Biology subjects

Reichenbach, T.

Publications and source records attributed to Reichenbach, T..

At least 19 recordsLinked to original sources

bioRxiv2026

CORSICA: Reproducible Suppression of Cochlear Implant Artifacts in EEG evoked by Continuous Speech

ObjectiveElectroencephalography (EEG) is a key tool for studying auditory processing in cochlear implant (CI) users. In particular, EEG recordings obtained during continuous speech are becoming increasingly important for assessing speech and language processing in CI users, and may be utilized for neurofeedback. However, CIs also induce strong stimulation artifacts that are time-locked to the stimulus and mask the neural responses that have smaller magnitudes. Existing artifact reduction methods are typically based on event-related potentials (ERPs) or require manual component selection, making them unsuitable for naturalistic listening conditions or large datasets. ApproachWe develop CORSICA (CORrelation-baSed ICA artifact rejection), a reproducible, parameter-efficient method for CI artifact reduction in EEG responses to continuous speech. CORSICA operates on independent components (ICs) obtained through Infomax ICA and requires no manual component labelling, with performance governed by a single tunable threshold. It exploits the observation that CI artifacts temporally follow the audio signal without delay, whereas neural responses have an inherent lag due to auditory pathway latencies. For each IC, CORSICA computes the cross-correlation with the speech stimulus. Artifacts are identified by a high signal-to-noise ratio (SNR) of the correlation peak near zero lag, and the component is rejected if this SNR exceeds a threshold. To benchmark CORSICA, we evaluate two alternatives: a TRF-based SNR method, in which temporal response functions are fitted to each IC and artifact-driven peaks near zero lag are used for rejection, and a variant replacing ICA with second-order blind identification (SOBI) as the source separation step. Main resultsCORSICA effectively suppressed CI artifacts while preserving neural activity, enabling recovery of physiologically plausible TRFs with only 2% of ICs rejected. Both benchmark methods confirmed the validity of the SNR-based rejection framework, but CORSICA outperformed the TRF-based alternative in artifact suppression quality. Replacing ICA with SOBI as the source separation step required more ICs to be rejected, further supporting ICA as the preferred backbone for CORSICA. SignificanceCORSICA provides a fully objective, label-free approach to identifying CI artifacts in speech-evoked EEG data, with no manual intervention required. By centering artifact rejection on a single interpretable threshold, it offers a reproducible preprocessing standard for future EEG studies on speech processing in CI users. ConclusionOur findings demonstrate that objective CI artifact suppression in speech-evoked EEG data is feasible on the basis of the ICs temporal response patterns.

neuroscience↗

bioRxiv2026

The frequency dependence of EEG-speech envelope tracking does not reflect the rates of speech units or pitch

During speech listening, neural activity partly synchronises to fluctuations in the acoustic amplitude envelope of the stimulus. This neural tracking of the speech envelope has frequently been linked to the processing of acoustic features such as syllabic rhythmicity and pitch periodicity. However, it has not yet been investigated to which degree the frequency dependence of neural envelope tracking reflects the rate of acoustic and linguistic speech units. Here, using a large dataset of electroencephalographic (EEG) responses from participants who listened to naturalistic speech, we quantified neural tracking of the speech envelope across a wide range of modulation frequencies using coherence analysis. The coherence profile exhibited distinct peaks in the low-delta band (0.2-2 Hz), the theta-alpha band (4-15 Hz), and at higher frequencies near 45, 95, and 175 Hz. We show that this structure is independent of the rates of phonemes, syllabes and words as well as of pitch periodicity. Using temporal response functions (TRFs), we further show that neural envelope tracking in the gamma frequency band (30-250 Hz) is primarily driven by two clusters of neural generators with latencies of approximately 8 ms and 25 ms, likely located in the rostral brainstem and across the thalamocortical pathway, respectively. Together, these results highlight the interplay of different neural mechanisms and sources in shaping the neural envelope tracking, and lead to important methodological and interpretative considerations for studies that assess neural envelope tracking within narrow frequency bands.

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bioRxiv2026

Deep Learning Reveals Cross-Modal Neural Representations of Auditory and Visual Mental Imagery in MEG

Mental imagery provides a unique window into the brains ability to internally simulate sensory experiences, offering valuable insights for both cognitive neuroscience and brain-computer interface (BCI) research. This study examined the neural representations of imagined auditory and visual stimuli using magnetoen-cephalography (MEG) and assessed the ability of machine learning models to decode these mental processes. MEG data were recorded from 18 right-handed participants during auditory and visual imagery tasks and source-reconstructed within modality-specific cortical regions of interest. We compared a convolutional neural network (CNN) and a linear logistic regression model within a subject-specific classification frame-work. Both approaches achieved above-chance decoding accuracies, with the CNN outperforming the linear model in the auditory task, whereas the linear model showed slightly higher accuracy for visual imagery. Notably, the CNN achieved significant decoding performance even when trained on non-task-relevant cortical regions, indicating that imagined stimuli are represented in distributed and partially overlapping neural networks across modalities. This cross-modal decoding capability highlights the potential of deep learning models to capture complex, multimodal neural patterns and suggests that future brain-computer interfaces could benefit from integrating auditory and visual information. A secondary, behavioral analysis revealed correlation of memory capacity and individual learning preferences with decoding performances, suggesting that individual cognitive differences may further shape the quality of neural representations. Together, these findings advance our understanding of cross-modal mental imagery and point toward more flexible and personalized approaches in BCI design. New and NoteworthyBy comparing linear and deep classifiers, this work shows that convolutional networks capture rich, cross-modal neural representations of auditory and visual mental imagery in MEG. Significant decoding from non-task-relevant regions indicates distributed cortical engagement, highlighting deep learnings potential for robust, modality-independent brain-computer interfaces.

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bioRxiv2026

The cortical contribution to the speech-FFR is not modulated by visual information

Seeing a speakers face can significantly aid understanding, particularly in challenging acoustic environments. An early neural response implicated in audiovisual speech processing is the frequency-following response (speech-FFR), which occurs at the fundamental frequency of the speech signal. This response arises from both subcortical areas and the auditory cortex. Previous studies have shown that subcortical responses are reduced when bimodal stimulation includes visual input from the talkers face. Here, we examined the cortical contribution to the speech-FFR and its potential modulation by visual information. We recorded MEG responses to four types of audiovisual signals: a still image, an artificially generated avatar, a degraded video, and a natural video. The audio stimuli were presented in a substantial level of background noise to make behavioral audiovisual effects stand out. Speech-in-noise comprehension increased significantly from the audio-only condition to the avatar and the degraded video, and further to the natural video. Moreover, we found that all types of audiovisual stimuli yielded robust speech-FFRs in the auditory cortex at an early latency of around 30 ms. However, the magnitude of this neural response was neither enhanced nor attenuated by the videos, nor could the cortical contribution of the speech-FFR explain a significant portion of the variance in the behavioral comprehension scores. Our results suggest that visual modulation of the speech-FFR in the auditory cortex is, if existent, too small to be measurable in scenarios where speech occurs in considerable background noise.

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bioRxiv2026

Talking avatars can differentially modulate cortical speech tracking in the high and in the low delta band

In noisy listening environments, visual cues from a speakers face can significantly boost speech compre-hension. The underlying audiovisual integration in the brain involves neural tracking of audiovisual speech features. Moreover, lip reading in silence is associated with tracking of the speech envelope in the low-delta frequency band (0.5 - 1 Hz). Recently, digital avatars have emerged that can support speech comprehen-sion. Yet, it remains unclear how the human brain integrates such artificial visual signals with natural speech. Here, we employed magnetoencephalography (MEG) to measure the neural response to a natural video, an avatar generated by deep neural networks, and a degraded video serving as a control. We demonstrate that the avatar can enhance speech-in-noise comprehension to a similar degree as the degraded video, although less than the natural video. We further identify a late response at 600 ms in the neural tracking of the audi-tory cortex in the high delta band (1 - 4 Hz) that predicts audiovisual speech comprehension. In contrast, we found that neural tracking in the low delta band is related to silent lip-reading performance. Importantly, the tracking in the low delta band evoked by the avatars is much weaker and occurs earlier than that elicited by the other audiovisual stimuli. Neural tracking in the theta band (4 - 8 Hz) is not involved in audiovisual integration. Our results show that the low delta band and the high delta band play clearly distinct roles in visual-only and audiovisual speech processing, and suggest potential avenues for further boosting the abilities of avatars to support speech comprehension. Significance StatementUnderstanding a conversational partner is essential for everyday communication. Yet, many people -- due to aging or other factors -- struggle to follow speech in noisy environments. Seeing the speakers face can greatly enhance speech comprehension, but visual cues are often unavailable, such as during public announcements or telephone conversations. Digital avatars offer a promising alternative, but how the brain integrates audiovisual information from such artificial sources remains unclear. Using magnetoencephalog-raphy (MEG), we investigated how the brain processes and integrates speech when visual information is provided by either natural or artificial (avatar-based) signals. Our findings reveal both shared and distinct neural mechanisms of audiovisual integration, providing critical insight into how visual input can support speech understanding in challenging listening conditions.

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bioRxiv2025

Attention Decoding at the Cocktail Party: Preserved in Hearing Aid Users, Reduced in Cochlear Implant Users

AbstractUsers of hearing aids (HAs) and cochlear implants (CIs) experience significant difficulty understanding a target speaker in multi-talker environments or when other background noise is present. Segregation of a particular voice from background noise occurs partly through enhanced cortical tracking of amplitude fluctuations in the target signal. Measuring a persons cortical tracking allows decoding their focus of attention and may be used for neurofeedback in hearing devices, potentially aiding their users with speech-in-noise comprehension. Most studies on cortical speech tracking have employed typical hearing (TH) individuals, whereas studies in people with hearing impairment whose cortical tracking may differ are still scarce. The objective of this study was to compare cortical speech tracking of HA (n=29) and CI users (n=24) to that of age-matched TH individuals (n=29). We recorded EEG data while the participants attended one of two competing talkers (one with a female and one with a male voice), in a free-field acoustic environment. Importantly, HA users as well as CI users used their personal, clinically-fitted devices. Cortical speech tracking was assessed through linear backward and forward models that related the EEG data to the speech envelope. For the CI users, electrical artifacts stemming from the implant were addressed through a bespoke method for artifact rejection. We found that the HA group exhibited cortical tracking and attentional modulation that were largely comparable to those of the TH group. CI users also showed successful cortical tracking. However, they displayed a profound deficit in attentional modulation, seen in the significantly poorer neural segregation of the attended vs. the ignored speech streams. These results shed light on a neurobiological mechanism for speech-in-noise comprehension and have implications for neurofeedback in hearing devices.

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bioRxiv2025

The inner ear's active process contributes to selective attention to speech in noise

Humans are remarkably skilled at understanding speech in noisy environments. While segregation of different audio streams is mostly accomplished in the auditory cortex, neural feedback connections run from the cortex to the brainstem and to the cochlea. The latter organ not only houses the mechanosensitive hair cells, but also possesses an active process enabling it to amplify sound in a frequency-dependent manner. A physiological correlate of the active process are distortion-product otoacoustic emissions (DPOAEs) that can be measured non-invasively from the ear canal. Here we employed speech-like DPOAEs that are connected to the spectral structure of voiced speech to show that these emissions are modulated by selective attention to one of two competing voices as well as by inter-modal attention. We found that speech-like DPOAEs evoked by the resolved harmonics of a voice were significantly reduced when that voice was attended as compared to when it was ignored. No such effect was observed for the unresolved harmonics of the target voice when the competing voices harmonics in that range were unresolved as well, indicating that attentional modulation is specific to those components of voiced speech that are spectrally resolved. Our findings support the hypothesis that the cochleas active process already shapes selective attention to speech in noise. Moreover, the speech-like DPOAEs that we developed open up further possibilities for investigating the contribution of the cochlear active process to auditory scene analysis in naturalistic settings.

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bioRxiv2024

Assessing the Impact of Selective Attention on the Cortical Tracking of the Speech Envelope in the Delta and Theta Frequency Bands and How Musical Training Does (Not) Affect It

Oral communication regularly takes place amidst background noise, requiring the ability to selectively attend to a target speech stream. Musical training has been shown to be beneficial for this task. Regarding the underlying neural mechanisms, recent studies showed that the speech envelope is tracked by neural activity in the auditory cortex, which plays a role in the neural processing of speech, including speech in noise. The neural tracking occurs predominantly in two frequency bands, the delta and the theta band. However, much regarding the specifics of these neural responses, as well as their modulation through musical training, still remain unclear. Here, we investigated the delta- and theta-band cortical tracking of the speech envelope of attended and ignored speech using magnetoencephalography (MEG) recordings. We thereby assessed both musicians and non-musicians to explore potential differences between these groups. The cortical speech tracking was quantified through source-reconstructing the MEG data and subsequently relating the speech envelope in a certain frequency band to the MEG data using linear models. We thereby found the theta-band tracking to be dominated by early responses with comparable magnitudes for attended and ignored speech, whereas the delta band tracking exhibited both earlier and later responses that were modulated by selective attention. Almost no significant differences emerged in the neural responses between musicians and non-musicians. Our findings show that only the speech tracking in the delta but not in the theta band contributes to selective attention, but that this mechanism is essentially unaffected by musical training.

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bioRxiv2024

No evidence of musical training influencing the cortical contribution to the speech-FFR and its modulation through selective attention

Musicians can have better abilities to understand speech in adverse conditions such as background noise than non-musicians. However, the neural mechanisms behind such enhanced behavioral performances remain largely unclear. Studies have found that the subcortical frequency-following response to the fundamental frequency of speech and its higher harmonics (speech-FFR) may be involved since it is larger in people with musical training than in those without. Recent research has shown that the speech-FFR consists of a cortical contribution in addition to the subcortical sources. Both the subcortical and the cortical contribution are modulated by selective attention to one of two competing speakers. However, it is unknown whether the strength of the cortical contribution to the speech-FFR, or its attention modulation, is influenced by musical training. Here we investigate these issues through magnetoencephalographic (MEG) recordings of 52 subjects (18 musicians, 25 non-musicians, and 9 neutral participants) listening to two competing male speakers while selectively attending one of them. The speech-in-noise comprehension abilities of the participants were not assessed. We find that musicians and non-musicians display comparable cortical speech-FFRs and additionally exhibit similar subject-to-subject variability in the response. Furthermore, we also do not observe a difference in the modulation of the neural response through selective attention between musicians and non-musicians. Moreover, when assessing whether the cortical speech-FFRs are influenced by particular aspects of musical training, no significant effects emerged. Taken together, we did not find any effect of musical training on the cortical speech-FFR. Significance statementIn previous research musicians have been found to exhibit larger subcortical responses to the pitch of a speaker than non-musicians. These larger responses may reflect enhanced pitch processing due to musical training and may explain why musicians tend to understand speech better in noisy environments than people without musical training. However, higher-level cortical responses to the pitch of a voice exist as well and are influenced by attention. We show here that, unlike the subcortical responses, the cortical activities do not differ between musicians and non-musicians. The attentional effects are not influenced by musical training. Our results suggest that, unlike the subcortical response, the cortical response to pitch is not shaped by musical training.

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bioRxiv2023

Attentional modulation of the cortical contribution to the frequency-following response evoked by continuous speech

Selective attention to one of several competing speakers is required for comprehending a target speaker amongst other voices and for successful communication with them. Selective attention has been found to involve the neural tracking of low-frequency speech rhythms in the auditory cortex. Effects of selective attention have also been found in subcortical neural activities, in particular regarding the high-frequency neural response at the fundamental frequency of speech, the speech-FFR. Recent investigations have, however, shown that the speech-FFR contains cortical contributions as well. It remains unclear whether these are also modulated by selective attention. Here we employed magnetoencephalography (MEG) to assess the attentional modulation of the cortical contributions to the speech-FFR. We presented participants with two competing speech signals and analyzed the cortical responses during attentional switching between the two speakers. Our findings revealed robust attentional modulation of the cortical contribution to the speech-FFR: the neural responses were higher when the speaker was attended than when they were ignored. We also found that, regardless of attention, a voice with a lower fundamental frequency elicited a larger cortical contribution to the speech-FFR than a voice with a higher fundamental frequency. Our results show that the attentional modulation of the speech-FFR does not only occur subcortically but extends to the auditory cortex as well.

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bioRxiv2023

Early subcortical response at the fundamental frequency of continuous speech measured with MEG

Most parts of speech are voiced, exhibiting a degree of periodicity with a fundamental frequency and many higher harmonics. Some neural populations respond to this temporal fine structure, in particular at the fundamental frequency. This frequency-following response to speech (speech-FFR) consists of both subcortical and cortical contributions and can be measured through electroen-cephalography (EEG) as well as through magnetoencephalography (MEG), although both differ in the aspects of neural activity that they capture: EEG is sensitive to both radial and tangential sources as well as to deep sources, while MEG is more restrained to the measurement of tangential and superficial neural activity. EEG responses to continuous speech have shown an early subcortical contribution, at a latency of around 9 ms, in agreement with MEG measurements in response to short speech tokens, whereas MEG responses to continuous speech have not yet revealed such an early component. Here we analyze MEG responses to long segments of continuous speech. We find an early subcortical response at a latency of 9 ms, followed by later right-lateralized cortical activities at delays of 20 - 57 ms as well as potential subcortical activities. Our results show that the early subcortical component of the FFR to continuous speech can be measured from MEG, and that its latency agrees with that measured with EEG. They furthermore show that the early subcortical component is temporally well separated from later cortical contributions, enabling an independent assessment of both components towards further aspects of speech processing.

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bioRxiv2023

Phase-locking of neural activity to the envelope of speech in the delta frequency band reflects differences between word lists and sentences

The envelope of a speech signal is tracked by neural activity in the cerebral cortex. The cortical tracking occurs mainly in two frequency bands, theta (4 - 8 Hz) and delta band (1 - 4 Hz). Tracking in the faster theta band has been mostly associated with lower-level acoustic processing, such as the parsing of syllables, whereas the slower tracking in the delta band relates to higher-level linguistic information of words and word sequences. However, much regarding the more specific association between cortical tracking and acoustic as well as linguistic processing remains to be uncovered. Here we recorded electroencephalographic (EEG) responses to both meaningful sentences as well as random word lists in different levels of signal-to-noise ratios (SNRs) that lead to different levels of speech comprehension as well as listening effort. We then related the neural signals to the acoustic stimuli by computing the phase-locking value (PLV) between the EEG recordings and the speech envelope. We found that the PLV in the delta band increases with increasing SNR for sentences but not for the random word lists, showing that the PLV in this frequency band reflects linguistic information. When attempting to disentangle the effects of SNR, speech comprehension, and listening effort, we observed a trend that the PLV in the delta band might reflect listening effort rather than the other two variables, although the effect was not statistically significant. In summary, our study shows that the PLV in the delta band reflects linguistic information and might be related to listening effort.

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bioRxiv2023

Audiotactile stimulation can improve syllable discrimination through multisensory integration in the theta frequency band

Syllables are an essential building block of speech. We recently showed that tactile stimuli linked to the perceptual centers of syllables in continuous speech can improve speech comprehension. The rate of syllables lies in the theta frequency range, between 4 and 8 Hz, and the behavioural effect appears linked to multisensory integration in this frequency band. Because this neural activity may be oscillatory, we hypothesized that a behavioural effect may also occur not only while but also after this activity has been evoked or entrained through vibrotactile pulses. Here we show that audiotactile integration regarding the perception of single syllables, both on the neural and on the behavioural level, is consistent with this hypothesis. We first stimulated subjects with a series of vibrotactile pulses and then presented them with a syllable in background noise. We show that, at a delay of 200 ms after the last vibrotactile pulse, audiotactile integration still occurred in the theta band and syllable discrimination was enhanced. Moreover, the dependence of both the neural multisensory integration as well as of the behavioral discrimination on the delay of the audio signal with respect to the last tactile pulse was consistent with a damped oscillation. In addition, the multisensory gain is correlated with the syllable discrimination score. Our results therefore evidence the role of the theta band in audiotactile integration and provide evidence that these effect may involve oscillatory activity that still persists after the tactile stimulation.

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bioRxiv2022

The Neural Response at the Fundamental Frequency of Speech is Modulated by Word-level Acoustic and Linguistic Information

Spoken language comprehension requires rapid and continuous integration of information, from lower-level acoustic to higher-level linguistic features. Much of this processing occurs in the cerebral cortex. Its neural activity exhibits, for instance, correlates of predictive processing, emerging at delays of a few hundred milliseconds. However, the auditory pathways are also characterized by extensive feedback loops from higher-level cortical areas to lower-level ones as well as to subcortical structures. Early neural activity can therefore be influenced by higher-level cognitive processes, but it remains unclear whether such feedback contributes to linguistic processing. Here, we investigated early speech-evoked neural activity that emerges at the fundamental frequency. We analyzed EEG recordings obtained when subjects listened to a story read by a single speaker. We identified a response tracking the speakers fundamental frequency that occurred at a delay of 11 ms, while another response elicited by the high-frequency modulation of the envelope of higher harmonics exhibited a larger magnitude and longer latency of about 18 ms. Subsequently, we determined the magnitude of these early neural responses for each individual word in the story. We then quantified the context-independent frequency of each word and used a language model to compute context-dependent word surprisal and precision. The word surprisal represented how predictable a word is, given the previous context, and the word precision reflected the confidence about predicting the next word from the past context. We found that the word-level neural responses at the fundamental frequency were predominantly influenced by the acoustic features: the average fundamental frequency and its variability. Amongst the linguistic features, only context-independent word frequency showed a weak but significant modulation of the neural response to the high-frequency envelope modulation. Our results show that the early neural response at the fundamental frequency is already influenced by acoustic as well as linguistic information, suggesting top-down modulation of this neural response.

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bioRxiv2021

Speech-driven Facial Animations Improve Speech-in-Noise Comprehension of Humans

Understanding speech becomes a demanding task when the environment is noisy. Comprehension of speech in noise can be substantially improved by looking at the speakers face, and this audiovisual benefit is even more pronounced in people with hearing impairment. Recent advances in AI have allowed to synthesize photorealistic talking faces from a speech recording and a still image of a persons face in an end-to-end manner. However, it has remained unknown whether such facial animations improve speech-in-noise comprehension. Here we consider facial animations produced by a recently introduced generative adversarial network (GAN), and show that humans cannot distinguish between the synthesized and the natural videos. Importantly, we then show that the end- to-end synthesized videos significantly aid humans in understanding speech in noise, although the natural facial motions yield a yet higher audiovisual benefit. We further find that an audiovisual speech recognizer benefits from the synthesized facial animations as well. Our results suggest that synthesizing facial motions from speech can be used to aid speech comprehension in difficult listening environments.

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bioRxiv2021

Cortical tracking of a background speaker modulates the comprehension of a foreground speech signal

Understanding speech in background noise is a difficult task. The tracking of speech rhythms such as the rate of syllables and words by cortical activity has emerged as a key neural mechanism for speech-in-noise comprehension. In particular, recent investigations have used transcranial alternating current stimulation (tACS) with the envelope of a speech signal to influence the cortical speech tracking, demonstrating that this type of stimulation modulates comprehension and therefore evidencing a functional role of the cortical tracking in speech processing. Cortical activity has been found to track the rhythms of a background speaker as well, but the functional significance of this neural response remains unclear. Here we employ a speech-comprehension task with a target speaker in the presence of a distractor voice to show that tACS with the speech envelope of the target voice as well as tACS with the envelope of the distractor speaker both modulate the comprehension of the target speech. Because the envelope of the distractor speech does not carry information about the target speech stream, the modulation of speech comprehension through tACS with this envelope evidences that the cortical tracking of the background speaker affects the comprehension of the foreground speech signal. The phase dependency of the resulting modulation of speech comprehension is, however, opposite to that obtained from tACS with the envelope of the target speech signal. This suggests that the cortical tracking of the ignored speech stream and that of the attended speech stream may compete for neural resources. Significance StatementLoud environments such as busy pubs or restaurants can make conversation difficult. However, they also allow us to eavesdrop into other conversations that occur in the background. In particular, we often notice when somebody else mentions our name, even if we have not been listening to that person. However, the neural mechanisms by which background speech is processed remain poorly understood. Here we employ transcranial alternating current stimulation, a technique through which neural activity in the cerebral cortex can be influenced, to show that cortical responses to rhythms in the distractor speech modulate the comprehension of the target speaker. Our results evidence that the cortical tracking of background speech rhythms plays a functional role in speech processing.

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bioRxiv2021

The neural response to the temporal fine structure of continuous musical pieces is not affected by selective attention

Speech and music are spectro-temporally complex acoustic signals that a highly relevant for humans. Both contain a temporal fine structure that is encoded in the neural responses of subcortical and cortical processing centres. The subcortical response to the temporal fine structure of speech has recently been shown to be modulated by selective attention to one of two competing voices. Music similarly often consists of several simultaneous melodic lines, and a listener can selectively attend to a particular one at a time. However, the neural mechanisms that enable such selective attention remain largely enigmatic, not least since most investigations to date have focussed on short and simplified musical stimuli. Here we study the neural encoding of classical musical pieces in human volunteers, using scalp electroencephalography (EEG) recordings. We presented volunteers with continuous musical pieces composed of one or two instruments. In the latter case, the participants were asked to selectively attend to one of the two competing instruments and to perform a vibrato identification task. We used linear encoding and decoding models to relate the recorded EEG activity to the stimulus waveform. We show that we can measure neural responses to the temporal fine structure of melodic lines played by one single instrument, at the population level as well as for most individual subjects. The neural response peaks at a latency of 7.6 ms and is not measurable past 15 ms. When analysing the neural responses elicited by competing instruments, we find no evidence of attentional modulation. Our results show that, much like speech, the temporal fine structure of music is tracked by neural activity. In contrast to speech, however, this response appears unaffected by selective attention in the context of our experiment.

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bioRxiv2018

Real-time decoding of selective attention from the human auditory brainstem response to continuous speech

Humans are highly skilled at analysing complex acoustic scenes. The segregation of different acoustic streams and the formation of corresponding neural representations is mostly attributed to the auditory cortex. Decoding of selective attention from neuroimaging has therefore focussed on cortical responses to sound. However, the auditory brainstem response to speech is modulated by selective attention as well, as recently shown through measuring the brainstems response to running speech. Although the response of the auditory brainstem has a smaller magnitude than that of the auditory cortex, it occurs at much higher frequencies and therefore has a higher information rate. Here we develop statistical models for extracting the brainstem response from multi-channel scalp recordings and for analysing the attentional modulation according to the focus of attention. We demonstrate that the attentional modulation of the brainstem response to speech can be employed to decode the attentional focus of a listener from short measurements of ten seconds or less in duration. The decoding remains accurate when obtained from three EEG channels only. We further show how out-of-the-box decoding that employs subject-independent models, as well as decoding that is independent of the specific attended speaker is capable of achieving similar accuracy. These results open up new avenues for investigating the neural mechanisms for selective attention in the brainstem and for developing efficient auditory brain-computer interfaces.

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