Quantitative functional imaging of the brain: towards mapping neuronal activity by BOLD fMRI

Hyder, Fahmeed; Kida, Ikuhiro; Behar, Kevin L.; Kennan, Richard P.; Maciejewski, Paul K.; Rothman, Douglas L.

doi:10.1002/nbm.733

Cited by 180 publications

(208 citation statements)

References 76 publications

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“…These results also showed that CMR O2 changes derived from calibrated fMRI are closely associated with glutamatergic function. 20,21 Results from other methods (e.g., electroencephalography (EEG), positron emission tomography (PET), 2-deoxyglucose (2DG) autoradiography) generally showed coupling between cortical activity and oxidative demand. 2DG autoradiographic studies in rats 22 and PET studies in primates 23 showed that anesthetic-dependent CMR glc decreased uniformly in the cerebral cortex.…”

Section: Introductionmentioning

confidence: 99%

Glutamatergic Function in the Resting Awake Human Brain is Supported by Uniformly High Oxidative Energy

Hyder

Fulbright

Shulman

et al. 2013

J Cereb Blood Flow Metab

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105

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Rodent 13 C magnetic resonance spectroscopy studies show that glutamatergic signaling requires high oxidative energy in the awake resting state and allowed calibration of functional magnetic resonance imaging (fMRI) signal in terms of energy relative to the resting energy. Here, we derived energy used for glutamatergic signaling in the awake resting human. We analyzed human data of electroencephalography (EEG), positron emission tomography (PET) maps of oxygen (CMR O2 ) and glucose (CMR glc ) utilization, and calibrated fMRI from a variety of experimental conditions. CMR glc and EEG in the visual cortex were tightly coupled over several conditions, showing that the oxidative demand for signaling was four times greater than the demand for nonsignaling events in the awake state. Variations of CMR O2 and CMR glc from gray-matter regions and networks were within ±10% of means, suggesting that most areas required similar energy for ubiquitously high resting activity. Human calibrated fMRI results suggest that changes of fMRI signal in cognitive studies contribute at most ± 10% CMR O2 changes from rest. The PET data of sleep, vegetative state, and anesthesia show metabolic reductions from rest, uniformly 420% across, indicating no region is selectively reduced when consciousness is lost. Future clinical investigations will benefit from using quantitative metabolic measures. Keywords: astrocytes; baseline; field potentials; glutamate; multiunit activity; resting state INTRODUCTIONThe human brain consumes 20% of the body's energy at rest despite being only 2% of total body mass. 1 Normally glucose oxidation is the source of energy production supporting brain function 2 in which gray-matter signaling (i.e., events associated with neuronal firing) is dominated by glutamatergic neurons. 3 Estimates of the fraction of resting brain energy devoted to signaling were originally quite low. 4 But recent experimental studies in rodents and theoretical modeling have converged on the conclusion that majority of the resting energy consumption supports glutamatergic signaling and the energy demand changes linearly with pyramidal neuron firing rates and glutamate neurotransmitter release and reuptake. [5][6][7][8][9] Therefore in rodent models it is possible, to a first order, to show that the resting energy is primarily dedicated to total glutamatergic signaling, and the changes in neuronal signaling relative to a well-defined resting activity level can be used to calibrate changes in energy consumption during functional magnetic resonance imaging (fMRI) experiments. 10,11 In the awake human brain, however, the fraction of resting energy usage devoted to glutamatergic signaling is less well understood. The magnitude of neuronal signaling in the human brain, and by inference the commensurate energy demand, underscores the functional relevance of resting activity and has profound implications for interpreting fMRI experiments in humans. [12][13][14] Given the rapidly increasing use of resting-state fMRI in mapping networks-defined as a...

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Section: Introductionmentioning

confidence: 99%

Glutamatergic Function in the Resting Awake Human Brain is Supported by Uniformly High Oxidative Energy

Hyder

Fulbright

Shulman

et al. 2013

J Cereb Blood Flow Metab

Self Cite

105

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“…which required multimodal MRI measurements of changes in cerebral blood f low (⌬CBF͞CBF), cerebral blood volume (⌬CBV͞CBV), and BOLD signal (⌬S͞S) as described (10,12). ⌬CBF͞CBF (spin labeling) and ⌬S͞S (gradient and spin echo) were measured in an interleaved manner (17) in both conditions I and II.…”

Section: Methodsmentioning

confidence: 99%

“…The value of Á (0.4 Ϯ 0.1) was determined from a prior calibration obtained by comparison of measured (by 13 C MRS) and predicted (from Eq. 1) values of ⌬CMR O2 ͞CMR O2 over a wide range of activity (10,12). A localized region of 2 ϫ…”

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confidence: 99%

“…All in vivo fMRI data were collected on a 7T Bruker (Billerica, MA) horizontal-bore spectrometer with a homogeneous transmit and local receive 1 H radio-frequency coil (10,16). Changes in CMR O2 were calculated from the BOLD signal (9, 10, 12)which required multimodal MRI measurements of changes in cerebral blood f low (⌬CBF͞CBF), cerebral blood volume (⌬CBV͞CBV), and BOLD signal (⌬S͞S) as described (10,12). ⌬CBF͞CBF (spin labeling) and ⌬S͞S (gradient and spin echo) were measured in an interleaved manner (17) in both conditions I and II.…”

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confidence: 99%

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Cerebral energetics and spiking frequency: The neurophysiological basis of fMRI

Smith

Blumenfeld

Behar

et al. 2002

Proc. Natl. Acad. Sci. U.S.A.

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320

274

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Functional MRI (fMRI) is widely assumed to measure neuronal activity, but no satisfactory mechanism for this linkage has been identified. Here we derived the changes in the energetic component from the blood oxygenation level-dependent (BOLD) fMRI signal and related it to changes in the neuronal spiking frequency in the activated voxels. Extracellular recordings were used to measure changes in cerebral spiking frequency (⌬ ͞ ) of a neuronal ensemble during forepaw stimulation in the ␣-chloralose anesthetized rat. Under the same conditions localized changes in brain energy metabolism (⌬CMR O2͞CMRO2) were obtained from BOLD fMRI data in conjunction with measured changes in cerebral blood flow (⌬CBF͞CBF), cerebral blood volume (⌬CBV͞CBV), and transverse relaxation rates of tissue water (T 2 * and T2) by MRI methods at 7T. On stimulation from two different depths of anesthesia ⌬CMRO2͞CMRO2 Ϸ ⌬ ͞ . Previous 13 C magnetic resonance spectroscopy studies, under similar conditions, had shown that ⌬CMR O2͞CMRO2 was proportional to changes in glutamatergic neurotransmitter flux (⌬Vcyc͞Vcyc). These combined results show that ⌬CMR O2͞CMRO2 Ϸ ⌬Vcyc͞Vcyc Ϸ ⌬ ͞ , thereby relating the energetic basis of brain activity to neuronal spiking frequency and neurotransmitter flux. Because ⌬CMRO2͞CMRO2 had the same high spatial and temporal resolutions of the fMRI signal, these results show how BOLD imaging, when converted to ⌬CMR O2͞CMRO2, responds to localized changes in neuronal spike frequency.R elations between cerebral energy consumption and neuronal activity have been intensely studied since such a coupling was suggested by Roy and Sherrington (1). Sokoloff and coworkers (2) showed that in peripheral neurons increases in energy consumption associated with electrical activity are localized to the neuropil and are approximately proportional to spiking frequency. This proportionality suggested that quantitation of regional brain energy metabolism may provide a direct measure of cortical activity. Nearly all cerebral energy consumption is derived from glucose oxidation (3). 13 C magnetic resonance spectroscopy (MRS) studies have measured the oxidative rate of [1-13 C]glucose use by the flow of the 13 C label into neuronal glutamate pools (4). The subsequent flow of the 13 C label into astrocytic glutamine pools showed that the rates of neuronal oxidative metabolism (CMR O2 ) and glutamate neurotransmitter release͞cycling (V cyc ) are stoichiometrically related (5). The model of glutamate neurotransmitter cycling (6) supported by the 13 C MRS data provides the hypothesis that V cyc , and consequently CMR O2 , should be proportional to spiking frequency of glutamatergic neurons.In this paper we have measured the relationship between energy metabolism and the neuronal spiking frequency in the ␣-chloralose anesthetized rat during forepaw stimulation (7,8). First, ⌬CMR O2 ͞CMR O2 values were derived from multimodal MRI measurements based on the blood oxygenation leveldependent (BOLD) image-contrast as described (9-12). Second, relative sp...

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“…It is natural to relate the recorded BOLD response to the neural response driving the metabolic demands on blood oxygenation (Hyder et al, 2001;Logothetis, 2002;Kayser et al, 2004). In our case, we are interested in the distinct neural responses that could have been driving the three independent components identified by the analysis.…”

Section: Estimated Neural Response N(t)mentioning

confidence: 99%

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

2008

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This is the published version of the paper.This version of the publication may differ from the final published version. Permanent repository link A R T I C L E I N F O A B S T R A C TArticle history: IntroductionFunctional magnetic-resonance imaging (fMRI) based on the blood oxygenation-level dependent (BOLD) signal is a powerful technique for studying the neural response in the cortex. Most previous work has been based on the assumption that the BOLD signal is a unitary response to a single form of stimulus S(t), usually in the form of a linear convolution of a hemodynamic response function (HRF) with the temporal waveform of the stimulus time sequence (Bandettini et al., 1993;Friston et al., 1994;Boynton et al., 1996). In most cases, it is assumed that the HRF incorporates both the cortical response to the stimulus and the hemodynamic response of the blood to the oxygen requirements of the cortical response. However, the situation may be much more complicated, with multiple components of neural response to the stimulus weighted differentially across the cortex (Zacks et al., 2001;d'Avossa et al., 2003;Bellgowan et al., 2003;Calhoun et al., 2004a;Fox et al., 2005), such that any one voxel contains contributions from more than one neural time course. If these time course variations are small relative to the BOLD temporal resolution, they may be negligible for an overall analysis of response strength, but the cited studies show non-negligible variations that require a more detailed analysis. For this reason, consistent with Friston et al. (1998Friston et al. ( , 2000, Buxton et al. (2004) and others, we restrict the term HRF to the dynamics of the blood response to the metabolic demands of the neural processing and consider the neural response to the stimulus as a separate process. This leads to the model of the BOLD mechanisms shown in Fig. 1.

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Quantitative functional imaging of the brain: towards mapping neuronal activity by BOLD fMRI

Cited by 180 publications

References 76 publications

Glutamatergic Function in the Resting Awake Human Brain is Supported by Uniformly High Oxidative Energy

Glutamatergic Function in the Resting Awake Human Brain is Supported by Uniformly High Oxidative Energy

Cerebral energetics and spiking frequency: The neurophysiological basis of fMRI

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

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