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9 - Voltage-sensitive dye imaging

Published online by Cambridge University Press:  05 October 2012

By
S. Chemla  and
F. Chavane
Edited by
Romain Brette  and
Alain Destexhe
S. Chemla
Affiliation:
University of Lethbridge, Canada
F. Chavane
Affiliation:
Aix-Marseille Université, Marseille, France
Romain Brette
Affiliation:
Ecole Normale Supérieure, Paris
Alain Destexhe
Affiliation:
Centre National de la Recherche Scientifique (CNRS), Paris
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Summary

Introduction

Modern neuroimaging and computational neuroscience are two recent neuroscience disciplines that are very important for understanding brain mechanisms. Optical imaging gives the opportunity of observing the brain in activity at the level of large populations of neurons with high resolution. Many types of optical imaging techniques exist, but only two are usually used in vivo (see Grinvald et al., 1999, for a detailed review): the first is based on intrinsic optical signals and records brain activity indirectly, the second is based on voltage-sensitive dyes (VSDs) and reports postsynaptic neuronal activation in real time. In this review, we focus on the second technique, aiming at a better understanding of the origin of the optical signal. Extensive reviews of VSDI have been published elsewhere (Roland, 2002; Grinvald and Hildesheim, 2004).

This amazing technique is based on complex interaction with the system which is not yet fully understood. Indeed, the recorded signal (VSD signal) originates from a large amount of intermingled neuronal and glial membrane components and it seems difficult to isolate the contributions from the different components. Combined intracellular recording with VSDI has demonstrated a linear correspondence between the VSD signal and membrane potential of an individual neuron, but so far no studies have focused on what exactly the VSD signal actually measures when applied to a cortical population in vivo.

Experimental approaches are not really feasible because the available methodologies do not offer the possibility to inspect simultaneously all the components that may contribute to the signal.

Type
Chapter
Information
Handbook of Neural Activity Measurement , pp. 327 - 361
Publisher: Cambridge University Press
Print publication year: 2012

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References

Ahmed, B., Hanazawa, A., Undeman, C., Eriksson, D., Valentiniene, S. and Roland, P. E. (2008). Cortical dynamics subserving visual apparent motion. Cereb. Cortex, 18 (12), 2796–2810.CrossRefGoogle ScholarPubMed
Aitken, J. T. (1955). Observations on the larger anterior horn cells in the lumbar region of the cat's spinal cord. J. Anat., 89, 571.Google Scholar
Albowitz, B. and Kuhnt, U. (1993). The contribution of intracortical connections to horizontal spread of activity in the neocortex as revealed by voltage sensitive dyes and a fast optical recording method. Eur. J. Neurosci., 5 (10), 1349–1359.CrossRefGoogle Scholar
Albrecht, D. and Hamilton, D. (1982). Striate cortex of monkey and cat: contrast response function. Neurophysiol., 48 (1), 217–233.CrossRefGoogle ScholarPubMed
Amit, D. and Brunel, N. (1997). Model of global spontaneous activity and local structured delay activity during delay periods in the cerebral cortex. Cereb. Cortex, 7, 237–252.CrossRefGoogle ScholarPubMed
Antic, S. and Zecevic, D. (1995). Optical signals from neurons with internally applied voltage-sensitive dyes. J. Neurosci., 15 (2), 1392–1405.CrossRefGoogle ScholarPubMed
Antic, S., Major, G. and Zecevic, D. (1999). Fast optical recordings of membrane potential changes from dendrites of pyramidal neurons. J. Neurophysiol., 82 (3), 1615–1621.CrossRefGoogle ScholarPubMed
Arieli, A., Shoham, D., Hildesheim, R. and Grinvald, A. (1995). Coherent spatiotemporal patterns of ongoing activity revealed by real-time optical imaging coupled with single-unit recording in the cat visual cortex. J. Neurophysiol., 73 (5), 2072–2093.CrossRefGoogle ScholarPubMed
Arieli, A., Sterkin, A., Grinvald, A. and Aerster, A. (1996). Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science, 273 (5283), 1868–1871.CrossRefGoogle ScholarPubMed
Benucci, A., Robert, A. F. and Carandini, M. (2007). Standing waves and traveling waves distinguish two circuits in visual cortex. Neuron, 55 (1), 103–117.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. Neurophysiol., 97 (5), 3751–3762.CrossRefGoogle ScholarPubMed
Binzegger, T., Douglas, R. and Martin, K. (2004). A quantitative map of the circuit of cat primary visual cortex. Neurosci., 24 (39), 8441–8453.CrossRefGoogle ScholarPubMed
Blasdel, G. G. and Salama, G. (1986). Voltage-sensitive dyes reveal a modular organization in monkey striate cortex. Nature, 321 (6070), 579–585.CrossRefGoogle ScholarPubMed
Bolz, J., Novak, N. and Staiger, V. (1992). Formation of specific afferent connections in organotypic slice cultures from rat visual cortex cocultured with lateral geniculate nucleus. J. Neurosci., 12 (8), 3054–3070.CrossRefGoogle ScholarPubMed
Bonhoeffer, T. and Grinvald, A. (1991). Iso-orientation domains in cat visual cortex are arranged in pinwheel-like patterns. Nature, 353 (6343), 429–431.CrossRefGoogle ScholarPubMed
Borg-Graham, L., Monier, C. and Fregnac, Y. (1998). Visual input evokes transient and strong shunting inhibition in visual cortical neurons. Nature, 393, 369–373.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 (5402), 695–699.CrossRefGoogle ScholarPubMed
Brown, C. E., Aminoltejari, K., Erb, H., Winship, I. R. and Murphy, T. H. (2009). In vivo voltage-sensitive dye imaging in adult mice reveals that somatosensory maps lost to stroke are replaced over weeks by new structural and functional circuits with prolonged modes of activation within both the peri-infarct zone and distant sites. J. Neurosci., 29 (6), 1719–1734.CrossRefGoogle Scholar
Brunel, N. and Hakim, V. (1999). Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural Comput., 11 (7), 1621–1671.CrossRefGoogle ScholarPubMed
Bush, P. and Sejnowski, T., (1993). Reduced compartmental models of neocortical pyramidal cells. Neurosci. Methods, 46, 159–166.CrossRefGoogle ScholarPubMed
Cameron, R. S. and Rakic, P. (1991). Glial cell lineage in the cerebral cortex: a review and synthesis. Glia, 4, 124–137.CrossRefGoogle ScholarPubMed
Carlson, G. C. and Coulter, D. A. (2008). In vitro functional imaging in brain slices using fast voltage-sensitive dye imaging combined with whole-cell patch recording. Nature Protocols, 3 (2), 249–255.CrossRefGoogle ScholarPubMed
Chemla, S. and Chavane, F. (2010a). A biophysical cortical column model to study the multi-component origin of the vsd signal. NeuroImage, 53 (2), 420–438.CrossRefGoogle Scholar
Chemla, S. and Chavane, F. (2010b). Voltage-sensitive dye imaging: technique review and models. J. Physiol. Paris, 104 (1–2), 40–50.CrossRefGoogle ScholarPubMed
Cinelli, A. R. and Salzberg, B. M. (1990). Multiple site optical recording of transmembrane voltage (msortv), single-unit recordings, and evoked field potentials from the olfactory bulb of skate (Raja erinacea). J. Neurophysiol., 64 (6), 1767–1790.CrossRefGoogle Scholar
Cinelli, A. R. and Salzberg, B. M. (1992). Dendritic origin of late events in optical recordings from salamander olfactory bulb. J. Neurophysiol., 68 (3), 786–806.CrossRefGoogle ScholarPubMed
Civillico, E. F. and Contreras, D. (2006). Integration of evoked responses in supragranular cortex studied with optical recordings in vivo. J. Membr. Biol., 96 (1), 336–351.Google ScholarPubMed
Cohen, L., Salzberg, B. M., Davila, H. V., Ross, W. N., Landowne, D., Waggoner, A. S. and Wang, C. H. (1974). Changes in axon fluorescence during activity: molecular probes of membrane potential. J. Membr. Biol., 19 (1), 1–36.CrossRefGoogle ScholarPubMed
Contreras, D. and Llinas, R. (2001). Voltage-sensitive dye imaging of neocortical spatiotemporal dynamics to afferent activation frequency. J. Neurosci., 21 (23), 9403–9413.CrossRefGoogle ScholarPubMed
Davila, H. V., Salzberg, B. M., Cohen, L. B. and Waggoner, A. S. (1973). A large change in axon fluorescence that provides a promising method for measuring membrane potential. Nature (London) New Biol., 241 (109), 159–160.Google ScholarPubMed
Derdikman, D., Hildesheim, R., Ahissar, E., Arieli, A. and Grinvald, A. (2003). Imaging spatiotemporal dynamics of surround inhibition in the barrels somatosensory cortex. J. Neurosci., 23 (8), 3100–3105.CrossRefGoogle ScholarPubMed
Destexhe, A., Rudolph, M., Fellous, J. and Sejnowski, T. (2001). Fluctuating synaptic conductances recreate in-vivo-like activity in neocortical neurons. Neuroscience, 107, 13–24.CrossRefGoogle ScholarPubMed
Douglas, R. J. and Martin, K. A. C. (1990). Neocortex. In: G, Shepeherd (editor), Synaptic Organization of the Brain. New York: Oxford University Press, pp. 220–248.Google Scholar
Douglas, R. and Martin, K. A. C. (2004). Neuronal circuit of the neocortex. Ann. Rev. Neurosci., 27, 419.CrossRefGoogle Scholar
Eberwine, J. (2001). Molecular biological of axons: a turning point…Neuron, 32 (6), 959–960.CrossRefGoogle Scholar
Ebner, T. J. and Chen, G. (1995). Use of voltage-sensitive dyes and optical recordings in the central nervous system. Prog. Neurobiol., 46 (5), 463–506.CrossRefGoogle ScholarPubMed
El Boustani, S. and Destexhe, A. (2009). A master equation formalism for macroscopic modeling of asynchronous irregular activity states. Neural Comput., 21 (1), 46–100.CrossRefGoogle ScholarPubMed
Faugeras, O., Grimbert, F. and Slotine, J.-J. (2008). Abolute stability and complete synchronization in a class of neural fields models. SIAM J. Appl. Math., 61 (1), 205–250.Google Scholar
Faugeras, O., Touboul, J. and Cessac, B. (2009). A constructive mean-field analysis of multi-population neural networks with random synaptic weights and stochastic inputs. Front. Comput. Neurosci., 3 (1), doi:10.3389/neuro.10.001.2009.CrossRefGoogle ScholarPubMed
Ferezou, I., Bolea, S. and Petersen, C. C. H. (2006). Visualizing the cortical representation of whisker touch: voltage-sensitive dye imaging in freely moving mice. Neuron, 50, 617–629.CrossRefGoogle ScholarPubMed
Geisler, C., Brunel, N. and Wang, X.-J. (2005). Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges. J. Neurophysiol., 94, 4344–4361.CrossRefGoogle ScholarPubMed
Grimbert, F., Faugeras, O. and Chavane, F. (2007). From neural fields to VSD optical imaging. In: Sixteenth Annnal Computational Neuroscience Meeting, CNS.www.cnsorg.org.Google Scholar
Grimbert, F., Faugeras, O. and Chavane, F. (2008). Neural field model of VSD optical imaging signals. In: Areadne08. www.areadne.org/
Grinvald, A. and Hildesheim, R. (2004). VSDI: a new era in functional imaging of cortical dynamics. Nature, 5, 874–885.Google ScholarPubMed
Grinvald, A., Manker, A. and Segal, M. (1982). Visualization of the spread of electrical activity in rat hippocampal slices by voltage-sensitive optical probes. J. Physiol., 333, 269–291.CrossRefGoogle ScholarPubMed
Grinvald, A., Anglister, L., Freeman, J. A., Hildesheim, R. and Manker, A. (1984). Real time optical imaging of naturally evoked electrical activity in the intact frog brain. Nature, 308 (5962), 848–850.CrossRefGoogle 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 (6095), 361–364.CrossRefGoogle ScholarPubMed
Grinvald, A., Frostig, R. D., Siegel, R. M. and Bartfeld, E. (1991). High-resolution optical imaging of functional brain architecture in the awake monkey. Proc. Natl. Acad. Sci. USA, 88 (24), 11559–11563.CrossRefGoogle ScholarPubMed
Grinvald, A., Lieke, 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
Grinvald, A., Shoham, D., Shmuel, A., Glaser, D., Vanzetta, I., Shtoyerman, E., Slovin, H. and Arieli, A. (1999). In-vivo optical imaging of cortical architecture and dynamics. In: U., Windhorst and H., Johansson (editors), Modern Techniques in Neuroscience Research. New York: Springer, pp. 893–969.Google Scholar
Gupta, R. G., Salzberg, B. M., Grinvald, A., Cohen, L., Kamino, K., Boyle, M. B., Wag-goner, S. and Wang, C. H. (1981). Improvements in optical methods for measuring rapid changes in membrane potential. J. Membr. Biol., 58 (2), 123–137.CrossRefGoogle ScholarPubMed
Haeusler, S. and Maass, W. (2007). A statistical analysis of information-processing properties of lamina-specific cortical microcircuits models. Cereb. Cortex, 17, 149–162.Google ScholarPubMed
Hines, M. and Carnevale, N. (1997). The neuron simulation environment. Neural Comput., 9, 1179–1209.CrossRefGoogle ScholarPubMed
Hodgkin, A. and Huxley, A. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol., 117, 500–544.CrossRefGoogle ScholarPubMed
Horton, J. and Adams, D. (2005). The cortical column: a structure without a function. Philos. Trans. R. Soc. London B. Ser., 360 (1456), 837–862.CrossRefGoogle ScholarPubMed
Hubel, D. and Wiesel, T. (1962). Receptive fields, binocular interaction and functional architecture in the cat visual cortex. J. Physiol., 160, 106–154.CrossRefGoogle Scholar
Hubel, D. and Wiesel, T. (1965). Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. J. Neurophysiol., 28, 229–289.CrossRefGoogle Scholar
Hubel, D. and Wiesel, T. (1977). Functional architecture of macaque monkey. Proc. R. Soc. London, Ser. B, 198, 1–59.CrossRefGoogle ScholarPubMed
Hubel, D. H., Wiesel, T. N. and Stryker, M. P. (1977). Orientation columns in macaque monkey visual cortex demonstrated by the 2-deoxyglucose autoradiographic technique. Nature, 269 (5626), 328–330.CrossRefGoogle ScholarPubMed
Hubener, M., Shoham, D., Grinvald, A. and Bonhoeffer, T. (1997). Spatial relationships among three columnar systems in cat area 17. J. Neurosci., 17 (23), 9270–9284.CrossRefGoogle ScholarPubMed
Jancke, D., Chavane, F., Naaman, S. and Grinvald, A. (2004). Imaging cortical correlates of illusion in early visual cortex. Nature, 428, 423–426.CrossRefGoogle ScholarPubMed
Jin, W., Zhang, R. and Wu, J. (2002). Voltage-sensitive dye imaging of population neuronal activity in cortical tissue. J. Neurosci. Methods, 115, 13–27.CrossRefGoogle ScholarPubMed
Kauer, J. S. (1988). Real-time imaging of evoked activity in local circuits of the salamander olfactory bulb. Nature, 331 (6152), 166–168.CrossRefGoogle ScholarPubMed
Kee, M. Z., Wuskell, J. P., Loew, L. M., Augustine, G. J. and Sekino, Y. (2009). Imaging activity of neuronal populations with new long-wavelength voltage-sensitive dyes. Brain Cell. Biol., 36 (5–6), 157–172.Google Scholar
Kelly, J. P. and Van Essen, D. C. (1974). Cell structure and function in the visual cortex of the cat. J. Physiol., 238, 515–547.CrossRefGoogle ScholarPubMed
Kennedy, C., Des Rosiers, M., Sakurada, O., Shinohara, M., Reivich, M., Jehle, J. and Sokoloff, L. (1976). Metabolic mapping of the primary visual system of the monkey by means of the autoradiographic (14c)deoxyglucose technique. Proc. Natl. Acad. Sci. USA, 73 (11), 4230–4234.CrossRefGoogle ScholarPubMed
Kisvarday, Z., Toth, E., Rausch, M. and Eysel, U. (1997). Orientation-specific relationship between populations of excitatory and inhibitory lateral connections in the visual cortex of the cat. Cereb. Cortex, 7 (7), 605–618.CrossRefGoogle ScholarPubMed
Kleinfeld, D. and Delaney, K. (1996). Distributed representation of vibrissa movement in the upper layers of somatosensory cortex revealed with voltage-sensitive dyes. J. Comp. Neurol., 375, 89–108.3.0.CO;2-K>CrossRefGoogle ScholarPubMed
Kohonen, T. (2001). Self-Organizing Maps (3rd edition). New York: Springer.CrossRefGoogle Scholar
Konnerth, A. and Orkand, R. K. (1986). Voltage-sensitive dyes measure potential changes in axons and glia of the frog optic nerve. Neurosci. Lett., 66 (1), 49–54.CrossRefGoogle ScholarPubMed
Konnerth, A., Obaid, A. L. and Salzberg, B. M. (1987). Optical recording of electrical activity from parallel fibres and other cell types in skate cerebellar slices in vitro. J. Physiol., 393, 681–702.CrossRefGoogle ScholarPubMed
Konnerth, A., Orkand, P. M. and Orkand, R. K. (1988). Optical recording of electrical activity from axons and glia of frog optic nerve: potentiometric dye responses and morphometrics. Glia, 1 (3), 225–232.CrossRefGoogle ScholarPubMed
Kubota, M., Hosokawa, Y. and Horikawa, J. (2006). Layer-specific short-term dynamics in network activity in the cerebral cortex. NeuroReport, 17 (11), 1107–1110.CrossRefGoogle ScholarPubMed
La Rota, C. (2003). Analyse de l'activité électrique multi-ties du cortex auditif chez le cobaye. Ph.D. thesis, Université Joseph Fourier, Grenoble I.Google Scholar
Laaris, N. and Keller, A. (2002). Functional independence of layer IV barrels. J. Neurophysiol., 87 (2), 1028–1034.CrossRefGoogle ScholarPubMed
Lev-Ram, V. and Grinvald, A. (1986). Ca2+− and K+-dependent communication between central nervous system myelinated axons and oligodendrocytes revealed by voltage-sensitive dyes. Proc. Natl. Acad. Sci. USA, 83 (17), 6651–6655.CrossRefGoogle ScholarPubMed
LeVay, S., Connolly, M., Houde, J. and Van Essen, D. (1985). The complete pattern of ocular dominance stripes in the striate cortex and visual field of the macaque monkey. J. Neurosci., 5, 486–501.CrossRefGoogle ScholarPubMed
Lippert, M. T., Takagaki, K., Xu, W., Huang, X. and Wu, J. Y. (2007). Methods for voltage-sensitive dye imaging of rat cortical activity with high signal-to-noise ratio. Neurophysiol., 98, 502–512.CrossRefGoogle ScholarPubMed
Manis, P. B. and Freeman, J. A. (1988). Fluorescence recordings of electrical activity in goldfish optic tectum in vitro. J. Neurosci., 8 (2), 383–394.CrossRefGoogle ScholarPubMed
Markounikau, V., Igel, C., Grinvald, A. and Jancke, D. (2010). A dynamic neural field model of mesoscopic cortical activity captured with voltage-sensitive dye imaging. PLoS Comput. Biol., 6 (9), 1–14.CrossRefGoogle ScholarPubMed
Miikkulainen, R., Bednar, J. A., Choe, Y. and Sirosh, J. (2005). Computational Maps in the Visual Cortex. Berlin: Springer.Google Scholar
Mountcastle, V. (1957). Modality and topographic properties of single neurons of cat's somatosensory cortex. Neurophysiol., 20, 408–434.CrossRefGoogle Scholar
Nelson, D. A. and Katz, L. C. (1995). Emergence of functional circuits in ferret visual cortex visualized by optical imaging. Neuron, 15 (1), 23–34.CrossRefGoogle ScholarPubMed
Nowak, L. G., Azouz, R., Sanchez-Vives, M. V., Gray, C. and McCormick, D. (2003). Electrophysiological classes of cat primary visual cortical neurons in vivo as revealed by quantitative analyses. J. Neurophysiol., 89, 1541–1566.CrossRefGoogle ScholarPubMed
Orbach, H. S. and Cohen, L. B. (1983). Optical monitoring of activity from many areas of the in vitro and in vivo salamander olfactory bulb: a new method for studying functional organization in the vertebrate central nervous system. J. Neurosci., 3, 2251–2262.CrossRefGoogle ScholarPubMed
Orbach, H. S. and Van Essen, D. C. (1993). In vivo tracing of pathways and spatio-temporal activity patterns in rat visual cortex using voltage sensitive dyes. Exp. Brain Res., 94 (3), 371–392.CrossRefGoogle ScholarPubMed
Orbach, H. S., Cohen, L. B. and Grinvald, A. (1985). Optical mapping of electrical activity in rat somatosensory and visual cortex. J. Neurosci., 5, 1886–1895.CrossRefGoogle ScholarPubMed
Petersen, C. and Sakmann, B. (2001). Functional independent columns of rat somatosensory barrel cortex revealed with voltage-sensitive dye imaging. J. Neurosci., 21 (21), 8435–8446.CrossRefGoogle ScholarPubMed
Petersen, C., Grinvald, A. and Sakmann, B. (2003a). Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell voltage recordings and neuron reconstructions. J. Neurosci., 23 (3), 1298–1309.CrossRefGoogle ScholarPubMed
Petersen, C., Hahn, T., Mehta, M., Grinvald, A. and Sakmann, B. (2003b). Interaction of sensory responses with spontaneous depolarization in layer 2/3 barrel cortex. Proc. Natl. Acad. Sci. USA, 100 (23), 13638–13643.CrossRefGoogle ScholarPubMed
Raizada, R. and Grossberg, S. (2003). Towards a theory of the laminar architecture of the cerebral cortex: computational clues from the visual system. Cereb. Cortex, 13, 100–113.CrossRefGoogle ScholarPubMed
Rangan, A. V., Cai, D. and McLaughlin, D. W. (2005). Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex. Proc. Natl. Acad. Sci. USA, 102 (52), 18793–18800.CrossRefGoogle ScholarPubMed
Reynaud, A., Barthelemy, F., Masson, G. and Chavane, F. (2007). Input-ouput transformation in the visuo-oculomotor network. Arch. Ital. Biol., 145, 251–262.Google Scholar
Roland, P. E. (2002). Dynamic depolarization fields in the cerebral cortex. Trends Neurosci., 25, 183–190.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. Natl. Acad. Sci. USA, 103 (33), 12586–12591.CrossRefGoogle ScholarPubMed
Ross, W. N., Salzberg, B. M., Cohen, L. B., Grinvald, A., Davila, H. V., Waggoner, A. S. and Wang, C. H. (1977). Changes in absorption, fluorescence, dichroism, and birefringence in stained giant axons: optical measurements of membrane potential. J. Membr. Biol., 33 (1–2), 141–183.CrossRefGoogle Scholar
Rubin, B. D. and Katz, L. C. (1999). Optical imaging of odorant representations in the mammalian olfactory bulb. Neuron, 23 (3), 499–511.CrossRefGoogle ScholarPubMed
Salin, P. and Bullier, J. (1995). Corticocortical connections in the visual system: structure and function. Psychol. Bull., 75, 107–154.Google ScholarPubMed
Salzberg, B. M., Davila, H. V. and Cohen, L. B. (1973). Optical recording of impulses in individual neurons of an invertebrate central nervous system. Nature, 246, 508–509.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
Seidemann, E., Arieli, A., Grinvald, A. and Slovin, H. (2002). Dynamics of depolarization and hyperpolarization in the frontal cortex and saccade goal. Science, 295 (5556), 862–865.CrossRefGoogle ScholarPubMed
Sharon, D. and Grinvald, A. (2002). Dynamics and constancy in cortical spatiotemporal patterns of orientation processing. Science, 295 (5554), 512–515.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 (12), 2866–2877.CrossRefGoogle ScholarPubMed
Shoham, D., Glaser, D., Arieli, A., Kenet, T., Wijnbergeb, 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 (4), 791–802.CrossRefGoogle ScholarPubMed
Sholl, D. A. 1955. The organization of the visual cortex in the cat. J. Anat., 89, 33–46.Google ScholarPubMed
Sirosh, J. and Miikkulainen, R. (1994). Cooperative self-organization of afferent and lateral connections in cortical maps. Biol. Cybernet., 71, 66–78.CrossRefGoogle Scholar
Sit, Y. F. and Miikkulainen, R. (2007). A computational model of the signals in optical imaging with voltage-sensitive dyes. Neurocomputing, 70 (10–12), 1853–1857.CrossRefGoogle Scholar
Slovin, H., Arieli, A., Hildesheim, R. and Grinvald, A. (2002). Long-term voltage-sensitive dye imaging reveals cortical dynamics in behaving monkeys. J. Neurophysiol., 88 (6), 3421–3438.CrossRefGoogle ScholarPubMed
Spors, H. and Grinvald, A. (2002). Spatio-temporal dynamics of odor representations in the mammalian olfacgtory bulb. Neuron, 34 (2), 301–315.CrossRefGoogle ScholarPubMed
Sterkin, A., Lampl, I., Ferster, D., Grinvald, A. and Arieli, A. (1998). Realtime optical imaging in cat visual cortex exhibits high similarity to intracellular activity. Neurosci. Lett., 51, S41.Google Scholar
Stuart, G., Spruston, N., Sakmann, B. and Hausser, M. (1997). Action potential initiation and backpropagation in neurons of the mammalian CNS. Trends Neurosci., 20 (3), 125–131.CrossRefGoogle ScholarPubMed
Symes, A. and Wennekers, T. (2009). Spatiotemporal dynamics in the cortical microcircuit: a modelling study of primary visual cortex layer 2/3. Neural Networks, 22 (8), 1079–1092.CrossRefGoogle ScholarPubMed
Takagaki, K., Lippert, M. T., Dann, B., Wanger, T. and Ohl, F. W. (2008). Normalization of voltage-sensitive dye signal with functional activity measures. PloS one, 3 (12), 1–12.CrossRefGoogle ScholarPubMed
Tasaki, I., Watanabe, A. and Carnay, L. (1968). Changes in fluorescence, turbidity, and bireference associated with nerve excitation. Proc. Natl. Acad. Sci. USA, 61, 883–888.CrossRefGoogle ScholarPubMed
Thomson, A. and Lamy, C. (2007). Functional maps of neocortical local circuitry. Front. Neurosci., 1 (1), 19–42.CrossRefGoogle ScholarPubMed
Thomson, A. and Morris, O. (2002). Selectivity in the inter-laminar connections made by neocortical neurones. J. Neurocytol., 31 (3–5), 239–246.CrossRefGoogle ScholarPubMed
Tootell, R., Silverman, M., Switked, E. and De Valois, R. (1982). Deoxyglucose analysis of retinotopic organization in primate striate cortex. Science, 218 (4575), 902–904.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 (4967), 417–420.CrossRefGoogle ScholarPubMed
Tsunoda, K., Yamane, Y., Nishizaki, M. and Tanifuji, M. (2001). Complex objects are represented in macaque inferotemporal cortex by the combination of feature columns. Nature Neurosci., 4 (8), 832–838.CrossRefGoogle ScholarPubMed
Tucker, T. R. and Katz, L. C. (2003a). Recruitment of local inhibitory networks by horizontal connections in layer 2/3 of ferret visual cortex. J. Neurophysiol., 89 (1), 501–512.Google ScholarPubMed
Tucker, T. R. and Katz, L. C. (2003b). Spatiotemporal patterns of excitation and inhibition evoked by the horizontal network in layer 2/3 of ferret visual cortex. J. Neurophysiol., 89 (1), 488–500.Google ScholarPubMed
van Vreeswijk, C. and Sompolinsky, H. (1998). Chaotic balanced state in a model of cortical circuits. Neural Comput., 10 (6), 1321–1371.Google Scholar
Waggoner, A. S. and Grinvald, A. (1977). Mechanisms of rapid optical changes of potential sensitive dyes. Ann. NY Acad. Sci., 30 (303), 217–241.Google Scholar
Waters, J., Schaefer, A. and Sakmann, B. (2005). Backpropagating action potentials in neurones: measurement, mechanisms and potential functions. Prog. Biophys. Mol. Biol., 87 (1), 145–170.CrossRefGoogle ScholarPubMed
Wiesel, T. N., Hubel, D. H. and Lam, D. M. (1974). Autoradiographic demonstration of ocular-dominance columns in the monkey striate cortex by means of transneuronal transport. Brain Res., 79 (2), 273–279.CrossRefGoogle ScholarPubMed
Wilson, H. and Cowan, J. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J., 12, 1–24.CrossRefGoogle ScholarPubMed
Wilson, H. and Cowan, J. (1973). A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue. Biol. Cybernet., 13 (2), 55–80.Google ScholarPubMed
Woolum, J. C. and Strumwasser, F. (1978). Membrane-potential-sensitive dyes for optical monitoring of activity in aplysia neurons. J. Neurobiol., 9 (3), 185–193.CrossRefGoogle ScholarPubMed
Xu, W., Huang, X., Takgaki, K. and Wu, J. (2007). Compression and reflection of visually evoked cortical waves. Neuron, 55 (1), 119–129.CrossRefGoogle ScholarPubMed
Yang, Z., Heeger, D. J. and Seidemann, E. (2007). Rapid and precise retinotopic mapping of the visual cortex obtained by voltage-sensitive dye imaging in the behaving monkey. J. Neurophysiol., 98 (2), 1002–1014.CrossRefGoogle ScholarPubMed
Young, J. Z. (1958). Anatomical considerations. EEG Clin. Neurophysiol., 10, 9–11.Google Scholar
Yuste, R., Tank, D. K. and Kleinfeld, D. (1997). Functional study of the rat cortical micro-circuitry with voltage-sensitive dye imaging of neocortical slices. Cereb. Cortex, 7 (6), 546–558.CrossRefGoogle Scholar
Zochowski, M., Wachowiak, M., Falk, C. X., Cohen, L. B., Lam, Y. W., Antic, S. and Zecevic, D. (2000). Imaging membrane potential with voltage-sensitive dyes. Biol. Bull., 198 (1), 749–762.CrossRefGoogle ScholarPubMed

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  • Voltage-sensitive dye imaging
    • By S. Chemla, University of Lethbridge, Canada, F. Chavane, Aix-Marseille Université, Marseille, France
  • Edited by Romain Brette, Ecole Normale Supérieure, Paris, Alain Destexhe, Centre National de la Recherche Scientifique (CNRS), Paris
  • Book: Handbook of Neural Activity Measurement
  • Online publication: 05 October 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511979958.009
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  • Voltage-sensitive dye imaging
    • By S. Chemla, University of Lethbridge, Canada, F. Chavane, Aix-Marseille Université, Marseille, France
  • Edited by Romain Brette, Ecole Normale Supérieure, Paris, Alain Destexhe, Centre National de la Recherche Scientifique (CNRS), Paris
  • Book: Handbook of Neural Activity Measurement
  • Online publication: 05 October 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511979958.009
Available formats
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To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Voltage-sensitive dye imaging
    • By S. Chemla, University of Lethbridge, Canada, F. Chavane, Aix-Marseille Université, Marseille, France
  • Edited by Romain Brette, Ecole Normale Supérieure, Paris, Alain Destexhe, Centre National de la Recherche Scientifique (CNRS), Paris
  • Book: Handbook of Neural Activity Measurement
  • Online publication: 05 October 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511979958.009
Available formats
×