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Efficient temporal processing of naturalistic sounds.

Lesica NA, Grothe B - PLoS ONE (2008)

Bottom Line: We find that the onset of ambient noise evokes a change in receptive field dynamics that corresponds to a change from bandpass to lowpass temporal filtering.We show that these changes occur within a few hundred milliseconds of the onset of the noise and are evident across a range of overall stimulus intensities.Using a simple model, we illustrate how these changes in temporal processing exploit differences in the statistical properties of vocalizations and ambient noises to increase the information in the neural response in a manner consistent with the principles of efficient coding.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology II, Ludwig-Maximilians-University Munich, Martinsried, Germany. lesica@zi.biologie.uni-muenchen.de

ABSTRACT
In this study, we investigate the ability of the mammalian auditory pathway to adapt its strategy for temporal processing under natural stimulus conditions. We derive temporal receptive fields from the responses of neurons in the inferior colliculus to vocalization stimuli with and without additional ambient noise. We find that the onset of ambient noise evokes a change in receptive field dynamics that corresponds to a change from bandpass to lowpass temporal filtering. We show that these changes occur within a few hundred milliseconds of the onset of the noise and are evident across a range of overall stimulus intensities. Using a simple model, we illustrate how these changes in temporal processing exploit differences in the statistical properties of vocalizations and ambient noises to increase the information in the neural response in a manner consistent with the principles of efficient coding.

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Rapid changes in temporal processing are evoked by the onset or offset of ambient noise.a) A schematic illustration of the stimulus, which switched between V and VN every 3 seconds. The gray line represents the actual stimulus and the black line represents the vocalization modulation signal. b) The temporal RFs of a typical cell estimated just before and just after noise onset and offset. The preferred frequency of the cell was 6.7 KHz. The error bars represent 95% confidence bounds. The RFs were normalized to have the same peak value for plotting. The colors of the RFs correspond to the time intervals marked in a. c) The MTFs corresponding to the RFs in b. Before computing the MTFs, RFs were normalized such that the variance of the result of the convolution of the RF with the vocalization signal was one. d) The LF area of the MTFs for a sample of 6 cells, estimated at 200 ms intervals after noise onset and offset. The colored circles correspond to the time intervals marked in a. The results for each cell were normalized such that the LF area just before noise offset was 0 and the LF area just before noise onset was 1. The error bars represent one standard deviation of the distribution of normalized LF areas across the sample of cells.
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pone-0001655-g004: Rapid changes in temporal processing are evoked by the onset or offset of ambient noise.a) A schematic illustration of the stimulus, which switched between V and VN every 3 seconds. The gray line represents the actual stimulus and the black line represents the vocalization modulation signal. b) The temporal RFs of a typical cell estimated just before and just after noise onset and offset. The preferred frequency of the cell was 6.7 KHz. The error bars represent 95% confidence bounds. The RFs were normalized to have the same peak value for plotting. The colors of the RFs correspond to the time intervals marked in a. c) The MTFs corresponding to the RFs in b. Before computing the MTFs, RFs were normalized such that the variance of the result of the convolution of the RF with the vocalization signal was one. d) The LF area of the MTFs for a sample of 6 cells, estimated at 200 ms intervals after noise onset and offset. The colored circles correspond to the time intervals marked in a. The results for each cell were normalized such that the LF area just before noise offset was 0 and the LF area just before noise onset was 1. The error bars represent one standard deviation of the distribution of normalized LF areas across the sample of cells.

Mentions: To determine the time-course of the observed changes in temporal processing, we recorded responses while the stimulus was repeatedly switched between V and VN, and estimated temporal RFs at a range of times relative to noise onset or offset. A schematic illustration of the stimulus, which switched between V and VN every 3 seconds, is shown in figure 4a. Figure 4b shows the temporal RFs of a typical cell estimated just before and just after noise onset and offset. The RFs estimated just after noise onset (green) and 3 seconds after noise onset (red) are nearly identical, as are the RFs estimated just after noise offset (blue) and 3 seconds after noise offset (black). This is also evident in the MTFs shown in figure 4c, as the MTFs just after noise onset (green) and 3 seconds after noise onset (red) are lowpass, while the MTFs estimated just after noise offset (blue) and 3 seconds after noise offset (black) are bandpass. As shown in figure 4d, these results were consistent across a sample of 6 cells, as the LF area of the MTFs changed immediately (within 200 ms) following noise onset and offset and remained relatively constant until the next switch.


Efficient temporal processing of naturalistic sounds.

Lesica NA, Grothe B - PLoS ONE (2008)

Rapid changes in temporal processing are evoked by the onset or offset of ambient noise.a) A schematic illustration of the stimulus, which switched between V and VN every 3 seconds. The gray line represents the actual stimulus and the black line represents the vocalization modulation signal. b) The temporal RFs of a typical cell estimated just before and just after noise onset and offset. The preferred frequency of the cell was 6.7 KHz. The error bars represent 95% confidence bounds. The RFs were normalized to have the same peak value for plotting. The colors of the RFs correspond to the time intervals marked in a. c) The MTFs corresponding to the RFs in b. Before computing the MTFs, RFs were normalized such that the variance of the result of the convolution of the RF with the vocalization signal was one. d) The LF area of the MTFs for a sample of 6 cells, estimated at 200 ms intervals after noise onset and offset. The colored circles correspond to the time intervals marked in a. The results for each cell were normalized such that the LF area just before noise offset was 0 and the LF area just before noise onset was 1. The error bars represent one standard deviation of the distribution of normalized LF areas across the sample of cells.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2249929&req=5

pone-0001655-g004: Rapid changes in temporal processing are evoked by the onset or offset of ambient noise.a) A schematic illustration of the stimulus, which switched between V and VN every 3 seconds. The gray line represents the actual stimulus and the black line represents the vocalization modulation signal. b) The temporal RFs of a typical cell estimated just before and just after noise onset and offset. The preferred frequency of the cell was 6.7 KHz. The error bars represent 95% confidence bounds. The RFs were normalized to have the same peak value for plotting. The colors of the RFs correspond to the time intervals marked in a. c) The MTFs corresponding to the RFs in b. Before computing the MTFs, RFs were normalized such that the variance of the result of the convolution of the RF with the vocalization signal was one. d) The LF area of the MTFs for a sample of 6 cells, estimated at 200 ms intervals after noise onset and offset. The colored circles correspond to the time intervals marked in a. The results for each cell were normalized such that the LF area just before noise offset was 0 and the LF area just before noise onset was 1. The error bars represent one standard deviation of the distribution of normalized LF areas across the sample of cells.
Mentions: To determine the time-course of the observed changes in temporal processing, we recorded responses while the stimulus was repeatedly switched between V and VN, and estimated temporal RFs at a range of times relative to noise onset or offset. A schematic illustration of the stimulus, which switched between V and VN every 3 seconds, is shown in figure 4a. Figure 4b shows the temporal RFs of a typical cell estimated just before and just after noise onset and offset. The RFs estimated just after noise onset (green) and 3 seconds after noise onset (red) are nearly identical, as are the RFs estimated just after noise offset (blue) and 3 seconds after noise offset (black). This is also evident in the MTFs shown in figure 4c, as the MTFs just after noise onset (green) and 3 seconds after noise onset (red) are lowpass, while the MTFs estimated just after noise offset (blue) and 3 seconds after noise offset (black) are bandpass. As shown in figure 4d, these results were consistent across a sample of 6 cells, as the LF area of the MTFs changed immediately (within 200 ms) following noise onset and offset and remained relatively constant until the next switch.

Bottom Line: We find that the onset of ambient noise evokes a change in receptive field dynamics that corresponds to a change from bandpass to lowpass temporal filtering.We show that these changes occur within a few hundred milliseconds of the onset of the noise and are evident across a range of overall stimulus intensities.Using a simple model, we illustrate how these changes in temporal processing exploit differences in the statistical properties of vocalizations and ambient noises to increase the information in the neural response in a manner consistent with the principles of efficient coding.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology II, Ludwig-Maximilians-University Munich, Martinsried, Germany. lesica@zi.biologie.uni-muenchen.de

ABSTRACT
In this study, we investigate the ability of the mammalian auditory pathway to adapt its strategy for temporal processing under natural stimulus conditions. We derive temporal receptive fields from the responses of neurons in the inferior colliculus to vocalization stimuli with and without additional ambient noise. We find that the onset of ambient noise evokes a change in receptive field dynamics that corresponds to a change from bandpass to lowpass temporal filtering. We show that these changes occur within a few hundred milliseconds of the onset of the noise and are evident across a range of overall stimulus intensities. Using a simple model, we illustrate how these changes in temporal processing exploit differences in the statistical properties of vocalizations and ambient noises to increase the information in the neural response in a manner consistent with the principles of efficient coding.

Show MeSH