional connections with DLPFC in group-disparate networks performed faster than patients with weaker connections with DLPFC in group-disparate networks. CONCLUSION: Results suggest that MS-related cognitive slowing can be accounted for by systemic alterations in executive functional networks.