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Adaptation and selective information transmission in the cricket auditory neuron AN2.

Wimmer K, Hildebrandt KJ, Hennig RM, Obermayer K - PLoS Comput. Biol. (2008)

Bottom Line: The spike responses were thus reduced for low-intensity sounds.Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals.The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Germany. klaus@cs.tu-berlin.de

ABSTRACT
Sensory systems adapt their neural code to changes in the sensory environment, often on multiple time scales. Here, we report a new form of adaptation in a first-order auditory interneuron (AN2) of crickets. We characterize the response of the AN2 neuron to amplitude-modulated sound stimuli and find that adaptation shifts the stimulus-response curves toward higher stimulus intensities, with a time constant of 1.5 s for adaptation and recovery. The spike responses were thus reduced for low-intensity sounds. We then address the question whether adaptation leads to an improvement of the signal's representation and compare the experimental results with the predictions of two competing hypotheses: infomax, which predicts that information conveyed about the entire signal range should be maximized, and selective coding, which predicts that "foreground" signals should be enhanced while "background" signals should be selectively suppressed. We test how adaptation changes the input-response curve when presenting signals with two or three peaks in their amplitude distributions, for which selective coding and infomax predict conflicting changes. By means of Bayesian data analysis, we quantify the shifts of the measured response curves and also find a slight reduction of their slopes. These decreases in slopes are smaller, and the absolute response thresholds are higher than those predicted by infomax. Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals. The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant. Less information is transmitted about signals with lower intensity.

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Summary of adaptation induced changes of the slope S50 of the response curves.Distribution of the mean values of the parameters S50 for individual cells (A1) and combined posterior density (cf. Methods, Bayesian data analysis) over all cells (A2) after adapting to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter S50 after adapting to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the relative change of S50 between the two stimulus distributions. Symbols depict the values predicted by infomax (stars) and the selective coding hypothesis (circles). Triangles denote the median value. The distribution of cells that showed changes in S50 that were significant (Bayesian posterior intervals, Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas in (A2,B2,C2) depict the 95% posterior intervals.
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pcbi-1000182-g012: Summary of adaptation induced changes of the slope S50 of the response curves.Distribution of the mean values of the parameters S50 for individual cells (A1) and combined posterior density (cf. Methods, Bayesian data analysis) over all cells (A2) after adapting to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter S50 after adapting to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the relative change of S50 between the two stimulus distributions. Symbols depict the values predicted by infomax (stars) and the selective coding hypothesis (circles). Triangles denote the median value. The distribution of cells that showed changes in S50 that were significant (Bayesian posterior intervals, Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas in (A2,B2,C2) depict the 95% posterior intervals.

Mentions: Figure 12 summarizes the mean estimates of the slope S50, for all 20 AN2 cells. The slopes in the bimodal adaptation paradigm (shown in Figure 12A1) have a median value of 0.16 dB−1 (mean: 0.17 dB−1), and are significantly smaller than the value of 0.98 dB−1 predicted by the selective coding hypothesis (Figure 12A2). The observed slopes S50 after adaptation to the trimodal stimulus are shown in Figure 12B, and the relative change of the slope compared to the bimodal paradigm is quantified in Figure 12C. The slope decreased for most cells (median: −15.1%, mean: −15.6%). Significant changes in S50 were found individually in 5 of 20 cells, and all of those cells showed decreases in slope. However, the changes are less pronounced than predicted by the infomax principle.


Adaptation and selective information transmission in the cricket auditory neuron AN2.

Wimmer K, Hildebrandt KJ, Hennig RM, Obermayer K - PLoS Comput. Biol. (2008)

Summary of adaptation induced changes of the slope S50 of the response curves.Distribution of the mean values of the parameters S50 for individual cells (A1) and combined posterior density (cf. Methods, Bayesian data analysis) over all cells (A2) after adapting to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter S50 after adapting to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the relative change of S50 between the two stimulus distributions. Symbols depict the values predicted by infomax (stars) and the selective coding hypothesis (circles). Triangles denote the median value. The distribution of cells that showed changes in S50 that were significant (Bayesian posterior intervals, Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas in (A2,B2,C2) depict the 95% posterior intervals.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2527132&req=5

pcbi-1000182-g012: Summary of adaptation induced changes of the slope S50 of the response curves.Distribution of the mean values of the parameters S50 for individual cells (A1) and combined posterior density (cf. Methods, Bayesian data analysis) over all cells (A2) after adapting to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter S50 after adapting to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the relative change of S50 between the two stimulus distributions. Symbols depict the values predicted by infomax (stars) and the selective coding hypothesis (circles). Triangles denote the median value. The distribution of cells that showed changes in S50 that were significant (Bayesian posterior intervals, Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas in (A2,B2,C2) depict the 95% posterior intervals.
Mentions: Figure 12 summarizes the mean estimates of the slope S50, for all 20 AN2 cells. The slopes in the bimodal adaptation paradigm (shown in Figure 12A1) have a median value of 0.16 dB−1 (mean: 0.17 dB−1), and are significantly smaller than the value of 0.98 dB−1 predicted by the selective coding hypothesis (Figure 12A2). The observed slopes S50 after adaptation to the trimodal stimulus are shown in Figure 12B, and the relative change of the slope compared to the bimodal paradigm is quantified in Figure 12C. The slope decreased for most cells (median: −15.1%, mean: −15.6%). Significant changes in S50 were found individually in 5 of 20 cells, and all of those cells showed decreases in slope. However, the changes are less pronounced than predicted by the infomax principle.

Bottom Line: The spike responses were thus reduced for low-intensity sounds.Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals.The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Germany. klaus@cs.tu-berlin.de

ABSTRACT
Sensory systems adapt their neural code to changes in the sensory environment, often on multiple time scales. Here, we report a new form of adaptation in a first-order auditory interneuron (AN2) of crickets. We characterize the response of the AN2 neuron to amplitude-modulated sound stimuli and find that adaptation shifts the stimulus-response curves toward higher stimulus intensities, with a time constant of 1.5 s for adaptation and recovery. The spike responses were thus reduced for low-intensity sounds. We then address the question whether adaptation leads to an improvement of the signal's representation and compare the experimental results with the predictions of two competing hypotheses: infomax, which predicts that information conveyed about the entire signal range should be maximized, and selective coding, which predicts that "foreground" signals should be enhanced while "background" signals should be selectively suppressed. We test how adaptation changes the input-response curve when presenting signals with two or three peaks in their amplitude distributions, for which selective coding and infomax predict conflicting changes. By means of Bayesian data analysis, we quantify the shifts of the measured response curves and also find a slight reduction of their slopes. These decreases in slopes are smaller, and the absolute response thresholds are higher than those predicted by infomax. Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals. The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant. Less information is transmitted about signals with lower intensity.

Show MeSH
Related in: MedlinePlus