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Nidiffer, A.

Publications and source records attributed to Nidiffer, A..

5 recordsLinked to original sources

Attention or prediction? Characterizing the top-down influence of predictive context on speech encoding

Theories of predictive coding propose that perception is the process of inferring the causes of our sensory input by comparing that input with predictions derived from our internal models of the world. Such predictive processes are thought to play a central role in language comprehension, however, robust neurophysiological evidence for such processes, particularly during natural speech perception, remains limited. Previous work has suggested that the early auditory encoding of words in natural speech is influenced by their preceding linguistic context. However, it remains unclear whether this effect is driven by prediction per se or dynamic modulations of attention based on contextual uncertainty. To distinguish between these alternatives, we recorded electroencephalography from 17 healthy adults while they listened to slightly changed audiobook. Specifically, we identified and replaced several unsurprising content words with more surprising words. We quantified the early auditory encoding of words using speech-envelope reconstruction accuracy within 100-ms time window after word onset and examined its relationship to word surprisal and contextual uncertainty. We found that more surprising words showed enhanced early auditory encoding despite matched contextual constraint. Moreover, the temporal profile of this enhancement depended on when the incoming speech signal diverged from the predicted phonological sequence, consistent with the emergence of prediction-error responses. Linear mixed-effects modeling further revealed that word surprisal had a substantially stronger influence on early auditory encoding than contextual uncertainty. Together, these findings indicate that the early auditory encoding of words during naturalistic speech perception is more strongly associated with predictive computations than with uncertainty-driven attentional gain. Significance StatementDuring natural speech comprehension, contextual information influences how the brain processes incoming sensory input. However, whether this context-dependent modulation of the early auditory encoding of words reflects predictive computations or dynamic changes in attentional gain has remained unresolved. By combining a naturalistic speech paradigm with a stimulus manipulation that varies word surprisal while controlling contextual uncertainty, we show that the early auditory encoding of words is driven by word surprisal under matched contextual constraint. Moreover, the temporal dynamics of this modulation closely follow the point at which the incoming speech signal departs from the predicted phonological sequence. These findings provide neurophysiological evidence that predictive computations contribute to the context- dependent modulation of early auditory processing during natural speech comprehension.

neuroscience↗

Articulatory timing and form support distinct neural benefits during audiovisual speech

In noisy environments, visible speech articulations improve listening comprehension. The benefit derives from several sources, including articulatory timing and shape. Recent research has shown that visual cortex encodes a categorical representation of articulatory features and that visual speech can benefit both acoustic and phonetic feature processing separately. The present study advances the hypothesis that the shape of the articulators specifically influences the categorization of auditory speech in terms of its phonetic features. We tested this by linearly modeling electroencephalographic responses to natural, continuous speech (in noise) in terms of the acoustic and articulatory features of the speech. We compared the performance of these models in conditions where the speech was accompanied by a natural video of the speaker with their mouth visible, and a video where their mouth was covered by a dynamic ellipse obscuring articulatory shape but preserving dynamics. The dynamic mask reduced comprehension, neural processing of phonetic features, the associated multisensory benefits, and indices of visual-only linguistic processing over occipital scalp. Our findings support substantial visual involvement in speech comprehension, derived largely from the shape of the articulators. They also corroborate several proposals involving audiovisual speech processing hierarchy and the nature of the information contained in visible speech. HighlightsO_LIVisual speech provides at least two forms of information to enhance acoustic speech processing: redundant temporal dynamics and complementary articulatory information C_LIO_LICovering the mouth with a dynamic mask preserves horizontal and vertical lip movement information, but largely removes articulatory detail C_LIO_LIVisual speech with a mask preserves some general multisensory benefits but removes visual linguistic information and its ability to enhance auditory processing at the level of phonetic features. C_LI

neuroscience↗

The effect of gaze on EEG measures of multisensory integration in a cocktail party scenario

Seeing the speakers face greatly improves our speech comprehension in noisy environments. This is due to the brains ability to combine the auditory and the visual information around us, a process known as multisensory integration. Selective attention also strongly influences what we comprehend in scenarios with multiple speakers - an effect known as the cocktail-party phenomenon. However, the interaction between attention and multisensory integration is not fully understood, especially when it comes to natural, continuous speech. In a recent electroencephalography (EEG) study, we explored this issue and showed that multisensory integration is enhanced when an audiovisual speaker is attended compared to when that speaker is unattended. Here, we extend that work to investigate how this interaction varies depending on a persons gaze behavior, which affects the quality of the visual information they have access to. To do so, we recorded EEG from 31 healthy adults as they performed selective attention tasks in several paradigms involving two concurrently presented audiovisual speakers. We then modeled how the recorded EEG related to the audio speech (envelope) of the presented speakers. Crucially, we compared two classes of model - one that assumed underlying multisensory integration (AV) versus another that assumed two independent unisensory audio and visual processes (A+V). This comparison revealed evidence of strong attentional effects on multisensory integration when participants were looking directly at the face of an audiovisual speaker. This effect was not apparent when the speakers face was in the peripheral vision of the participants. Overall, our findings suggest a strong influence of attention on multisensory integration when high fidelity visual (articulatory) speech information is available. More generally, this suggests that the interplay between attention and multisensory integration during natural audiovisual speech is dynamic and is adaptable based on the specific task and environment.

neuroscience↗

Incorporating models of subcortical processing improves the ability to predict EEG responses to natural speech

The goal of describing how the human brain responds to complex acoustic stimuli has driven auditory neuroscience research for decades. Often, a systems-based approach has been taken, in which neurophysiological responses are modeled based on features of the presented stimulus. This includes a wealth of work modeling electroencephalogram (EEG) responses to complex acoustic stimuli such as speech. Examples of the acoustic features used in such modeling include the amplitude envelope and spectrogram of speech. These models implicitly assume a direct mapping from stimulus representation to cortical activity. However, in reality, the representation of sound is transformed as it passes through early stages of the auditory pathway, such that inputs to the cortex are fundamentally different from the raw audio signal that was presented. Thus, it could be valuable to account for the transformations taking place in lower-order auditory areas, such as the auditory nerve, cochlear nucleus, and inferior colliculus (IC) when predicting cortical responses to complex sounds. Specifically, because IC responses are more similar to cortical inputs than acoustic features derived directly from the audio signal, we hypothesized that linear mappings (temporal response functions; TRFs) fit to the outputs of an IC model would better predict EEG responses to speech stimuli. To this end, we modeled responses to the acoustic stimuli as they passed through the auditory nerve, cochlear nucleus, and inferior colliculus before fitting a TRF to the output of the modeled IC responses. Results showed that using model-IC responses in traditional systems analyses resulted in better predictions of EEG activity than using the envelope or spectrogram of a speech stimulus. Further, it was revealed that model-IC derived TRFs predict different aspects of the EEG than acoustic-feature TRFs, and combining both types of TRF models provides a more accurate prediction of the EEG response.x

neuroscience↗

Multisensory perception reflects individual differences in processing temporal correlations

Sensory signals originating from a single event, such as audiovisual speech, are temporally correlated. Correlated signals are known to facilitate multisensory integration and binding. We sought to further elucidate the nature of this relationship, hypothesizing that multisensory perception will vary with the strength of audiovisual correlation. Human participants detected near-threshold amplitude modulations in auditory and/or visual stimuli. During audiovisual trials, the frequency and phase of auditory modulations were varied, producing signals with a range of correlations. After accounting for individual differences which likely reflect relative temporal processing abilities of participants auditory and visual systems, we found that multisensory perception varied linearly with strength of correlation. Diffusion modelling confirmed this and revealed that correlation is supplied to the decisional system as sensory evidence. These data implicate correlation as an important cue in audiovisual feature integration and binding and suggest correlational strength as an important factor for flexibility in these processes.

neuroscience↗