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Probing real sensory worlds of receivers with unsupervised clustering.

Pfeiffer M, Hartbauer M, Lang AB, Maass W, Römer H - PLoS ONE (2012)

Bottom Line: Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab.Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions.This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands.

View Article: PubMed Central - PubMed

Affiliation: Institute for Theoretical Computer Science, TU Graz, Graz, Austria. pfeiffer@ini.phys.ethz.ch

ABSTRACT
The task of an organism to extract information about the external environment from sensory signals is based entirely on the analysis of ongoing afferent spike activity provided by the sense organs. We investigate the processing of auditory stimuli by an acoustic interneuron of insects. In contrast to most previous work we do this by using stimuli and neurophysiological recordings directly in the nocturnal tropical rainforest, where the insect communicates. Different from typical recordings in sound proof laboratories, strong environmental noise from multiple sound sources interferes with the perception of acoustic signals in these realistic scenarios. We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. We can thus ask how much information the central nervous system of the receiver can extract from bursts without ever being told which type and which variants of bursts are characteristic for particular stimuli. Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab. Simultaneous recordings in two preparations exposed to the same acoustic environment reveal that characteristics of burst patterns are largely preserved among individuals of the same species. Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions. This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands.

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Firing and bursting during simultaneous recordings.A) Short sequence of the original spike recording of both cells recorded simultaneously. B): Firing and burst rates of both cells for a duration of 20 minutes. The firing rates of preparation 1 and 2 are correlated with a correlation coefficient of . The burst rates are correlated with . Mean firing rates over the entire 20 minute recordings are 9.98 Hz (preparation 1) and 12.20 Hz (preparation 2), and mean bursting rates are 0.53 Hz and 0.41 Hz respectively. (Bin size: 1 sec for firing rate, 100 sec for bursting rate).
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pone-0037354-g011: Firing and bursting during simultaneous recordings.A) Short sequence of the original spike recording of both cells recorded simultaneously. B): Firing and burst rates of both cells for a duration of 20 minutes. The firing rates of preparation 1 and 2 are correlated with a correlation coefficient of . The burst rates are correlated with . Mean firing rates over the entire 20 minute recordings are 9.98 Hz (preparation 1) and 12.20 Hz (preparation 2), and mean bursting rates are 0.53 Hz and 0.41 Hz respectively. (Bin size: 1 sec for firing rate, 100 sec for bursting rate).

Mentions: In the previous section we compared the similarity of burst activity in the omega-neuron between lab and outdoor recordings, or between different cells in different nights. The “biological microphone approach” offers in addition one unique opportunity to test the power of our method, by comparing the burst responses of omega cells from two different preparations recorded simultaneously, and placed next to each other, so that they experience the same acoustic events. For the experiment presented in Figures 11 and 12 the two preparations were placed in the nocturnal rainforest, at a distance of about 10 cm from each other, so that they were exposed to the same acoustic environment. Prior to these recordings, the threshold of each omega-cell in response to a pure tone, 20 kHz stimulus was determined in the laboratory, and one preparation was 5 dB less sensitive compared to the other preparation. In this experiment, no artificial sound stimuli were broadcast to the preparations, so all bursts had been elicited as a result of background noise alone. Figure 11A shows a short sequence of the original spike recording of both cells, and in Figure 11B the firing and burst rates of both cells are illustrated for a sequence of continuous 20 minutes of recording. The gross firing and bursting pattern of both cells is rather similar (Figure 11A), although the less sensitive cell exhibits a reduced firing rate (Figure 11B). The firing rates are actually correlated with a correlation coefficient of , the bursting rates are correlated with .


Probing real sensory worlds of receivers with unsupervised clustering.

Pfeiffer M, Hartbauer M, Lang AB, Maass W, Römer H - PLoS ONE (2012)

Firing and bursting during simultaneous recordings.A) Short sequence of the original spike recording of both cells recorded simultaneously. B): Firing and burst rates of both cells for a duration of 20 minutes. The firing rates of preparation 1 and 2 are correlated with a correlation coefficient of . The burst rates are correlated with . Mean firing rates over the entire 20 minute recordings are 9.98 Hz (preparation 1) and 12.20 Hz (preparation 2), and mean bursting rates are 0.53 Hz and 0.41 Hz respectively. (Bin size: 1 sec for firing rate, 100 sec for bursting rate).
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3368931&req=5

pone-0037354-g011: Firing and bursting during simultaneous recordings.A) Short sequence of the original spike recording of both cells recorded simultaneously. B): Firing and burst rates of both cells for a duration of 20 minutes. The firing rates of preparation 1 and 2 are correlated with a correlation coefficient of . The burst rates are correlated with . Mean firing rates over the entire 20 minute recordings are 9.98 Hz (preparation 1) and 12.20 Hz (preparation 2), and mean bursting rates are 0.53 Hz and 0.41 Hz respectively. (Bin size: 1 sec for firing rate, 100 sec for bursting rate).
Mentions: In the previous section we compared the similarity of burst activity in the omega-neuron between lab and outdoor recordings, or between different cells in different nights. The “biological microphone approach” offers in addition one unique opportunity to test the power of our method, by comparing the burst responses of omega cells from two different preparations recorded simultaneously, and placed next to each other, so that they experience the same acoustic events. For the experiment presented in Figures 11 and 12 the two preparations were placed in the nocturnal rainforest, at a distance of about 10 cm from each other, so that they were exposed to the same acoustic environment. Prior to these recordings, the threshold of each omega-cell in response to a pure tone, 20 kHz stimulus was determined in the laboratory, and one preparation was 5 dB less sensitive compared to the other preparation. In this experiment, no artificial sound stimuli were broadcast to the preparations, so all bursts had been elicited as a result of background noise alone. Figure 11A shows a short sequence of the original spike recording of both cells, and in Figure 11B the firing and burst rates of both cells are illustrated for a sequence of continuous 20 minutes of recording. The gross firing and bursting pattern of both cells is rather similar (Figure 11A), although the less sensitive cell exhibits a reduced firing rate (Figure 11B). The firing rates are actually correlated with a correlation coefficient of , the bursting rates are correlated with .

Bottom Line: Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab.Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions.This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands.

View Article: PubMed Central - PubMed

Affiliation: Institute for Theoretical Computer Science, TU Graz, Graz, Austria. pfeiffer@ini.phys.ethz.ch

ABSTRACT
The task of an organism to extract information about the external environment from sensory signals is based entirely on the analysis of ongoing afferent spike activity provided by the sense organs. We investigate the processing of auditory stimuli by an acoustic interneuron of insects. In contrast to most previous work we do this by using stimuli and neurophysiological recordings directly in the nocturnal tropical rainforest, where the insect communicates. Different from typical recordings in sound proof laboratories, strong environmental noise from multiple sound sources interferes with the perception of acoustic signals in these realistic scenarios. We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. We can thus ask how much information the central nervous system of the receiver can extract from bursts without ever being told which type and which variants of bursts are characteristic for particular stimuli. Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab. Simultaneous recordings in two preparations exposed to the same acoustic environment reveal that characteristics of burst patterns are largely preserved among individuals of the same species. Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions. This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands.

Show MeSH