Source-Modeling Auditory Processes of EEG Data Using EEGLAB and Brainstorm

Rhythm Complexity Modulates Behavioral and Neural Dynamics During Auditory–Motor Synchronization

We addressed how rhythm complexity influences auditory–motor synchronization in musically trained individuals who perceived and produced complex rhythms while EEG was recorded. Participants first listened to two-part auditory sequences (Listen condition). Each part featured a single pitch presented at a fixed rate; the integer ratio formed between the two rates varied in rhythmic complexity from low (1:1) to moderate (1:2) to high (3:2). One of the two parts occurred at a constant rate across conditions. Then, participants heard the same rhythms as they synchronized their tapping at a fixed rate (Synchronize condition). Finally, they tapped at the same fixed rate (Motor condition). Auditory feedback from their taps was present in all conditions. Behavioral effects of rhythmic complexity were evidenced in all tasks; detection of missing beats (Listen) worsened in the most complex (3:2) rhythm condition, and tap durations (Synchronize) were most variable and least synchronous with stimulus onsets in the 3:2 condition. EEG power spectral density was lowest at the fixed rate during the 3:2 rhythm and greatest during the 1:1 rhythm (Listen and Synchronize). ERP amplitudes corresponding to an N1 time window were smallest for the 3:2 rhythm and greatest for the 1:1 rhythm (Listen). Finally, synchronization accuracy (Synchronize) decreased as amplitudes in the N1 time window became more positive during the high rhythmic complexity condition (3:2). Thus, measures of neural entrainment corresponded to synchronization accuracy, and rhythmic complexity modulated the behavioral and neural measures similarly.

Local syntactic violations evoke fast mismatch-related neural activity detected by optical neuroimaging

It remains to be investigated whether syntax-related mismatch activity would be evoked in event-related optical signals by syntactic violations that deviate from our language knowledge and expectations. In the current study, we have employed fast optical neuroimaging with a frequency-domain oximeter to examine whether syntactic violations of English bare infinitives in the non-finite complement clause would trigger syntax-related mismatch effects. Recorded sentences of bare or full infinitive structures (without or with the 'to' infinitival marker) with syntactically correct or incorrect versions and non-syntactic lexical items (verbs) were presented to native speakers of English (n = 8) during silent movie viewing as a passive oddball task. The analysis of source strength (i.e., minimum norm current amplitudes) revealed that the syntactic category violations of bare object infinitives led to significantly more robust optical mismatch effects than the other syntactic violation and non-structural, lexical elements. This mismatch response had a peak latency of 186 ms in the left anterior superior temporal gyrus. In combination with our prior MEG report (Kubota et al. in Neurosci Lett 662:195-204, 2018), the present optical neuroimaging findings show that syntactic marking (unmarked-to-marked) violations of the bare object infinitive against the rule of the mental grammar enhance the signal strength exactly in the same manner seen with MEG scanning, including the peak latency of mismatch activity and the activated area of the brain.

Progesterone modulates theta oscillations in the frontal-parietal network

The neuroactive metabolites of the steroid hormones progesterone (P4) and testosterone (T) are GABAergic modulators that influence cognition, yet, the specific effect of P4 and T on brain network activity remains poorly understood. Here, we investigated if a fundamental oscillatory network activity pattern, often related to cognitive control, frontal midline theta (FMT) oscillations, are modulated by steroids hormones, P4 and T. We measured the concentration of P4 and T using salivary enzyme immunoassay and FMT oscillations using high-density electroencephalography (EEG) during eyes-open resting-state in 55 healthy women and men. Electrical brain activity was analyzed using Fourier analysis, aperiodic signal fitting, and beamformer source localization. Steroid hormone concentrations and biological sex were used as predictors for scalp and source-estimated amplitude of theta oscillations. Elevated concentrations of P4 predicted increased amplitude of FMT oscillations across both sexes, and no relationship was found with T. The positive correlation with P4 was specific to the frontal midline electrodes and survived correction for the background aperiodic signal of the brain. Using source localization, FMT oscillations were localized to the frontal-parietal network (FPN). Additionally, theta amplitude within the FPN, but not the default mode network, positively correlated with P4 concentration. Our results suggest that P4 concentration modulates brain activity via upregulation of theta oscillations in the FPN.

Distinct Oscillatory Dynamics Underlie Different Components of Hierarchical Cognitive Control

Hierarchical cognitive control enables us to execute actions guided by abstract goals. Previous research has suggested that neuronal oscillations at different frequency bands are associated with top-down cognitive control; however, whether distinct neural oscillations have similar or different functions for cognitive control is not well understood. The aim of the current study was to investigate the oscillatory neuronal mechanisms underlying two distinct components of hierarchical cognitive control: the level of abstraction of a rule, and the number of rules that must be maintained (set-size). We collected EEG data in 31 men and women who performed a hierarchical cognitive control task that varied in levels of abstraction and set-size. Results from time-frequency analysis in frontal electrodes showed an increase in theta amplitude for increased set-size, whereas an increase in δ was associated with increased abstraction. Both theta and δ amplitude correlated with behavioral performance in the tasks but in an opposite manner: theta correlated with response time slowing when the number of rules increased, whereas δ correlated with response time when rules became more abstract. Phase-amplitude coupling analysis revealed that δ phase-coupled with β amplitude during conditions with a higher level of abstraction, whereby beta band may potentially represent motor output that was guided by the δ phase. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control.SIGNIFICANCE STATEMENT Cognitive control allows us to perform immediate actions while maintaining more abstract, overarching goals in mind and to choose between competing actions. We found distinct oscillatory signatures that correspond to two different components of hierarchical control: the level of abstraction of a rule and the number of rules in competition. An increase in the level of abstraction was associated with δ oscillations, whereas theta oscillations were observed when the number of rules increased. Oscillatory amplitude correlated with behavioral performance in the task. Finally, the expression of β amplitude was coordinated via the phase of δ oscillations, and theta phase-coupled with γ amplitude. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control.

Expectancy effects in the EEG during joint and spontaneous word-by-word sentence production in German

Our aim in the present study is to measure neural correlates during spontaneous interactive sentence production. We present a novel approach using the word-by-word technique from improvisational theatre, in which two speakers jointly produce one sentence. This paradigm allows the assessment of behavioural aspects, such as turn-times, and electrophysiological responses, such as event-related-potentials (ERPs). Twenty-five participants constructed a cued but spontaneous four-word German sentence together with a confederate, taking turns for each word of the sentence. In 30% of the trials, the confederate uttered an unexpected gender-marked article. To complete the sentence in a meaningful way, the participant had to detect the violation and retrieve and utter a new fitting response. We found significant increases in response times after unexpected words and - despite allowing unscripted language production and naturally varying speech material - successfully detected significant N400 and P600 ERP effects for the unexpected word. The N400 EEG activity further significantly predicted the response time of the subsequent turn. Our results show that combining behavioural and neuroscientific measures of verbal interactions while retaining sufficient experimental control is possible, and that this combination provides promising insights into the mechanisms of spontaneous spoken dialogue.

Push-pull competition between bottom-up and top-down auditory attention to natural soundscapes

In everyday social environments, demands on attentional resources dynamically shift to balance our attention to targets of interest while alerting us to important objects in our surrounds. The current study uses electroencephalography to explore how the push-pull interaction between top-down and bottom-up attention manifests itself in dynamic auditory scenes. Using natural soundscapes as distractors while subjects attend to a controlled rhythmic sound sequence, we find that salient events in background scenes significantly suppress phase-locking and gamma responses to the attended sequence, countering enhancement effects observed for attended targets. In line with a hypothesis of limited attentional resources, the modulation of neural activity by bottom-up attention is graded by degree of salience of ambient events. The study also provides insights into the interplay between endogenous and exogenous attention during natural soundscapes, with both forms of attention engaging a common fronto-parietal network at different time lags.

A novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN

OBJECTIVE

To develop and implement a novel approach which combines the technique of scout EEG source imaging (ESI) with convolutional neural network (CNN) for the classification of motor imagery (MI) tasks.

APPROACH

The technique of ESI uses a boundary element method (BEM) and weighted minimum norm estimation (WMNE) to solve the EEG forward and inverse problems, respectively. Ten scouts are then created within the motor cortex to select the region of interest (ROI). We extract features from the time series of scouts using a Morlet wavelet approach. Lastly, CNN is employed for classifying MI tasks.

MAIN RESULTS

The overall mean accuracy on the Physionet database reaches 94.5% and the individual accuracy of each task reaches 95.3%, 93.3%, 93.6%, 96% for the left fist, right fist, both fists and both feet, correspondingly, validated using ten-fold cross validation. We report an increase of up to 14.4% for overall classification compared with the competitive results from the state-of-the-art MI classification methods. Then, we add four new subjects to verify the validity of the method and the overall mean accuracy is 92.5%. Furthermore, the global classifier was adapted to single subjects improving the overall mean accuracy to 94.54%.

SIGNIFICANCE

The combination of scout ESI and CNN enhances BCI performance of decoding EEG four-class MI tasks.

Real-time monitoring and regulating auditory cortex alpha activity in patients with chronic tinnitus

OBJECTIVE

Low levels of alpha activity (8-13Hz) mirror a state of enhanced responsiveness, whereas high levels of alpha are a state of reduced responsiveness. Tinnitus is accompanied by reduction of alpha activity in the perisylvian regions compared to normal hearing controls. This reduction might be a key mechanism in the chain of reactions leading to tinnitus. We devised a novel spatial filter as an on-line source monitoring method, which can be used to control alpha activity in the primary auditory cortex. In addition, we designed an innovative experimental procedure to enable suppression of visual and somatosensory alpha, facilitating auditory alpha control during alpha neurofeedback.

APPROACH

An amplitude-modulated auditory stimulation with 40 Hz modulation frequency and 1000 Hz carrier frequency specifically activates the primary auditory cortex. The topography of 40 Hz oscillation depicts the activity of the auditory cortices. We used this map as a spatial filter, which passes the activity originating from the auditory cortex. To suppress superposition of auditory alpha by somatosensory and visual alpha, we used a continuous tactile jaw-stimulation and visual stimulation protocol to suppress somatosensory alpha of regions adjacent to the auditory cortex and visual alpha for local regulation of auditory alpha activity only.

MAIN RESULTS

This novel spatial filter for online detection of auditory alpha activity and the usage of multi-sensory stimulation facilitate the appearance of alpha activity from the auditory cortex at the sensor level.

SIGNIFICANCE

The proposed procedure can be used in an EEG-neurofeedback-treatment approach allowing online auditory alpha self-regulation training in patients with chronic tinnitus.

Effects of mindfulness on psychological and psychophysiological responses during self-paced walking

The aim of the present study was to investigate the effects of an audio-guided mindfulness (MF) single session on psychological and psychophysiological responses during an outdoor walking task. Twenty-four participants (12 females and 12 males; M_age  = 23.6, SD = 3.9 years) were required to walk 200 m at a pace of their choosing. Two experimental conditions (mindfulness meditation and mindlessness [ML] meditation) and a control condition (CO) were administered. Electrical activity in the brain was measured by the use of a portable electroencephalography (EEG) system during walking. Fast Fourier Transform was used to decompose the EEG samples into theta (5-7 Hz), alpha (8-14 Hz), and beta (15-29 Hz) frequencies. Brain connectivity analysis between frontal and temporo-parietal electrode sites was conducted to explore functional interactions through the use of spectral coherence. Affective and perceptual responses were measured by the use of single-item scales and questionnaires. The present findings indicate that MF was sufficiently potent to reallocate attention toward task-related thoughts, downregulate perceived activation, and enhance affective responses to a greater degree than the other two conditions. Conversely, ML was sufficient to increase the use of dissociative thoughts, make participants less aware of their physical sensations and emotions, induce a more negative affective state, and upregulate perceived activation to a greater extent than MF and CO. The brain mechanisms that underlie the effects of MF on exercise appear to be associated with the enhanced inter-hemispheric connectivity of high-frequency waves between right frontal and left temporo-parietal areas of the cortex.

Super-Resolution for Improving EEG Spatial Resolution using Deep Convolutional Neural Network-Feasibility Study

Electroencephalography (EEG) has relatively poor spatial resolution and may yield incorrect brain dynamics and distort topography; thus, high-density EEG systems are necessary for better analysis. Conventional methods have been proposed to solve these problems, however, they depend on parameters or brain models that are not simple to address. Therefore, new approaches are necessary to enhance EEG spatial resolution while maintaining its data properties. In this work, we investigated the super-resolution (SR) technique using deep convolutional neural networks (CNN) with simulated EEG data with white Gaussian and real brain noises, and experimental EEG data obtained during an auditory evoked potential task. SR EEG simulated data with white Gaussian noise or brain noise demonstrated a lower mean squared error and higher correlations with sensor information, and detected sources even more clearly than did low resolution (LR) EEG. In addition, experimental SR data also demonstrated far smaller errors for N1 and P2 components, and yielded reasonable localized sources, while LR data did not. We verified our proposed approach’s feasibility and efficacy, and conclude that it may be possible to explore various brain dynamics even with a small number of sensors.

Neuronal Correlates of Informational and Energetic Masking in the Human Brain in a Multi-Talker Situation

Human listeners can follow the voice of one speaker while several others are talking at the same time. This process requires segregating the speech streams from each other and continuously directing attention to the target stream. We investigated the functional brain networks underlying this ability. Two speech streams were presented simultaneously to participants, who followed one of them and detected targets within it (target stream). The loudness of the distractor speech stream varied on five levels: moderately softer, slightly softer, equal, slightly louder, or moderately louder than the attended. Performance measures showed that the most demanding task was the moderately softer distractors condition, which indicates that a softer distractor speech may receive more covert attention than louder distractors and, therefore, they require more cognitive resources. EEG-based measurement of functional connectivity between various brain regions revealed frequency-band specific networks: (1) energetic masking (comparing the louder distractor conditions with the equal loudness condition) was predominantly associated with stronger connectivity between the frontal and temporal regions at the lower alpha (8–10 Hz) and gamma (30–70 Hz) bands; (2) informational masking (comparing the softer distractor conditions with the equal loudness condition) was associated with a distributed network between parietal, frontal, and temporal regions at the theta (4–8 Hz) and beta (13–30 Hz) bands. These results suggest the presence of distinct cognitive and neural processes for solving the interference from energetic vs. informational masking.

Does Fractional Anisotropy Predict Motor Imagery Neurofeedback Performance in Healthy Older Adults?

Motor imagery neurofeedback training has been proposed as a potential add-on therapy for motor impairment after stroke, but not everyone benefits from it. Previous work has used white matter integrity to predict motor imagery neurofeedback aptitude in healthy young adults. We set out to test this approach with motor imagery neurofeedback that is closer to that used for stroke rehabilitation and in a sample whose age is closer to that of typical stroke patients. Using shrinkage linear discriminant analysis with fractional anisotropy values in 48 white matter regions as predictors, we predicted whether each participant in a sample of 21 healthy older adults (48–77 years old) was a good or a bad performer with 84.8% accuracy. However, the regions used for prediction in our sample differed from those identified previously, and previously suggested regions did not yield significant prediction in our sample. Including demographic and cognitive variables which may correlate with motor imagery neurofeedback performance and white matter structure as candidate predictors revealed an association with age but also led to loss of statistical significance and somewhat poorer prediction accuracy (69.6%). Our results suggest cast doubt on the feasibility of predicting the benefit of motor imagery neurofeedback from fractional anisotropy. At the very least, such predictions should be based on data collected using the same paradigm and with subjects whose characteristics match those of the target case as closely as possible.

Attention and speech-processing related functional brain networks activated in a multi-speaker environment

Human listeners can focus on one speech stream out of several concurrent ones. The present study aimed to assess the whole-brain functional networks underlying a) the process of focusing attention on a single speech stream vs. dividing attention between two streams and 2) speech processing on different time-scales and depth. Two spoken narratives were presented simultaneously while listeners were instructed to a) track and memorize the contents of a speech stream and b) detect the presence of numerals or syntactic violations in the same ("focused attended condition") or in the parallel stream ("divided attended condition"). Speech content tracking was found to be associated with stronger connectivity in lower frequency bands (delta band- 0,5-4 Hz), whereas the detection tasks were linked with networks operating in the faster alpha (8-10 Hz) and beta (13-30 Hz) bands. These results suggest that the oscillation frequencies of the dominant brain networks during speech processing may be related to the duration of the time window within which information is integrated. We also found that focusing attention on a single speaker compared to dividing attention between two concurrent speakers was predominantly associated with connections involving the frontal cortices in the delta (0.5-4 Hz), alpha (8-10 Hz), and beta bands (13-30 Hz), whereas dividing attention between two parallel speech streams was linked with stronger connectivity involving the parietal cortices in the delta and beta frequency bands. Overall, connections strengthened by focused attention may reflect control over information selection, whereas connections strengthened by divided attention may reflect the need for maintaining two streams in parallel and the related control processes necessary for performing the tasks.