Neurovascular imaging
- 1 Neurovascular Imaging Laboratory, University of California San Diego, San Diego, CA, USA
- 2 Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
In this e-book we present a collection of papers submitted to Frontiers in Neuroenergetics in response to the “Special topic” initiative titled “Neurovascular Imaging.” Advances in imaging technology, both optical and MRI based methods, traditionally have played (and continue playing) a major role in the advancement of neuroscience in general and in the understanding of cerebral blood flow and metabolism in particular. Therefore, our initial intent was to highlight the technological advances and impact they had on neurovascular/neurometabolic research, including description of the key biological results. However, it was the last aspect of our proposal – the biological results – that was met with the most overwhelming enthusiasm. Thus, while improvements of imaging technology are featured in the majority of the included articles, the main focus is on using those technological advances to better understand neurovascular and neurometabolic coupling.
So, what does it take to make significant progress in understanding of this coupling? First, as in every study in this e-book, it requires a team of investigators armed with state-of-the-art measurement tools and a novel (“transformative”) approach, a.k.a. imagination. Second, one has to recognize the limitations of their measurement tools and consider the measurement theory – the relationship between the experimental “observables” and the underlying physiological parameters (Harris et al., 2010; Lindauer et al., 2010; Logothetis, 2010; Vanzetta and Slovin, 2010). For example, although BOLD fMRI measures deoxyhemoglobin, one has to consider both intra- and extravascular contributions to the signal and effects of vessel size, which vary as a function of the magnetic field of an MRI scanner. Likewise, one has to account for specific experimental conditions producing a biological behavior that might or might not translate to the intact brain situation (Filosa, 2010). Finally, merely the number of physiological parameters, which interact to produce a biological behavior, necessitates the use of computational modeling (Buxton, 2010). In particular, a solid theoretical framework is required to bridge between micro- and macroscopic levels of description – a critical step for translation of basic science observations in healthy brain (Cauli and Hamel, 2010; Hamilton et al., 2010; Saka et al., 2010; Sirotin and Das, 2010; Vazquez et al., 2010; Kleinfeld et al., 2011) and in experimental disorders (Luckl et al., 2010) to human studies (Koch et al., 2010; Lindauer et al., 2010; Obrig et al., 2010; Lin et al., 2011).
With the continuing development of optical (Akkin et al., 2010; Gregg et al., 2010; Hu and Wang, 2010; Srienc et al., 2010) and MRI (Harel et al., 2010; Hyder et al., 2010; Lin et al., 2011) imaging technology, and the steadily increasing availability of specific fluorescent and MR-visible indicators (Barros, 2010), our ability to probe the biological mechanisms underlying functional hyperemia is on a steep rise. Importantly, new methods allow not only measurement, but also well-controlled manipulations (Allegra Mascaro et al., 2010; Kleinfeld et al., 2011) crucial for testing causality rather than simply establishing a correlation between measurement parameters (that does not automatically imply that one of the parameters drives the other). Moreover, the present collection of papers reaches well beyond the current state of knowledge, defining important questions and roadmaps for future research (Buxton, 2010; Cauli and Hamel, 2010; Hamilton et al., 2010; Vazquez et al., 2010; Kleinfeld et al., 2011; Lin et al., 2011).
For us, Neurovascular Imaging is a lifetime-long affair that combines the magic of imaging (“seeing is believing”) with the enigma of neurovascular communication waiting to be resolved, and the excitement of basic discovery with satisfaction of the usefulness/medical relevance of the results. We hope that the present collection of papers will be of particular encouragement for the young people in the field. The Neurovascular Imaging train is on a fast track toward genuine understanding of neurovascular and neurometabolic mechanisms with outstanding clinical importance.
References
Akkin, T., Landowne, D., and Sivaprakasam, A. (2010). Detection of neural action potentials using optical coherence tomography: intensity and phase measurements with and without dyes. Front. Neuroenergetics 2:22. doi: 10.3389/fnene.2010.00022
Allegra Mascaro, A. L., Sacconi, L., and Pavone, F. S. (2010). Multi-photon nanosurgery in live brain. Front. Neuroenergetics 2:21. doi: 10.3389/fnene.2010.00021
Barros, L. F. (2010). Towards single-cell real-time imaging of energy metabolism in the brain. Front. Neuroenergetics 2:4. doi: 10.3389/fnene.2010.00004
Buxton, R. B. (2010). Interpreting oxygenation-based neuroimaging signals: the importance and the challenge of understanding brain oxygen metabolism. Front. Neuroenergetics 2:8. doi: 10.3389/fnene.2010.00008
Cauli, B., and Hamel, E. (2010). Revisiting the role of neurons in neurovascular coupling. Front. Neuroenergetics 2:9. doi: 10.3389/fnene.2010.00009
Filosa, J. A. (2010). Vascular tone and neurovascular coupling: considerations toward an improved in vitro model. Front. Neuroenergetics 2:16. doi: 10.3389/fnene.2010.00016
Gregg, N. M., White, B. R., Zeff, B. W., Berger, A. J., and Culver, J. P. (2010). Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography. Front. Neuroenergetics 2:14. doi: 10.3389/fnene.2010.00014
Hamilton, N. B., Attwell, D., and Hall, C. N. (2010). Pericyte-mediated regulation of capillary diameter: a component of neurovascular coupling in health and disease. Front. Neuroenergetics 2:5. doi: 10.3389/fnene.2010.00005
Harel, N., Bolan, P. J., Turner, R., Ugurbil, K., and Yacoub, E. (2010). Recent advances in high-resolution mr application and its implications for neurovascular coupling research. Front. Neuroenergetics 2:130. doi: 10.3389/fnene.2010.00130
Harris, S., Jones, M., Zheng, Y., and Berwick, J. (2010). Does neural input or processing play a greater role in the magnitude of neuroimaging signals?. Front Neuroenergetics 2:15. doi: 10.3389/fnene.2010.00015
Hu, S., and Wang, L. V. (2010). Neurovascular photoacoustic tomography. Front. Neuroenergetics 2:10. doi: 10.3389/fnene.2010.00010
Hyder, F., Sanganahalli, B. G., Herman, P., Coman, D., Maandag, N. J., Behar, K. L., Blumenfeld, H., and Rothman, D. L. (2010). Neurovascular and neurometabolic couplings in dynamic calibrated fMRI: transient oxidative neuroenergetics for block-design and event-related paradigms. Front. Neuroenergetics 2:18. doi: 10.3389/fnene.2010.00018
Kleinfeld, D., Blinder, P., Drew, P. J., Driscoll, J. D., Muller, A., Tsai, P. S., and Shih, A. Y. (2011). A guide to delineate the logic of neurovascular signaling in the brain. Front. Neuroenergetics 3:1. doi: 10.3389/fnene.2011.00001
Koch, S. P., Habermehl, C., Mehnert, J., Schmitz, C. H., Holtze, S., Villringer, A., Steinbrink, J., and Obrig, H. (2010). High-resolution optical functional mapping of the human somatosensory cortex. Front. Neuroenergetics 2:12. doi: 10.3389/fnene.2010.00012
Lin, A. L., Gao, J. H., Duong, T. Q., and Fox, P. T. (2011). Functional neuroimaging: a physiological perspective. Front. Neuroenergetics 2:17. doi: 10.3389/fnene.2010.00017
Lindauer, U., Dirnagl, U., Fuchtemeier, M., Bottiger, C., Offenhauser, N., Leithner, C., and Royl, G. (2010). Pathophysiological interference with neurovascular coupling – when imaging based on hemoglobin might go blind. Front. Neuroenergetics 2:25. doi: 10.3389/fnene.2010.00025
Logothetis, N. K. (2010). Neurovascular uncoupling: much ado about nothing. Front. Neuroenergetics 2:2. doi: 10.3389/fnene.2010.00002
Luckl, J., Baker, W., Sun, Z. H., Durduran, T., Yodh, A. G., and Greenberg, J. H. (2010). The biological effect of contralateral forepaw stimulation in rat focal cerebral ischemia: a multispectral optical imaging study. Front. Neuroenergetics 2:19. doi: 10.3389/fnene.2010.00019
Obrig, H., Rossi, S., Telkemeyer, S., and Wartenburger, I. (2010). From acoustic segmentation to language processing: evidence from optical imaging. Front. Neuroenergetics 2:13. doi: 10.3389/fnene.2010.00013
Saka, M., Berwick, J., and Jones, M. (2010). Linear superposition of sensory-evoked and ongoing cortical hemodynamics. Front. Neuroenergetics 2:23. doi: 10.3389/fnene.2010.00023
Sirotin, Y. B., and Das, A. (2010). Spatial relationship between flavoprotein fluorescence and the hemodynamic response in the primary visual cortex of alert macaque monkeys. Front. Neuroenergetics 2:6. doi: 10.3389/fnene.2010.00006
Srienc, A. I., Kurth-Nelson, Z. L., and Newman, E. A. (2010). Imaging retinal blood flow with laser speckle flowmetry. Front. Neuroenergetics 2:128. doi: 10.3389/fnene.2010.00128
Vanzetta, I., and Slovin, H. (2010). A BOLD assumption. Front. Neuroenergetics 2:24. doi: 10.3389/fnene.2010.00024
Citation: Devor A and Boas D (2012) Neurovascular imaging. Front. Neuroenerg. 4:1. doi: 10.3389/fnene.2012.00001
Received: 16 December 2011; Accepted: 03 January 2012;
Published online: 18 January 2012.
Copyright: © 2012 Devor and Boas. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
*Correspondence: adevor@ucsd.edu