scholarly journals The thermodynamics of thinking: connections between neural activity, energy metabolism and blood flow

2019 ◽  
Author(s):  
Richard B. Buxton
Keyword(s):  
Blood Flow ◽  
Neural Activity ◽  
Oxidative Metabolism ◽  
Functional Neuroimaging ◽  
Cerebral Metabolism ◽  
Oxygen Metabolism ◽  
Oxygen Extraction Fraction ◽  
Neural Activation ◽  
Thermodynamic Framework ◽  
Wide Range

SummarySeveral current functional neuroimaging methods are sensitive to cerebral metabolism and cerebral blood flow (CBF) rather than the underlying neural activity itself. Empirically, the connections between metabolism, flow and neural activity are complex and somewhat counterintuitive: CBF and glycolysis increase more than seems to be needed to provide oxygen and pyruvate for oxidative metabolism, and the oxygen extraction fraction is relatively low in the brain and decreases when oxygen metabolism increases. This work lays a foundation for the idea that this unexpected pattern of physiological changes is consistent with basic thermodynamic considerations related to metabolism. In the context of this thermodynamic framework, the apparent mismatches in metabolic rates and CBF are related to preserving the entropy change of oxidative metabolism, specifically the O2/CO2 ratio in the mitochondria. However, the mechanism supporting this CBF response is likely not due to feedback from a hypothetical O2 sensor in tissue, but rather is consistent with feed-forward control by signals from both excitatory and inhibitory neural activity. Quantitative predictions of the thermodynamic framework, based on models of O2 and CO2 transport and possible neural drivers of CBF control, are in good agreement with a wide range of experimental data, including responses to neural activation, hypercapnia, hypoxia and high-altitude acclimatization.

scholarly journals The thermodynamics of thinking: connections between neural activity, energy metabolism and blood flow

2020 ◽  
Vol 376 (1815) ◽  
pp. 20190624
Author(s):  
Richard B. Buxton
Keyword(s):  
Blood Flow ◽  
Neural Activity ◽  
Oxidative Metabolism ◽  
Functional Neuroimaging ◽  
Cerebral Metabolism ◽  
Oxygen Metabolism ◽  
Oxygen Extraction Fraction ◽  
Neural Activation ◽  
Thermodynamic Framework ◽  
Wide Range

Several current functional neuroimaging methods are sensitive to cerebral metabolism and cerebral blood flow (CBF) rather than the underlying neural activity itself. Empirically, the connections between metabolism, flow and neural activity are complex and somewhat counterintuitive: CBF and glycolysis increase more than seems to be needed to provide oxygen and pyruvate for oxidative metabolism, and the oxygen extraction fraction is relatively low in the brain and decreases when oxygen metabolism increases. This work lays a foundation for the idea that this unexpected pattern of physiological changes is consistent with basic thermodynamic considerations related to metabolism. In the context of this thermodynamic framework, the apparent mismatches in metabolic rates and CBF are related to preserving the entropy change of oxidative metabolism, specifically the O 2 /CO 2 ratio in the mitochondria. However, the mechanism supporting this CBF response is likely not owing to feedback from a hypothetical O 2 sensor in tissue, but rather is consistent with feed-forward control by signals from both excitatory and inhibitory neural activity. Quantitative predictions of the thermodynamic framework, based on models of O 2 and CO 2 transport and possible neural drivers of CBF control, are in good agreement with a wide range of experimental data, including responses to neural activation, hypercapnia, hypoxia and high-altitude acclimatization. This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.

scholarly journals Cerebral Blood Flow Response to Functional Activation

2009 ◽  
Vol 30 (1) ◽  
pp. 2-14 ◽  
Author(s):  
Olaf B Paulson ◽  
Steen G Hasselbalch ◽  
Egill Rostrup ◽  
Gitte Moos Knudsen ◽  
Dale Pelligrino
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Glucose Metabolism ◽  
Oxidative Metabolism ◽  
Glucose Consumption ◽  
Oxygen Metabolism ◽  
Neural Activation ◽  
Metabolic Demand ◽  
Tight Coupling ◽  
Pronounced Increase

Cerebral blood flow (CBF) and cerebral metabolic rate are normally coupled, that is an increase in metabolic demand will lead to an increase in flow. However, during functional activation, CBF and glucose metabolism remain coupled as they increase in proportion, whereas oxygen metabolism only increases to a minor degree—the so-called uncoupling of CBF and oxidative metabolism. Several studies have dealt with these issues, and theories have been forwarded regarding the underlying mechanisms. Some reports have speculated about the existence of a potentially deficient oxygen supply to the tissue most distant from the capillaries, whereas other studies point to a shift toward a higher degree of non-oxidative glucose consumption during activation. In this review, we argue that the key mechanism responsible for the regional CBF (rCBF) increase during functional activation is a tight coupling between rCBF and glucose metabolism. We assert that uncoupling of rCBF and oxidative metabolism is a consequence of a less pronounced increase in oxygen consumption. On the basis of earlier studies, we take into consideration the functional recruitment of capillaries and attempt to accommodate the cerebral tissue's increased demand for glucose supply during neural activation with recent evidence supporting a key function for astrocytes in rCBF regulation.

scholarly journals Coupling of Neural Activation to Blood Flow in the Somatosensory Cortex of Rats is Time-Intensity Separable, but Not Linear

2000 ◽  
Vol 20 (6) ◽  
pp. 921-930 ◽  
Author(s):  
Beau M. Ances ◽  
Eric Zarahn ◽  
Joel H. Greenberg ◽  
John A. Detre
Keyword(s):  
Blood Flow ◽  
Stimulus Duration ◽  
Neural Activity ◽  
Time Series Data ◽  
Functional Neuroimaging ◽  
Linear Time ◽  
Second Order ◽  
Series Data ◽  
Neural Activation ◽  
Linear Time Invariant

Changes in cerebral blood flow (CBF) because of functional activation are used as a surrogate for neural activity in many functional neuroimaging studies. In these studies, it is often assumed that the CBF response is a linear-time invariant (LTI) transform of the underlying neural activity. By using a previously developed animal model system of electrical forepaw stimulation in rats (n = 11), laser Doppler measurements of CBF, and somatosensory evoked potentials, measurements of neural activity were obtained when the stimulus duration and intensity were separately varied. These two sets of time series data were used to assess the LTI assumption. The CBF data were modeled as a transform of neural activity (N1–P2 amplitude of the somatosensory evoked potential) by using first-order (linear) and second-order (nonlinear) components. Although a pure LTI model explained a large amount of the variance in the data for changes in stimulus duration, our results demonstrated that the second-order kernel (i.e., a nonlinear component) contributed an explanatory component that is both statistically significant and appreciable in magnitude. For variations in stimulus intensity, a pure LTI model explained almost all of the variance in the CBF data. In particular, the shape of the CBF response did not depend on intensity of neural activity when duration was held constant (time-intensity separability). These results have important implications for the analysis and interpretation of neuroimaging data.

scholarly journals A frequency-domain machine learning method for dual-calibrated fMRI mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2)

2019 ◽  
Author(s):  
Michael Germuska ◽  
Hannah Chandler ◽  
Thomas Okell ◽  
Fabrizio Fasano ◽  
Valentina Tomassini ◽  
...  
Keyword(s):  
Machine Learning ◽  
Blood Flow ◽  
Oxygen Consumption ◽  
Oxygen Metabolism ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Single Subject ◽  
Extraction Fraction ◽  
Wide Range ◽  
Calibrated Fmri

AbstractMagnetic resonance imaging (MRI) offers the possibility to non-invasively map the brain’s metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. However, in depth study of oxygen metabolism with MRI has so far been hindered by the lack of robust methods. One MRI method of mapping CMRO2 is based on the simultaneous acquisition of cerebral blood flow (CBF) and blood oxygen level dependent (BOLD) weighted images during respiratory modulation of both oxygen and carbon dioxide. Although this dual-calibrated methodology has shown promise in the research setting, current analysis methods are unstable in the presence of noise and/or are computationally demanding. In this paper, we present a machine learning implementation for the multi-parametric assessment of dual-calibrated fMRI data. The proposed method aims to address the issues of stability, accuracy, and computational overhead, removing significant barriers to the investigation of oxygen metabolism with MRI. The method utilizes a time-frequency transformation of the acquired perfusion and BOLD-weighted data, from which appropriate feature vectors are selected for training of machine learning regressors. The implemented machine learning methods are chosen for their robustness to noise and their ability to map complex non-linear relationships (such as those that exist between BOLD signal weighting and blood oxygenation). An extremely randomized trees (ET) regressor is used to estimate resting blood flow and a multi-layer perceptron (MLP) is used to estimate CMRO2 and the oxygen extraction fraction (OEF). Synthetic data with additive noise are used to train the regressors, with data simulated to cover a wide range of physiologically plausible parameters. The performance of the implemented analysis method is compared to published methods both in simulation and with in-vivo data (n=30). The proposed method is demonstrated to significantly reduce computation time, error, and proportional bias in both CMRO2 and OEF estimates. The introduction of the proposed analysis pipeline has the potential to not only increase the detectability of metabolic difference between groups of subjects, but may also allow for single subject examinations within a clinical context.

scholarly journals Dynamics of the cerebral blood flow response to brief neural activity in human visual cortex

2019 ◽  
Vol 40 (9) ◽  
pp. 1823-1837 ◽  
Author(s):  
Jung Hwan Kim ◽  
Amanda J Taylor ◽  
Danny JJ Wang ◽  
Xiaowei Zou ◽  
David Ress
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Visual Cortex ◽  
Temporal Dynamics ◽  
Oxygen Metabolism ◽  
Late Time ◽  
Neural Activation ◽  
Hemodynamic Response Function ◽  
Time Dynamics ◽  
Human Visual Cortex

The blood oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal depends on an interplay of cerebral blood flow (CBF), oxygen metabolism, and cerebral blood volume. Despite wide usage of BOLD fMRI, it is not clear how these physiological components create the BOLD signal. Here, baseline CBF and its dynamics evoked by a brief stimulus (2 s) in human visual cortex were measured at 3T. We found a stereotypical CBF response: immediate increase, rising to a peak a few second after the stimulus, followed by a significant undershoot. The BOLD hemodynamic response function (HRF) was also measured in the same session. Strong correlations between HRF and CBF peak responses indicate that the flow responses evoked by neural activation in nearby gray matter drive the early HRF. Remarkably, peak CBF and HRF were also strongly modulated by baseline perfusion. The CBF undershoot was reliable and significantly correlated with the HRF undershoot. However, late-time dynamics of the HRF and CBF suggest that oxygen metabolism can also contribute to the HRF undershoot. Combined measurement of the CBF and HRF for brief neural activation is a useful tool to understand the temporal dynamics of neurovascular and neurometabolic coupling.

scholarly journals Neural–metabolic coupling in the central visual pathway

2016 ◽  
Vol 371 (1705) ◽  
pp. 20150357 ◽  
Author(s):  
Ralph D. Freeman ◽  
Baowang Li
Keyword(s):  
Blood Flow ◽  
Neural Activity ◽  
Visual Pathway ◽  
Blood Oxygenation ◽  
Neural Function ◽  
Neural Activation ◽  
Visual Response ◽  
Tissue Oxygen ◽  
Neural Imaging ◽  
Initial Dip

Studies are described which are intended to improve our understanding of the primary measurements made in non-invasive neural imaging. The blood oxygenation level-dependent signal used in functional magnetic resonance imaging (fMRI) reflects changes in deoxygenated haemoglobin. Tissue oxygen concentration, along with blood flow, changes during neural activation. Therefore, measurements of tissue oxygen together with the use of a neural sensor can provide direct estimates of neural–metabolic interactions. We have used this relationship in a series of studies in which a neural microelectrode is combined with an oxygen micro-sensor to make simultaneous co-localized measurements in the central visual pathway. Oxygen responses are typically biphasic with small initial dips followed by large secondary peaks during neural activation. By the use of established visual response characteristics, we have determined that the oxygen initial dip provides a better estimate of local neural function than the positive peak. This contrasts sharply with fMRI for which the initial dip is unreliable. To extend these studies, we have examined the relationship between the primary metabolic agents, glucose and lactate, and associated neural activity. For this work, we also use a Doppler technique to measure cerebral blood flow (CBF) together with neural activity. Results show consistent synchronously timed changes such that increases in neural activity are accompanied by decreases in glucose and simultaneous increases in lactate. Measurements of CBF show clear delays with respect to neural response. This is consistent with a slight delay in blood flow with respect to oxygen delivery during neural activation. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

Cerebrospinal fluid production and its relationship to cerebral metabolism and cerebral blood flow

1959 ◽  
Vol 197 (4) ◽  
pp. 825-828 ◽  
Author(s):  
Edgar A. Bering
Keyword(s):  
Blood Flow ◽  
Cerebrospinal Fluid ◽  
Cerebral Blood Flow ◽  
Oxygen Consumption ◽  
Choroid Plexus ◽  
Cerebral Metabolism ◽  
Oxygen Metabolism ◽  
Csf Flow ◽  
Constant Composition ◽  
Fluid Production

The cerebrospinal fluid production has been studied in the dog under conditions of maximum obtainable flow rates from the cisterna magna. Under these conditions the fluid had constant composition and was assumed to represent the cerebrospinal fluid in the intact state. Cerebral blood flow and cerebral oxygen consumption were measured by the method of Kety and Schmidt. The only significant correlations found were with oxygen consumption when the CSF flow rate was in terms of brain weight and with cerebral blood flow and cerebral vascular resistance when CSF flow was in terms of choroid plexus weight. A combined regression equation was calculated which satisfactorily accounted for the observed CSF flow: CSF cu mm/min. = .128 x CMRO2 x brain wgt. + 0.15 x CVR x choroid plexus wt. This suggested separate physiological processes, one correlated with oxygen metabolism and one with hydrodynamic factors of the cerebral blood flow. The data demonstrated that the choroid plexus alone could not have accounted for the entire CSF flow and some must have come from another source, presumably the brain.

scholarly journals A neural model of valuation and information virality

2017 ◽  
Vol 114 (11) ◽  
pp. 2881-2886 ◽  
Author(s):  
Christin Scholz ◽  
Elisa C. Baek ◽  
Matthew Brook O’Donnell ◽  
Hyun Suk Kim ◽  
Joseph N. Cappella ◽  
...  
Keyword(s):  
Information Sharing ◽  
Neural Activity ◽  
Functional Neuroimaging ◽  
New York Times ◽  
Population Level ◽  
Social Consequences ◽  
Human Interaction ◽  
Self Report ◽  
Neural Activation ◽  
Advance Theory

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds.

scholarly journals Quantitative mapping of cerebral oxygen metabolism using breath-hold calibrated fMRI

2021 ◽  
Author(s):  
Michael Germuska ◽  
Rachael C Stickland ◽  
Antonio Maria Chiarelli ◽  
Hannah L Chandler ◽  
Richard G Wise
Keyword(s):  
Blood Flow ◽  
Oxygen Metabolism ◽  
Oxygen Extraction Fraction ◽  
Arterial Oxygen ◽  
Breath Holding ◽  
Breath Hold ◽  
Neural Function ◽  
Cerebral Oxygen ◽  
Cerebral Oxygen Metabolism

Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the rate of cerebral metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. Existing methods of mapping CMRO2, based on respiratory modulation of arterial spin labelling (ASL) and blood oxygen level dependent (BOLD) signals, require lengthy acquisitions and independent modulation of both arterial oxygen and carbon dioxide levels. Here, we present a new simplified method for mapping the rate of cerebral oxygen metabolism that can be performed using a simple breath-holding paradigm. The method incorporates flow-diffusion modelling of oxygen transport and physiological constraints to create a non-linear mapping between the maximum BOLD signal, M, baseline blood flow (CBF0), and CMRO2. A gradient boosted decision tree is used to learn this mapping directly from simulated MRI data. Modelling studies demonstrate that the proposed method is robust to variation in cerebral physiology and metabolism. This new gas-free methodology offers a rapid and pragmatic alternative to existing dual-calibrated methods, removing the need for specialist respiratory equipment and long acquisition times. In-vivo testing of the method, using an 8-minute 45 second protocol of repeated breath-holding, was performed on 15 healthy volunteers, producing quantitative maps of cerebral blood flow (CBF), oxygen extraction fraction (OEF), and CMRO2.

Neural activation in the brain with uncoupling between blood flow and oxygen metabolism

NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 1017
Author(s):  
Hiroshi Yamauchi ◽  
Hidehiko Okazawa ◽  
Kanji Sugimoto ◽  
Masaaki Takahashi ◽  
Yoshihiko Kishibe ◽  
...  
Keyword(s):  
Blood Flow ◽  
Oxygen Metabolism ◽  
Neural Activation ◽  
The Brain
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