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Visual signal processing in the macaque lateral geniculate nucleus

Published online by Cambridge University Press:  01 March 2012

THORSTEIN SEIM ,
ARNE VALBERG  and
BARRY B. LEE
THORSTEIN SEIM*
Affiliation:
Institute of Physics, Norwegian University of Science and Technology, Trondheim, Norway MikroSens, Slependen, Norway
ARNE VALBERG
Affiliation:
Institute of Physics, Norwegian University of Science and Technology, Trondheim, Norway
BARRY B. LEE
Affiliation:
Graduate Center for Visual Science (SUNY), State University of New York, New York, USA Max Planck Institute of Biophysical Chemistry, Department of Neurobiology (MPI), Göttingen, Germany
*
*Address correspondence and reprint requests to: Thorstein Seim, Institute of Physics, Norwegian University of Science and Technology, N-7491 Trondheim, Norway. Email: thorstein.seim@c2i.net
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Abstract

Comparisons of S- or prepotential activity, thought to derive from a retinal ganglion cell afferent, with the activity of relay cells of the lateral geniculate nucleus (LGN) have sometimes implied a loss, or leak, of visual information. The idea of the “leaky” relay cell is reconsidered in the present analysis of prepotential firing and LGN responses of color-opponent cells of the macaque LGN to stimuli varying in size, relative luminance, and spectral distribution. Above a threshold prepotential spike frequency, called the signal transfer threshold (STT), there is a range of more than 2 log units of test field luminance that has a 1:1 relationship between prepotential- and LGN-cell firing rates. Consequently, above this threshold, the LGN cell response can be viewed as an extension of prepotential firing (a “nonleaky relay cell”). The STT level decreased when the size of the stimulus increased beyond the classical receptive field center, indicating that the LGN cell is influenced by factors other than the prepotential input. For opponent ON cells, both the excitatory and the inhibitory response decreased similarly when the test field size increased beyond the center of the receptive field. These findings have consequences for the modeling of LGN cell responses and transmission of visual information, particularly for small fields. For instance, for LGN ON cells, information in the prepotential intensity–response curve for firing rates below the STT is left to be discriminated by OFF cells. Consequently, for a given light adaptation, the STT improves the separation of the response range of retinal ganglion cells into “complementary” ON and OFF pathways.

Keywords

VisionPrepotentialsS-potentialsLGN PC-cellsInformation transfer
Type
Research Articles
Information
Visual Neuroscience , Volume 29 , Issue 2 , March 2012 , pp. 105 - 117
Copyright
Copyright © Cambridge University Press 2012

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References

Augustinaite, S. & Heggelund, P. (2007). Changes in firing pattern of lateral geniculate neurons caused by membrane potential dependent modulation of retinal input through NMDA receptors. The Journal of Physiology 582, 297–315.Google Scholar
Augustinaite, S., Yanagawa, Y. & Heggelund, S. (2011). Cortical feedback regulation of input to visual cortex: Role of intrageniculate interneurons. The Journal of Physiology 589, 2963–2977.CrossRefGoogle ScholarPubMed
Babadi, B., Castidi, A., Xiao, Y., Kaplan, E. & Paninski, L. (2010). A generalized linear model of the impact of direct and indirect inputs to the lateral geniculate nucleus. Journal of Vision 10, 1–14.Google Scholar
Bishop, P.O., Burke, W. & Davis, R. (1958). Synapse discharge by single fibre in mammalian visual system. Nature 182, 228–230.CrossRefGoogle ScholarPubMed
Buchsbaum, G. & Gottschalk, A. (1983). Trichromacy, opponent colours coding and optimum colour information transmission in the retina. Proceedings of the Royal Society of London. Series B, Biological Sciences 220, 89–113.Google Scholar
Brenner, N., Strong, S.P., Koberle, R. & de Ruyter van Steveninck, R.R. (2000). Synergy in a neural code. Neural Computation 12, 1531–1552.CrossRefGoogle Scholar
Carandini, M., Horton, J.C. & Sincich, L.C. (2007). Thalamic filtering of retinal spike trains by postsynaptic summation. Journal of Vision 7, 1–11.Google Scholar
Casti, A., Hayot, F., Xiao, Y. & Kaplan, E. (2008). A simple model of retina-LGN transmission. Journal of Computational Neuroscience 24, 235–252.CrossRefGoogle ScholarPubMed
Cleland, B.G., Dubin, M.W. & Levick, W.R. (1971). Sustained and transient neurons in the cat’s retina and lateral geniculate nucleus. The Journal of Physiology 217, 473–496.CrossRefGoogle ScholarPubMed
Cleland, B.G. & Lee, B.B. (1985). A comparison of visual responses of cat lateral geniculate nucleus with those of ganglion cells afferent to them. The Journal of Physiology 369, 249–268.Google Scholar
De Valois, R. & De Valois, K.K. (1993). A multi-stage color model. Vision Research 33, 1053–1065.CrossRefGoogle ScholarPubMed
Fjeld, I.T., Ruksenas, O. & Heggelund, P. (2002). Brainstem modulation of visual response properties of single cells in the dorsal lateral geniculate nucleus of cat. The Journal of Physiology 543, 541–554.Google Scholar
Hartveit, E. & Heggelund, P. (1995). Brainstem modulation of signal transmission through the cat dorsal lateral geniculate nucleus. Experimental Brain Research 103, 372–384.Google Scholar
Hartveit, E., Ramberg, S.I. & Heggelund, P. (1993). Brain stem modulation of spatial receptive field properties of single cells in the dorsal laterale geniculate nucleus of the cat. Journal of Neurophysiology 70, 1644–1655.Google Scholar
Hill, A.V. (1910). The possible effect of the aggregation of the molecules of haemoglobin on its dissociation curves. The Journal of Physiology 40(Suppl.), iv–vii.Google Scholar
Hubel, D.H. & Wiesel, T.N. (1961). Integrative action in the cat’s lateral geniculate body. The Journal of Physiology 155, 385–398.CrossRefGoogle ScholarPubMed
Jung, R. (1973). Visual perception and neurophysiology. In Handbook of Sensory Physiology, Vol. VII/3A, ed. Jung, R., pp. 1–152. Berlin, Germany: Springer.Google Scholar
Kaplan, E., Purpura, K. & Shapley, R.M. (1987). Contrast affects the transmission of visual information through the mammalian lateral geniculate nucleus. The Journal of Physiology 391, 267–288.Google Scholar
Kaplan, E. & Shapley, R. (1984). The origin of the S (Slow) potential in the mammalian lateral geniculate nucleus. Experimental Brain Research 55, 111–116.Google Scholar
Kinoshita, M. & Komatsu, H. (2001). Neural representation of the luminance and brightness of a uniform surface in the macaque primary cortex. The Journal of Neuroscience 86, 2559–2570.Google Scholar
Lee, B.B., Martin, P.R. & Valberg, A. (1988). The physiological basis of heterochromatic flicker photometry demonstrated in the ganglion cells of the macaque retina. The Journal of Physiology 404, 323–347.Google Scholar
Lee, B.B., Valberg, A., Tigwell, D.A. & Tryti, J. (1987). An account of responses of spectrally opponent neurones in macaque lateral geniculate nucleus to successive contrast. Proceedings of the Royal Society of London. Series B, Biological Sciences 230, 293–314.Google ScholarPubMed
Lee, B.B., Virsu, V. & Creutzfeldt, O.D. (1983 a). Linear signal transmission from prepotentials to cells in the macaque lateral geniculate nucleus. Experimental Brain Research 52, 50–56.Google Scholar
Lee, B.B., Virsu, V. & Elepfandt, A. (1983 b). Cell responses in dorsal layers of macaque lateral geniculate nucleus as a function of intensity and wavelength. Journal of Neurophysiology 50, 849–863.Google Scholar
Lee, H-C. (2005). Introduction to Color Imaging Science. Cambridge University Press, New York, NY.Google Scholar
Mastronarde, D.N. (1987 a). Two classes of single-input X-cells in cat lateral geniculate nucleus. I. Receptive field properties and classification of cells. Journal of Neurophysiology 57, 357–380.Google Scholar
Mastronarde, D.N. (1987 b). Two classes of single-input X-cells in cat lateral geniculate nucleus. II. Retinal inputs and the generation of receptive field properties. Journal of Neurophysiology 57, 381–413.CrossRefGoogle ScholarPubMed
Naka, K. I. & Rushton, W.A.H.R. (1967). The generation and spread of S-potentials in fish (Cyprinidae). The Journal of Physiology 192, 437–461.CrossRefGoogle ScholarPubMed
Nakano, Y., Ikeda, M. & Kaiser, P. (1988). Contributions of the opponent mechanisms to brightness and nonlinear models. Vision Research 28, 799–810.Google Scholar
Ruksenas, O., Bulatov, A. & Heggelund, P. (2007). Dynamics of spatial resolution of single units in the lateral geniculate nucleus of cat during brief visual stimulation. Journal of Neurophysiology 97, 1445–1456.CrossRefGoogle ScholarPubMed
Schiller, P.H. (1992). The ON and OFF channels of the visual system. Trends in Neurosciences 15, 86–92.Google Scholar
Sincich, L.C., Adams, D.L., Economides, J.R. & Horton, J.C. (2007). Transmission of spike trains at the retinogeniculate synapse. The Journal of Neuroscience 27, 2683–2692.Google Scholar
Sincich, L.C., Horton, J.C. & Sharpee, T.O. (2009). Preserving information in neural transmission. Journal of Neuroscience 29, 6207–6216.Google Scholar
Stockmann, A. & Sharpe, L. (2000). The spectral sensitivity of the middle- and long wavelength sensitive cones derived from measurements in observers with known genotype. Vision Research 40, 1711–1737.Google Scholar
Uglesich, R., Casti, A., Hayot, F. & Kaplan, E. (2009). Stimulus size dependence of information transfer from retina to thalamus. Frontiers in System Neuroscience 3, 1–9.Google ScholarPubMed
Usrey, W.M., Reppas, J.B. & Reid, R.C. (1998). Paired-spike interactions and synaptic efficacy of retinal inputs to the thalamus. Nature 395, 384–387.CrossRefGoogle Scholar
Usrey, W.M., Reppas, J.B. & Reid, R.C. (1999). Specificity and strength of retinogenuculate connections. Journal of Neurophysiology 82, 3527–3540.Google Scholar
Valberg, A. (2005). Light Vision Color. Chichester, UK: Wiley & Sons.Google Scholar
Valberg, A., Lee, B.B., Tigwell, D.A. & Creutzfeldt, O.D. (1985 b). A simultaneous contrast effect of steady remote surrounds on responses of cells in macaque lateral geniculate nucleus. Experimental Brain Research 58, 604–608.Google Scholar
Valberg, A., Lee, B.B. & Tryti, J. (1987). Simulation of responses of spectrally-opponent neurones in the macaque lateral geniculate nucleus to chromatic and achromatic light stimuli. Vision Research 27, 867–882.Google Scholar
Valberg, A. & Seim, T. (2008). Neural mechanisms of chromatic and achromatic vision. Color Research & Application 33, 433–443.Google Scholar
Valberg, A., Seim, T., Lee, B.B. & Tryti, J. (1985 a). Reconstruction of equidistant color space from responses of visual neurones of macaques. Journal of the Optical Society of America A 3, 1726–1734.Google Scholar
Valeton, J.M. & van Norren, D. (1983). Light adaptation of primate cones: An analysis based on extracellular data. Vision Research 23, 1539–1547.Google Scholar
van Hateren, J.H., Ruetiger, L., Sun, H. & Lee, B.B. (2002). Processing of natural temporal stimuli by macaque retinal ganglion cells. Journal of Neuroscience 22, 9945–9960.Google Scholar
von Der Twer, T. & MacLeod, D.I.A. (2001). Optimal nonlinear codes for perception of natural colours. Computational Neural Systems 12, 395–407.Google Scholar