Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-23T17:44:49.806Z Has data issue: false hasContentIssue false
  • English
  • Français

Retinal ganglion cell coding in simulated active vision

Published online by Cambridge University Press:  03 February 2006

FRANKLIN R. AMTHOR ,
JOHN S. TOOTLE  and
TIMOTHY J. GAWNE
FRANKLIN R. AMTHOR
Affiliation:
Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama
JOHN S. TOOTLE
Affiliation:
Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama
TIMOTHY J. GAWNE
Affiliation:
Department of Vision Sciences, School of Optometry, University of Alabama at Birmingham, Birmingham, Alabama
Get access Rights & Permissions [Opens in a new window]

Abstract

The image on the retina is almost never static. Eye, head, and body movements, and externally generated motion create rapid and continual changes in the retinal image (“active vision”). Virtually all vision in animals such as primates, which make saccades as often as 3–4 times/s, is based on information that must be derived from the first few hundred milliseconds after sudden, global changes in the retinal image. These changes may be accompanied by large changes in area mean luminance, as well as higher order image contrast statistics. This study investigated how retinal ganglion cell responses, whose response properties have been typically studied and defined in a stable stimulus regime, are affected by sudden changes in mean luminance that are characteristic of active vision. Specifically, the steady-state responses of retinal ganglion cells to static or moving square-wave grating stimuli were recorded in an isolated, superfused rabbit eyecup preparation and compared to responses after saccade-like changes in luminance. The manner of coding after luminance changes was different for different ganglion cell classes; both suppression and enhancement of responses to patterns following luminance changes were found. Brisk-transient Off cells unambiguously signaled the darkening of the overall image, but were also modulated by the subsequently appearing grating stimulus. Several types of On-center cell behavior were observed, ranging from strong suppression of the subsequent response by luminance changes, to strong enhancement. Overall, most ganglion cells distinguished static patterns after a luminance change via differences in their spike discharges nearly as well as before, although there were clear asymmetries between the On and Off pathways. Changes in mean luminance in some ganglion cells, such as On–Off directionally selective ganglion cells, could create large phase shifts in the response to patterned, moving stimuli, although these stimuli were still detected immediately after luminance changes. The results of this study show that the image dynamics of active vision may be a fundamental challenge for the visual system because of strong effects on retinal ganglion cell function. However, rapid extraction of unambiguous information after luminance changes appears to be encoded in differences in the spike discharges in different retinal ganglion cell classes. Asymmetries among ganglion cell classes in sensitivity to luminance changes may provide a basis by which some provide the “context” for interpreting the firing of others.

Keywords

VisionSaccadesRabbit retinaGanglion cells
Type
Research Article
Information
Visual Neuroscience , Volume 22 , Issue 6 , November 2005 , pp. 789 - 806
Copyright
© 2005 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ames, A.D. & Nesbett, F.B. (1981). In vitro retina as an experimental model of the nervous system. Journal of Neurochemistry 37, 867–877.CrossRefGoogle Scholar
Amthor, F.R. & Oyster, C.W. (1995). Spatial organization of retinal information about movement detection. Proceedings of the National Academy of Sciences of the U.S.A. 92(9), 4002–4005.CrossRefGoogle Scholar
Amthor, F.R., Takahashi, E.S., & Oyster, C.W. (1989a). Morphologies of rabbit retinal ganglion cells with concentric receptive fields. Journal of Comparative Neurology 280(1), 72–96.Google Scholar
Amthor, F.R., Takahashi, E.S., & Oyster, C.W. (1989b). Morphologies of rabbit retinal ganglion cells with complex receptive fields. Journal of Comparative Neurology 280(1), 97–121.Google Scholar
Amthor, F.R., Tootle, J.S., & Yildirim, A. (2003). A new transparent multi-unit recording array system fabricated by in-house laboratory technology. Journal of Neuroscience Methods 126(2), 209–219.CrossRefGoogle Scholar
Baccus, S.A. & Meister, M. (2002). Fast and slow contrast adaptation in retinal circuitry. Neuron 36, 909–919.CrossRefGoogle Scholar
Benardete, E.A. & Kaplan, E. (1999). The dynamics of primate retinal ganglion cells. Visual Neuroscience 16, 355–368.CrossRefGoogle Scholar
Brown, S.P. & Masland, R.H. (2001). Spatial scale and cellular substrate of contrast adaptation by retinal ganglion cells. Nature Neuroscience 4(1), 44–51.CrossRefGoogle Scholar
Burr, D.C., Morrone, M.C., & Ross, J. (1994). Selective suppression of the magnocellular visual pathway during saccadic eye movements. Nature 371, 511–513.CrossRefGoogle Scholar
Chander, D. & Chichilnisky, E.J. (2001). Adaptation to temporal contrast in primate and salamander retina. Journal of Neuroscience 21(24), 9904–9916.Google Scholar
Derrington, A.M. & Felisberti, F. (1998). Peripheral shift reduces visual sensitivity in cat geniculate neurones. Visual Neuroscience 15, 875–880.Google Scholar
DiCarlo, J.J. & Maunsell, J.H.R. (2000). Form representation in monkey inferotemporal cortex is virtually unaltered by free viewing. Nature Neuroscience 3, 814–821.CrossRefGoogle Scholar
Garcia-Perez, M.A. & Peli, E. (2001). Intrasaccadic perception Journal of Neuroscience 12(18), 7313–7322.Google Scholar
Gawne, T.J. & Martin, J.M. (2002). Responses of primate visual cortical neurons to stimuli presented by flash, saccade, blink and external darkening. Journal of Neurophysiology 88, 2178–2186.CrossRefGoogle Scholar
Gawne, T.J. & Woods, J.M. (2003). The responses of visual cortical neurons encode differences across saccades. Neuroreport 14, 105–109.CrossRefGoogle Scholar
Graur, D., Duret, L., & Manolo, G. (1996). Phylogenetic position of the order Lagomorpha (rabbits, hares and allies). Nature 379, 333–335.CrossRefGoogle Scholar
Grzywacz, N.M., Tootle, J.S., & Amthor, F.R. (1997). Is the input to a GABAergic or cholinergic synapse the sole asymmetry in rabbit's retinal directional selectivity? Visual Neuroscience 14(1), 39–54.Google Scholar
Kim, K.J. & Rieke, F. (2001). Temporal contrast adaptation in the input and output signals of salamander retinal ganglion cells. Journal of Neuroscience 21(1), 287–299.Google Scholar
Kraft, T.W. (1988). Photocurrents of cone photoreceptors of the golden-mantled ground squirrel. Journal of Physiology 404, 199–213.CrossRefGoogle Scholar
Levick, W.R. (1967). Receptive fields and trigger features of ganglion cells in the visual streak of the rabbit's retina. Journal of Physiology (London) 188, 285–307.CrossRefGoogle Scholar
Ölveczky, B.P., Baccus, S.A., & Meister, M. (2003). Segregation of object and background motion in the retina. Nature 11, 401–408.CrossRefGoogle Scholar
Paradiso, M.A. (2001). Stimulus structure and expectation reflected in the delayed responses of macaque V1 neurons. Society for Neuroscience Abstracts 27, 450.Google Scholar
Poot, L., Snippe, H.P., & Hateren, J.H. (1997). Dynamics of adaptation at high luminances: Adaptation is faster after luminance decrements than after luminance increments. Journal of the Optical Society of America A 14(9), 2499–2509.CrossRefGoogle Scholar
Richmond, B.J., Hertz, J.A., & Gawne, T.J. (1999). The relation between V1 neuronal responses and eye movement-like stimulus presentations. Neurocomputing 26–27, 247–254.CrossRefGoogle Scholar
Rodieck, R.W. (1979). Visual pathways. Annual Reviews of Neuroscience 2, 193–225.CrossRefGoogle Scholar
Roska, B. & Werblin, F. (2003). Rapid global shifts in natural scenes block spiking in specific ganglion cell types. Nature Neuroscience 6(6), 600–608.CrossRefGoogle Scholar
Sakai, H.M., Wang, J.L., & Naka, K.I. (1995). Contrast gain control in the lower vertebrate retinas. Journal of General Physiology 105, 815–835.CrossRefGoogle Scholar
Shapley, R. (1997). Retinal physiology: Adapting to the changing scene. Current Biology 7, R421–R423.CrossRefGoogle Scholar
Shapley, R. & Enroth-Cugell, C. (1984). Visual adaptation and retinal gain controls. Progress in Retinal Research 3, 263–346.CrossRefGoogle Scholar
Shapley, R.M. & Victor, J.D. (1981). How the contrast gain control modifies the frequency responses of cat retinal ganglion cells. Journal of Physiology 318, 161–180.CrossRefGoogle Scholar
Smirnakis, S.M., Berry, M.J., Warland, D.K., Bialek, W., & Meister, M. (1997). Adaptation of retinal processing to image contrast and spatial scale. Nature 386, 69–73.CrossRefGoogle Scholar
Thiele, A., Henning, J., Kubischik, M., & Hoffman, K.P. (2002). Neural mechanisms of saccadic suppression. Science 295, 2460–2462.CrossRefGoogle Scholar
Van Hof, M.W. (1967). Visual acuity in the rabbit. Vision Research 7, 749–751.CrossRefGoogle Scholar
VanRullen, R. & Thorpe, S.J. (2001). Rate coding versus temporal order coding: what the retinal ganglion cells tell the visual cortex. Neural Computation 13, 1255–1283.Google Scholar
Victor, J.D. (1987). The dynamics of the cat retinal x cell center. Journal of Physiology 386, 219–246.CrossRefGoogle Scholar
Zaghloul, K.A., Boahen, K., & Demb, J.B. (2003). Different circuits for On and Off retinal ganglion cells cause different contrast sensitivities. Journal of Neuroscience 23(7), 2645–2654.Google Scholar