CHARACTERISTICS OF Μ-RHYTHM FREQUENCY MODULATION UNDER IMAGINARY MOVEMENTS

The aim of the paper is to assess the phenomena of EEG frequency modulation while performing real and imaginary movements necessary for BCI control. Materials and Methods. The study enrolled a group of 30 volunteers of both sexes, aged 17 to 23. The subjects had to execute four commands and to run them randomly following the program instruction. The experiment was carried out in two ways: physically and mentally. Firstly, each command corresponded to a certain subject’s movement. Secondly, the same commands were not performed, they were only imaginary. The command was considered successfully executed if a volunteer was able to follow the program instruction and to hold the position for 2 seconds. The analysis of the results was carried out for five frequency ranges: 7–10 Hz, 9–12 Hz, 12–15 Hz, 15–20 Hz, 20–25 Hz. Results. Correlation analysis and exploratory statistics (namely, correspondence analysis and cluster analysis) were used to process the generated electroencephalographic parameters. The actually performed subjects’ movements were associated with a high number of low-frequency modulations in the 12–20 Hz range in the absence of modulating influences in the range below 12 Hz. Pronounced patterns of high-frequency modulation were peculiar for unexecuted commands. Conclusion. The results of the correlation analysis demonstrate a positive relationship between the number of cases of high-frequency modulation in the range of 9–12 Hz with the number of cases of low-frequency modulation in all other studied signal ranges in case of successful command execution. Key words: brain-computer interface, μ-rhythm, frequency modulation, EEG. Цель – оценка феноменов частотной модуляции ЭЭГ в условиях выполнения реальных и воображаемых движений, необходимых для управления ИМК. Материалы и методы. Для получения данных была сформирована группа из 30 добровольцев обоих полов в возрасте от 17 до 23 лет. Участники эксперимента должны были выполнить четыре команды и повторить их в неизвестном для них порядке, заданном программой. Эксперимент проводился двумя способами: физически и мысленно. То есть при первом способе каждая команда соответствовала определенному движению человека, при втором те же команды выполнялись воображаемо, движение представлялось мысленно. Команда считалась успешно исполненной, если добровольцу удавалось повторить и удержать заданное программой положение в течение 2 с. Анализ результатов проводился для пяти частотных диапазонов: 7–10 Гц, 9–12 Гц, 12–15 Гц, 15–20 Гц, 20–25 Гц. Результаты. Сгенерированные электроэнцефалографические показатели обрабатывались методом корреляционного анализа и методами разведочной статистики, такими как анализ соответствий и кластерный анализ. Реально выполняемые движения испытуемых связаны с высоким количеством низкочастотных модуляций в диапазоне 12–20 Гц при отсутствии модулирующих влияний в диапазоне ниже 12 Гц. Для случаев невыполнения команд характерны выраженные паттерны высокочастотной модуляции. Выводы. Результаты корреляционного анализа демонстрируют положительную связь между числом случаев высокочастотной модуляции в диапазоне 9–12 Гц с числом случаев низкочастотной модуляции во всех других исследуемых диапазонах сигнала в случае успешного выполнения команд. Ключевые слова: интерфейс «мозг – компьютер», μ-ритм, частотная модуляция, ЭЭГ.

Characterizing speech rhythm using spectral coherence between jaw displacement and speech temporal envelope

Lower modulation rates in the temporal envelope (ENV) of the acoustic signal are believed to be the rhythmic backbone in speech, facilitating speech comprehension in terms of neuronal entrainments at δ- and θ-rates (these rates are comparable to the foot- and syllable-rates phonetically). The jaw plays the role of a carrier articulator regulating mouth opening in a quasi-cyclical way, which correspond to the low-frequency modulations as a physical consequence. This paper describes a method to examine the joint roles of jaw oscillation and ENV in realizing speech rhythm using spectral coherence. Relative powers in the frequency bands corresponding to the δ-and θ-oscillations in the coherence (respectively notated as %δ and %θ) were quantified as one possible way of revealing the amount of concomitant foot- and syllable-level rhythmicities carried by both acoustic and articulatory domains. Two English corpora (mngu0 and MOCHA-TIMIT) were used for the proof of concept. %δ and %θ were regressed on utterance duration for an initial analysis. Results showed that the degrees of foot- and syllable-sized rhythmicities are different and are contingent upon the utterance length.

Right-hemisphere coherence to speech at pre-reading stages predicts reading performance one year later

The hypothesis that neural entrainment to the low-frequency modulations of speech contributes significantly to reading acquisition receives increasing support in the literature. Still, no previous study has actually attempted to establish a longitudinal link between them. The present study tested Basque-speaking children twice: once before reading was formally instructed (t1; 5-6 years old) and once after they had received a full school year of reading instruction (t2; 6-7 years old). At t1, speech-brain coherence was recorded via EEG. At t2, in addition to the coherence measure, reading performance was assessed. Our results show that children with larger pre-reading delta-band (< 1 Hz) speech-brain coherence at right sites of the scalp performed better in the reading tasks one year later. Moreover, the increase in coherence from pre-reading into reading stages tended to correlate negatively with reading outcome. The latter result, though statistically weak, suggests that reading instruction might lead to the recruitment of less delta tracking resources. Overall, our results provide preliminary support for a relevant contribution of right-hemisphere speech-brain coherence to successful reading development and point towards pre-reading neural coherence indexes as useful tools for the early detection of developmental reading disorders.

Hemispheric and Sex Differences in Mustached Bat Primary Auditory Cortex Revealed by Neural Responses to Slow Frequency Modulations

The mustached bat (Pteronotus parnellii) is a mammalian model of cortical hemispheric asymmetry. In this species, complex social vocalizations are processed preferentially in the left Doppler-shifted constant frequency (DSCF) subregion of primary auditory cortex. Like hemispheric specializations for speech and music, this bat brain asymmetry differs between sexes (i.e., males>females) and is linked to spectrotemporal processing based on selectivities to frequency modulations (FMs) with rapid rates (>0.5 kHz/ms). Analyzing responses to the long-duration (>10 ms), slow-rate (<0.5 kHz/ms) FMs to which most DSCF neurons respond may reveal additional neural substrates underlying this asymmetry. Here, we bilaterally recorded responses from 176 DSCF neurons in male and female bats that were elicited by upward and downward FMs fixed at 0.04 kHz/ms and presented at 0–90 dB SPL. In females, we found inter-hemispheric latency differences consistent with applying different temporal windows to precisely integrate spectrotemporal information. In males, we found a substrate for asymmetry less related to spectrotemporal processing than to acoustic energy (i.e., amplitude). These results suggest that in the DSCF area, (1) hemispheric differences in spectrotemporal processing manifest differently between sexes, and (2) cortical asymmetry for social communication is driven by spectrotemporal processing differences and neural selectivities for amplitude.

Holo-Hilbert Spectral-based Removal of Gamma-Band Noise from Simultaneous EEG-fMRI Recordings

Simultaneous EEG-fMRI is a growing and promising field, as it has great potential to further our understanding of the spatiotemporal dynamics of brain function in health and disease. In particular, there is much interest in understanding the fMRI correlates of brain activity in the gamma band (30–100 Hz), as these frequencies are thought to be associated with cognitive processes involving perception, attention and memory, as well as with disorders such as schizophrenia and autism. However, progress in this area has been limited due to the MR-induced artifacts in EEG recordings, which seem to be more problematic for gamma frequencies. This paper presents a method of MR-induced noise removal from the gamma band of EEG that is based on Holo-Hilbert spectral analysis (HHSA), but with a new implementation strategy. HHSA uses a nested empirical mode decomposition (EMD) to identify amplitude and frequency modulations (AM and FM, respectively). Instead of including all FM components, our method examines only gamma-band FM and AM components, removes components with very low power based on the power-instantaneous frequency spectrum, and subsequently reconstructs the denoised gamma-band signal from the remaining components. Simulations demonstrate that our proposed method effectively reduces artifacts while preserving the original signal.

Dissociable Cortical and Subcortical Mechanisms for Mediating the Influences of Visual Cues on Microsaccadic Eye Movements

Visual selection in primates is intricately linked to eye movements, which are generated by a network of cortical and subcortical neural circuits. When visual selection is performed covertly, without foveating eye movements toward the selected targets, a class of fixational eye movements, called microsaccades, is still involved. Microsaccades are small saccades that occur when maintaining precise gaze fixation on a stationary point, and they exhibit robust modulations in peripheral cueing paradigms used to investigate covert visual selection mechanisms. These modulations consist of changes in both microsaccade directions and frequencies after cue onsets. Over the past two decades, the properties and functional implications of these modulations have been heavily studied, revealing a potentially important role for microsaccades in mediating covert visual selection effects. However, the neural mechanisms underlying cueing effects on microsaccades are only beginning to be investigated. Here we review the available causal manipulation evidence for these effects’ cortical and subcortical substrates. In the superior colliculus (SC), activity representing peripheral visual cues strongly influences microsaccade direction, but not frequency, modulations. In the cortical frontal eye fields (FEF), activity only compensates for early reflexive effects of cues on microsaccades. Using evidence from behavior, theoretical modeling, and preliminary lesion data from the primary visual cortex and microstimulation data from the lower brainstem, we argue that the early reflexive microsaccade effects arise subcortically, downstream of the SC. Overall, studying cueing effects on microsaccades in primates represents an important opportunity to link perception, cognition, and action through unaddressed cortical-subcortical neural interactions. These interactions are also likely relevant in other sensory and motor modalities during other active behaviors.

Modelling of Amplitude Modulated Vocal Fry Glottal Area Waveforms Using an Analysis-by-Synthesis Approach

The characterization of voice quality is important for the diagnosis of a voice disorder. Vocal fry is a voice quality which is traditionally characterized by a low frequency and a long closed phase of the glottis. However, we also observed amplitude modulated vocal fry glottal area waveforms (GAWs) without long closed phases (positive group) which we modelled using an analysis-by-synthesis approach. Natural and synthetic GAWs are modelled. The negative group consists of euphonic, i.e., normophonic GAWs. The analysis-by-synthesis approach fits two modelled GAWs for each of the input GAW. One modelled GAW is modulated to replicate the amplitude and frequency modulations of the input GAW and the other modelled GAW is unmodulated. The modelling errors of the two modelled GAWs are determined to classify the GAWs into the positive and the negative groups using a simple support vector machine (SVM) classifier with a linear kernel. The modelling errors of all vocal fry GAWs obtained using the modulating model are smaller than the modelling errors obtained using the unmodulated model. Using the two modelling errors as predictors for classification, no false positives or false negatives are obtained. To further distinguish the subtypes of amplitude modulated vocal fry GAWs, the entropy of the modulator’s power spectral density and the modulator-to-carrier frequency ratio are obtained.

The Relationship between Weekly Periodicity and COVID-19 Progression

COVID-19 is extraordinary both as once-in-a-lifetime pandemic and having abundant real-time case data, thus providing an extraordinary opportunity for timely independent analysis and novel perspectives. We investigate the weekly periodicity in the daily reported new cases and new deaths with the implied relationships to the societal and institutional responses using autocorrelation and Fourier transformation. The results show significant linear correlations between the weekly periodicity and the total cases and deaths, ranging from 50% to 84% for sizable groups of countries with population normalized deaths spanning nearly three orders of magnitude, from a few to approaching a thousand per million. In particular, the Strength Indicator of the periodicity in the new cases, defined by the autocorrelation with a 7-day lag, is positively correlated strongly to the total deaths per million in respective countries. The Persistence Indicator of the periodicity, defined as the average of three autocorrelations with 7-, 14- and 21-day lags, is an overall better indicator of the progression of the pandemic. For longer time series, Fourier transformation gives similar results. This analysis begins to fill the gap in modeling and simulation of epidemics with the inclusion of high frequency modulations, in this case most likely from human behaviors and institutional practices, and reveals that they can be highly correlated to the magnitude and duration of the pandemic. The results show that there is significant need to understand the causes and effects of the periodicity and its relationship to the progression and outcome of the pandemic, and how we could adapt our strategies and implementations to reduce the extent of the impact of COVID-19.

Micro-Doppler-Based Space Target Recognition with a One-Dimensional Parallel Network

Space target identification is key to missile defense. Micromotion, as an inherent attribute of the target, can be used as the theoretical basis for target recognition. Meanwhile, time-varying micro-Doppler (m-D) frequency shifts induce frequency modulations on the target echo, which can be referred to as the m-D effect. m-D features are widely used in space target recognition as it can reflect the physical attributes of the space targets. However, the traditional recognition method requires human participation, which often leads to misjudgment. In this paper, an intelligent recognition method for space target micromotion is proposed. First, accurate and suitable models of warhead and decoy are derived, and then the m-D formulae are offered. Moreover, we present a deep-learning (DL) model composed of a one-dimensional parallel structure and long short-term memory (LSTM). Then, we utilize this DL model to recognize time-frequency distribution (TFD) of different targets. Finally, simulations are performed to validate the effectiveness of the proposed method.

Seismic and hydroacoustic observations from recent underwater events in the South Atlantic Ocean

SUMMARY To study the location and characterize two underwater events in the South Atlantic Ocean, we analyse both seismic and hydroacoustic signals. The first event (2017 November 15) occurred around 550 km east of Argentina, near the last reported position of the Argentine Navy submarine the ARA San Juan, the seafloor wreck of which was found one year later. The second event (2017 December 1) was due to an aircraft-dropped depth charge, detonated as part of the search for the ARA San Juan. We use signal arrival times and azimuths recorded at two seismic and two hydroacoustic stations to estimate epicentres for both events; our estimates were within 10 km of the ground-truth locations. We used geophysical models and databases to determine the sound-speed structure of the water and the presence of sea-ice to help interpret differences in the frequency content and dispersion of signals at the two hydrophone stations. Hydrophone signals for the 2017 November 15 event contain significant energy at high frequencies, which is inconsistent with an earthquake source. Hydrophone signals for the 2017 December 1 event show frequency modulations consistent with those expected from the known depth and explosive energy. Hydrophone signals from the 2017 November 15 event also show frequency modulations, though differences between these for the two events suggest differences in the details of the source mechanisms. Using estimates of the local seismic magnitudes, the peak pressures recorded on the hydrophones, and the known charge weight for the 2017 December 1 event, we estimate that the 2017 November 15 event had an acoustic energy release equivalent to around 428 kg of trinitrotoluene. This analysis demonstrates the importance of high-precision traveltime predictions from models of seismic and ocean acoustic velocities when analysing low-magnitude underwater events.