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Visual coding in locust photoreceptors.

Faivre O, Juusola M - PLoS ONE (2008)

Bottom Line: We found that brightening or warming increase and accelerate voltage responses, but reduce noise, enabling photoreceptors to encode more information.Furthermore, the Q(10)s of bump duration and latency distribution depended on light intensity.Altogether, this study suggests that biochemical constraints imposed upon signaling change continuously as locust photoreceptors adapt to environmental light and temperature conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Zoology, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Information capture by photoreceptors ultimately limits the quality of visual processing in the brain. Using conventional sharp microelectrodes, we studied how locust photoreceptors encode random (white-noise, WN) and naturalistic (1/f stimuli, NS) light patterns in vivo and how this coding changes with mean illumination and ambient temperature. We also examined the role of their plasma membrane in shaping voltage responses. We found that brightening or warming increase and accelerate voltage responses, but reduce noise, enabling photoreceptors to encode more information. For WN stimuli, this was accompanied by broadening of the linear frequency range. On the contrary, with NS the signaling took place within a constant bandwidth, possibly revealing a 'preference' for inputs with 1/f statistics. The faster signaling was caused by acceleration of the elementary phototransduction current--leading to bumps--and their distribution. The membrane linearly translated phototransduction currents into voltage responses without limiting the throughput of these messages. As the bumps reflected fast changes in membrane resistance, the data suggest that their shape is predominantly driven by fast changes in the light-gated conductance. On the other hand, the slower bump latency distribution is likely to represent slower enzymatic intracellular reactions. Furthermore, the Q(10)s of bump duration and latency distribution depended on light intensity. Altogether, this study suggests that biochemical constraints imposed upon signaling change continuously as locust photoreceptors adapt to environmental light and temperature conditions.

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Signal and noise analysis of the voltage responses to a white-noise (WN) light stimulus.A, A pseudorandom light intensity pattern superimposed on a constant light background provided a WN contrast stimulus that was presented 30 times to the cell. The evoked responses are averaged to give the voltage signal and the remaining differences are the noise traces (A, scale bars: 500 ms, 5 mV). B, The corresponding power spectra are calculated for each of the five light BGs. Note that 〈/S(f)/2〉, 〈/N(f)/2〉, and 〈/r(f)/2〉 are displayed using the same scale, in mV2 Hz−1. 〈/C(f)/2〉 is in c2 Hz−1. C, These changes can be further quantified by computing the signal-to-noise ratio spectrum, SNR(f), and the cross-spectrum between the signal and the stimulus. These two spectra are the starting points to quantify the properties of the photoreceptor voltage responses (Figs. 2 and 3), the SNR(f) being used for the analysis of the coding properties (Fig. 2) and the cross-spectrum for the analysis of the transfer properties (Fig. 3). ‘Power’ on the ordinate scale of the cross-spectrum means here c mV Hz−1.
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pone-0002173-g001: Signal and noise analysis of the voltage responses to a white-noise (WN) light stimulus.A, A pseudorandom light intensity pattern superimposed on a constant light background provided a WN contrast stimulus that was presented 30 times to the cell. The evoked responses are averaged to give the voltage signal and the remaining differences are the noise traces (A, scale bars: 500 ms, 5 mV). B, The corresponding power spectra are calculated for each of the five light BGs. Note that 〈/S(f)/2〉, 〈/N(f)/2〉, and 〈/r(f)/2〉 are displayed using the same scale, in mV2 Hz−1. 〈/C(f)/2〉 is in c2 Hz−1. C, These changes can be further quantified by computing the signal-to-noise ratio spectrum, SNR(f), and the cross-spectrum between the signal and the stimulus. These two spectra are the starting points to quantify the properties of the photoreceptor voltage responses (Figs. 2 and 3), the SNR(f) being used for the analysis of the coding properties (Fig. 2) and the cross-spectrum for the analysis of the transfer properties (Fig. 3). ‘Power’ on the ordinate scale of the cross-spectrum means here c mV Hz−1.

Mentions: Membrane potentials of green-sensitive R1–R6 photoreceptor cells [29], [30] were recorded with a switched-clamp amplifier SEC-10L (NPI Electronic) operating in the compensated current-clamp mode. A successful photoreceptor penetration was seen as a 60–80 mV drop in the electrode potential followed by vigorous responses to dim pulses. Before the experiments, the cells were allowed to dark-adapt and seal properly. Only data from photoreceptors with saturating impulse responses ≥40 mV and dark resting potential ≤−60 mV were used in the analysis. In this article, we exhibit our findings using two exemplary photoreceptors. Similar results were obtained from other photoreceptors (n = 15) that endured long-lasting recordings. These data are presented in the Supporting Information. A first photoreceptor is used throughout Materials and Methods to illustrate the way data was analyzed (Figs. 1 to 3) at a constant temperature (19°C). The second one is used throughout the article (Figs. 4 to 12). Because of its exceptional stability, we were able to use this cell in many separate experiments and so to explore how light adaptation occurs over a vast range of background intensities and temperatures (from 17 to 23°C). For these experiments we used both white-noise (WN) and naturalistic stimulation (NS), and were able to further investigate how the membrane properties of the cell varied at each experimental condition. Additionally, we made recordings from many other photoreceptors (>30 of outstanding quality) over a smaller range of experimental conditions. These recordings were consistent with the general framework presented here. Because we believe that intrinsic functional variability between photoreceptors could be an important feature of locust vision (see Discussion), we do not show averaged quantities. Data from these cells is shown as Q10 values in Table 1 and detailed further in Table S1.


Visual coding in locust photoreceptors.

Faivre O, Juusola M - PLoS ONE (2008)

Signal and noise analysis of the voltage responses to a white-noise (WN) light stimulus.A, A pseudorandom light intensity pattern superimposed on a constant light background provided a WN contrast stimulus that was presented 30 times to the cell. The evoked responses are averaged to give the voltage signal and the remaining differences are the noise traces (A, scale bars: 500 ms, 5 mV). B, The corresponding power spectra are calculated for each of the five light BGs. Note that 〈/S(f)/2〉, 〈/N(f)/2〉, and 〈/r(f)/2〉 are displayed using the same scale, in mV2 Hz−1. 〈/C(f)/2〉 is in c2 Hz−1. C, These changes can be further quantified by computing the signal-to-noise ratio spectrum, SNR(f), and the cross-spectrum between the signal and the stimulus. These two spectra are the starting points to quantify the properties of the photoreceptor voltage responses (Figs. 2 and 3), the SNR(f) being used for the analysis of the coding properties (Fig. 2) and the cross-spectrum for the analysis of the transfer properties (Fig. 3). ‘Power’ on the ordinate scale of the cross-spectrum means here c mV Hz−1.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2367440&req=5

pone-0002173-g001: Signal and noise analysis of the voltage responses to a white-noise (WN) light stimulus.A, A pseudorandom light intensity pattern superimposed on a constant light background provided a WN contrast stimulus that was presented 30 times to the cell. The evoked responses are averaged to give the voltage signal and the remaining differences are the noise traces (A, scale bars: 500 ms, 5 mV). B, The corresponding power spectra are calculated for each of the five light BGs. Note that 〈/S(f)/2〉, 〈/N(f)/2〉, and 〈/r(f)/2〉 are displayed using the same scale, in mV2 Hz−1. 〈/C(f)/2〉 is in c2 Hz−1. C, These changes can be further quantified by computing the signal-to-noise ratio spectrum, SNR(f), and the cross-spectrum between the signal and the stimulus. These two spectra are the starting points to quantify the properties of the photoreceptor voltage responses (Figs. 2 and 3), the SNR(f) being used for the analysis of the coding properties (Fig. 2) and the cross-spectrum for the analysis of the transfer properties (Fig. 3). ‘Power’ on the ordinate scale of the cross-spectrum means here c mV Hz−1.
Mentions: Membrane potentials of green-sensitive R1–R6 photoreceptor cells [29], [30] were recorded with a switched-clamp amplifier SEC-10L (NPI Electronic) operating in the compensated current-clamp mode. A successful photoreceptor penetration was seen as a 60–80 mV drop in the electrode potential followed by vigorous responses to dim pulses. Before the experiments, the cells were allowed to dark-adapt and seal properly. Only data from photoreceptors with saturating impulse responses ≥40 mV and dark resting potential ≤−60 mV were used in the analysis. In this article, we exhibit our findings using two exemplary photoreceptors. Similar results were obtained from other photoreceptors (n = 15) that endured long-lasting recordings. These data are presented in the Supporting Information. A first photoreceptor is used throughout Materials and Methods to illustrate the way data was analyzed (Figs. 1 to 3) at a constant temperature (19°C). The second one is used throughout the article (Figs. 4 to 12). Because of its exceptional stability, we were able to use this cell in many separate experiments and so to explore how light adaptation occurs over a vast range of background intensities and temperatures (from 17 to 23°C). For these experiments we used both white-noise (WN) and naturalistic stimulation (NS), and were able to further investigate how the membrane properties of the cell varied at each experimental condition. Additionally, we made recordings from many other photoreceptors (>30 of outstanding quality) over a smaller range of experimental conditions. These recordings were consistent with the general framework presented here. Because we believe that intrinsic functional variability between photoreceptors could be an important feature of locust vision (see Discussion), we do not show averaged quantities. Data from these cells is shown as Q10 values in Table 1 and detailed further in Table S1.

Bottom Line: We found that brightening or warming increase and accelerate voltage responses, but reduce noise, enabling photoreceptors to encode more information.Furthermore, the Q(10)s of bump duration and latency distribution depended on light intensity.Altogether, this study suggests that biochemical constraints imposed upon signaling change continuously as locust photoreceptors adapt to environmental light and temperature conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Zoology, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Information capture by photoreceptors ultimately limits the quality of visual processing in the brain. Using conventional sharp microelectrodes, we studied how locust photoreceptors encode random (white-noise, WN) and naturalistic (1/f stimuli, NS) light patterns in vivo and how this coding changes with mean illumination and ambient temperature. We also examined the role of their plasma membrane in shaping voltage responses. We found that brightening or warming increase and accelerate voltage responses, but reduce noise, enabling photoreceptors to encode more information. For WN stimuli, this was accompanied by broadening of the linear frequency range. On the contrary, with NS the signaling took place within a constant bandwidth, possibly revealing a 'preference' for inputs with 1/f statistics. The faster signaling was caused by acceleration of the elementary phototransduction current--leading to bumps--and their distribution. The membrane linearly translated phototransduction currents into voltage responses without limiting the throughput of these messages. As the bumps reflected fast changes in membrane resistance, the data suggest that their shape is predominantly driven by fast changes in the light-gated conductance. On the other hand, the slower bump latency distribution is likely to represent slower enzymatic intracellular reactions. Furthermore, the Q(10)s of bump duration and latency distribution depended on light intensity. Altogether, this study suggests that biochemical constraints imposed upon signaling change continuously as locust photoreceptors adapt to environmental light and temperature conditions.

Show MeSH