Modeling the contribution of neuron-astrocyte cross talk to slow blood oxygenation level-dependent signal oscillations

DiNuzzo, Mauro; Gili, Tommaso; Maraviglia, B.; Giove, Federico

doi:10.1152/jn.00416.2011

Cited by 16 publications

(17 citation statements)

References 53 publications

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“…Recent modeling of the neuron-astrocyte cross-talk during oscillations linked to blood oxygenation levels verified the possibility that the slow fMRI BOLD signals might reflect the spontaneous ongoing activity of neuroglial networks [66]. Our results support this view by accurately modeling results from human imaging experiments [52, 60].…”

Section: Discussionsupporting

confidence: 81%

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

et al. 2015

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Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

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Section: Discussionsupporting

confidence: 81%

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

et al. 2015

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“…Regional glutamate release increases the metabolic rate of not only post-synaptic neurons (Smith et al, 2002), but also of surrounding astrocytes (DiNuzzo et al, 2011), quite unambiguously leading to regional BOLD signal increases (Logothetis, 2008). In contrast, the effects of regional GABAergic inhibition on BOLD signal are complex and might even be regionally-specific (Buzsaki et al, 2007; Logothetis, 2008): some studies show inhibition increasing a region’s metabolic rate (Jueptner and Weiller, 1995), while other studies demonstrate a BOLD signal decrease (Stefanovic et al, 2004).…”

Section: Discussionmentioning

confidence: 99%

Posteromedial cortex glutamate and GABA predict intrinsic functional connectivity of the default mode network

et al. 2013

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The balance between excitatory glutamatergic projection neurons and inhibitory GABAergic interneurons determines the function of cortical microcircuits. How these neurotransmitters relate to the functional status of an entire macro-scale network remains unknown. The posteromedial cortex (PMC) is the default mode network (DMN) node with the greatest functional connectivity; therefore, we hypothesized that PMC glutamate and GABA predict intrinsic functional connectivity (iFC) across the DMN. In 20 healthy men, we combined J-resolved magnetic resonance spectroscopy to measure glutamate and GABA in the PMC and resting fMRI followed by group Independent Components Analysis to extract the DMN. We showed that, controlling for age and GM volume in the MRS voxel, PMC glutamate and GABA explained about half of the variance in DMN iFC (represented by the network’s beta coefficient for rest). Glutamate correlated positively and GABA correlated negatively with DMN iFC; in an alternative statistical model which included the glutamate/GABA ratio, the ratio correlated positively with DMN iFC. Age had no independent effect on DMN iFC. No other network was associated with PMC glutamate or GABA. We conclude that regional neurotransmitter concentrations in a network node strongly predict network but not global brain iFC.

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“…In principle, a common source of physiological noise could also account for their positive correlation pattern. Cardiac and respiratory fluctuations, spontaneous oscillation in carbon dioxide, and many other physiological phenomena have been identified or proposed as source of BOLD fluctuations [ 54 – 59 ]. For example, ALFF has been shown to correlate with BOLD response in breath holding (BH) task, suggesting that the spectral amplitude of LFFs might be used to scale task-related BOLD signal to account for variability in vascular reactivity [ 60 , 61 ].…”

Section: Discussionmentioning

confidence: 99%

Intrinsic Patterns of Coupling between Correlation and Amplitude of Low-Frequency fMRI Fluctuations Are Disrupted in Degenerative Dementia Mainly due to Functional Disconnection

et al. 2015

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Low frequency fluctuations (LFFs) of the BOLD signal are a major discovery in the study of the resting brain with functional magnetic resonance imaging (fMRI). Two fMRI-based measures, functional connectivity (FC), a measure of signal synchronicity, and the amplitude of LFFs (ALFF), a measure of signal periodicity, have been proved to be sensitive to changes induced by several neurological diseases, including degenerative dementia. In spite of the increasing use of these measures, whether and how they are related to each other remains to be elucidated. In this work we used voxel-wise FC and ALFF computed in different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; and full-band: 0.01-0.073 Hz), in order to assess their relationship in healthy elderly as well as the relevant changes induced by Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI). We found that in healthy elderly subjects FC and ALFF are positively correlated in anterior and posterior cingulate cortex (full-band, slow-4 and slow-5), temporal cortex (full-band and slow-5), and in a set of subcortical regions (full-band and slow-4). These correlation patterns between FC and ALFF were absent in either AD or MCI patients. Notably, the loss of correlation between FC and ALFF in the AD group was primarily due to changes in FC rather than in ALFF. Our results indicate that degenerative dementia is characterized by a loss of global connection rather than by a decrease of fluctuation amplitude.

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Modeling the contribution of neuron-astrocyte cross talk to slow blood oxygenation level-dependent signal oscillations

Abstract: DiNuzzo M, Gili T, Maraviglia B, Giove F. Modeling the contribution of neuron-astrocyte cross talk to slow blood oxygenation leveldependent signal oscillations.

Cited by 16 publications

References 53 publications

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

Posteromedial cortex glutamate and GABA predict intrinsic functional connectivity of the default mode network

Intrinsic Patterns of Coupling between Correlation and Amplitude of Low-Frequency fMRI Fluctuations Are Disrupted in Degenerative Dementia Mainly due to Functional Disconnection

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