Delta/theta band EEG differentially tracks low and high frequency speech-derived envelopes

Speech perception difficulty modulates theta-band encoding of articulatory synergies

The human brain tracks available speech acoustics and extrapolates missing information such as the speaker's articulatory patterns. However, the extent to which articulatory reconstruction supports speech perception remains unclear. This study explores the relationship between articulatory reconstruction and task difficulty. Participants listened to sentences and performed a speech-rhyming task. Real kinematic data of the speaker's vocal tract were recorded via electromagnetic articulography (EMA) and aligned to corresponding acoustic outputs. We extracted articulatory synergies from the EMA data with principal component analysis (PCA) and employed partial information decomposition (PID) to separate the electroencephalographic (EEG) encoding of acoustic and articulatory features into unique, redundant, and synergistic atoms of information. We median-split sentences into easy (ES) and hard (HS) based on participants' performance and found that greater task difficulty involved greater encoding of unique articulatory information in the theta band. We conclude that fine-grained articulatory reconstruction plays a complementary role in the encoding of speech acoustics, lending further support to the claim that motor processes support speech perception.NEW & NOTEWORTHY Top-down processes originating from the motor system contribute to speech perception through the reconstruction of the speaker's articulatory movement. This study investigates the role of such articulatory simulation under variable task difficulty. We show that more challenging listening tasks lead to increased encoding of articulatory kinematics in the theta band and suggest that, in such situations, fine-grained articulatory reconstruction complements acoustic encoding.

Graph theoretical brain connectivity measures to investigate neural correlates of music rhythms associated with fear and anger

The present study tests the hypothesis that emotions of fear and anger are associated with distinct psychophysiological and neural circuitry according to discrete emotion model due to contrasting neurotransmitter activities, despite being included in the same affective group in many studies due to similar arousal-valance scores of them in emotion models. EEG data is downloaded from OpenNeuro platform with access number of ds002721. Brain connectivity estimations are obtained by using both functional and effective connectivity estimators in analysis of short (2 sec) and long (6 sec) EEG segments across the cortex. In tests, discrete emotions and resting-states are identified by frequency band specific brain network measures and then contrasting emotional states are deep classified with 5-fold cross-validated Long Short Term Memory Networks. Logistic regression modeling has also been examined to provide robust performance criteria. Commonly, the best results are obtained by using Partial Directed Coherence in Gamma (31.5 - 60.5 H z ) sub-bands of short EEG segments. In particular, Fear and Anger have been classified with accuracy of 91.79%. Thus, our hypothesis is supported by overall results. In conclusion, Anger is found to be characterized by increased transitivity and decreased local efficiency in addition to lower modularity in Gamma-band in comparison to fear. Local efficiency refers functional brain segregation originated from the ability of the brain to exchange information locally. Transitivity refer the overall probability for the brain having adjacent neural populations interconnected, thus revealing the existence of tightly connected cortical regions. Modularity quantifies how well the brain can be partitioned into functional cortical regions. In conclusion, PDC is proposed to graph theoretical analysis of short EEG epochs in presenting robust emotional indicators sensitive to perception of affective sounds.

Cross-linguistic and acoustic-driven effects on multiscale neural synchrony to stress rhythms

We investigated how neural oscillations code the hierarchical nature of stress rhythms in speech and how stress processing varies with language experience. By measuring phase synchrony of multilevel EEG-acoustic tracking and intra-brain cross-frequency coupling, we show the encoding of stress involves different neural signatures (delta rhythms = stress foot rate; theta rhythms = syllable rate), is stronger for amplitude vs. duration stress cues, and induces nested delta-theta coherence mirroring the stress-syllable hierarchy in speech. Only native English, but not Mandarin, speakers exhibited enhanced neural entrainment at central stress (2 Hz) and syllable (4 Hz) rates intrinsic to natural English. English individuals with superior cortical-stress tracking capabilities also displayed stronger neural hierarchical coherence, highlighting a nuanced interplay between internal nesting of brain rhythms and external entrainment rooted in language-specific speech rhythms. Our cross-language findings reveal brain-speech synchronization is not purely a "bottom-up" but benefits from "top-down" processing from listeners' language-specific experience.

EEG-based assessment of temporal fine structure and envelope effect in mandarin syllable and tone perception

In recent years, speech perception research has benefited from low-frequency rhythm entrainment tracking of the speech envelope. However, speech perception is still controversial regarding the role of speech envelope and temporal fine structure, especially in Mandarin. This study aimed to discuss the dependence of Mandarin syllables and tones perception on the speech envelope and the temporal fine structure. We recorded the electroencephalogram (EEG) of the subjects under three acoustic conditions using the sound chimerism analysis, including (i) the original speech, (ii) the speech envelope and the sinusoidal modulation, and (iii) the fine structure of time and the modulation of the non-speech (white noise) sound envelope. We found that syllable perception mainly depended on the speech envelope, while tone perception depended on the temporal fine structure. The delta bands were prominent, and the parietal and prefrontal lobes were the main activated brain areas, regardless of whether syllable or tone perception was involved. Finally, we decoded the spatiotemporal features of Mandarin perception from the microstate sequence. The spatiotemporal feature sequence of the EEG caused by speech material was found to be specific, suggesting a new perspective for the subsequent auditory brain-computer interface. These results provided a new scheme for the coding strategy of new hearing aids for native Mandarin speakers.

HIGHLIGHTS

Detection of Pilot's Mental Workload Using a Wireless EEG Headset in Airfield Traffic Pattern Tasks

Elevated mental workload (MWL) experienced by pilots can result in increased reaction times or incorrect actions, potentially compromising flight safety. This study aims to develop a functional system to assist administrators in identifying and detecting pilots' real-time MWL and evaluate its effectiveness using designed airfield traffic pattern tasks within a realistic flight simulator. The perceived MWL in various situations was assessed and labeled using NASA Task Load Index (NASA-TLX) scores. Physiological features were then extracted using a fast Fourier transformation with 2-s sliding time windows. Feature selection was conducted by comparing the results of the Kruskal-Wallis (K-W) test and Sequential Forward Floating Selection (SFFS). The results proved that the optimal input was all PSD features. Moreover, the study analyzed the effects of electroencephalography (EEG) features from distinct brain regions and PSD changes across different MWL levels to further assess the proposed system's performance. A 10-fold cross-validation was performed on six classifiers, and the optimal accuracy of 87.57% was attained using a multi-class K-Nearest Neighbor (KNN) classifier for classifying different MWL levels. The findings indicate that the wireless headset-based system is reliable and feasible. Consequently, numerous wireless EEG device-based systems can be developed for application in diverse real-driving scenarios. Additionally, the current system contributes to future research on actual flight conditions.

Hyperscanning EEG Paradigm Applied to Remote vs. Face-To-Face Learning in Managerial Contexts: Which Is Better?

We propose a hyperscanning research design, where electroencephalographic (EEG) data were collected on an instructor and teams of learners. We compared neurophysiological measures within the frequency domain (delta, theta, alpha, and beta EEG bands) in the two conditions: face-to-face and remote settings. Data collection was carried out using wearable EEG systems. Conversational analysis was previously applied to detect comparable EEG time blocks and semantic topics. The digitalization of training can be considered a challenge but also a chance for organizations. However, if not carefully addressed, it might constitute a criticality. Limited research explored how remote, as opposed to face-to-face, training affects cognitive, (such as memory and attention), affective, and social processes in workgroups. Data showed an alpha desynchronization and, conversely, a theta and beta synchronization for the face-to-face condition. Moreover, trainees showed different patterns for beta power depending on the setting condition, with significantly increased power spectral density (PSD) in the face-to-face condition. These results highlight the relevance of neurophysiological measures in testing the e-learning process, in relation to the emotional engagement, memory encoding, and attentional processing.

Dexmedetomidine Preserves Activity of Neurons in Primary Somatosensory Cortex Compared to Propofol and Ketamine

General anesthesia has been shown to induce significant changes in the functional connectivity of the cerebral cortex. However, traditional methods such as electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) lack the spatial resolution to study the effects of general anesthesia on individual cortical neurons. This study aimed to use high-resolution two-photon imaging, which can provide single-neuron resolution, to investigate the characteristics of consciousness under general anesthesia. We used C57BL/6J and Thy1-GCamp6s mice and found that at similar levels of sedation, as measured by EEG, dexmedetomidine did not significantly inhibit the spontaneous activity of neuronal somata in the S1 cortex, but preserved the frequency of calcium events in neuronal spines. In contrast, propofol and ketamine dramatically inhibited the spontaneous activity of both neuronal somata and spines. The S1 cortex still responded to whisker stimulation under dexmedetomidine anesthesia, but not under propofol or ketamine anesthesia. Our results suggest that dexmedetomidine anesthesia has unique neuronal properties associated with its ability to facilitate easy awakening in the clinic. These findings provide insights into the development of more effective strategies for monitoring consciousness during general anesthesia.

Speech listening entails neural encoding of invisible articulatory features

Speech processing entails a complex interplay between bottom-up and top-down computations. The former is reflected in the neural entrainment to the quasi-rhythmic properties of speech acoustics while the latter is supposed to guide the selection of the most relevant input subspace. Top-down signals are believed to originate mainly from motor regions, yet similar activities have been shown to tune attentional cycles also for simpler, non-speech stimuli. Here we examined whether, during speech listening, the brain reconstructs articulatory patterns associated to speech production. We measured electroencephalographic (EEG) data while participants listened to sentences during the production of which articulatory kinematics of lips, jaws and tongue were also recorded (via Electro-Magnetic Articulography, EMA). We captured the patterns of articulatory coordination through Principal Component Analysis (PCA) and used Partial Information Decomposition (PID) to identify whether the speech envelope and each of the kinematic components provided unique, synergistic and/or redundant information regarding the EEG signals. Interestingly, tongue movements contain both unique as well as synergistic information with the envelope that are encoded in the listener's brain activity. This demonstrates that during speech listening the brain retrieves highly specific and unique motor information that is never accessible through vision, thus leveraging audio-motor maps that arise most likely from the acquisition of speech production during development.

MEG Activity in Visual and Auditory Cortices Represents Acoustic Speech-Related Information during Silent Lip Reading

Speech is an intrinsically multisensory signal, and seeing the speaker's lips forms a cornerstone of communication in acoustically impoverished environments. Still, it remains unclear how the brain exploits visual speech for comprehension. Previous work debated whether lip signals are mainly processed along the auditory pathways or whether the visual system directly implements speech-related processes. To probe this, we systematically characterized dynamic representations of multiple acoustic and visual speech-derived features in source localized MEG recordings that were obtained while participants listened to speech or viewed silent speech. Using a mutual-information framework we provide a comprehensive assessment of how well temporal and occipital cortices reflect the physically presented signals and unique aspects of acoustic features that were physically absent but may be critical for comprehension. Our results demonstrate that both cortices feature a functionally specific form of multisensory restoration: during lip reading, they reflect unheard acoustic features, independent of co-existing representations of the visible lip movements. This restoration emphasizes the unheard pitch signature in occipital cortex and the speech envelope in temporal cortex and is predictive of lip-reading performance. These findings suggest that when seeing the speaker's lips, the brain engages both visual and auditory pathways to support comprehension by exploiting multisensory correspondences between lip movements and spectro-temporal acoustic cues.

Pushing the envelope: Evaluating speech rhythm with different envelope extraction techniques

The amplitude of the speech signal varies over time, and the speech envelope is an attempt to characterise this variation in the form of an acoustic feature. Although tacitly assumed, the similarity between the speech envelope-derived time series and that of phonetic objects (e.g., vowels) remains empirically unestablished. The current paper, therefore, evaluates several speech envelope extraction techniques, such as the Hilbert transform, by comparing different acoustic landmarks (e.g., peaks in the speech envelope) with manual phonetic annotation in a naturalistic and diverse dataset. Joint speech tasks are also introduced to determine which acoustic landmarks are most closely coordinated when voices are aligned. Finally, the acoustic landmarks are evaluated as predictors for the temporal characterisation of speaking style using classification tasks. The landmark that performed most closely to annotated vowel onsets was peaks in the first derivative of a human audition-informed envelope, consistent with converging evidence from neural and behavioural data. However, differences also emerged based on language and speaking style. Overall, the results show that both the choice of speech envelope extraction technique and the form of speech under study affect how sensitive an engineered feature is at capturing aspects of speech rhythm, such as the timing of vowels.

Multivariate Analysis of Evoked Responses during the Rubber Hand Illusion Suggests a Temporal Parcellation into Manipulation and Illusion-Specific Correlates

The neurophysiological processes reflecting body illusions such as the rubber hand remain debated. Previous studies investigating the neural responses evoked by the illusion-inducing stimulation have provided diverging reports as to when these responses reflect the illusory state of the artificial limb becoming embodied. One reason for these diverging reports may be that different studies contrasted different experimental conditions to isolate potential correlates of the illusion, but individual contrasts may reflect multiple facets of the adopted experimental paradigm and not just the illusory state. To resolve these controversies, we recorded EEG responses in human participants and combined multivariate (cross-)classification with multiple Illusion and non-Illusion conditions. These conditions were designed to probe for markers of the illusory state that generalize across the spatial arrangements of limbs or the specific nature of the control object (a rubber hand or participant’s real hand), hence which are independent of the precise experimental conditions used as contrast for the illusion. Our results reveal a parcellation of evoked responses into a temporal sequence of events. Around 125 and 275 ms following stimulus onset, the neurophysiological signals reliably differentiate the illusory state from non-Illusion epochs. These results consolidate previous work by demonstrating multiple neurophysiological correlates of the rubber hand illusion and illustrate how multivariate approaches can help pinpointing those that are independent of the precise experimental configuration used to induce the illusion.

Acoustically Driven Cortical δ Oscillations Underpin Prosodic Chunking

Oscillation-based models of speech perception postulate a cortical computational principle by which decoding is performed within a window structure derived by a segmentation process. Segmentation of syllable-size chunks is realized by a θ oscillator. We provide evidence for an analogous role of a δ oscillator in the segmentation of phrase-sized chunks. We recorded magnetoencephalography (MEG) in humans, while participants performed a target identification task. Random-digit strings, with phrase-long chunks of two digits, were presented at chunk rates of 1.8 or 2.6 Hz, inside or outside the δ frequency band (defined here to be 0.5–2 Hz). Strong periodicities were elicited by chunk rates inside of δ in superior, middle temporal areas and speech-motor integration areas. Periodicities were diminished or absent for chunk rates outside δ, in line with behavioral performance. Our findings show that prosodic chunking of phrase-sized acoustic segments is correlated with acoustic-driven δ oscillations, expressing anatomically specific patterns of neuronal periodicities.