Neural basis of sound pattern recognition in anurans

Feng, Albert S.; Hall, Jim C.; Gooler, David M.

doi:10.1016/0301-0082(90)90008-5

Cited by 152 publications

(59 citation statements)

References 56 publications

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“…(12) Duration-tuned neurons are found not only in several species of bats (Pinheiro et al, 1991;Casseday et al, 1994;Galazyuk and Feng, 1997;Ma and Suga, 2001b), but also in cats (He et al, 1997), chinchillas (Chen, 1998), mice (Brand et al, 2000), and frogs (Potter, 1965;Feng et al, 1990;Gooler and Feng, 1992).…”

Section: Discussionmentioning

confidence: 99%

Specific and Nonspecific Plasticity of the Primary Auditory Cortex Elicited by Thalamic Auditory Neurons

Ma¹,

Suga²

2009

J. Neurosci.

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The ventral and medial divisions of the medial geniculate body (MGBv and MGBm) respectively are the lemniscal and nonlemniscal thalamic auditory nuclei. Lemniscal neurons are narrowly frequency tuned and provide highly specific frequency information to the primary auditory cortex (AI), whereas nonlemniscal neurons are broadly frequency tuned and project widely to auditory cortical areas including AI. The MGBv and MGBm are presumably different not only in auditory signal processing, but also in eliciting cortical plastic changes. We electrically stimulated MGBv or MGBm neurons and found the following: (1)

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Section: Discussionmentioning

confidence: 99%

Specific and Nonspecific Plasticity of the Primary Auditory Cortex Elicited by Thalamic Auditory Neurons

Ma¹,

Suga²

2009

J. Neurosci.

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“…Historically, the first use of natural sounds in auditory neuroscience came from neuro-ethologists who investigated how conspecific vocalizations or communication signals were selectively processed in the auditory system of auditory specialists. These investigations in model systems led to the discovery of cricket-song selective neurons and their contribution to the females' phonotaxis behavior [77], of call selective neurons in frogs [78] and guinea pigs [79], of song selective neurons in songbirds [7,[80][81][82], of neurons selective to the echolocation signal in bats [5], and of brain regions selective for conspecific calls in primates [83]. Selectivity for conspecific communication calls can be reflected not only in the mean rate of single neurons but also (and sometimes only) in time-varying responses [84,85] or ensemble responses [86,87].…”

Section: Animal Vocalizationsmentioning

confidence: 99%

Neural processing of natural sounds

2014

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Natural sounds have unique statistical structure that makes them perceptually salient. The auditory system is finely tuned to this natural structure. Selective neurons found at the higher levels of the auditory system respond selectively to vocalizations used in communication. On-line Summary1. Natural sounds include animal vocalizations, environmental sounds such as wind, water and fire noises and non-vocal sounds made by animals and humans for communication. These natural sounds have characteristic statistical properties that make them perceptually salient and that drive auditory neurons in optimal regimes for information transmission. 2.Recent advances in statistics and computer sciences have allowed neuro-physiologists to extract the stimulus-response function of complex auditory neurons from responses to natural sounds. These studies have shown a hierarchical processing that leads to the neural detection of progressively more complex natural sound features and have demonstrated the importance of the acoustical and behavioral contexts for the neural responses.3. High-level auditory neurons have shown to be exquisitely selective for conspecific calls.This fine selectivity could play an important role for species recognition, for vocal learning in songbirds and, in the case of the bats, for the processing of the sounds used in echolocation. Research that investigates how communication sounds are categorized into behaviorally meaningful groups (e.g. call types in animals, words in human speech) remains in its infancy. Animals and humans also excel at separating communication sounds from each otherand from background noise. Neurons that detect communication calls in noise have been found but the neural computations involved in sound source separation and natural auditory scene analysis remain overall poorly understood. Thus, future auditory research will have to focus not only on how natural sounds are processed by the auditory system but also on the computations that allow for this processing to occur in natural listening situations. 5.The complexity of the computations needed in the natural hearing task might require a high-dimensional representation provided by ensemble of neurons and the use of natural sounds might be the best solution for understanding the ensemble neural code.The final publication is available at Nature via http://www.nature.com/nrn/journal/v15/n6/full/nrn3731.html PrefaceWe might be forced to listen to a high frequency tone at our audiologist's office or we might enjoy falling asleep with a white-noise machine but the sounds that really matter to us are the voices of our companions or music from our favorite radio station; the auditory system has evolved to process behaviorally relevant natural sounds. Research has shown not only that our brain is optimized for natural hearing tasks but also that using natural sounds to probe the auditory system is the best way to understand the neural computations that allow us to comprehend speech or appreciate music.

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“…Although we know something about how the anuran brain encodes amplitude-modulated signals (e.g. Feng et al, 1990;Leary et al, 2008;Rose and Capranica, 1994), we know little about how it encodes these types of changes in frequency (i.e. frequency steps) that are critical for species recognition in the túngara frog [although see Narins et al (Narins et al, 1983)].…”

Section: Introductionmentioning

confidence: 99%

Auditory selectivity for acoustic features that confer species recognition in the túngara frog

Mangiamele

Burmeister

2011

Journal of Experimental Biology

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SUMMARYIn anurans, recognition of species-specific acoustic signals is essential to finding a mate. In many species, behavioral tests have elucidated which acoustic features contribute to species recognition, but the mechanisms by which the brain encodes these species-specific signal components are less well understood. The túngara frog produces a 'whine' mating call that is characterized by a descending frequency sweep. However, much of the signal is unnecessary for recognition, as recognition behavior can be triggered by a descending two-tone step that mimics the frequency change in a portion of the whine. To identify the brain regions that contribute to species recognition in the túngara frog, we exposed females to a full-spectrum whine, a descending two-tone step that elicits recognition, the reversed two-tone step that does not elicit recognition, or no sound, and we measured expression of the neural activity-dependent gene egr-1 in the auditory brainstem and thalamus. We found that the behavioral relevance of the stimuli was the best predictor of egr-1 expression in the laminar nucleus of the torus semicircularis but not elsewhere. That is, the laminar nucleus responded more to the whine and the two-tone step that elicits recognition than to the reversed two-tone step. In contrast, in other brainstem and thalamic nuclei, whines induced egr-1 expression but tones did not. These data demonstrate that neural responses in the laminar nucleus correspond to behavioral responses of females and they suggest that the laminar nucleus may act as a feature detector for the descending frequencies characteristic of conspecific calls.

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Neural basis of sound pattern recognition in anurans

Cited by 152 publications

References 56 publications

Specific and Nonspecific Plasticity of the Primary Auditory Cortex Elicited by Thalamic Auditory Neurons

Specific and Nonspecific Plasticity of the Primary Auditory Cortex Elicited by Thalamic Auditory Neurons

Neural processing of natural sounds

Auditory selectivity for acoustic features that confer species recognition in the túngara frog

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