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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 response curve parameter B50 for all 20 AN2 cells.Distribution of the mean values of the parameters B50 for individual cells (A1) and combined posterior density (see Methods, Bayesian data analysis) over all cells (A2) after adaptation to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter B50 after adaptation to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the change of the parameter B50 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 B50 that were significant (Bayesian posterior intervals, see Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas depict the two-tailed 95% posterior intervals in (A2,B2) and the right-tailed 95% posterior interval in (C2).
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pcbi-1000182-g011: Summary of adaptation induced changes of the response curve parameter B50 for all 20 AN2 cells.Distribution of the mean values of the parameters B50 for individual cells (A1) and combined posterior density (see Methods, Bayesian data analysis) over all cells (A2) after adaptation to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter B50 after adaptation to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the change of the parameter B50 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 B50 that were significant (Bayesian posterior intervals, see Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas depict the two-tailed 95% posterior intervals in (A2,B2) and the right-tailed 95% posterior interval in (C2).

Mentions: Figure 11 summarizes the mean values of the posterior densities of the B50 parameters for all 20 AN2 cells. Figure 11A1 shows the values of parameter B50 after adaptation to the bimodal stimulus. The median value in the population is 2.34 dB (mean: 2.43 dB) and 2.02 dB (mean: 2.07 dB) for cells in which adaptation to the trimodal stimulus led to individual statistically significant changes in parameter B50 compared to adaptation to the bimodal stimulus (black distribution). The optimal B50 value predicted by the infomax principle is −1.5 dB (star), while selective coding predicts a B50 value of 0 dB (circle). The combined posterior distribution of B50 (cf. Methods, Bayesian data analysis) is shown in Figure 11A2 (mean: 2.43 dB). The measured B50 values are significantly larger than the values predicted by either hypotheses (infomax: −1.5 dB, selective coding: 0 dB). Figure 11B1 shows the histogram of B50 values after adaptation to the trimodal stimulus (median: 3.92 dB, mean: 4.04 dB; individually significant cells: median: 3.57 dB, mean: 3.69 dB). These values are significantly larger than the infomax prediction, but similar to the selective coding prediction (Figure 11B2). Figure 11C1 quantifies the difference of the parameter B50 between the two adaptation conditions. The median of the distribution of differences is 1.53 dB (mean: 1.61 dB). The right-tailed posterior interval in Figure 11C2 excludes the value 0 dB, indicating that adaptation to the trimodal stimulus significantly shifts the distribution of response curves towards higher signal intensities. Individual differences are statistically significant in 8 of 20 cells (see Methods, Bayesian data analysis); the median of the changes in these cells is 1.46 dB (mean: 1.62 dB). The observed shifts are smaller than expected for optimal selective coding (predicted shift: 3 dB), but compatible with the infomax principle (predicted shift: 1.5 dB). Due to the high absolute values of the thresholds, however, the response curves do not allow for reliable encoding of the whole stimulus range.


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 response curve parameter B50 for all 20 AN2 cells.Distribution of the mean values of the parameters B50 for individual cells (A1) and combined posterior density (see Methods, Bayesian data analysis) over all cells (A2) after adaptation to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter B50 after adaptation to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the change of the parameter B50 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 B50 that were significant (Bayesian posterior intervals, see Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas depict the two-tailed 95% posterior intervals in (A2,B2) and the right-tailed 95% posterior interval in (C2).
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pcbi-1000182-g011: Summary of adaptation induced changes of the response curve parameter B50 for all 20 AN2 cells.Distribution of the mean values of the parameters B50 for individual cells (A1) and combined posterior density (see Methods, Bayesian data analysis) over all cells (A2) after adaptation to the bimodal stimulus distribution. (B1,B2) Distribution and combined posterior density of the parameter B50 after adaptation to the trimodal stimulus distribution. (C1,C2) Distribution and combined posterior density of the change of the parameter B50 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 B50 that were significant (Bayesian posterior intervals, see Methods, Bayesian data analysis) is marked black in (A1,B1,C1). Shaded areas depict the two-tailed 95% posterior intervals in (A2,B2) and the right-tailed 95% posterior interval in (C2).
Mentions: Figure 11 summarizes the mean values of the posterior densities of the B50 parameters for all 20 AN2 cells. Figure 11A1 shows the values of parameter B50 after adaptation to the bimodal stimulus. The median value in the population is 2.34 dB (mean: 2.43 dB) and 2.02 dB (mean: 2.07 dB) for cells in which adaptation to the trimodal stimulus led to individual statistically significant changes in parameter B50 compared to adaptation to the bimodal stimulus (black distribution). The optimal B50 value predicted by the infomax principle is −1.5 dB (star), while selective coding predicts a B50 value of 0 dB (circle). The combined posterior distribution of B50 (cf. Methods, Bayesian data analysis) is shown in Figure 11A2 (mean: 2.43 dB). The measured B50 values are significantly larger than the values predicted by either hypotheses (infomax: −1.5 dB, selective coding: 0 dB). Figure 11B1 shows the histogram of B50 values after adaptation to the trimodal stimulus (median: 3.92 dB, mean: 4.04 dB; individually significant cells: median: 3.57 dB, mean: 3.69 dB). These values are significantly larger than the infomax prediction, but similar to the selective coding prediction (Figure 11B2). Figure 11C1 quantifies the difference of the parameter B50 between the two adaptation conditions. The median of the distribution of differences is 1.53 dB (mean: 1.61 dB). The right-tailed posterior interval in Figure 11C2 excludes the value 0 dB, indicating that adaptation to the trimodal stimulus significantly shifts the distribution of response curves towards higher signal intensities. Individual differences are statistically significant in 8 of 20 cells (see Methods, Bayesian data analysis); the median of the changes in these cells is 1.46 dB (mean: 1.62 dB). The observed shifts are smaller than expected for optimal selective coding (predicted shift: 3 dB), but compatible with the infomax principle (predicted shift: 1.5 dB). Due to the high absolute values of the thresholds, however, the response curves do not allow for reliable encoding of the whole stimulus range.

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