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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.

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

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References

Bathellier, B., Van De Ville, D., Blu, T., Unser, M. and Carleton, A. (2007). Wavelet-based multi-resolution statistics for optical imaging signals: Application to automated detection of odour activated glomeruli in the mouse olfactory bulb. NeuroImage, 34, 1020–1035.CrossRefGoogle ScholarPubMed
Berger, T., Borgdorff, A., Crochet, S., Neubauer, F. B., Lefort, S., Fauvet, B., Ferezou, I., Carleton, A., Luscher, H.R. and Petersen, C.C. (2007). Combined voltage and calcium epifluorescence imaging in vitro and in vivo reveals subthreshold and suprathreshold dynamics of mouse barrel cortex. J. Neurophysio., 97, 3751–3762.CrossRefGoogle ScholarPubMed
Berwick, J., Johnston, D., Jones, M., Martindale, J., Martin, C., Kennerley, A.J., Redgrave, P., and Mayhew, J.E. (2008). Fine detail of neurovascular coupling revealed by spatiotemporal analysis of the hemodynamic response to single whisker stimulation in rat barrel cortex. J. Neurophysio., 99, 787–798.CrossRefGoogle ScholarPubMed
Bringuier, V., Chavane, F., Glaeser, L., and Fregnac, Y. (1999). Horizontal propagation of visual activity in the synaptic integration field of area 17 neurons. Science, 283, 695–699.CrossRefGoogle ScholarPubMed
Carmona, R.A., Hwang, W.L. and Frostig, R.D. (1995). Wavelet analysis for brain-function imaging. IEEE Trans. Med. Imaging, 14, 556–564.CrossRefGoogle ScholarPubMed
Chen-Bee, C. H., Kwon, M.C., Masino, S.A. and Frostig, R.D. (1996). Areal extent quantification of functional representations using intrinsic signal optical imaging. J. Neurosci. Methods, 68, 27–37.CrossRefGoogle ScholarPubMed
Chen-Bee, C. H., Polley, D.B., Brett-Green, B., Prakash, N., Kwon, M.C. and Frostig, R. D. (2000). Visualizing and quantifying evoked cortical activity assessed with intrinsic signal imaging. J. Neurosci. Methods, 97, 157–173.CrossRefGoogle ScholarPubMed
Chen-Bee, C. H., Agoncillo, T., Xiong, Y. and Frostig, R.D. (2007). The triphasic intrinsic signal: implications for functional imaging. J. Neurosci., 27, 572–4586.CrossRefGoogle ScholarPubMed
Chen, L.M., Friedman, R.M. and Roe, A.W. (2005). Optical imaging of SI topography in anesthetized and awake squirrel monkeys. J. Neurosci., 25, 7648–7659.CrossRefGoogle ScholarPubMed
Das, A. and Gilbert, C.D. (1995). Long-range horizontal connections and their role in cortical reorganization revealed by optical recording of cat primary visual cortex [see comments]. Nature, 375, 780–784.CrossRefGoogle Scholar
Fekete, T., Omer, D.B., Naaman, S. and Grinvald, A. (2009). Removal of spatial biological artifacts in functional maps by local similarity minimization. J. Neurosci. Methods, 178, 31–39.CrossRefGoogle ScholarPubMed
Feldman, D.E. and Brecht, M. (2005). Map plasticity in somatosensory cortex. Science, 310, 810–815.CrossRefGoogle ScholarPubMed
Ferezou, I., Bolea, S. and Petersen, C.C. (2006). Visualizing the cortical representation of whisker touch: voltage-sensitive dye imaging in freely moving mice. Neuron, 50, 617–629.CrossRefGoogle ScholarPubMed
Ferezou, I., Haiss, F., Gentet, L.J., Aronoff, R., Weber, B. and Petersen, C.C. (2007). Spatiotemporal dynamics of cortical sensorimotor integration in behaving mice. Neuron, 56, 907–923.CrossRefGoogle ScholarPubMed
Ferezou, I., Matyas, F. and Petersen, C.C.H. (2009). Imaging the brain in action – real-time voltage-sensitive dye imaging of sensorimotor cortex of awake behaving mice. In: R.D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
Fox, M.D. and Raichle, M.E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Revi., 8, 700–711.Google ScholarPubMed
Frostig, R.D., Lieke, E.E., Ts'o, D. Y. and Grinvald, A. (1990). Cortical functional architecture and local coupling between neuronal activity and the microcirculation revealed by in vivo high-resolution optical imaging of intrinsic signals. Proc. Nati. Acad. Sci. USA, 87, 6082–6086.CrossRefGoogle ScholarPubMed
Frostig, R.D., Xiong, Y., Chen-Bee, C.H., Kvasnak, E. and Stehberg, J. (2008). Large-scale organization of rat sensorimotor cortex based on a motif of large activation spreads. J. Neurosci., 28, 13274–13284.CrossRefGoogle ScholarPubMed
Gabbay, M., Brennan, C., Kaplan, E. and Sirovich, L. (2000). A principal components-based method for the detection of neuronal activity maps: application to optical imaging. NeuroImage, 11, 313–325.CrossRefGoogle ScholarPubMed
Grinvald, A. and Hildesheim, R. (2004). VSDI: a new era in functional imaging of cortical dynamics. Nature Revi, 5, 874–885.Google ScholarPubMed
Grinvald, A., Lieke, E., Frostig, R.D., Gilbert, C.D. and Wiesel, T.N. (1986). Functional architecture of cortex revealed by optical imaging of intrinsic signals. Nature, 324, 361–364.CrossRefGoogle ScholarPubMed
Grinvald, A., Lieke, E.E., Frostig, R.D. and Hildesheim, R. (1994). Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of macaque monkey primary visual cortex. J. Neurosci., 14, 2545–2568.CrossRefGoogle ScholarPubMed
Gurden, H., Uchida, N. and Mainen, Z.F. (2006). Sensory-evoked intrinsic optical signals in the olfactory bulb are coupled to glutamate release and uptake. Neuron, 52, 335–345.CrossRefGoogle ScholarPubMed
Hillman, E.M., Devor, A., Bouchard, M.B., Dunn, A.K., Krauss, G.W., Skoch, J., Bacskai, B.J., Dale, A.M. and Boas, D.A. (2007). Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation. NeuroImage, 35, 89–104.CrossRefGoogle ScholarPubMed
Hofer, S.B., Mrsic-Flogel, T.D., Bonhoeffer, T. and Hubener, M. (2006). Prior experience enhances plasticity in adult visual cortex. Nature neurosci., 9, 127–132.CrossRefGoogle ScholarPubMed
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
Kalatsky, V.A. (2009). Fourier approach to optical imaging. In: R. D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
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
Logothetis, N.K. (2008). What we can do and what we cannot do with fMRI. Nature, 453, 869–878.CrossRefGoogle Scholar
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 ScholarPubMed
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
Schiessl, I., Wang, W. and McLoughlin, N. (2008). Independent components of the haemodynamic response in intrinsic optical imaging. NeuroImage, 39, 634–646.CrossRefGoogle ScholarPubMed
Schummers, J., Yu, H. and Sur, M. (2008). Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science, 320, 1638–1643.CrossRefGoogle ScholarPubMed
Sharon, D., Jancke, D., Chavane, F., Na'aman, S. and Grinvald, A. (2007). Cortical response field dynamics in cat visual cortex. Cereb. Cortex, 17, 2866–2877.CrossRefGoogle ScholarPubMed
Sheth, S.A., Nemoto, M., Guiou, M., Walker, M., Pouratian, N., Hageman, N. and Toga, A.W. (2004). Columnar specificity of microvascular oxygenation and volume responses: implications for functional brain mapping. J. Neurosci., 24, 634–641.CrossRefGoogle ScholarPubMed
Shibuki, K., Hishida, R., Tohmi, M., Takahashi, K., Kitaura, H. and Kubota, Y. (2009). Flavoprotein fluorescence imaging of experience-dependent cortical plasticity in rodents. In: R. D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
Shoham, D., Glaser, D.E., Arieli, A., Kenet, T., Wijnbergen, C., Toledo, Y., Hildesheim, R. and Grinvald, A. (1999). Imaging cortical dynamics at high spatial and temporal resolution with novel blue voltage-sensitive dyes. Neuron, 24, 791–802.CrossRefGoogle ScholarPubMed
Siegel, R.M., Duann, J.R., Jung, T.P. and Sejnowski, T. (2007). Spatiotemporal dynamics of the functional architecture for gain fields in inferior parietal lobule of behaving monkey. Cereb. Cortex, 17, 378–390.Google ScholarPubMed
Slovin, H., Arieli, A., Hildesheim, R. and Grinvald, A. (2002). Long-term voltage-sensitive dye imaging reveals cortical dynamics in behaving monkeys. J. Neurophysio., 88, 3421–3438.CrossRefGoogle ScholarPubMed
Stetter, M., Schiessl, I., Otto, T., Sengpiel, F., Hubener, M., Bonhoeffer, T. and Obermayer, K. (2000). Principal component analysis and blind separation of sources for optical imaging of intrinsic signals. NeuroImage, 11, 482–490.CrossRefGoogle ScholarPubMed
Toth, L.J., Rao, S.C., Kim, D.S., Somers, D. and Sur, M. (1996). Subthreshold facilitation and suppression in primary visual cortex revealed by intrinsic signal imaging. Proc. Nati. Acad. Sci. USA, 93, 9869–9874.CrossRefGoogle ScholarPubMed
Ts'o, D.Y., Frostig, R.D., Lieke, E.E. and Grinvald, A. (1990). Functional organization of primate visual cortex revealed by high resolution optical imaging. Science, 249, 417–420.CrossRefGoogle ScholarPubMed
Vanzetta, I., Hildesheim, R. and Grinvald, A. (2005). Compartment-resolved imaging of activity-dependent dynamics of cortical blood volume and oximetry. J. Neurosci., 25, 2233–2244.CrossRefGoogle ScholarPubMed
Vanzetta, I. and Grinvald, A. (2008). Coupling between neuronal activity and microcirculation: implications for functional brain imaging. HFSP J., 2, 79–98.CrossRefGoogle ScholarPubMed
Viswanathan, A. and Freeman, R.D. (2007). Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity. Nature neurosci., 10, 1308–1312.CrossRefGoogle Scholar
Xerri, C. (2008). Imprinting of idyosyncratic experience in cortical sensory maps: Neural substrates of representational remodeling and correlative perceptual changes. Behavi. Brain Res., 192, 26–41.CrossRefGoogle ScholarPubMed
Bathellier, B., Van De Ville, D., Blu, T., Unser, M. and Carleton, A. (2007). Wavelet-based multi-resolution statistics for optical imaging signals: Application to automated detection of odour activated glomeruli in the mouse olfactory bulb. NeuroImage, 34, 1020–1035.CrossRefGoogle ScholarPubMed
Berger, T., Borgdorff, A., Crochet, S., Neubauer, F. B., Lefort, S., Fauvet, B., Ferezou, I., Carleton, A., Luscher, H.R. and Petersen, C.C. (2007). Combined voltage and calcium epifluorescence imaging in vitro and in vivo reveals subthreshold and suprathreshold dynamics of mouse barrel cortex. J. Neurophysio., 97, 3751–3762.CrossRefGoogle ScholarPubMed
Berwick, J., Johnston, D., Jones, M., Martindale, J., Martin, C., Kennerley, A.J., Redgrave, P., and Mayhew, J.E. (2008). Fine detail of neurovascular coupling revealed by spatiotemporal analysis of the hemodynamic response to single whisker stimulation in rat barrel cortex. J. Neurophysio., 99, 787–798.CrossRefGoogle ScholarPubMed
Bringuier, V., Chavane, F., Glaeser, L., and Fregnac, Y. (1999). Horizontal propagation of visual activity in the synaptic integration field of area 17 neurons. Science, 283, 695–699.CrossRefGoogle ScholarPubMed
Carmona, R.A., Hwang, W.L. and Frostig, R.D. (1995). Wavelet analysis for brain-function imaging. IEEE Trans. Med. Imaging, 14, 556–564.CrossRefGoogle ScholarPubMed
Chen-Bee, C. H., Kwon, M.C., Masino, S.A. and Frostig, R.D. (1996). Areal extent quantification of functional representations using intrinsic signal optical imaging. J. Neurosci. Methods, 68, 27–37.CrossRefGoogle ScholarPubMed
Chen-Bee, C. H., Polley, D.B., Brett-Green, B., Prakash, N., Kwon, M.C. and Frostig, R. D. (2000). Visualizing and quantifying evoked cortical activity assessed with intrinsic signal imaging. J. Neurosci. Methods, 97, 157–173.CrossRefGoogle ScholarPubMed
Chen-Bee, C. H., Agoncillo, T., Xiong, Y. and Frostig, R.D. (2007). The triphasic intrinsic signal: implications for functional imaging. J. Neurosci., 27, 572–4586.CrossRefGoogle ScholarPubMed
Chen, L.M., Friedman, R.M. and Roe, A.W. (2005). Optical imaging of SI topography in anesthetized and awake squirrel monkeys. J. Neurosci., 25, 7648–7659.CrossRefGoogle ScholarPubMed
Das, A. and Gilbert, C.D. (1995). Long-range horizontal connections and their role in cortical reorganization revealed by optical recording of cat primary visual cortex [see comments]. Nature, 375, 780–784.CrossRefGoogle Scholar
Fekete, T., Omer, D.B., Naaman, S. and Grinvald, A. (2009). Removal of spatial biological artifacts in functional maps by local similarity minimization. J. Neurosci. Methods, 178, 31–39.CrossRefGoogle ScholarPubMed
Feldman, D.E. and Brecht, M. (2005). Map plasticity in somatosensory cortex. Science, 310, 810–815.CrossRefGoogle ScholarPubMed
Ferezou, I., Bolea, S. and Petersen, C.C. (2006). Visualizing the cortical representation of whisker touch: voltage-sensitive dye imaging in freely moving mice. Neuron, 50, 617–629.CrossRefGoogle ScholarPubMed
Ferezou, I., Haiss, F., Gentet, L.J., Aronoff, R., Weber, B. and Petersen, C.C. (2007). Spatiotemporal dynamics of cortical sensorimotor integration in behaving mice. Neuron, 56, 907–923.CrossRefGoogle ScholarPubMed
Ferezou, I., Matyas, F. and Petersen, C.C.H. (2009). Imaging the brain in action – real-time voltage-sensitive dye imaging of sensorimotor cortex of awake behaving mice. In: R.D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
Fox, M.D. and Raichle, M.E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Revi., 8, 700–711.Google ScholarPubMed
Frostig, R.D., Lieke, E.E., Ts'o, D. Y. and Grinvald, A. (1990). Cortical functional architecture and local coupling between neuronal activity and the microcirculation revealed by in vivo high-resolution optical imaging of intrinsic signals. Proc. Nati. Acad. Sci. USA, 87, 6082–6086.CrossRefGoogle ScholarPubMed
Frostig, R.D., Xiong, Y., Chen-Bee, C.H., Kvasnak, E. and Stehberg, J. (2008). Large-scale organization of rat sensorimotor cortex based on a motif of large activation spreads. J. Neurosci., 28, 13274–13284.CrossRefGoogle ScholarPubMed
Gabbay, M., Brennan, C., Kaplan, E. and Sirovich, L. (2000). A principal components-based method for the detection of neuronal activity maps: application to optical imaging. NeuroImage, 11, 313–325.CrossRefGoogle ScholarPubMed
Grinvald, A. and Hildesheim, R. (2004). VSDI: a new era in functional imaging of cortical dynamics. Nature Revi, 5, 874–885.Google ScholarPubMed
Grinvald, A., Lieke, E., Frostig, R.D., Gilbert, C.D. and Wiesel, T.N. (1986). Functional architecture of cortex revealed by optical imaging of intrinsic signals. Nature, 324, 361–364.CrossRefGoogle ScholarPubMed
Grinvald, A., Lieke, E.E., Frostig, R.D. and Hildesheim, R. (1994). Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of macaque monkey primary visual cortex. J. Neurosci., 14, 2545–2568.CrossRefGoogle ScholarPubMed
Gurden, H., Uchida, N. and Mainen, Z.F. (2006). Sensory-evoked intrinsic optical signals in the olfactory bulb are coupled to glutamate release and uptake. Neuron, 52, 335–345.CrossRefGoogle ScholarPubMed
Hillman, E.M., Devor, A., Bouchard, M.B., Dunn, A.K., Krauss, G.W., Skoch, J., Bacskai, B.J., Dale, A.M. and Boas, D.A. (2007). Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation. NeuroImage, 35, 89–104.CrossRefGoogle ScholarPubMed
Hofer, S.B., Mrsic-Flogel, T.D., Bonhoeffer, T. and Hubener, M. (2006). Prior experience enhances plasticity in adult visual cortex. Nature neurosci., 9, 127–132.CrossRefGoogle ScholarPubMed
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
Kalatsky, V.A. (2009). Fourier approach to optical imaging. In: R. D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
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
Logothetis, N.K. (2008). What we can do and what we cannot do with fMRI. Nature, 453, 869–878.CrossRefGoogle Scholar
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
Schiessl, I., Wang, W. and McLoughlin, N. (2008). Independent components of the haemodynamic response in intrinsic optical imaging. NeuroImage, 39, 634–646.CrossRefGoogle ScholarPubMed
Schummers, J., Yu, H. and Sur, M. (2008). Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science, 320, 1638–1643.CrossRefGoogle ScholarPubMed
Sharon, D., Jancke, D., Chavane, F., Na'aman, S. and Grinvald, A. (2007). Cortical response field dynamics in cat visual cortex. Cereb. Cortex, 17, 2866–2877.CrossRefGoogle ScholarPubMed
Sheth, S.A., Nemoto, M., Guiou, M., Walker, M., Pouratian, N., Hageman, N. and Toga, A.W. (2004). Columnar specificity of microvascular oxygenation and volume responses: implications for functional brain mapping. J. Neurosci., 24, 634–641.CrossRefGoogle ScholarPubMed
Shibuki, K., Hishida, R., Tohmi, M., Takahashi, K., Kitaura, H. and Kubota, Y. (2009). Flavoprotein fluorescence imaging of experience-dependent cortical plasticity in rodents. In: R. D., Frostig (editor), In Vivo Optical Imaging of Brain Function (2nd edition). Boca Raton, FL: CRC Press.Google ScholarPubMed
Shoham, D., Glaser, D.E., Arieli, A., Kenet, T., Wijnbergen, C., Toledo, Y., Hildesheim, R. and Grinvald, A. (1999). Imaging cortical dynamics at high spatial and temporal resolution with novel blue voltage-sensitive dyes. Neuron, 24, 791–802.CrossRefGoogle ScholarPubMed
Siegel, R.M., Duann, J.R., Jung, T.P. and Sejnowski, T. (2007). Spatiotemporal dynamics of the functional architecture for gain fields in inferior parietal lobule of behaving monkey. Cereb. Cortex, 17, 378–390.Google ScholarPubMed
Slovin, H., Arieli, A., Hildesheim, R. and Grinvald, A. (2002). Long-term voltage-sensitive dye imaging reveals cortical dynamics in behaving monkeys. J. Neurophysio., 88, 3421–3438.CrossRefGoogle ScholarPubMed
Stetter, M., Schiessl, I., Otto, T., Sengpiel, F., Hubener, M., Bonhoeffer, T. and Obermayer, K. (2000). Principal component analysis and blind separation of sources for optical imaging of intrinsic signals. NeuroImage, 11, 482–490.CrossRefGoogle ScholarPubMed
Toth, L.J., Rao, S.C., Kim, D.S., Somers, D. and Sur, M. (1996). Subthreshold facilitation and suppression in primary visual cortex revealed by intrinsic signal imaging. Proc. Nati. Acad. Sci. USA, 93, 9869–9874.CrossRefGoogle ScholarPubMed
Ts'o, D.Y., Frostig, R.D., Lieke, E.E. and Grinvald, A. (1990). Functional organization of primate visual cortex revealed by high resolution optical imaging. Science, 249, 417–420.CrossRefGoogle ScholarPubMed
Vanzetta, I., Hildesheim, R. and Grinvald, A. (2005). Compartment-resolved imaging of activity-dependent dynamics of cortical blood volume and oximetry. J. Neurosci., 25, 2233–2244.CrossRefGoogle ScholarPubMed
Vanzetta, I. and Grinvald, A. (2008). Coupling between neuronal activity and microcirculation: implications for functional brain imaging. HFSP J., 2, 79–98.CrossRefGoogle ScholarPubMed
Viswanathan, A. and Freeman, R.D. (2007). Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity. Nature neurosci., 10, 1308–1312.CrossRefGoogle ScholarPubMed
Xerri, C. (2008). Imprinting of idyosyncratic experience in cortical sensory maps: Neural substrates of representational remodeling and correlative perceptual changes. Behavi. Brain Res., 192, 26–41.CrossRefGoogle ScholarPubMed

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