Biology subjects

Metcalf, N.

Publications and source records attributed to Metcalf, N..

6 recordsLinked to original sources

bioRxiv2025

Precision measurements of brain oxygen utilization with positron emission tomography

Oxygen utilization is important for studies of brain metabolism, alongside other measurements such as for glucose metabolism. Oxygen and other measurements with [15O] tracers and PET, however, are significantly more challenging than measurements of [18F]fluorodeoxyglucose, the standard for probing tissue glucose metabolism in vivo, in part due to the much shorter radioactive half-life of [15O]. This work examines details of precision measurement of [15O] tracers and their kinetics. Investigations of arterial input functions (AIFs) and image-derived input functions (IDIFs) have figured prominently for PET, but [15O] tracers are rarely studied given the small numbers of PET facilities equipped to work with these tracers, particularly in their inhaled form. Estimates of IDIFs and AIFs for [15O] tracers have demonstrably distinct characteristics arising from instrumentation as well as circulatory physiology. To reconcile IDIFs and AIFs, we developed a generalizable model for bolus tracer transport, corrected for known effects of instrumentation for measuring IDIFs and AIFs, and found intravascular [15O]CO to be especially suited for constructing a robust recovery coefficient for IDIFs compared against AIFs. Within a Bayesian framework for posterior estimation and estimating data evidence, IDIFs provide parameter estimates compatible with AIFs in the setting of biological variability. IDIFs also provide data evidence that exceeds that of results from AIFs. These suggest that scalar recovery coefficients may be adequate to estimate partial volume effects, and that the circulatory consistency of internal carotid IDIFs with brain tissue perfusion provides greater precision than what can be estimated using radial artery AIFs, which exhibit greater variability of recirculation wave forms.

bioengineering↗

bioRxiv2024

Aging and the Spectral Properties of Brain Hemodynamics

Cerebral glucose metabolism (CMRGlc) systematically decreases with advancing age. We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task-free state. We analyzed lifespan resting-state fMRI data acquired in 455 healthy adults (ages 18-87 years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25-45 years, 65-85 years). We characterized the spectral properties of the fMRI data in terms of the relative predominance of slow vs. fast activity using the spectral slope (SS) measure. We found that the relative proportion of fast activity increases with advancing age (SS flattening) across most cortical regions. The regional distribution of spectral slope was topographically correlated with CMRGlc in young adults. Notably, whereas most older adults maintained a youthful pattern of SS topography, a distinct subset of older adults significantly diverged from the youthful pattern. This subset of older adults also diverged from the youthful pattern of CMRGlc metabolism. This divergent pattern was associated with T2-weighted signal changes in frontal lobe white matter, an independent marker of small vessel disease. These findings suggest that BOLD signal spectral slope flattening may represent a biomarker of age-associated neurometabolic pathology. Significance StatementAging is associated with a decline in cerebral glucose metabolism (CMRGlc). Here, we identified correlates of CMRGlc in the spectral properties of resting-state fMRI data using spectral slope (SS), which quantifies the relative predominance of slow vs. fast activity. We found that SS flattening with advancing age is most prominent in regions characterized by high CMRGlc in youth. A subset of older adults who diverged from the youthful pattern of SS topography also exhibited evidence of frontal lobe white matter pathology. These findings suggest that the spectral properties of rs-fMRI data provide mechanistic insights into age-related neuropathology. In particular, spectral slope measures may serve as early indicators of age-related neurometabolic decline and potentially identify individuals in whom intervention is indicated.

neuroscience↗

bioRxiv2024

Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients

Computational whole-brain models describe the resting activity of each brain region based on a local model, inter-regional functional interactions, and a structural connectome that specifies the strength of inter-regional connections. Strokes damage the healthy structural connectome that forms the backbone of these models and produce large alterations in inter-regional functional interactions. These interactions are typically measured by correlating the timeseries of activity between two brain regions, so-called resting functional connectivity. We show that adding information about the structural disconnections produced by a patients lesion to a whole-brain model previously trained on structural and functional data from a large cohort of healthy subjects predicts the resting functional connectivity of the patient about as well as fitting the model directly to the patients data. Furthermore, the model dynamics reproduce functional connectivity-based measures that are typically abnormal in stroke patients as well as measures that specifically isolate these abnormalities. Therefore, although whole-brain models typically involve a large number of free parameters, the results show that even after fixing those parameters, the model reproduces results from a population very different than the population on which the model was trained. In addition to validating the model, these results show that the model mechanistically captures relationships between the anatomical structure and functional activity of the human brain.

neuroscience↗

bioRxiv2022

Brain aerobic glycolysis and resilience in Alzheimer disease

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (A{beta}) deposition in individuals with dementia of the Alzheimer type (DAT) and asymptomatic individuals with brain amyloid deposition. Brain AG decreases with age but the functional significance of this decrease with regard to the development of DAT symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption and glucose utilization--from which we derive AG--we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in typical, cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results implicate preserved AG as a factor in brain resilience to amyloid pathology and suggest that white matter disease may be a cause and/or consequence of this impaired resilience.

neuroscience↗

bioRxiv2021

Stroke-related alterations in inter-areal communication revealed via Granger causality analysis

Beyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned.

neuroscience↗

bioRxiv2019

Resting multivoxel activity patterns in human visual cortex are linked to patterns evoked by preferred 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 and tasks. We compared in human visual cortex multi-vertex 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. extra-striate body area for bodies), measured multi-vertex 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 multi-vertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, i.e. both positive and negative, was significantly greater for the preferred stimulus category of an ROI (e.g. body category in body-preferring ROIs). The relationship between spontaneous and stimulus-evoked multi-vertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and patterns related to different categories fluctuated independently within their respective preferred ROIs (e.g. body- and scene-related multi-vertex patterns within body- and scene-preferring ROIs). These results support the general proposal that spontaneous multi-vertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.

neuroscience↗