5 research outputs found
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The integration of continuous audio and visual speech in a cocktail-party environment depends on attention
In noisy environments, our ability to understand speech benefits greatly from seeing the speaker's face. This is attributed to the brain's ability to integrate audio and visual information, a process known as multisensory integration. In addition, selective attention plays an enormous role in what we understand, the so-called cocktail-party phenomenon. But how attention and multisensory integration interact remains incompletely understood, particularly in the case of natural, continuous speech. Here, we addressed this issue by analyzing EEG data recorded from participants who undertook a multisensory cocktail-party task using natural speech. To assess multisensory integration, we modeled the EEG responses to the speech in two ways. The first assumed that audiovisual speech processing is simply a linear combination of audio speech processing and visual speech processing (i.e., an A + V model), while the second allows for the possibility of audiovisual interactions (i.e., an AV model). Applying these models to the data revealed that EEG responses to attended audiovisual speech were better explained by an AV model, providing evidence for multisensory integration. In contrast, unattended audiovisual speech responses were best captured using an A + V model, suggesting that multisensory integration is suppressed for unattended speech. Follow up analyses revealed some limited evidence for early multisensory integration of unattended AV speech, with no integration occurring at later levels of processing. We take these findings as evidence that the integration of natural audio and visual speech occurs at multiple levels of processing in the brain, each of which can be differentially affected by attention
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Linear modeling of neurophysiological responses to speech and other continuous stimuli: methodological considerations for applied research
Cognitive neuroscience, in particular research on speech and language, has seen an increase in the use of linear modeling techniques for studying the processing of natural, environmental stimuli. The availability of such computational tools has prompted similar investigations in many clinical domains, facilitating the study of cognitive and sensory deficits under more naturalistic conditions. However, studying clinical (and often highly heterogeneous) cohorts introduces an added layer of complexity to such modeling procedures, potentially leading to instability of such techniques and, as a result, inconsistent findings. Here, we outline some key methodological considerations for applied research, referring to a hypothetical clinical experiment involving speech processing and worked examples of simulated electrophysiological (EEG) data. In particular, we focus on experimental design, data preprocessing, stimulus feature extraction, model design, model training and evaluation, and interpretation of model weights. Throughout the paper, we demonstrate the implementation of each step in MATLAB using the mTRF-Toolbox and discuss how to address issues that could arise in applied research. In doing so, we hope to provide better intuition on these more technical points and provide a resource for applied and clinical researchers investigating sensory and cognitive processing using ecologically rich stimuli
Interactions between the spatial and temporal stimulus factors that influence multisensory integration in human performance
The variability of multisensory processes of natural stimuli in human and non-human primates in a detection task
BACKGROUND:Behavioral studies in both human and animals generally converge to the dogma that multisensory integration improves reaction times (RTs) in comparison to unimodal stimulation. These multisensory effects depend on diverse conditions among which the most studied were the spatial and temporal congruences. Further, most of the studies are using relatively simple stimuli while in everyday life, we are confronted to a large variety of complex stimulations constantly changing our attentional focus over time, a modality switch that can impact on stimuli detection. In the present study, we examined the potential sources of the variability in reaction times and multisensory gains with respect to the intrinsic features of a large set of natural stimuli. METHODOLOGY/PRINCIPLE FINDINGS:Rhesus macaque monkeys and human subjects performed a simple audio-visual stimulus detection task in which a large collection of unimodal and bimodal natural stimuli with semantic specificities was presented at different saliencies. Although we were able to reproduce the well-established redundant signal effect, we failed to reveal a systematic violation of the race model which is considered to demonstrate multisensory integration. In both monkeys and human species, our study revealed a large range of multisensory gains, with negative and positive values. While modality switch has clear effects on reaction times, one of the main causes of the variability of multisensory gains appeared to be linked to the intrinsic physical parameters of the stimuli. CONCLUSION/SIGNIFICANCE:Based on the variability of multisensory benefits, our results suggest that the neuronal mechanisms responsible of the redundant effect (interactions vs. integration) are highly dependent on the stimulus complexity suggesting different implications of uni- and multisensory brain regions. Further, in a simple detection task, the semantic values of individual stimuli tend to have no significant impact on task performances, an effect which is probably present in more cognitive tasks