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8 - Intrinsic signal optical imaging

Published online by Cambridge University Press:  05 October 2012

By
Ron D. Frostig  and
Cynthia H. Chen-Bee
Edited by
Romain Brette  and
Alain Destexhe
Ron D. Frostig
Affiliation:
University of California Irvine, USA
Cynthia H. Chen-Bee
Affiliation:
University of California Irvine, USA
Romain Brette
Affiliation:
Ecole Normale Supérieure, Paris
Alain Destexhe
Affiliation:
Centre National de la Recherche Scientifique (CNRS), Paris
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Summary

Introduction

The most popular technique for investigating the functional organization and plasticity of the cortex involves the use of a single microelectrode. It offers the advantage of recording action potentials and subthreshold activity directly from cortical neurons with high spatial (point) and temporal (millisecond) resolution sufficient to follow real-time changes in neuronal activity at any location along a volume of cortex, with the disadvantage that recordings are invasive to the cortex. In order to assess the functional representation of a sensory organ (e.g. a finger, a whisker), neurons are recorded from different cortical locations and the functional representation of the organ is then defined as the cortical region containing neurons responsive to stimulation of that organ (i.e. neurons that have receptive fields localized at the sensory organ). A change in the spatial distribution of neurons responsive to a given sensory organ and/or in their amplitude of response is typically taken as evidence for plasticity in the functional representation of that sensory organ (Merzenich et al., 1984). As a cortical functional representation could comprise thousands to millions of neurons distributed over a volume of cortex, the use of a single microelectrode to map a functional representation and its plasticity requires many recordings across a large cortical region, recordings that can only be obtained in a serial fashion and require many hours to complete, thus the animal is typically anesthetized.

Type
Chapter
Information
Handbook of Neural Activity Measurement , pp. 287 - 326
Publisher: Cambridge University Press
Print publication year: 2012

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References

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Husson, R.T. and Issa, N.P. (2009). Functional imaging with mitochondrial flavoprotein autofluorescence: theory, practice, and applications. In: R. D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
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Kalatsky, V.A. and Stryker, M.P. (2003). New paradigm for optical imaging: temporally encoded maps of intrinsic signal. Neuron, 38, 529–545.CrossRefGoogle ScholarPubMed
Kaur, S., Lazar, R. and Metherate, R. (2004). Intracortical pathways determine breadth of subthreshold frequency receptive fields in primary auditory cortex. J. Neurophysio., 91, 2551–2567.CrossRefGoogle ScholarPubMed
Keck, T., Mrsic-Flogel, T.D., Vaz Afonso, M., Eysel, U.T., Bonhoeffer, T. and Hubener, M. (2008). Massive restructuring of neuronal circuits during functional reorganization of adult visual cortex. Nature Neurosci., 11, 1162–1167.CrossRefGoogle ScholarPubMed
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Logothetis, N.K. and Pfeuffer, J. (2004). On the nature of the BOLD fMRI contrast mechanism. Magn. Reson. Imaging, 22, 1517–1531.CrossRefGoogle ScholarPubMed
Malonek, D. and Grinvald, A. (1996). Interactions between electrical activity and cortical microcirculation revealed by imaging spectroscopy: implications for functional brain mapping. Science, 272, 551–554.CrossRefGoogle ScholarPubMed
Masino, S.A., Kwon, M.C., Dory, Y. and Frostig, R.D. (1993). Characterization of functional organization within rat barrel cortex using intrinsic signal optical imaging through a thinned skull. Proc. Nati. Acad. Sci. USA, 90, 9998–10002.CrossRefGoogle ScholarPubMed
Mathiesen, C., Caesar, K., Akgoren, N. and Lauritzen, M. (1998). Modification of activity-dependent increases of cerebral blood flow by excitatory synaptic activity and spikes in rat cerebellar cortex. J. Physiol., 512 (2), 555–566.CrossRefGoogle ScholarPubMed
Mcloughlin, N.P. and Blasdel, G.G. (1998). Wavelength-dependent differences between optically determined functions maps from macaque striate cortex. NeuroImage, 7, 326–336.Google Scholar
Merzenich, M.M., Nelson, R.J., Stryker, M.P., Cynader, M.S., Schoppmann, A. and Zook, J. M. (1984). Somatosensory cortical map changes following digit amputation in adult monkeys. J. Comp. Neurol., 224, 591–605.CrossRefGoogle ScholarPubMed
Mukamel, R., Gelbard, H., Arieli, A., Hasson, U., Fried, I. and Malach, R. (2005). Coupling between neuronal firing, field potentials, and FMRI in human auditory cortex. Science, 309, 951–954.CrossRefGoogle ScholarPubMed
Nicolelis, M.A. and Ribeiro, S. (2002). Multielectrode recordings: the next steps. Curr. Opinion Neurobiol., 12, 602–606.CrossRefGoogle Scholar
Niessing, J., Ebisch, B., Schmidt, K.E., Niessing, M., Singer, W. and Galuske, R.A. (2005). Hemodynamic signals correlate tightly with synchronized gamma oscillations. Science, 309, 948–951.CrossRefGoogle ScholarPubMed
Petersen, C.C. (2007). The functional organization of the barrel cortex. Neuron, 56, 339–355.CrossRefGoogle ScholarPubMed
Prakash, N., Vanderhaeghen, P., Cohen-Cory, S., Frisen, J., Flanagan, J.G. and Frostig, R. D. (2000). Malformation of the functional organization of somatosensory cortex in adult ephrin-A5 knock-out mice revealed by in vivo functional imaging. J. Neurosci., 20, 5841–5847.CrossRefGoogle ScholarPubMed
Rauch, A., Rainer, G. and Logothetis, N.K. (2008). The effect of a serotonin-induced dissociation between spiking and perisynaptic activity on BOLD functional MRI. Proc. Nati. Acad. Sci. USA, 105, 6759–6764.CrossRefGoogle ScholarPubMed
Rector, D.M., Yao, X., Harper, R.M. and George, J.S. (2009). In-vivo observations of rapid scattered light changes associated with neurophysiological activity. In: R. D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
Reidl, J., Starke, J., Omer, D.B., Grinvald, A. and Spors, H. (2007). Independent component analysis of high-resolution imaging data identifies distinct functional domains. NeuroImage, 34, 94–108.CrossRefGoogle ScholarPubMed
Roland, P.E., Hanazawa, A., Undeman, C., Eriksson, D., Tompa, T., Nakamura, H., Valentiniene, S. and Ahmed, B. (2006). Cortical feedback depolarization waves: a mechanism of top-down influence on early visual areas. Proc. Nati. Acad. Sci. USA, 103, 12586–12591.CrossRefGoogle ScholarPubMed
Schiessl, I., Stetter, M., Mayhew, J.E., McLoughlin, N., Lund, J.S. and Obermayer, K. (2000). Blind signal separation from optical imaging recordings with extended spatial decorrelation. IEEE Trans. Biomed. Eng., 47, 573–577.CrossRefGoogle ScholarPubMed
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