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A potential neural substrate for processing functional classes of complex acoustic signals.

George I, Cousillas H, Richard JP, Hausberger M - PLoS ONE (2008)

Bottom Line: Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons.These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members.Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

View Article: PubMed Central - PubMed

Affiliation: Université Rennes 1, CNRS, UMR 6552 Ethologie Animale et Humaine, Rennes, France. isabelle.george@univ-rennes1.fr

ABSTRACT
Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM) has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

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Mean (+SE) percentage of responsive sites that responded to each class of stimulus.Grey bars: pooled data of both hemispheres; white bars: data of the left hemisphere; black bars: data of the right hemisphere. * p<0.001 compared to every other groups (PLSD Fisher tests).
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pone-0002203-g004: Mean (+SE) percentage of responsive sites that responded to each class of stimulus.Grey bars: pooled data of both hemispheres; white bars: data of the left hemisphere; black bars: data of the right hemisphere. * p<0.001 compared to every other groups (PLSD Fisher tests).

Mentions: Most importantly, when we considered responses to each class of stimuli, it appeared that both the proportion of responsive neuronal sites (Fig. 4) and the magnitude of the neuronal responses (as measured by Z scores; Fig. 5) significantly differed from one class to another: responses were the strongest for the highly individual class-III motifs, followed by the individual-specific class-II songs, the species-specific class-I whistles, and finally the artificial non-specific stimuli (two-way repeated-measures ANOVAs and PLSD Fisher tests, stimulus class effect: p<0.0001 for both the proportion of responding sites and the Z scores, post-hoc comparisons: p<0.05 for all pairwise comparisons in both cases, no hemisphere effect, no interaction). These differences were neither due to a specific bird (since within-bird comparisons showed the same effect or trend in each bird) nor to one particular subset of stimuli (as, with the exception of the species-specific clicks in class III, proportions of sites responding to each stimulus appeared to be relatively homogenous within each class; see Fig. 3). Thus, intra-class variations appeared to be lower than inter-class variations, especially for class-II and individual-specific class-III stimuli which showed coefficients of variation (CVs) that were 3 to more than 7 times lower than the CV observed across all stimuli (mean CVs for class II = 21 and 22%, for class III w/o clicks = 12 and 9% and for all stimuli = 64 and 69%, respectively for the left and right hemispheres).


A potential neural substrate for processing functional classes of complex acoustic signals.

George I, Cousillas H, Richard JP, Hausberger M - PLoS ONE (2008)

Mean (+SE) percentage of responsive sites that responded to each class of stimulus.Grey bars: pooled data of both hemispheres; white bars: data of the left hemisphere; black bars: data of the right hemisphere. * p<0.001 compared to every other groups (PLSD Fisher tests).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2376065&req=5

pone-0002203-g004: Mean (+SE) percentage of responsive sites that responded to each class of stimulus.Grey bars: pooled data of both hemispheres; white bars: data of the left hemisphere; black bars: data of the right hemisphere. * p<0.001 compared to every other groups (PLSD Fisher tests).
Mentions: Most importantly, when we considered responses to each class of stimuli, it appeared that both the proportion of responsive neuronal sites (Fig. 4) and the magnitude of the neuronal responses (as measured by Z scores; Fig. 5) significantly differed from one class to another: responses were the strongest for the highly individual class-III motifs, followed by the individual-specific class-II songs, the species-specific class-I whistles, and finally the artificial non-specific stimuli (two-way repeated-measures ANOVAs and PLSD Fisher tests, stimulus class effect: p<0.0001 for both the proportion of responding sites and the Z scores, post-hoc comparisons: p<0.05 for all pairwise comparisons in both cases, no hemisphere effect, no interaction). These differences were neither due to a specific bird (since within-bird comparisons showed the same effect or trend in each bird) nor to one particular subset of stimuli (as, with the exception of the species-specific clicks in class III, proportions of sites responding to each stimulus appeared to be relatively homogenous within each class; see Fig. 3). Thus, intra-class variations appeared to be lower than inter-class variations, especially for class-II and individual-specific class-III stimuli which showed coefficients of variation (CVs) that were 3 to more than 7 times lower than the CV observed across all stimuli (mean CVs for class II = 21 and 22%, for class III w/o clicks = 12 and 9% and for all stimuli = 64 and 69%, respectively for the left and right hemispheres).

Bottom Line: Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons.These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members.Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

View Article: PubMed Central - PubMed

Affiliation: Université Rennes 1, CNRS, UMR 6552 Ethologie Animale et Humaine, Rennes, France. isabelle.george@univ-rennes1.fr

ABSTRACT
Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM) has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

Show MeSH
Related in: MedlinePlus