Wide-field Ca2+ imaging reveals visually evoked activity in the retrosplenial area

Frontiers in Molecular Neuroscience

Volumn 8, Issue June, 2015, Pages

  Murakami, Tomonari ^a   Yoshida, Takashi ^a,b   Matsui, Teppei ^a   Ohki, Kenichi ^a,b  

^a KYUSHU UNIVERSITY   (Japan)

^b JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

Author keywords

GCaMP3; Retrosplenial area; Transgenic mouse; Visual response; Wide field Ca2+imaging

Indexed keywords

ANIMAL EXPERIMENT; ARTICLE; ASTROCYTE; CALCIUM IMAGING; EVOKED VISUAL RESPONSE; FLUORESCENCE MICROSCOPY; GRATING; IMAGING; MOUSE; NONHUMAN; PROTEIN EXPRESSION; RETROSPLENIAL CORTEX; TRANSGENIC MOUSE; VISUAL STIMULATION;

EID: 84935921419     PISSN: 16625099     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnmol.2015.00020     Document Type: Article

References (53)

1. Akerboom, J., Chen, T. W., Wardill, T. J., Tian, L., Marvin, J. S., Mutlu, S., et al. (2012).Optimization of a GCaMP calcium indicator forneural activityimaging. J. Neurosci. 32, 13819-13840. doi: 10.1523/JNEUR0SCI.2601-12.2012
2. Andermann, M. L., Kerlin, A. M., Roumis, D. K., Glickfeld, L. L., and Reid, R. C. (2011). Functional specialization of mouse higher visual cortical areas. Neuron 72, 1025-1039. doi: 10.1016/j.neuron.2011.11.013
3. Belliveau, J. W., Kennedy, D. N. Jr., McKinstry, R. C., Buchbinder, B. R., Weisskoff, R. M., Cohen, M. S., et al. (1991). Functional mapping of the human visual cortex by magnetic resonance imaging. Science 254, 716-719. doi: 10.1126/science.1948051
4. Bonder, D. E., and McCarthy, K. D. (2014). Astrocytic Gq-GPCR-linked IP3R-dependent Ca2+ signaling does not mediate neurovascular coupling in mouse visual cortex in vivo. J. Neurosci. 34, 13139-13150. doi: 10.1523/JNEUR0SCI.2591-14.2014
5. Chen, T. W., Wardill, T. J., Sun, Y., Pulver, S. R., Renninger, S. L., Baohan, A., et al. (2013). Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295-300. doi: 10.1038/nature12354
6. Cho, J., and Sharp, P. E. (2001). Head direction, place, and movement correlates for cells in the rat retrosplenial cortex. Behav. Neurosci. 115, 3-25. doi: 10.1037/0735-7044.115.1.3
7. Czajkowski, R., Jayaprakash, B., Wiltgen, B., Rogerson, T., Guzman-Karlsson, M. C., Barth, A. L., et al. (2014). Encoding and storage of spatial information in the retrosplenial cortex. Proc. Natl. Acad. Sci. U.S.A. 111, 8661-8666. doi: 10.1073/pnas.1313222111
8. Desai, M., Kahn, I., Knoblich, U., Bernstein, J., Atallah, H., Yang, A., et al. (2011). Mapping brain networks in awake mice using combined optical neural control and fMRI. J. Neurophysiol. 105, 1393-1405. doi: 10.1152/jn.00828.2010
9. Dombeck, D. A., Harvey, C. D., Tian, L., Looger, L. L., and Tank, D. W. (2010). Functional imaging of hippocampal place cells at cellular resolution during virtual navigation. Nat. Neurosci. 13, 1433-1440. doi: 10.1038/nn.2648
10. Felleman, D. J., and Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1-47. doi: 10.1093/cercor/1.1.1
11. Franklin, K. B. J., and Paxinos, G. (2008). The Mouse Brain in Stereotaxic Coordinates, 3rd Edn. San Diego, CA: Academic Press.
12. Gao, E., Deangelis, G. C., and Burkhalter, A. H. (2007). Functionally specialized areas in mouse extrastriate visual cortex. Abstract in 2007 Neuroscience Meeting Planner of the 37th Annual Meeting of Society for Neuroscience, San Diego, CA. Program No. 280.12/ FF25.
13. Gerfen, C. R., Paletzki, R., and Heintz, N. (2013). GENSAT BAC cre-recombinase driver lines to study the functional organization of cerebral cortical and basal ganglia circuits. Neuron 80, 1368-1383. doi: 10.1016/j.neuron.2013.10.016
14. Glickfeld, L. L., Andermann, M. L., Bonin, V., and Reid, R. C. (2013). Cortico- cortical projections in mouse visual cortex are functionally target specific. Nat. Neurosci. 16, 219-226. doi: 10.1038/nn.3300
15. Glickfeld, L. L., Reid, R. C., and Andermann, M. L. (2014). A mouse model of higher visual cortical function. Curr. Opin. Neurobiol. 24, 28-33. doi: 10.1016/j.conb.2013.08.009
16. Gorski, J. A., Talley, T., Qiu, M., Puelles, L., Rubenstein, J. L., and Jones, K. R. (2002). Cortical excitatory neurons and glia, but not GABAergic neurons, are produced in the Emx1-expressing lineage. J. Neurosci. 22, 6309­6314.
17. Guilfoyle, D. N., Gerum, S. V., Sanchez, J. L., Balla, A., Sershen, H., Javitt, D. C., et al. (2013). Functional connectivity fMRI in mouse brain at 7T using isoflurane. J. Neurosci. Methods 214, 144-148. doi: 10.1016/j.jneumeth.2013.01.019
18. Hagihara, K. M., and Ohki, K. (2013). Long-term down-regulation of GABA decreases orientation selectivitywithout affecting direction selectivityin mouse primary visual cortex. Front. Neural Circuits 7:28. doi: 10.3389/fncir.2013.00028
19. Hishida, R., Kudoh, M., and Shibuki, K. (2014). Multimodal cortical sensory pathways revealed by sequential transcranial electrical stimulation in mice. Neurosci. Res. 87, 49-55. doi: 10.1016/j.neures.2014.07.004
20. Issa, J. B., Haeffele, B. D., Agarwal, A., Bergles, D. E., Young, E. D., and Yue, D. T. (2014). Multiscale optical Ca2+ imaging of tonal organization in mouse auditory cortex. Neuron 83, 944-959. doi: 10.1016/j.neuron.2014.07.009
21. Jonckers, E., Van Audekerke, J., De Visscher, G., Van der Linden, A., and Verhoye, M. (2011). Functional connectivity fMRI of the rodent brain: comparison of functional connectivity networks in rat and mouse. PLoS ONE 6:e18876. doi: 10.1371/journal.pone.0018876
22. Kalatsky, V. A., and Stryker, M. P. (2003). New paradigm for optical imaging: temporally encoded maps of intrinsic signal. Neuron 38, 529-545. doi: 10.1016/S0896-6273(03)00286-1
23. Kerlin, A. M., Andermann, M. L., Berezovskii, V. K., and Reid, R. C. (2010). Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex. Neuron 67, 858-871. doi: 10.1016/j.neuron.2010.08.002
24. Kravitz, D. J., Saleem, K. S., Baker, C. I., and Mishkin, M. (2011). A new neural framework for visuospatial processing. Nat. Rev. Neurosci. 12, 217-230.doi: 10.1038/nrn3008
25. Lim, D. H., Mohajerani, M. H., Ledue, J., Boyd, J., Chen, S., and Murphy, T. H. (2012). In vivo large-scale cortical mapping using channelrhodopsin-stimulation in transgenic mice reveals asymmetric and reciprocal relationships between cortical areas. Front. Neural Circuits 6:11. doi: 10.3389/fncir.2012.00011
26. Madisen, L., Garner, A. R., Shimaoka, D., Chuong, A. S., Klapoetke, N. C., Li, L., et al. (2015). Transgenic mice for intersectional targeting of neural sensors and effectors with high specificity and performance. Neuron 85, 942-958. doi: 10.1016/j.neuron.2015.02.022
27. Madisen, L., Zwingman, T. A., Sunkin, S. M., Oh, S. W., Zariwala, H. A., Gu, H., et al. (2010). A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133-140. doi: 10.1038/nn.2467
28. Mantini, D., Hasson, U., Betti, V., Perrucci, M. G., Romani, G. L., Corbetta, M., et al. (2012). Interspecies activitycorrelations reveal functional correspondence between monkey and human brain areas. Nat. Methods 9, 277-282. doi: 10.1038/nmeth.1868
29. Marshel, J. H., Garrett, M. E., Nauhaus, I., and Callaway, E. M. (2011). Functional specialization of seven mouse visual cortical areas. Neuron 72, 1040-1054. doi: 10.1016/j.neuron.2011.12.004
30. Matsui, T., and Ohki, K. (2013). Target dependence of orientation and direction selectivity of corticocortical projection neurons in the mouse V1. Front. Neural Circuits 7:143. doi: 10.3389/fncir.2013.00143
31. Mohajerani, M. H., Chan, A. W., Mohsenvand, M., LeDue, J., Liu, R., McVea, D. A., et al. (2013). Spontaneous cortical activity alternates between motifs defined by regional axonal projections. Nat. Neurosci. 16, 1426-1435. doi: 10.1038/nn.3499
32. Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., et al. (2014). A mesoscale connectome of the mouse brain. Nature 508, 207-214. doi: 10.1038/nature13186
33. Ohki, K., Chung, S., Ch'ng, Y. H., Kara, P., and Reid, R. C. (2005). Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597-603. doi: 10.1038/nature03274
34. Ohtsuki, G., Nishiyama, M., Yoshida, T., Murakami, T., Histed, M., Lois, C., et al. (2012). Similarity of visual selectivity among clonally related neurons in visual cortex. Neuron 75, 65-72. doi: 10.1016/j.neuron.2012.05.023
35. Park, H. J., and Friston, K. (2013). Structural and functional brain networks: from connections to cognition. Science 342, 1238411. doi: 10.1126/science.1238411
36. Paukert, M., Agarwal, A., Cha, J., Doze, V. A., Kang, J. U., and Bergles, D. E. (2014). Norepinephrine controls astroglial responsiveness to local circuit activity. Neuron 82, 1263-1270. doi: 10.1016/j.neuron.2014.04.038
37. Peirce, J. W. (2007). PsychoPy-Psychophysics software in Python. J. Neurosci. Methods 162, 8-13. doi: 10.1016/j.jneumeth.2006.11.017
38. Prusky, G. T., Silver, B. D., Tschetter, W. W., Alam, N. M., and Douglas, R. M. (2008). Experience-dependent plasticity from eye opening enables lasting, visual cortex-dependent enhancement of motion vision. J. Neurosci. 28, 9817­9827. doi: 10.1523/JNEUROSCI.1940-08.2008
39. Roth, M. M., Helmchen, F., and Kampa, B. M. (2012). Distinct functional properties of primary and posteromedial visual area of mouse neocortex. J. Neurosci. 32, 9716-9726. doi: 10.1523/JNEUROSCI.0110-12.2012
40. Smith, S. L., and Hausser, M. (2010). Parallel processing of visual space by neighboring neurons in mouse visual cortex. Nat. Neurosci. 13, 1144-1149. doi: 10.1038/nn.2620
41. Stein, B. E., and Stanford, T. R. (2008). Multisensory integration: current issues from the perspective of the single neuron. Nat. Rev. Neurosci. 9, 255-266. doi: 10.1038/nrn2331
42. Stoewer, S., Ku, S. P., Goense, J., Steudel, T., Logothetis, N. K., Duncan, J., et al. (2010). Frontoparietal activity with minimal decision and control in the awake macaque at 7 T. Magn. Reson. Imaging 28, 1120-1128. doi: 10.1016/j.mri.2009.12.024
43. Tohmi, M., Kitaura, H., Komagata, S., Kudoh, M., and Shibuki, K. (2006). Enduring critical period plasticity visualized by transcranial flavoprotein imaging in mouse primary visual cortex. J. Neurosci. 26, 11775-11785. doi: 10.1523/JNEUROSCI.1643-06.2006
44. Umino, Y., Solessio, E., and Barlow, R. B. (2008). Speed, spatial, and temporal tuning of rod and cone vision in mouse. J. Neurosci. 28, 189-198. doi: 10.1523/JNEUROSCI.3551-07.2008
45. Ungerleider, L. G., and Mishkin, M. (1982). “Two cortical visual systems" in Analysis of Visual Behavior, eds D. J. Ingel, M. A. Goodale, and R. J. W. Mansfield (Cambridge, MA: Massachusetts Institute of Technology), 549-586.
46. Vann, S. D., Aggleton, J. P., and Maguire, E. A. (2009). What does the retrosplenial cortex do? Nat. Rev. Neurosci. 10, 792-802. doi: 10.1038/nrn2733
47. Vanni, M. P., and Murphy, T. H. (2014). Mesoscale transcranial spontaneous activity mapping in GCaMP3 transgenic mice reveals extensive reciprocal connections between areas of somatomotor cortex. J. Neurosci. 34, 15931­15946. doi: 10.1523/JNEUROSCI.1818-14.2014
48. Wang, Q., Gao, E., and Burkhalter, A. (2011). Gateways of ventral and dorsal streams in mouse visual cortex. J. Neurosci. 31, 1905-1918. doi: 10.1523/JNEUROSCI.3488-10.2011
49. Wang, Q., Sporns, O., and Burkhalter, A. (2012). Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. J. Neurosci. 32, 4386-4399. doi: 10.1523/JNEUROSCI.6063-11.2012
50. Yoder, R. M., Clark, B. J., and Taube, J. S. (2011). Origins of landmark encoding in the brain. Trends Neurosci. 34, 561-571. doi: 10.1016/j.tins.2011.08.004
51. Zariwala, H. A., Borghuis, B. G., Hoogland, T. M., Madisen, L., Tian, L., De Zeeuw, C. I., et al. (2012). A Cre-dependent GCaMP3 reporter mouse for neuronal imaging in vivo. J. Neurosci. 32, 3131-3141. doi: 10.1523/JNEUROSCI.4469-11.2012
52. Zhang, S., Xu, M., Kamigaki, T., Hoang Do, J. P., Chang, W. C., Jenvay, S., et al. (2014). Selective attention. Long-range and local circuits for top- down modulation of visual cortex processing. Science 345, 660-665. doi: 10.1126/science.1254126
53. Zingg, B., Hintiryan, H., Gou, L., Song, M. Y., Bay, M., Bienkowski, M. S., et al. (2014). Neural networks of the mouse neocortex. Cell 156, 1096-1111. doi: 10.1016/j.cell.2014.02.023