On the ontogeny of combination-sensitive neurons in speech perception

1998 ◽  
Vol 21 (2) ◽  
pp. 280-281
Author(s):  
Athanassios Protopapas ◽  
Paula Tallal

The arguments for the orderly output constraint concern phylogenetic matters and do not address the ontogeny of combination-specific neurons and the corresponding processing mechanisms. Locus equations are too variable to be strongly predetermined and too inconsistent to be easily learned. Findings on the development of speech perception and underlying auditory processing must be taken into account in the formulation of neural encoding theories.

2021 ◽  
Vol 11 (1) ◽  
pp. 112-128
Author(s):  
Caitlin N. Price ◽  
Deborah Moncrieff

Communication in noise is a complex process requiring efficient neural encoding throughout the entire auditory pathway as well as contributions from higher-order cognitive processes (i.e., attention) to extract speech cues for perception. Thus, identifying effective clinical interventions for individuals with speech-in-noise deficits relies on the disentanglement of bottom-up (sensory) and top-down (cognitive) factors to appropriately determine the area of deficit; yet, how attention may interact with early encoding of sensory inputs remains unclear. For decades, attentional theorists have attempted to address this question with cleverly designed behavioral studies, but the neural processes and interactions underlying attention’s role in speech perception remain unresolved. While anatomical and electrophysiological studies have investigated the neurological structures contributing to attentional processes and revealed relevant brain–behavior relationships, recent electrophysiological techniques (i.e., simultaneous recording of brainstem and cortical responses) may provide novel insight regarding the relationship between early sensory processing and top-down attentional influences. In this article, we review relevant theories that guide our present understanding of attentional processes, discuss current electrophysiological evidence of attentional involvement in auditory processing across subcortical and cortical levels, and propose areas for future study that will inform the development of more targeted and effective clinical interventions for individuals with speech-in-noise deficits.


2011 ◽  
Vol 32 (2) ◽  
pp. 560-570 ◽  
Author(s):  
Bart Boets ◽  
Maaike Vandermosten ◽  
Hanne Poelmans ◽  
Heleen Luts ◽  
Jan Wouters ◽  
...  

2021 ◽  
Vol 64 (10) ◽  
pp. 4014-4029
Author(s):  
Kathy R. Vander Werff ◽  
Christopher E. Niemczak ◽  
Kenneth Morse

Purpose Background noise has been categorized as energetic masking due to spectrotemporal overlap of the target and masker on the auditory periphery or informational masking due to cognitive-level interference from relevant content such as speech. The effects of masking on cortical and sensory auditory processing can be objectively studied with the cortical auditory evoked potential (CAEP). However, whether effects on neural response morphology are due to energetic spectrotemporal differences or informational content is not fully understood. The current multi-experiment series was designed to assess the effects of speech versus nonspeech maskers on the neural encoding of speech information in the central auditory system, specifically in terms of the effects of speech babble noise maskers varying by talker number. Method CAEPs were recorded from normal-hearing young adults in response to speech syllables in the presence of energetic maskers (white or speech-shaped noise) and varying amounts of informational maskers (speech babble maskers). The primary manipulation of informational masking was the number of talkers in speech babble, and results on CAEPs were compared to those of nonspeech maskers with different temporal and spectral characteristics. Results Even when nonspeech noise maskers were spectrally shaped and temporally modulated to speech babble maskers, notable changes in the typical morphology of the CAEP in response to speech stimuli were identified in the presence of primarily energetic maskers and speech babble maskers with varying numbers of talkers. Conclusions While differences in CAEP outcomes did not reach significance by number of talkers, neural components were significantly affected by speech babble maskers compared to nonspeech maskers. These results suggest an informational masking influence on neural encoding of speech information at the sensory cortical level of auditory processing, even without active participation on the part of the listener.


2021 ◽  
Author(s):  
Shannon L.M. Heald ◽  
Stephen C. Van Hedger ◽  
John Veillette ◽  
Katherine Reis ◽  
Joel S. Snyder ◽  
...  

AbstractThe ability to generalize rapidly across specific experiences is vital for robust recognition of new patterns, especially in speech perception considering acoustic-phonetic pattern variability. Behavioral research has demonstrated that listeners are rapidly able to generalize their experience with a talker’s speech and quickly improve understanding of a difficult-to-understand talker without prolonged practice, e.g., even after a single training session. Here, we examine the differences in neural responses to generalized versus rote learning in auditory cortical processing by training listeners to understand a novel synthetic talker using a Pretest-Posttest design with electroencephalography (EEG). Participants were trained using either (1) a large inventory of words where no words repeated across the experiment (generalized learning) or (2) a small inventory of words where words repeated (rote learning). Analysis of long-latency auditory evoked potentials at Pretest and Posttest revealed that while rote and generalized learning both produce rapid changes in auditory processing, the nature of these changes differed. In the context of adapting to a talker, generalized learning is marked by an amplitude reduction in the N1-P2 complex and by the presence of a late-negative (LN) wave in the auditory evoked potential following training. Rote learning, however, is marked only by temporally later source configuration changes. The early N1-P2 change, found only for generalized learning, suggests that generalized learning relies on the attentional system to reorganize the way acoustic features are selectively processed. This change in relatively early sensory processing (i.e. during the first 250ms) is consistent with an active processing account of speech perception, which proposes that the ability to rapidly adjust to the specific vocal characteristics of a new talker (for which rote learning is rare) relies on attentional mechanisms to adaptively tune early auditory processing sensitivity.Statement of SignificancePrevious research on perceptual learning has typically examined neural responses during rote learning: training and testing is carried out with the same stimuli. As a result, it is not clear that findings from these studies can explain learning that generalizes to novel patterns, which is critical in speech perception. Are neural responses to generalized learning in auditory processing different from neural responses to rote learning? Results indicate rote learning of a particular talker’s speech involves brain regions focused on the memory encoding and retrieving of specific learned patterns, whereas generalized learning involves brain regions involved in reorganizing attention during early sensory processing. In learning speech from a novel talker, only generalized learning is marked by changes in the N1-P2 complex (reflective of secondary auditory cortical processing). The results are consistent with the view that robust speech perception relies on the fast adjustment of attention mechanisms to adaptively tune auditory sensitivity to cope with acoustic variability.


2016 ◽  
Author(s):  
Jennifer Padilla ◽  
Thierry Morlet ◽  
Kyoko Nagao ◽  
Rachel Crum ◽  
L. Ashleigh Greenwood ◽  
...  

1998 ◽  
Vol 21 (2) ◽  
pp. 273-274 ◽  
Author(s):  
Keith R. Kluender

Although neural encoding by bats and owls presents seductive analogies, the major contribution of locus equations and orderly output constraints discussed by Sussman et al. is the demonstration that important acoustic information for speech perception can be captured by elegant and neurally-plausible learning processes.


2020 ◽  
Vol 6 (30) ◽  
pp. eaba7830
Author(s):  
Laurianne Cabrera ◽  
Judit Gervain

Speech perception is constrained by auditory processing. Although at birth infants have an immature auditory system and limited language experience, they show remarkable speech perception skills. To assess neonates’ ability to process the complex acoustic cues of speech, we combined near-infrared spectroscopy (NIRS) and electroencephalography (EEG) to measure brain responses to syllables differing in consonants. The syllables were presented in three conditions preserving (i) original temporal modulations of speech [both amplitude modulation (AM) and frequency modulation (FM)], (ii) both fast and slow AM, but not FM, or (iii) only the slowest AM (<8 Hz). EEG responses indicate that neonates can encode consonants in all conditions, even without the fast temporal modulations, similarly to adults. Yet, the fast and slow AM activate different neural areas, as shown by NIRS. Thus, the immature human brain is already able to decompose the acoustic components of speech, laying the foundations of language learning.


Author(s):  
Bernd J. Kröger

This chapter outlines a comprehensive neurocomputational model of voice and speech perception based on (i) already established computational models, as well as on (ii) neurophysiological data of the underlying neural processes. Neurocomputational models of speech perception comprise auditory as well as cognitive modules, in order to extract sound features as well as linguistic information (linguistic content). A model of voice and speech perception in addition needs to process paralinguistic information like gender, age, emotional or affective state of speaker, etc. It is argued here that modules of a neurocomputational model of voice and speech perception need to interact with modules which go beyond unimodal auditory processing because, for example, processing of paralinguistic information is closely related to such as visual facial perception. Thus, this chapter describes neural modelling of voice and speech perception in relation to general communication and social-interaction processes, which makes it necessary to develop a hypermodal processing approach.


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