Attention to audiovisual speech shapes neural processing through feedback-feedforward loops between different nodes of the speech network.

Selective attention-related top-down modulation plays a significant role in separating relevant speech from irrelevant background speech when vocal attributes separating concurrent speakers are small and continuously evolving. Electrophysiological studies have shown that such top-down modulation enhances neural tracking of attended speech. Yet, the specific cortical regions involved remain unclear due to the limited spatial resolution of most electrophysiological techniques. To overcome such limitations, we collected both electroencephalography (EEG) (high temporal resolution) and functional magnetic resonance imaging (fMRI) (high spatial resolution), while human participants selectively attended to speakers in audiovisual scenes containing overlapping cocktail party speech. To utilise the advantages of the respective techniques, we analysed neural tracking of speech using the EEG data and performed representational dissimilarity-based EEG-fMRI fusion. We observed that attention enhanced neural tracking and modulated EEG correlates throughout the latencies studied. Further, attention-related enhancement of neural tracking fluctuated in predictable temporal profiles. We discuss how such temporal dynamics could arise from a combination of interactions between attention and prediction as well as plastic properties of the auditory cortex. EEG-fMRI fusion revealed attention-related iterative feedforward-feedback loops between hierarchically organised nodes of the ventral auditory object related processing stream. Our findings support models where attention facilitates dynamic neural changes in the auditory cortex, ultimately aiding discrimination of relevant sounds from irrelevant ones while conserving neural resources.

Neural correlates of audiovisual narrative speech perception in children and adults on the autism spectrum: A functional magnetic resonance imaging study.

Autistic individuals show substantially reduced benefit from observing visual articulations during audiovisual speech perception, a multisensory integration deficit that is particularly relevant to social communication. This has mostly been studied using simple syllabic or word-level stimuli and it remains unclear how altered lower-level multisensory integration translates to the processing of more complex natural multisensory stimulus environments in autism. Here, functional neuroimaging was used to examine neural correlates of audiovisual gain (AV-gain) in 41 autistic individuals to those of 41 age-matched non-autistic controls when presented with a complex audiovisual narrative. Participants were presented with continuous narration of a story in auditory-alone, visual-alone, and both synchronous and asynchronous audiovisual speech conditions. We hypothesized that previously identified differences in audiovisual speech processing in autism would be characterized by activation differences in brain regions well known to be associated with audiovisual enhancement in neurotypicals. However, our results did not provide evidence for altered processing of auditory alone, visual alone, audiovisual conditions or AV- gain in regions associated with the respective task when comparing activation patterns between groups. Instead, we found that autistic individuals responded with higher activations in mostly frontal regions where the activation to the experimental conditions was below baseline (de-activations) in the control group. These frontal effects were observed in both unisensory and audiovisual conditions, suggesting that these altered activations were not specific to multisensory processing but reflective of more general mechanisms such as an altered disengagement of Default Mode Network processes during the observation of the language stimulus across conditions.

Predictors for estimating subcortical EEG responses to continuous speech.

Perception of sounds and speech involves structures in the auditory brainstem that rapidly process ongoing auditory stimuli. The role of these structures in speech processing can be investigated by measuring their electrical activity using scalp-mounted electrodes. However, typical analysis methods involve averaging neural responses to many short repetitive stimuli that bear little relevance to daily listening environments. Recently, subcortical responses to more ecologically relevant continuous speech were detected using linear encoding models. These methods estimate the temporal response function (TRF), which is a regression model that minimises the error between the measured neural signal and a predictor derived from the stimulus. Using predictors that model the highly non-linear peripheral auditory system may improve linear TRF estimation accuracy and peak detection. Here, we compare predictors from both simple and complex peripheral auditory models for estimating brainstem TRFs on electroencephalography (EEG) data from 24 participants listening to continuous speech. We also investigate the data length required for estimating subcortical TRFs, and find that around 12 minutes of data is sufficient for clear wave V peaks (>3 dB SNR) to be seen in nearly all participants. Interestingly, predictors derived from simple filterbank-based models of the peripheral auditory system yield TRF wave V peak SNRs that are not significantly different from those estimated using a complex model of the auditory nerve, provided that the nonlinear effects of adaptation in the auditory system are appropriately modelled. Crucially, computing predictors from these simpler models is more than 50 times faster compared to the complex model. This work paves the way for efficient modelling and detection of subcortical processing of continuous speech, which may lead to improved diagnosis metrics for hearing impairment and assistive hearing technology.

Audiovisual integration in the McGurk effect is impervious to music training.

The McGurk effect refers to an audiovisual speech illusion where the discrepant auditory and visual syllables produce a fused percept between the visual and auditory component. However, little is known about how individual differences contribute to the McGurk effect. Here, we examined whether music training experience-which involves audiovisual integration-can modulate the McGurk effect. Seventy-three participants completed the Goldsmiths Musical Sophistication Index (Gold-MSI) questionnaire to evaluate their music expertise on a continuous scale. Gold-MSI considers participants' daily-life exposure to music learning experiences (formal and informal), instead of merely classifying people into different groups according to how many years they have been trained in music. Participants were instructed to report, via a 3-alternative forced choice task, "what a person said": /Ba/, /Ga/ or /Da/. The experiment consisted of 96 audiovisual congruent trials and 96 audiovisual incongruent (McGurk) trials. We observed no significant correlations between the susceptibility of the McGurk effect and the different subscales of the Gold-MSI (active engagement, perceptual abilities, music training, singing abilities, emotion) or the general musical sophistication composite score. Together, these findings suggest that music training experience does not modulate audiovisual integration in speech as reflected by the McGurk effect.

Effects of Stimulus Rate and Periodicity on Auditory Cortical Entrainment to Continuous Sounds.

The neural mechanisms underlying the exogenous coding and neural entrainment to repetitive auditory stimuli have seen a recent surge of interest. However, few studies have characterized how parametric changes in stimulus presentation alter entrained responses. We examined the degree to which the brain entrains to repeated speech (i.e., /ba/) and nonspeech (i.e., click) sounds using phase-locking value (PLV) analysis applied to multichannel human electroencephalogram (EEG) data. Passive cortico-acoustic tracking was investigated in N = 24 normal young adults utilizing EEG source analyses that isolated neural activity stemming from both auditory temporal cortices. We parametrically manipulated the rate and periodicity of repetitive, continuous speech and click stimuli to investigate how speed and jitter in ongoing sound streams affect oscillatory entrainment. Neuronal synchronization to speech was enhanced at 4.5 Hz (the putative universal rate of speech) and showed a differential pattern to that of clicks, particularly at higher rates. PLV to speech decreased with increasing jitter but remained superior to clicks. Surprisingly, PLV entrainment to clicks was invariant to periodicity manipulations. Our findings provide evidence that the brain's neural entrainment to complex sounds is enhanced and more sensitized when processing speech-like stimuli, even at the syllable level, relative to nonspeech sounds. The fact that this specialization is apparent even under passive listening suggests a priority of the auditory system for synchronizing to behaviorally relevant signals.

What are wereallydecoding? Unveiling biases in EEG-based decoding of the spatial focus of auditory attention.

Objective.Spatial auditory attention decoding (Sp-AAD) refers to the task of identifying the direction of the speaker to which a person is attending in a multi-talker setting, based on the listener's neural recordings, e.g. electroencephalography (EEG). The goal of this study is to thoroughly investigate potential biases when training such Sp-AAD decoders on EEG data, particularly eye-gaze biases and latent trial-dependent confounds, which may result in Sp-AAD models that decode eye-gaze or trial-specific fingerprints rather than spatial auditory attention.Approach.We designed a two-speaker audiovisual Sp-AAD protocol in which the spatial auditory and visual attention were enforced to be either congruent or incongruent, and we recorded EEG data from sixteen participants undergoing several trials recorded at distinct timepoints. We trained a simple linear model for Sp-AAD based on common spatial patterns filters in combination with either linear discriminant analysis (LDA) or k-means clustering, and evaluated them both across- and within-trial.Main results.We found that even a simple linear Sp-AAD model is susceptible to overfitting to confounding signal patterns such as eye-gaze and trial fingerprints (e.g. due to feature shifts across trials), resulting in artificially high decoding accuracies. Furthermore, we found that changes in the EEG signal statistics across trials deteriorate the trial generalization of the classifier, even when the latter is retrained on the test trial with an unsupervised algorithm.Significance.Collectively, our findings confirm that there exist subtle biases and confounds that can strongly interfere with the decoding of spatial auditory attention from EEG. It is expected that more complicated non-linear models based on deep neural networks, which are often used for Sp-AAD, are even more vulnerable to such biases. Future work should perform experiments and model evaluations that avoid and/or control for such biases in Sp-AAD tasks.

Attention Drives Visual Processing and Audiovisual Integration During Multimodal Communication.

During communication in real-life settings, our brain often needs to integrate auditory and visual information and at the same time actively focus on the relevant sources of information, while ignoring interference from irrelevant events. The interaction between integration and attention processes remains poorly understood. Here, we use rapid invisible frequency tagging and magnetoencephalography to investigate how attention affects auditory and visual information processing and integration, during multimodal communication. We presented human participants (male and female) with videos of an actress uttering action verbs (auditory; tagged at 58 Hz) accompanied by two movie clips of hand gestures on both sides of fixation (attended stimulus tagged at 65 Hz; unattended stimulus tagged at 63 Hz). Integration difficulty was manipulated by a lower-order auditory factor (clear/degraded speech) and a higher-order visual semantic factor (matching/mismatching gesture). We observed an enhanced neural response to the attended visual information during degraded speech compared to clear speech. For the unattended information, the neural response to mismatching gestures was enhanced compared to matching gestures. Furthermore, signal power at the intermodulation frequencies of the frequency tags, indexing nonlinear signal interactions, was enhanced in the left frontotemporal and frontal regions. Focusing on the left inferior frontal gyrus, this enhancement was specific for the attended information, for those trials that benefitted from integration with a matching gesture. Together, our results suggest that attention modulates audiovisual processing and interaction, depending on the congruence and quality of the sensory input.

Short- and long-term neuroplasticity interact during the perceptual learning of concurrent speech.

Plasticity from auditory experience shapes the brain's encoding and perception of sound. However, whether such long-term plasticity alters the trajectory of short-term plasticity during speech processing has yet to be investigated. Here, we explored the neural mechanisms and interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians. Participants learned to identify double-vowel mixtures during ~ 45 min training sessions recorded simultaneously with high-density electroencephalography (EEG). We analyzed frequency-following responses (FFRs) and event-related potentials (ERPs) to investigate neural correlates of learning at subcortical and cortical levels, respectively. Although both groups showed rapid perceptual learning, musicians showed faster behavioral decisions than nonmusicians overall. Learning-related changes were not apparent in brainstem FFRs. However, plasticity was highly evident in cortex, where ERPs revealed unique hemispheric asymmetries between groups suggestive of different neural strategies (musicians: right hemisphere bias; nonmusicians: left hemisphere). Source reconstruction and the early (150-200 ms) time course of these effects localized learning-induced cortical plasticity to auditory-sensory brain areas. Our findings reinforce the domain-general benefits of musicianship but reveal that successful speech sound learning is driven by a critical interplay between long- and short-term mechanisms of auditory plasticity, which first emerge at a cortical level.

Complexity of STG signals and linguistic rhythm: a methodological study for EEG data.

The superior temporal and the Heschl's gyri of the human brain play a fundamental role in speech processing. Neurons synchronize their activity to the amplitude envelope of the speech signal to extract acoustic and linguistic features, a process known as neural tracking/entrainment. Electroencephalography has been extensively used in language-related research due to its high temporal resolution and reduced cost, but it does not allow for a precise source localization. Motivated by the lack of a unified methodology for the interpretation of source reconstructed signals, we propose a method based on modularity and signal complexity. The procedure was tested on data from an experiment in which we investigated the impact of native language on tracking to linguistic rhythms in two groups: English natives and Spanish natives. In the experiment, we found no effect of native language but an effect of language rhythm. Here, we compare source projected signals in the auditory areas of both hemispheres for the different conditions using nonparametric permutation tests, modularity, and a dynamical complexity measure. We found increasing values of complexity for decreased regularity in the stimuli, giving us the possibility to conclude that languages with less complex rhythms are easier to track by the auditory cortex.

Different hemispheric lateralization for periodicity and formant structure of vowels in the auditory cortex and its changes between childhood and adulthood.

The spectral formant structure and periodicity pitch are the major features that determine the identity of vowels and the characteristics of the speaker. However, very little is known about how the processing of these features in the auditory cortex changes during development. To address this question, we independently manipulated the periodicity and formant structure of vowels while measuring auditory cortex responses using magnetoencephalography (MEG) in children aged 7-12 years and adults. We analyzed the sustained negative shift of source current associated with these vowel properties, which was present in the auditory cortex in both age groups despite differences in the transient components of the auditory response. In adults, the sustained activation associated with formant structure was lateralized to the left hemisphere early in the auditory processing stream requiring neither attention nor semantic mapping. This lateralization was not yet established in children, in whom the right hemisphere contribution to formant processing was strong and decreased during or after puberty. In contrast to the formant structure, periodicity was associated with a greater response in the right hemisphere in both children and adults. These findings suggest that left-lateralization for the automatic processing of vowel formant structure emerges relatively late in ontogenesis and pose a serious challenge to current theories of hemispheric specialization for speech processing.

Musical experience is linked to enhanced dimension-selective attention to pitch and increased primary weighting during suprasegmental categorization.

Speech perception requires the integration of evidence from acoustic cues across multiple dimensions. Individuals differ in their cue weighting strategies, that is, the weight they assign to different dimensions during speech categorization. In two experiments, we investigate musical training as one potential predictor of individual differences in prosodic cue weighting strategies. Attentional theories of speech categorization suggest that prior experience with the task-relevance of a particular dimension leads that dimension to attract attention. Experiment 1 tested whether musicians and nonmusicians differed in their ability to selectively attend to pitch and loudness in speech. Compared to nonmusicians, musicians showed enhanced dimension-selective attention to pitch but not loudness. Experiment 2 tested the hypothesis that musicians would show greater pitch weighting during prosodic categorization due to prior experience with the task-relevance of pitch cues in music. Listeners categorized phrases that varied in the extent to which pitch and duration signaled the location of linguistic focus and phrase boundaries. During linguistic focus categorization, musicians upweighted pitch compared to nonmusicians. During phrase boundary categorization, musicians upweighted duration relative to nonmusicians. These results suggest that musical experience is linked with domain-general enhancements in the ability to selectively attend to certain acoustic dimensions in speech. As a result, musicians may place greater perceptual weight on a single primary dimension during prosodic categorization, while nonmusicians may be more likely to choose a perceptual strategy that integrates across multiple dimensions. These findings support attentional theories of cue weighting, which suggest attention influences listeners' perceptual weighting of acoustic dimensions during categorization. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Advancing Auditory Processing by Detecting Frequency-Following Responses Through a Specialized Machine Learning Model.

In this study, we explore the feasibility and performance of detecting scalp-recorded frequency-following responses (FFRs) with a specialized machine learning (ML) model. By leveraging the strengths of feature extraction of the source separation non-negative matrix factorization (SSNMF) algorithm and its adeptness in handling limited training data, we adapted the SSNMF algorithm into a specialized ML model with a hybrid architecture to enhance FFR detection amidst background noise. We recruited 40 adults with normal hearing and evoked their scalp recorded FFRs using the English vowel/i/with a rising pitch contour. The model was trained on FFR-present and FFR-absent conditions, and its performance was evaluated using sensitivity, specificity, efficiency, false-positive rate, and false-negative rate metrics. This study revealed that the specialized SSNMF model achieved heightened sensitivity, specificity, and efficiency in detecting FFRs as the number of recording sweeps increased. Sensitivity exceeded 80% at 500 sweeps and maintained over 89% from 1000 sweeps onwards. Similarly, specificity and efficiency also improved rapidly with increasing sweeps. The progressively enhanced sensitivity, specificity, and efficiency of this specialized ML model underscore its practicality and potential for broader applications. These findings have immediate implications for FFR research and clinical use, while paving the way for further advancements in the assessment of auditory processing.

Generalization of auditory expertise in audio engineers and instrumental musicians.

From auditory perception to general cognition, the ability to play a musical instrument has been associated with skills both related and unrelated to music. However, it is unclear if these effects are bound to the specific characteristics of musical instrument training, as little attention has been paid to other populations such as audio engineers and designers whose auditory expertise may match or surpass that of musicians in specific auditory tasks or more naturalistic acoustic scenarios. We explored this possibility by comparing students of audio engineering (n = 20) to matched conservatory-trained instrumentalists (n = 24) and to naive controls (n = 20) on measures of auditory discrimination, auditory scene analysis, and speech in noise perception. We found that audio engineers and performing musicians had generally lower psychophysical thresholds than controls, with pitch perception showing the largest effect size. Compared to controls, audio engineers could better memorise and recall auditory scenes composed of non-musical sounds, whereas instrumental musicians performed best in a sustained selective attention task with two competing streams of tones. Finally, in a diotic speech-in-babble task, musicians showed lower signal-to-noise-ratio thresholds than both controls and engineers; however, a follow-up online study did not replicate this musician advantage. We also observed differences in personality that might account for group-based self-selection biases. Overall, we showed that investigating a wider range of forms of auditory expertise can help us corroborate (or challenge) the specificity of the advantages previously associated with musical instrument training.

Speech Perception in Noise and Medial Olivocochlear Reflex: Effects of Age, Speech Stimulus, and Response-Related Variables.

PURPOSE: The role of the medial olivocochlear system in speech perception in noise has been debated over the years, with studies showing mixed results. One possible reason for this could be the dependence of this relationship on the parameters used in assessing the speech perception ability (age, stimulus, and response-related variables). METHODS: The current study assessed the influence of the type of speech stimuli (monosyllables, words, and sentences), the signal-to-noise ratio (+5, 0, -5, and -10 dB), the metric used to quantify the speech perception ability (percent-correct, SNR-50, and slope of the psychometric function) and age (young vs old) on the relationship between medial olivocochlear reflex (quantified by contralateral inhibition of transient evoked otoacoustic emissions) and speech perception in noise. RESULTS: A linear mixed-effects model revealed no significant contributions of the medial olivocochlear reflex to speech perception in noise. CONCLUSION: The results suggest that there was no evidence of any modulatory influence of the indirectly measured medial olivocochlear reflex strength on speech perception in noise.

Characteristics of Frequency Resolution and Speech Perception Using Bone Conduction on Different Human Facial Parts.

In conventional bone-conduction (BC) devices, a vibrator is typically attached to the mastoid process of the temporal bone or the condyle process of the mandible. However, BC-sound presentations to facial parts such as the nose and cheek have also been investigated recently. As the face is the among the most complex structures of the human body, transmission of sounds using BC on different facial parts are likely to show different perception and propagation characteristics than those presented to conventional parts. However, the characteristics of BC sound presented to different part of the face have not yet been studied in detail. To test the frequency discrimination ability, we measured difference limens for frequency (DLFs). We also conducted monosyllable articulation tests in Japanese to assess the speech-perception characteristics when BC sounds are presented to various facial (nasal, infraorbital region, zygomatic, jaw angle, and chin) and conventional (mastoid and condyle process) parts of a normal-hearing subject. The results suggest that, at least in the parts investigated in the current study, the frequency resolution and intelligibility of the facial parts were about the same as those of the conventional parts. These results indicate that practical frequency information and speech perception are possible with BC devices attached to different facial parts.

Validation of cost-efficient EEG experimental setup for neural tracking in an auditory attention task.

When individuals listen to speech, their neural activity phase-locks to the slow temporal rhythm, which is commonly referred to as "neural tracking". The neural tracking mechanism allows for the detection of an attended sound source in a multi-talker situation by decoding neural signals obtained by electroencephalography (EEG), known as auditory attention decoding (AAD). Neural tracking with AAD can be utilized as an objective measurement tool for diverse clinical contexts, and it has potential to be applied to neuro-steered hearing devices. To effectively utilize this technology, it is essential to enhance the accessibility of EEG experimental setup and analysis. The aim of the study was to develop a cost-efficient neural tracking system and validate the feasibility of neural tracking measurement by conducting an AAD task using an offline and real-time decoder model outside the soundproof environment. We devised a neural tracking system capable of conducting AAD experiments using an OpenBCI and Arduino board. Nine participants were recruited to assess the performance of the AAD using the developed system, which involved presenting competing speech signals in an experiment setting without soundproofing. As a result, the offline decoder model demonstrated an average performance of 90%, and real-time decoder model exhibited a performance of 78%. The present study demonstrates the feasibility of implementing neural tracking and AAD using cost-effective devices in a practical environment.

Auditory enhancement in younger and older listeners with normal and impaired hearinga).

Auditory enhancement is a spectral contrast aftereffect that can facilitate the detection of novel events in an ongoing background. A single-interval paradigm combined with roved frequency content between trials can yield as much as 20 dB enhancement in young normal-hearing listeners. This study compared such enhancement in 15 listeners with sensorineural hearing loss with that in 15 age-matched adults and 15 young adults with normal audiograms. All groups were presented with stimulus levels of 70 dB sound pressure level (SPL) per component. The two groups with normal hearing were also tested at 45 dB SPL per component. The hearing-impaired listeners showed very little enhancement overall. However, when tested at the same high (70-dB) level, both young and age-matched normal-hearing listeners also showed substantially reduced enhancement, relative to that found at 45 dB SPL. Some differences in enhancement emerged between young and older normal-hearing listeners at the lower sound level. The results suggest that enhancement is highly level-dependent and may also decrease somewhat with age or slight hearing loss. Implications for hearing-impaired listeners may include a poorer ability to adapt to real-world acoustic variability, due in part to the higher levels at which sound must be presented to be audible.

Competing influence of visual speech on auditory neural adaptation.

Visual information from a speaker's face enhances auditory neural processing and speech recognition. To determine whether auditory memory can be influenced by visual speech, the degree of auditory neural adaptation of an auditory syllable preceded by an auditory, visual, or audiovisual syllable was examined using EEG. Consistent with previous findings and additional adaptation of auditory neurons tuned to acoustic features, stronger adaptation of N1, P2 and N2 auditory evoked responses was observed when the auditory syllable was preceded by an auditory compared to a visual syllable. However, although stronger than when preceded by a visual syllable, lower adaptation was observed when the auditory syllable was preceded by an audiovisual compared to an auditory syllable. In addition, longer N1 and P2 latencies were then observed. These results further demonstrate that visual speech acts on auditory memory but suggest competing visual influences in the case of audiovisual stimulation.

Neural tracking measures of speech intelligibility: Manipulating intelligibility while keeping acoustics unchanged.

Neural speech tracking has advanced our understanding of how our brains rapidly map an acoustic speech signal onto linguistic representations and ultimately meaning. It remains unclear, however, how speech intelligibility is related to the corresponding neural responses. Many studies addressing this question vary the level of intelligibility by manipulating the acoustic waveform, but this makes it difficult to cleanly disentangle the effects of intelligibility from underlying acoustical confounds. Here, using magnetoencephalography recordings, we study neural measures of speech intelligibility by manipulating intelligibility while keeping the acoustics strictly unchanged. Acoustically identical degraded speech stimuli (three-band noise-vocoded, ~20 s duration) are presented twice, but the second presentation is preceded by the original (nondegraded) version of the speech. This intermediate priming, which generates a "pop-out" percept, substantially improves the intelligibility of the second degraded speech passage. We investigate how intelligibility and acoustical structure affect acoustic and linguistic neural representations using multivariate temporal response functions (mTRFs). As expected, behavioral results confirm that perceived speech clarity is improved by priming. mTRFs analysis reveals that auditory (speech envelope and envelope onset) neural representations are not affected by priming but only by the acoustics of the stimuli (bottom-up driven). Critically, our findings suggest that segmentation of sounds into words emerges with better speech intelligibility, and most strongly at the later (~400 ms latency) word processing stage, in prefrontal cortex, in line with engagement of top-down mechanisms associated with priming. Taken together, our results show that word representations may provide some objective measures of speech comprehension.

Improving EEG-based decoding of the locus of auditory attention through domain adaptation.

Objective.This paper presents a novel domain adaptation (DA) framework to enhance the accuracy of electroencephalography (EEG)-based auditory attention classification, specifically for classifying the direction (left or right) of attended speech. The framework aims to improve the performances for subjects with initially low classification accuracy, overcoming challenges posed by instrumental and human factors. Limited dataset size, variations in EEG data quality due to factors such as noise, electrode misplacement or subjects, and the need for generalization across different trials, conditions and subjects necessitate the use of DA methods. By leveraging DA methods, the framework can learn from one EEG dataset and adapt to another, potentially resulting in more reliable and robust classification models.Approach.This paper focuses on investigating a DA method, based on parallel transport, for addressing the auditory attention classification problem. The EEG data utilized in this study originates from an experiment where subjects were instructed to selectively attend to one of the two spatially separated voices presented simultaneously.Main results.Significant improvement in classification accuracy was observed when poor data from one subject was transported to the domain of good data from different subjects, as compared to the baseline. The mean classification accuracy for subjects with poor data increased from 45.84% to 67.92%. Specifically, the highest achieved classification accuracy from one subject reached 83.33%, a substantial increase from the baseline accuracy of 43.33%.Significance.The findings of our study demonstrate the improved classification performances achieved through the implementation of DA methods. This brings us a step closer to leveraging EEG in neuro-steered hearing devices.