Neuronal or Hemodynamic? Grappling with the Functional MRI Signal

Overview

Journal Brain Connect

Specialty Neurology

Date 2014 Aug 6

PMID 25093397

Citations 13

Authors

Peter A Bandettini

Affiliations

Soon will be listed here.

Abstract

Magnetic resonance imaging (MRI) and functional MRI (fMRI) continue to advance because creative physicists, engineers, neuroscientists, clinicians, and physiologists find new ways for extracting more information from the signal. Innovations in pulse sequence design, paradigm design, and processing methods have advanced the field and firmly established fMRI as a cornerstone for understanding the human brain. In this article, the field of fMRI is described through consideration of the central problem of separating hemodynamic from neuronal information. Discussed here are examples of how pulse sequences, activation paradigms, and processing methods are integrated such that novel, high-quality information can be obtained. Examples include the extraction of information such as activation onset latency, metabolic rate, neuronal adaptation, vascular patency, vessel diameter, vigilance, and subvoxel activation. Experimental measures include time series latency, hemodynamic shape, MR phase, multivoxel patterns, ratios of activation-related R2* to R2, metabolic rate changes, fluctuation correlations and frequencies, changes in fluctuation correlations and frequencies over time, resting correlation states, echo time dependence, and more.

Citing Articles

Concussion: Beyond the Cascade.

Neumann K, Broshek D, Newman B, Druzgal T, Kundu B, Resch J Cells. 2023; 12(17).

PMID: 37681861 PMC: 10487087. DOI: 10.3390/cells12172128.

Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling.

Belkhatir Z, Alhazmi F, Bahloul M, Laleg-Kirati T IEEE Open J Eng Med Biol. 2023; 3:69-77.

PMID: 36860497 PMC: 9970046. DOI: 10.1109/OJEMB.2022.3167281.

Voxel-Wise Linearity Analysis of Increments and Decrements in BOLD Responses in Human Visual Cortex Using a Contrast Adaptation Paradigm.

Lin Y, Zhou X, Naya Y, Gardner J, Sun P Front Hum Neurosci. 2021; 15:541314.

PMID: 34531731 PMC: 8439421. DOI: 10.3389/fnhum.2021.541314.

Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI.

Dowdle L, Ghose G, Chen C, Ugurbil K, Yacoub E, Vizioli L Prog Neurobiol. 2021; 207:102171.

PMID: 34492308 PMC: 8688272. DOI: 10.1016/j.pneurobio.2021.102171.

How Human Single-Neuron Recordings Can Help Us Understand Cognition: Insights from Memory Studies.

Kubska Z, Kaminski J Brain Sci. 2021; 11(4).

PMID: 33808391 PMC: 8067009. DOI: 10.3390/brainsci11040443.

References

Boxerman J, Bandettini P, Kwong K, Baker J, Davis T, Rosen B . The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusion-weighted studies in vivo. Magn Reson Med. 1995; 34(1):4-10. DOI: 10.1002/mrm.1910340103. View

Menon R, Luknowsky D, Gati J . Mental chronometry using latency-resolved functional MRI. Proc Natl Acad Sci U S A. 1998; 95(18):10902-7. PMC: 27993. DOI: 10.1073/pnas.95.18.10902. View

Logothetis N, Eschenko O, Murayama Y, Augath M, Steudel T, Evrard H . Hippocampal-cortical interaction during periods of subcortical silence. Nature. 2012; 491(7425):547-53. DOI: 10.1038/nature11618. View

Kundu P, Brenowitz N, Voon V, Worbe Y, Vertes P, Inati S . Integrated strategy for improving functional connectivity mapping using multiecho fMRI. Proc Natl Acad Sci U S A. 2013; 110(40):16187-92. PMC: 3791700. DOI: 10.1073/pnas.1301725110. View

Bandettini P, Jesmanowicz A, Wong E, Hyde J . Processing strategies for time-course data sets in functional MRI of the human brain. Magn Reson Med. 1993; 30(2):161-73. DOI: 10.1002/mrm.1910300204. View

Davis T, Kwong K, Weisskoff R, Rosen B . Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc Natl Acad Sci U S A. 1998; 95(4):1834-9. PMC: 19199. DOI: 10.1073/pnas.95.4.1834. View

Kundu P, Inati S, Evans J, Luh W, Bandettini P . Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI. Neuroimage. 2012; 60(3):1759-70. PMC: 3350785. DOI: 10.1016/j.neuroimage.2011.12.028. View

Hoge R, Atkinson J, Gill B, Crelier G, Marrett S, Pike G . Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex. Proc Natl Acad Sci U S A. 1999; 96(16):9403-8. PMC: 17795. DOI: 10.1073/pnas.96.16.9403. View

Reed C, Shoham S, Halgren E . Neural substrates of tactile object recognition: an fMRI study. Hum Brain Mapp. 2004; 21(4):236-46. PMC: 6871926. DOI: 10.1002/hbm.10162. View

10.

Bulte D, Kelly M, Germuska M, Xie J, Chappell M, Okell T . Quantitative measurement of cerebral physiology using respiratory-calibrated MRI. Neuroimage. 2012; 60(1):582-91. PMC: 7100043. DOI: 10.1016/j.neuroimage.2011.12.017. View

11.

Lu H, Golay X, Pekar J, van Zijl P . Functional magnetic resonance imaging based on changes in vascular space occupancy. Magn Reson Med. 2003; 50(2):263-74. DOI: 10.1002/mrm.10519. View

12.

Cordes D, Haughton V, Arfanakis K, Carew J, Turski P, Moritz C . Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data. AJNR Am J Neuroradiol. 2001; 22(7):1326-33. PMC: 7975218. View

13.

Birn R, Bandettini P . The effect of stimulus duty cycle and "off" duration on BOLD response linearity. Neuroimage. 2005; 27(1):70-82. DOI: 10.1016/j.neuroimage.2005.03.040. View

14.

Buxton R, Uludag K, Dubowitz D, Liu T . Modeling the hemodynamic response to brain activation. Neuroimage. 2004; 23 Suppl 1:S220-33. DOI: 10.1016/j.neuroimage.2004.07.013. View

15.

Norris D . Spin-echo fMRI: The poor relation?. Neuroimage. 2012; 62(2):1109-15. DOI: 10.1016/j.neuroimage.2012.01.003. View

16.

Murphy K, Birn R, Handwerker D, Jones T, Bandettini P . The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?. Neuroimage. 2008; 44(3):893-905. PMC: 2750906. DOI: 10.1016/j.neuroimage.2008.09.036. View

17.

Mullinger K, Mayhew S, Bagshaw A, Bowtell R, Francis S . Evidence that the negative BOLD response is neuronal in origin: a simultaneous EEG-BOLD-CBF study in humans. Neuroimage. 2014; 94:263-274. DOI: 10.1016/j.neuroimage.2014.02.029. View

18.

Boas D, Elwell C, Ferrari M, Taga G . Twenty years of functional near-infrared spectroscopy: introduction for the special issue. Neuroimage. 2013; 85 Pt 1:1-5. DOI: 10.1016/j.neuroimage.2013.11.033. View

19.

Sui J, Adali T, Yu Q, Chen J, Calhoun V . A review of multivariate methods for multimodal fusion of brain imaging data. J Neurosci Methods. 2011; 204(1):68-81. PMC: 3690333. DOI: 10.1016/j.jneumeth.2011.10.031. View

20.

Jochimsen T, Ivanov D, Ott D, Heinke W, Turner R, Moller H . Whole-brain mapping of venous vessel size in humans using the hypercapnia-induced BOLD effect. Neuroimage. 2010; 51(2):765-74. DOI: 10.1016/j.neuroimage.2010.02.037. View