scholarly journals Acoustic context modulates natural sound discrimination in auditory cortex through frequency-specific adaptation

2021 ◽  
pp. JN-RM-0873-21
Author(s):  
Luciana López-Jury ◽  
Francisco García-Rosales ◽  
Eugenia González-Palomares ◽  
Manfred Kössl ◽  
Julio C. Hechavarria
2021 ◽  
Author(s):  
Luciana López-Jury ◽  
Francisco García-Rosales ◽  
Eugenia González-Palomares ◽  
Manfred Kössl ◽  
Julio C. Hechavarria

AbstractVocal communication is essential to coordinate social interactions in mammals and it requires a fine discrimination of communication sounds. It is known that auditory neurons can exhibit selectivity for specific natural sounds, but how this selectivity is affected by acoustic context (i.e. other natural sounds that precede the sound in question) is still debated. Here we tackled this question by using ethologically relevant vocalizations in a highly vocal mammalian species: Seba’s short-tailed bat (Carollia perspicillata). We show that neurons in the bat auditory cortex present several degrees of selectivity for navigation (i.e. echolocation) and distress calls (a type of communication sound), ranging from exclusive selectivity to one sound category to equal responsiveness to both types of signals. Embedding vocalizations within natural acoustic streams leads to stimulus-specific suppression of neuronal responses. Such suppression changes natural sound selectivity in a disparate manner: selectivity increases in neurons that displayed poor sound discriminability in the absence of context (i.e. when sounds were preceded by silence), and decreases sound selectivity in neurons classified as selective in silent settings. A computational model indicates that the observed context-dependent effects arise from two forms of adaptation: presynaptic frequency specific adaptation acting in cortical inputs and stimulus unspecific postsynaptic adaptation. These results shed light into how acoustic context modulates natural sound discriminability in the mammalian cortex.


2013 ◽  
Vol 110 (8) ◽  
pp. 1892-1902 ◽  
Author(s):  
Ben D. Richardson ◽  
Kenneth E. Hancock ◽  
Donald M. Caspary

Novel stimulus detection by single neurons in the auditory system, known as stimulus-specific adaptation (SSA), appears to function as a real-time filtering/gating mechanism in processing acoustic information. Particular stimulus paradigms allowing for quantification of a neuron's ability to detect novel or deviant stimuli have been used to examine SSA in the inferior colliculus, medial geniculate body (MGB), and auditory cortex of anesthetized rodents. However, the study of SSA in awake animals is limited to auditory cortex. The present study used individually advanceable tetrodes to record single-unit responses from auditory thalamus (MGB) of awake young adult and aged Fischer Brown Norway (FBN) rats to 1) examine the presence of SSA in the MGB of awake rats and 2) determine whether SSA is altered by aging in MGB. MGB single units in awake FBN rats displayed SSA in response to two stimulus paradigms: the oddball paradigm and a random blocked/interleaved presentation of a set of frequencies. SSA levels were modestly, but nonsignificantly, increased in the nonlemniscal regions of the MGB and at lower stimulus intensities, where 27 of 57 (47%) young adult MGB units displayed SSA. The present findings provide the initial description of SSA in the MGB of awake rats and support SSA as being qualitatively independent of arousal level or anesthetized state. Finally, contrary to previous studies in auditory cortex of anesthetized rats, MGB units in aged rats showed SSA levels indistinguishable from SSA levels in young adult rats, suggesting that SSA in MGB was not impacted by aging in an awake preparation.


2009 ◽  
Vol 102 (3) ◽  
pp. 1483-1490 ◽  
Author(s):  
Francois D. Szymanski ◽  
Jose A. Garcia-Lazaro ◽  
Jan W. H. Schnupp

Neurons in primary auditory cortex (A1) are known to exhibit a phenomenon known as stimulus-specific adaptation (SSA), which means that, when tested with pure tones, they will respond more strongly to a particular frequency if it is presented as a rare, unexpected “oddball” stimulus than when the same stimulus forms part of a series of common, “standard” stimuli. Although SSA has occasionally been observed in midbrain neurons that form part of the paraleminscal auditory pathway, it is thought to be weak, rare, or nonexistent among neurons of the leminscal pathway that provide the main afferent input to A1, so that SSA seen in A1 is likely generated within A1 by local mechanisms. To study the contributions that neural processing within the different cytoarchitectonic layers of A1 may make to SSA, we recorded local field potentials in A1 of the rat in response to standard and oddball tones and subjected these to current source density analysis. Although our results show that SSA can be observed throughout all layers of A1, right from the earliest part of the response, there are nevertheless significant differences between layers, with SSA becoming significantly stronger as stimulus-related activity passes from the main thalamorecipient layers III and IV to layer V.


Neuroreport ◽  
2008 ◽  
Vol 19 (1) ◽  
pp. 93-97 ◽  
Author(s):  
Iiro P. Jääskeläinen ◽  
Jaakko Kauramäki ◽  
Juuso Tujunen ◽  
Mikko Sams

2019 ◽  
Author(s):  
Kelly K Chong ◽  
Alex G Dunlap ◽  
Dorottya B Kacsoh ◽  
Robert C Liu

SUMMARYFrequency modulations are an inherent feature of many behaviorally relevant sounds, including vocalizations and music. Changing trajectories in a sound’s frequency often conveys meaningful information, which can be used to differentiate sound categories, as in the case of intonations in tonal languages. However, it is not clear what features of the neural responses in what parts of the auditory cortical pathway might be more important for conveying information about behaviorally relevant frequency modulations, and how these responses change with experience. Here we uncover tuning to subtle variations in frequency trajectories in mouse auditory cortex. Surprisingly, we found that auditory cortical responses could be modulated by variations in a pure tone trajectory as small as 1/24th of an octave. Offset spiking accounted for a significant portion of tuned responses to subtle frequency modulation. Offset responses that were present in the adult A2, but not those in Core auditory cortex, were plastic in a way that enhanced the representation of an acquired behaviorally relevant sound category, which we illustrate with the maternal mouse paradigm for natural communication sound learning. By using this ethologically inspired sound-feature tuning paradigm to drive auditory responses in higher-order neurons, our results demonstrate that auditory cortex can track much finer frequency modulations than previously appreciated, which allows A2 offset responses in particular to attune to the pitch trajectories that distinguish behaviorally relevant, natural sound categories.


2007 ◽  
Vol 21 (3-4) ◽  
pp. 214-223 ◽  
Author(s):  
Israel Nelken ◽  
Nachum Ulanovsky

Animal models of MMN may serve both to further our understanding of neural processing beyond pure sensory coding and for unraveling the neural and pharmacological processes involved in the generation of MMN. We start this review by discussing the methodological issues that are especially important when pursuing a single-neuron correlate of MMN. Correlates of MMN have been studied in mice, rats, cats, and primates. Whereas essentially all of these studies demonstrated the presence of stimulus-specific adaptation, in the sense that responses to deviant tones are larger than the responses to standard tones, the presence of real MMN has been established only in a few. We argue for the use of more and better controls in order to clarify the situation. Finally, we discuss in detail the relationships between stimulus-specific adaptation of single-neuron responses, as established in the cat auditory cortex, and MMN. We argue that this is currently the only fully established correlate of true change detection, and hypothesize that it precedes and probably induces the neural activity that is eventually measured as MMN.


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