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First published online April 18, 2008
Journal of Experimental Biology 211, 1376-1385 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.015941
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Retinal processing and opponent mechanisms mediating ultraviolet polarization sensitivity in rainbow trout (Oncorhynchus mykiss)

Samuel D. Ramsden1, Leslie Anderson1, Martina Mussi1, Maarten Kamermans2,3 and Craig W. Hawryshyn1,*

1 Department of Biology, University of Victoria, PO Box 3020 STN CSC, Victoria, British Columbia, V8W 3N5, Canada
2 Retinal Signal Processing Group, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands
3 Department of Neurogenetics, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands


Figure 1
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  		Fig. 1. Spectral energy distribution of the adapting backgrounds. The irradiance measurements are plotted as log irradiance (photons cm2 s–1). (A) Broad-spectrum tungsten halogen adapting background used in control and cobalt PS and spectral sensitivity experiments. (B) UVS cone mechanism, adapting background using a UG-11 filter in a tungsten halogen background channel. (C) LWS cone mechanism, adapting background using a 600LP cut-off filter.

 

Figure 2
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  		Fig. 2. Waveforms and response versus intensity curves for compound action potential (CAP) and electroretinogram (ERG) recording. (A) CAP waveforms (`ON' responses) at increasing intensities. Note that individual traces for A and B were vertically displaced for clarity of presentation. Intensity was incremented in 0.2 log unit steps of a 360 nm linearly polarized stimulus with an e-vector orientation of 45°. (B) ERG waveforms at increasing intensities recorded from a control fish (sham control, intraocular injection of saline). (C) Response versus intensity curve based on CAP data taken from panel A. (D) Response versus intensity curve based on ERG data taken from B.

 

Figure 3
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  		Fig. 3. Mean normalized spectral sensitivity of rainbow trout (±1 standard error) using electroretinogram (ERG) recording. For each treatment condition, panels on the left side show the spectral sensitivity curves for the control and treatment conditions and the panels on the right side show the difference curves between the control and treatment spectral sensitivity. Green points represent the control and red points represent the treatment condition. The sensitivity measurements were normalized to 360 nm. (A) Mean normalized spectral sensitivity of control fish where the spectral sensitivity was measured using a broad-spectrum tungsten halogen background (N=3), and treatment fish where spectral sensitivity was measured using a broad spectrum and UG-11 background (N=3). (B) Mean difference spectrum as a result of short wavelength chromatic adaptation (UG-11 filter). The black line fitted to the data points at the shortwave end of the spectrum represents an additive function based on the UVS and short wavelength-sensitive (SWS) visual pigment templates. (C) Mean normalized spectral sensitivity of the same control fish as in A, and treatment fish where spectral sensitivity was measured using a broad spectrum and 600 nm long pass background (N=3). (D) Mean difference spectrum as a result of long wavelength chromatic adaptation (600 nm long pass filter). The black line fitted to the points represents the LWS cone visual pigment template.

 

Figure 4
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  		Fig. 4. Mean ultraviolet polarization sensitivity of rainbow trout (±1 standard error). Two different recording techniques were used, electroretinogram (ERG) and compound action potential (CAP) recording (solid circles). Sv is represented by squares and Sh by diamonds (see Table 2 for weighting coefficients). Dashed lines connect the symbols. (A) ERG PS (N=21). The solid line connects the sensitivity points representing the intermediary peaks. (B) CAP PS (N=5). For both figures, a 360 nm linear polarized stimulus in 15° e-vector increments was used. Note the differences in sensitivity between the two curves at 45° and 135°.

 

Figure 5
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  		Fig. 5. Mean ultraviolet polarization sensitivity of rainbow trout (±1 standard error). (A) Electroretinogram (ERG) UV PS with LWS cone mechanism adaptation using the 600 nm long pass background (N=3). Note the intermediary peak shifts towards the horizontal polarization mechanism and the angular breadth of the horizontal polarization mechanism decreases while the vertical polarization mechanism increases. (B) ERG UV PS with UVS cone mechanism chromatic adaptation using a UG-11 background (N=3). Note the intermediary peaks shift towards the vertical polarization mechanism and the angular breadth of the horizontal polarization mechanism increases and the vertical decreases. Sv is represented by squares and Sh by diamonds. See Table 2 for linear subtractive model weighting functions.

 

Figure 6
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  		Fig. 6. Analysis of the effect of cobalt chloride on electroretinogram (ERG) responses. (A) ERG waveforms at increasing intensities recorded from a cobalt-treated fish (intraocular injection of cobalt chloride, intraocular concentration of 0.275 mmol l–1). (B) Comparison of ERG waveforms from cobalt chloride-injected fish (upper trace) and the control (lower trace). (C) Response versus intensity based on ERG data taken from a cobalt chloride-injected fish and a control fish. The cobalt-injected fish show a lower slope in the dynamic range resulting in a difference in the interpolated threshold intensity.

 

Figure 7
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  		Fig. 7. Mean normalized spectral sensitivity (±1 standard error). (A) Sensitivity of control fish in green (N=3) and cobalt chloride-treated fish (estimated intraocular concentration was 0.275 mmol l–1; N=3) in red. (B) Mean difference spectrum (control minus treated).

 

Figure 8
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  		Fig. 8. Mean normalized ultraviolet polarization sensitivity of rainbow trout (±1 standard error). (A) Electroretinogram (ERG) UV PS of fish treated with cobalt chloride (intraocular concentration ~0.275 mmol l–1; N=3). (B) Sham control intraocular injection of saline (N=3). Sv is represented by squares and Sh by diamonds. See Table 2 for linear subtractive model weighting factors.

 

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© The Company of Biologists Ltd 2008