scholarly journals Time-frequency analysis methods and their application in developmental EEG data

2021 ◽  
Author(s):  
Santiago Morales ◽  
Maureen Bowers
Keyword(s):  
Brain Activity ◽  
Event Related Potentials ◽  
Phase Lag ◽  
Phase Synchrony ◽  
Time Frequency ◽  
Use Of Time ◽  
Eeg Data ◽  
Related Potentials ◽  
Neurophysiological Mechanisms ◽  
The Fourier Transform

EEG provides a rich measure of brain activity that can be characterized as neuronal oscillations. However, most developmental EEG work to date has focused on analyzing EEG data as Event-Related Potentials (ERPs) or power based on the Fourier transform. While these measures have been productive, they do not leverage all the information contained within the EEG signal. Namely, ERP analyses ignore non-phase-locked signals and Fourier-based power analyses ignore temporal information. Time-frequency analyses can better characterize the oscillations contained in the EEG data. By separating power and phase information across different frequencies, time-frequency measures provide a closer interpretation of the neurophysiological mechanisms, facilitate translation across neurophysiology disciplines, and capture processes not observed by ERP or Fourier-based analyses (e.g., connectivity). Despite their unique contributions, a literature review of this journal reveals that time-frequency analyses of EEG are yet to be embraced by the developmental cognitive neuroscience field. This manuscript presents a conceptual introduction to time-frequency analyses for developmental researchers. To facilitate the use of time-frequency analyses, we include a tutorial of accessible scripts, based on Cohen (2014), to calculate time-frequency power (signal strength), inter-trial phase synchrony (signal consistency), and two types of phase-based connectivity (inter-channel phase synchrony and weighted phase lag index).

Intramodal and crossmodal refractory effects: Evidence from oscillatory brain activity

2012 ◽  
Vol 25 (0) ◽  
pp. 192
Author(s):  
Davide Bottari ◽  
Sophie Rohlf ◽  
Marlene Hense ◽  
Boukje Habets ◽  
Brigitte Roeder
Keyword(s):  
Brain Activity ◽  
Event Related Potentials ◽  
Random Order ◽  
Oddball Paradigm ◽  
Brain Response ◽  
Time Frequency ◽  
Tactile Stimuli ◽  
Related Potentials ◽  
Oscillatory Brain Activity ◽  
Auditory Cortices

Event-related potentials (ERP) to the second stimulus of a pair are known to be reduced in amplitude. The magnitude of this ‘refractoriness’ is modulated by both the interstimulus interval and the similarity between the two stimuli. Intramodal refractoriness is interpreted as an index of a temporary decrement in neural responsiveness. So, cross-modal refractoriness might be an indicator of shared neural generators between modalities. We analysed oscillatory neuronal activity while participants were engaged in an oddball paradigm with auditory (4000 Hz, 50 ms-long, 90 db, bilateral) and tactile stimuli (50 ms-long, 125 Hz-vibrations, index fingers) presented in a random order with an ISI of either 1000 or 2000 ms. Participants were required to detect rare tactile (middle fingers) and auditory deviants (600 Hz). A time–frequency analysis of the brain response to the second stimulus of each pair (T-T, A-A, T-A and A-T) contrasting Short and Long ISIs revealed a reduced refractory effect after Long ISI with respect to Short ISI, in all pairs (both intramodal and cross-modal). This emerged as a broadly distributed increase of evoked theta activity (3–7 Hz, 100–500 ms). Only in intramodal tactile pairs and cross-modal tactile-auditory pairs we also observed that Long ISI with respect to Short ISI determined a decrease of induced alpha (8–12 Hz, 200–700 ms), a typical sign of enhanced neural excitability and thus decreased refractoriness. These data suggest that somatosensory and auditory cortices display different neural markers of refractoriness and that the auditory cortex might have a stronger low level degree of influence on the tactile cortex than vice-versa.

Different Frequency Bands of Electromagnetic Wave on Age-Related Developmental Changes

2013 ◽  
Vol 479-480 ◽  
pp. 480-485
Author(s):  
Ming Chung Ho ◽  
Chin Fei Huang ◽  
Chia Yi Chou ◽  
Ming Chi Lu ◽  
Chen Hsieh ◽  
...  
Keyword(s):  
Spectral Power ◽  
Brain Activity ◽  
Phase Locking ◽  
Age Groups ◽  
Event Related Potentials ◽  
Brain Dynamics ◽  
Alpha Power ◽  
Time Frequency ◽  
Age Related ◽  
Related Potentials

Brain dynamics is an important issue in understanding child development. However, very little research of the event-related responses has been used to explore changes during childhood. The aim of this study was to investigate mature changes in spatiotemporal organization of brain dynamics. We hypothesized that oscillatory event-related brain activity were affected by age-related changes. The sample include three age groups, namely 7 years (N = 18), 11 years (N = 18), and adults (N = 18). The event-related spectral power (ERPSP), and inter-trial phase locking (ITPL) of the event-related potentials (ERPs) were obtained from the time-frequency analysis of the auditory oddball task. Results revealed that: (a) decreased theta power, but alpha power increased with age; (b) the values of ITPL in the theta and alpha bands increased with age. These suggest that ERPSP, and ITPL provide useful indicators of cognitive maturation processes in children aged 7 and 11 years.

scholarly journals Real-time audio processing of real-life soundscapes for EEG analysis: ERPs based on natural sound onsets

2021 ◽  
Author(s):  
Daniel Hölle ◽  
Sarah Blum ◽  
Sven Kissner ◽  
Stefan Debener ◽  
Martin Georg Bleichner
Keyword(s):  
Auditory Processing ◽  
Brain Activity ◽  
Real Life ◽  
Event Related Potentials ◽  
Information Need ◽  
Sound Perception ◽  
Temporal Precision ◽  
Audio Features ◽  
Eeg Data ◽  
Related Potentials

With smartphone-based mobile electroencephalography (EEG), we can investigate sound perception beyond the lab. To understand sound perception in the real world, we need to relate naturally occurring sounds to EEG data. For this, EEG and audio information need to be synchronized precisely, only then it is possible to capture fast and transient evoked neural responses and relate them to individual sounds. We have developed Android applications (AFEx and Record-a) that allow for the concurrent acquisition of EEG data and audio features, i.e., sound onsets, average signal power (RMS) and power spectral density (PSD) on smartphone. In this paper, we evaluate these apps by computing event-related potentials (ERPs) evoked by everyday sounds. One participant listened to piano notes (played live by a pianist) and to a home-office soundscape. Timing tests showed that the temporal precision of the system is very good. We calculated ERPs to sound onsets and observed the typical P1-N1-P2 complex of auditory processing. Furthermore, we show how to relate information on loudness (RMS) and spectra (PSD) to brain activity. In future studies, we can use this system to study sound processing in everyday life.

scholarly journals Human Neocortical Neurosolver (HNN): A new software tool for interpreting the cellular and network origin of human MEG/EEG data

2019 ◽  
Author(s):  
Samuel A Neymotin ◽  
Dylan S Daniels ◽  
Blake Caldwell ◽  
Robert A McDougal ◽  
Nicholas T Carnevale ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Software Tool ◽  
Translational Neuroscience ◽  
Electrical Currents ◽  
Disease States ◽  
Neuroscience Research ◽  
Eeg Data ◽  
Related Potentials

AbstractMagneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN’s core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal’s origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN’s ability to associate signals across scales makes it a unique tool for translational neuroscience research.

scholarly journals Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Samuel A Neymotin ◽  
Dylan S Daniels ◽  
Blake Caldwell ◽  
Robert A McDougal ◽  
Nicholas T Carnevale ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Software Tool ◽  
Translational Neuroscience ◽  
Electrical Currents ◽  
Disease States ◽  
Neuroscience Research ◽  
Eeg Data ◽  
Related Potentials

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN’s core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal’s origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN’s ability to associate signals across scales makes it a unique tool for translational neuroscience research.

scholarly journals Energy Distribution Evaluation Using Renyi Entropy Measures With Application in EEG Data Analysis

2021 ◽  
Vol 17 ◽  
pp. 99-107
Author(s):  
Theodor D. Popescu
Keyword(s):  
Energy Distribution ◽  
Medical Diagnosis ◽  
Event Related Potentials ◽  
Eeg Signals ◽  
Time Frequency ◽  
Eeg Data ◽  
Entropy Measures ◽  
Related Potentials ◽  
The Subject ◽  
Eeg Recordings

The ”corrected” EEG recordings, after artifact removing, may be the subject of further investigations, for example segmentation and energy distribution, resulting new informa- tion to be used for feature extraction, of great help for medical diagnosis. The paper presents a generally method for energy distribution evalua- tion using measures of R´enyi entropy. The pre- sented approach ensures the possibility of quan- titative analysis of the information contained in time-frequency distribution of EEG signals. The proposed procedure is applied with good results in the analysis of a sample lowpass event-related potentials (ERP) data, collected from 13 scalp and 1 EOG electrodes.

scholarly journals Eliciting and Recording Event Related Potentials (ERPs) in Behaviourally Unresponsive Populations: A Retrospective Commentary on Critical Factors

2021 ◽  
Vol 11 (7) ◽  
pp. 835
Author(s):  
Alexander Rokos ◽  
Richard Mah ◽  
Rober Boshra ◽  
Amabilis Harrison ◽  
Tsee Leng Choy ◽  
...  
Keyword(s):  
Event Related Potentials ◽  
Stimulus Presentation ◽  
Event Related Potential ◽  
Critical Factors ◽  
Healthy Elderly ◽  
States Of Consciousness ◽  
Long Latency ◽  
Eeg Data ◽  
Related Potentials ◽  
The Relationship

A consistent limitation when designing event-related potential paradigms and interpreting results is a lack of consideration of the multivariate factors that affect their elicitation and detection in behaviorally unresponsive individuals. This paper provides a retrospective commentary on three factors that influence the presence and morphology of long-latency event-related potentials—the P3b and N400. We analyze event-related potentials derived from electroencephalographic (EEG) data collected from small groups of healthy youth and healthy elderly to illustrate the effect of paradigm strength and subject age; we analyze ERPs collected from an individual with severe traumatic brain injury to illustrate the effect of stimulus presentation speed. Based on these critical factors, we support that: (1) the strongest paradigms should be used to elicit event-related potentials in unresponsive populations; (2) interpretation of event-related potential results should account for participant age; and (3) speed of stimulus presentation should be slower in unresponsive individuals. The application of these practices when eliciting and recording event-related potentials in unresponsive individuals will help to minimize result interpretation ambiguity, increase confidence in conclusions, and advance the understanding of the relationship between long-latency event-related potentials and states of consciousness.

scholarly journals Anytime collaborative brain–computer interfaces for enhancing perceptual group decision-making

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Davide Valeriani ◽  
Caterina Cinel ◽  
Luca Citi ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Brain Computer Interfaces ◽  
Appearance Time ◽  
Perceptual Group ◽  
Computer Interfaces ◽  
Related Potentials

AbstractIn this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

Brain Responses to World Knowledge Violations: A Comparison of Stimulus- and Fixation-triggered Event-related Potentials and Neural Oscillations

2015 ◽  
Vol 27 (5) ◽  
pp. 1017-1028 ◽  
Author(s):  
Paul Metzner ◽  
Titus von der Malsburg ◽  
Shravan Vasishth ◽  
Frank Rösler
Keyword(s):  
Word Meaning ◽  
Event Related Potentials ◽  
Visual Presentation ◽  
World Knowledge ◽  
N400 Effect ◽  
Brain Potentials ◽  
Time Frequency ◽  
Gamma Range ◽  
Brain Responses ◽  
Related Potentials

Recent research has shown that brain potentials time-locked to fixations in natural reading can be similar to brain potentials recorded during rapid serial visual presentation (RSVP). We attempted two replications of Hagoort, Hald, Bastiaansen, and Petersson [Hagoort, P., Hald, L., Bastiaansen, M., & Petersson, K. M. Integration of word meaning and world knowledge in language comprehension. Science, 304, 438–441, 2004] to determine whether this correspondence also holds for oscillatory brain responses. Hagoort et al. reported an N400 effect and synchronization in the theta and gamma range following world knowledge violations. Our first experiment (n = 32) used RSVP and replicated both the N400 effect in the ERPs and the power increase in the theta range in the time–frequency domain. In the second experiment (n = 49), participants read the same materials freely while their eye movements and their EEG were monitored. First fixation durations, gaze durations, and regression rates were increased, and the ERP showed an N400 effect. An analysis of time–frequency representations showed synchronization in the delta range (1–3 Hz) and desynchronization in the upper alpha range (11–13 Hz) but no theta or gamma effects. The results suggest that oscillatory EEG changes elicited by world knowledge violations are different in natural reading and RSVP. This may reflect differences in how representations are constructed and retrieved from memory in the two presentation modes.

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