scholarly journals Including measures of high gamma power can improve the decoding of natural speech from EEG

2019 ◽  
Author(s):  
Shyanthony R. Synigal ◽  
Emily S. Teoh ◽  
Edmund C. Lalor
Keyword(s):  
Brain Imaging ◽  
Neural Activity ◽  
Speech Processing ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Natural Speech ◽  
Low Frequencies ◽  
High Gamma ◽  
Gamma Power ◽  
Speech Tracking

ABSTRACTThe human auditory system is adept at extracting information from speech in both single-speaker and multi-speaker situations. This involves neural processing at the rapid temporal scales seen in natural speech. Non-invasive brain imaging (electro-/magnetoencephalography [EEG/MEG]) signatures of such processing have shown that the phase of neural activity below 16 Hz tracks the dynamics of speech, whereas invasive brain imaging (electrocorticography [ECoG]) has shown that such rapid processing is even more strongly reflected in the power of neural activity at high frequencies (around 70-150 Hz; known as high gamma). The aim of this study was to determine if high gamma power in scalp recorded EEG carries useful stimulus-related information, despite its reputation for having a poor signal to noise ratio. Furthermore, we aimed to assess whether any such information might be complementary to that reflected in well-established low frequency EEG indices of speech processing. We used linear regression to investigate speech envelope and attention decoding in EEG at low frequencies, in high gamma power, and in both signals combined. While low frequency speech tracking was evident for almost all subjects as expected, high gamma power also showed robust speech tracking in a minority of subjects. This same pattern was true for attention decoding using a separate group of subjects who undertook a cocktail party attention experiment. For the subjects who showed speech tracking in high gamma power, the spatiotemporal characteristics of that high gamma tracking differed from that of low-frequency EEG. Furthermore, combining the two neural measures led to improved measures of speech tracking for several subjects. Overall, this indicates that high gamma power EEG can carry useful information regarding speech processing and attentional selection in some subjects and combining it with low frequency EEG can improve the mapping between natural speech and the resulting neural responses.

scholarly journals General auditory and speech-specific contributions to cortical envelope tracking revealed using auditory chimeras

2020 ◽  
Author(s):  
Kevin D. Prinsloo ◽  
Edmund C. Lalor
Keyword(s):  
Auditory Cortex ◽  
Speech Processing ◽  
Low Frequency ◽  
Communication Disorders ◽  
Speech Stimulus ◽  
Natural Speech ◽  
Amplitude Envelope ◽  
Envelope Tracking ◽  
Acoustic Processing ◽  
Speech Tracking

AbstractIn recent years research on natural speech processing has benefited from recognizing that low frequency cortical activity tracks the amplitude envelope of natural speech. However, it remains unclear to what extent this tracking reflects speech-specific processing beyond the analysis of the stimulus acoustics. In the present study, we aimed to disentangle contributions to cortical envelope tracking that reflect general acoustic processing from those that are functionally related to processing speech. To do so, we recorded EEG from subjects as they listened to “auditory chimeras” – stimuli comprised of the temporal fine structure (TFS) of one speech stimulus modulated by the amplitude envelope (ENV) of another speech stimulus. By varying the number of frequency bands used in making the chimeras, we obtained some control over which speech stimulus was recognized by the listener. No matter which stimulus was recognized, envelope tracking was always strongest for the ENV stimulus, indicating a dominant contribution from acoustic processing. However, there was also a positive relationship between intelligibility and the tracking of the perceived speech, indicating a contribution from speech specific processing. These findings were supported by a follow-up analysis that assessed envelope tracking as a function of the (estimated) output of the cochlea rather than the original stimuli used in creating the chimeras. Finally, we sought to isolate the speech-specific contribution to envelope tracking using forward encoding models and found that indices of phonetic feature processing tracked reliably with intelligibility. Together these results show that cortical speech tracking is dominated by acoustic processing, but also reflects speech-specific processing.This work was supported by a Career Development Award from Science Foundation Ireland (CDA/15/3316) and a grant from the National Institute on Deafness and Other Communication Disorders (DC016297). The authors thank Dr. Aaron Nidiffer, Dr. Aisling O’Sullivan, Thomas Stoll and Lauren Szymula for assistance with data collection, and Dr. Nathaniel Zuk, Dr. Aaron Nidiffer, Dr. Aisling O’Sullivan for helpful comments on this manuscript.Significance StatementActivity in auditory cortex is known to dynamically track the energy fluctuations, or amplitude envelope, of speech. Measures of this tracking are now widely used in research on hearing and language and have had a substantial influence on theories of how auditory cortex parses and processes speech. But, how much of this speech tracking is actually driven by speech-specific processing rather than general acoustic processing is unclear, limiting its interpretability and its usefulness. Here, by merging two speech stimuli together to form so-called auditory chimeras, we show that EEG tracking of the speech envelope is dominated by acoustic processing, but also reflects linguistic analysis. This has important implications for theories of cortical speech tracking and for using measures of that tracking in applied research.

scholarly journals Sequences of Intonation Units form a ~ 1 Hz rhythm

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Maya Inbar ◽  
Eitan Grossman ◽  
Ayelet N. Landau
Keyword(s):  
Speech Processing ◽  
Temporal Structure ◽  
Low Frequency ◽  
Neural System ◽  
Specific Pattern ◽  
Physiological Data ◽  
Low Frequencies ◽  
Speech Stimuli ◽  
Intonation Units ◽  
Speech Envelope

Abstract Studies of speech processing investigate the relationship between temporal structure in speech stimuli and neural activity. Despite clear evidence that the brain tracks speech at low frequencies (~ 1 Hz), it is not well understood what linguistic information gives rise to this rhythm. In this study, we harness linguistic theory to draw attention to Intonation Units (IUs), a fundamental prosodic unit of human language, and characterize their temporal structure as captured in the speech envelope, an acoustic representation relevant to the neural processing of speech. IUs are defined by a specific pattern of syllable delivery, together with resets in pitch and articulatory force. Linguistic studies of spontaneous speech indicate that this prosodic segmentation paces new information in language use across diverse languages. Therefore, IUs provide a universal structural cue for the cognitive dynamics of speech production and comprehension. We study the relation between IUs and periodicities in the speech envelope, applying methods from investigations of neural synchronization. Our sample includes recordings from every-day speech contexts of over 100 speakers and six languages. We find that sequences of IUs form a consistent low-frequency rhythm and constitute a significant periodic cue within the speech envelope. Our findings allow to predict that IUs are utilized by the neural system when tracking speech. The methods we introduce here facilitate testing this prediction in the future (i.e., with physiological data).

scholarly journals Deep learning for low-frequency extrapolation from multioffset seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. R989-R1001 ◽  
Author(s):  
Oleg Ovcharenko ◽  
Vladimir Kazei ◽  
Mahesh Kalita ◽  
Daniel Peter ◽  
Tariq Alkhalifah
Keyword(s):  
Deep Learning ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Low Frequencies ◽  
Seismic Surveys ◽  
Full Waveform ◽  
Frequency Components ◽  
Marine Seismic

Low-frequency seismic data are crucial for convergence of full-waveform inversion (FWI) to reliable subsurface properties. However, it is challenging to acquire field data with an appropriate signal-to-noise ratio in the low-frequency part of the spectrum. We have extrapolated low-frequency data from the respective higher frequency components of the seismic wavefield by using deep learning. Through wavenumber analysis, we find that extrapolation per shot gather has broader applicability than per-trace extrapolation. We numerically simulate marine seismic surveys for random subsurface models and train a deep convolutional neural network to derive a mapping between high and low frequencies. The trained network is then tested on sections from the BP and SEAM Phase I benchmark models. Our results indicate that we are able to recover 0.25 Hz data from the 2 to 4.5 Hz frequencies. We also determine that the extrapolated data are accurate enough for FWI application.

Interpretation of full-azimuth broadband land data from Saudi Arabia and implications for improved inversion, reservoir characterization, and exploration

2013 ◽  
Vol 1 (2) ◽  
pp. T167-T176 ◽  
Author(s):  
Brian P. Wallick ◽  
Luis Giroldi
Keyword(s):  
Saudi Arabia ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Gas Field ◽  
Frequency Model ◽  
Low Frequencies ◽  
Limited Bandwidth

Interpretation of conventional land seismic data over a Permian-age gas field in Eastern Saudi Arabia has proven difficult over time due to low signal-to-noise ratio and limited bandwidth in the seismic volume. In an effort to improve the signal and broaden the bandwidth, newly acquired seismic data over this field have employed point receiver technology, dense wavefield sampling, a full azimuth geometry, and a specially designed sweep with useful frequencies as low as three hertz. The resulting data display enhanced reflection continuity and improved resolution. With the extension of low frequencies and improved interpretability, acoustic impedance inversion results are more robust and allow greater flexibility in reservoir characterization and prediction. In addition, because inversion to acoustic impedance is no longer completely tied to a wells-only low-frequency model, there are positive implications for exploration.

Low Frequency NQR using Double Contact Cross-relaxation

2000 ◽  
Vol 55 (1-2) ◽  
pp. 37-40
Author(s):  
David Stephenson ◽  
John A. S. Smith
Keyword(s):  
Ammonium Sulphate ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Cross Relaxation ◽  
Relaxation Technique ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Line Shapes ◽  
Ammonium Dichromate ◽  
Noise Ratio

A cross-relaxation technique is described which involves two spin contacts per double reso-nance cycle. The result is an improvement in signal to noise ratio particularly at low frequencies. Experimental spectra and analyses are presented: 14N in ammonium sulphate showing that the tech-nique gives essentially the same information as previous studies; 14N in ammonium dichromate determining e2Qq/h as (76±3) kHz and η = 0.84±.04; 7Li in lithium acetylacetonate for which the spectrum (corrected for Zeeman distortion) yields e2Qq/h = (152 ±5) kHz and η=.5 ±.2. Calculated spectra are presented to demonstrate the η dependence of the line shapes for 7Li.

scholarly journals Intraoperative mapping of executive function using electrocorticography for patients with low-grade gliomas

2020 ◽  
Author(s):  
Yaara Erez ◽  
Moataz Assem ◽  
Pedro Coelho ◽  
Rafael Romero-Garcia ◽  
Mallory Owen ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Executive Function ◽  
Executive Functions ◽  
Neural Activity ◽  
Task Difficulty ◽  
Awake Surgery ◽  
Low Grade ◽  
Direct Electrical Stimulation ◽  
High Gamma ◽  
Gamma Power

Abstract Background Intraoperative functional mapping with direct electrical stimulation during awake surgery for patients with diffuse low-grade glioma has been used in recent years to optimize the balance between surgical resection and quality of life following surgery. Mapping of executive functions is particularly challenging because of their complex nature, with only a handful of reports published so far. Here, we propose the recording of neural activity directly from the surface of the brain using electrocorticography to map executive functions and demonstrate its feasibility and potential utility. Methods To track a neural signature of executive function, we recorded neural activity using electrocorticography during awake surgery from the frontal cortex of three patients judged to have an appearance of diffuse low-grade glioma. Based on existing functional magnetic resonance imaging (fMRI) evidence from healthy participants for the recruitment of areas associated with executive function with increased task demands, we employed a task difficulty manipulation in two counting tasks performed intraoperatively. Following surgery, the data were extracted and analyzed offline to identify increases in broadband high-gamma power with increased task difficulty, equivalent to fMRI findings, as a signature of activity related to executive function. Results All three patients performed the tasks well. Data were recorded from five electrode strips, resulting in data from 15 channels overall. Eleven out of the 15 channels (73.3%) showed significant increases in high-gamma power with increased task difficulty, 26.6% of the channels (4/15) showed no change in power, and none of the channels showed power decrease. High-gamma power increases with increased task difficulty were more likely in areas that are within the canonical frontoparietal network template. Conclusions These results are the first step toward developing electrocorticography as a tool for mapping of executive function complementarily to direct electrical stimulation to guide resection. Further studies are required to establish this approach for clinical use.

scholarly journals Including Measures of High Gamma Power Can Improve the Decoding of Natural Speech From EEG

2020 ◽  
Vol 14 ◽  
Author(s):  
Shyanthony R. Synigal ◽  
Emily S. Teoh ◽  
Edmund C. Lalor
Keyword(s):  
Natural Speech ◽  
High Gamma ◽  
Gamma Power

scholarly journals The effect of the ionosphere on ultra-low-frequency radio-interferometric observations

2018 ◽  
Vol 615 ◽  
pp. A179 ◽  
Author(s):  
F. de Gasperin ◽  
M. Mevius ◽  
D. A. Rafferty ◽  
H. T. Intema ◽  
R. A. Fallows
Keyword(s):  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Systematic Errors ◽  
Electron Content ◽  
Satellite Measurements ◽  
Third Order ◽  
Low Frequencies ◽  
Total Electron ◽  
Main Driver ◽  
Systematic Effects

Context. The ionosphere is the main driver of a series of systematic effects that limit our ability to explore the low-frequency (<1 GHz) sky with radio interferometers. Its effects become increasingly important towards lower frequencies and are particularly hard to calibrate in the low signal-to-noise ratio (S/N) regime in which low-frequency telescopes operate. Aims. In this paper we characterise and quantify the effect of ionospheric-induced systematic errors on astronomical interferometric radio observations at ultra-low frequencies (<100 MHz). We also provide guidelines for observations and data reduction at these frequencies with the LOw Frequency ARray (LOFAR) and future instruments such as the Square Kilometre Array (SKA). Methods. We derive the expected systematic error induced by the ionosphere. We compare our predictions with data from the Low Band Antenna (LBA) system of LOFAR. Results. We show that we can isolate the ionospheric effect in LOFAR LBA data and that our results are compatible with satellite measurements, providing an independent way to measure the ionospheric total electron content (TEC). We show how the ionosphere also corrupts the correlated amplitudes through scintillations. We report values of the ionospheric structure function in line with the literature. Conclusions. The systematic errors on the phases of LOFAR LBA data can be accurately modelled as a sum of four effects (clock, ionosphere first, second, and third order). This greatly reduces the number of required calibration parameters, and therefore enables new efficient calibration strategies.

scholarly journals Intraoperative mapping of executive function using electrocorticography for patients with low-grade gliomas

2020 ◽  
Author(s):  
Yaara Erez ◽  
Moataz Assem ◽  
Pedro Coelho ◽  
Rafael Romero-Garcia ◽  
Mallory Owen ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Executive Function ◽  
Executive Functions ◽  
Neural Activity ◽  
Task Difficulty ◽  
Awake Surgery ◽  
Low Grade ◽  
Direct Electrical Stimulation ◽  
High Gamma ◽  
Gamma Power

Background: Intraoperative functional mapping with direct electrical stimulation during awake surgery for patients with diffuse low-grade glioma has been used in recent years to optimize the balance between surgical resection and quality of life following surgery. Mapping of executive functions is particularly challenging because their complex nature, with only a handful of reports so far. Here, we propose recording of neural activity directly from the surface of the brain using electrocorticography to map executive functions and demonstrate its feasibility and potential utility.Methods: To track a neural signature of executive function, we recorded neural activity using electrocorticography during awake surgery from the frontal cortex of three patients judged to have an appearance of diffuse low-grade glioma. Based on existing functional magnetic resonance imaging (fMRI) evidence from healthy participants for the recruitment of areas associated with executive function with increased task demands, we employed a task difficulty manipulation in two counting tasks performed intraoperatively. Following surgery, the data were extracted and analyzed offline to identify increases in broadband high-gamma power with increased task difficulty, equivalent to fMRI findings, as a signature of activity related to executive function.Results: All three patients performed the tasks well. Data were recorded from five electrode strips, resulting in data from 15 channels overall. 73.3% of the channels (11/15) showed significant increases in high-gamma power with increased task difficulty, 26.6% channels (4/15) showed no change in power, and none of the channels showed power decrease. High-gamma power increases with increased task difficulty were more likely in areas that are within the canonical frontoparietal network template.Conclusions: These results are the first step towards developing electrocorticography as a tool for mapping of executive function complementarily to direct electrical stimulation to guide resection. Further studies and clinical trials are required to establish this approach for clinical use.

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