Quantitative EEG and Cognitive Neuroscience

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 71295

Special Issue Editor


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Guest Editor
Faculty of Psychology, University of Akureyri, 600 Akureyri, Iceland
Interests: quantitative EEG; cognitive; neuroscience; memory; epilepsy; dementia; psychology; computer science; seasonal affective disorder

Special Issue Information

Dear Colleagues, 

Quantitative EEG is the most classical non-invasive method in cognitive neuroscience. It offers a cheap and well-established method to examine neural correlates of cognitive processes at the level of milliseconds. This opens the door for cognitive research as well as clinical applications that take advantage of digital signal processing for recorded brain activity.

This special issue sets the stage for researchers devoted to classical and advanced methods in quantitative EEG research in cognitive neuroscience. Methodological work as well as applied science in healthy and clinical samples  is welcome. Cognitive domains include but are not limited to memory, attention, consciousness, executive functions, motivation, sensation and perception.

After hypes on connectivity, brain computer interfaces that promise mind-reading based on artificial intelligence, and easy-to use mobile EEG systems for entertainment and gaming, critical views on replicability of EEG research in cognitive neuroscience are highly warranted to restore awareness of common methodological pitfalls and to rise the reputation of the field. Quantitative EEG combined with cognitive tasks has been introduced as a biometric modality to supplement user-authentication systems - a domain that requires reliable and replicable signals. Large sample sizes, longitudinal research with repeated EEG recordings and studies that employ robust statistical methods that were tested on EEG data can propel this field forward.

Dr. Yvonne Höller
Guest Editor

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Keywords

  • quantitative EEG
  • cognitive neuroscience
  • artificial intelligence
  • EEG reliability
  • EEG-biometrics
  • memory
  • attention
  • consciousness
  • sensation
  • perception
  • brain connectivity
  • brain networks
  • brain computer interfaces

Published Papers (20 papers)

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Editorial

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3 pages, 175 KiB  
Editorial
Quantitative EEG in Cognitive Neuroscience
by Yvonne Höller
Brain Sci. 2021, 11(4), 517; https://doi.org/10.3390/brainsci11040517 - 19 Apr 2021
Cited by 5 | Viewed by 4086
Abstract
Quantitative electroencephalography (EEG) distinguishes itself from clinical EEG by the application of mathematical approaches and computer scientific methods [...] Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)

Research

Jump to: Editorial, Review

15 pages, 11619 KiB  
Article
Emergency Braking Intention Detect System Based on K-Order Propagation Number Algorithm: A Network Perspective
by Yuhong Zhang, Yuan Liao, Yudi Zhang and Liya Huang
Brain Sci. 2021, 11(11), 1424; https://doi.org/10.3390/brainsci11111424 - 27 Oct 2021
Cited by 4 | Viewed by 1781
Abstract
In order to avoid erroneous braking responses when vehicle drivers are faced with a stressful setting, a K-order propagation number algorithm–Feature selection–Classification System (KFCS) is developed in this paper to detect emergency braking intentions in simulated driving scenarios using electroencephalography (EEG) signals. Two [...] Read more.
In order to avoid erroneous braking responses when vehicle drivers are faced with a stressful setting, a K-order propagation number algorithm–Feature selection–Classification System (KFCS) is developed in this paper to detect emergency braking intentions in simulated driving scenarios using electroencephalography (EEG) signals. Two approaches are employed in KFCS to extract EEG features and to improve classification performance: the K-Order Propagation Number Algorithm is the former, calculating the node importance from the perspective of brain networks as a novel approach; the latter uses a set of feature extraction algorithms to adjust the thresholds. Working with the data collected from seven subjects, the highest classification accuracy of a single trial can reach over 90%, with an overall accuracy of 83%. Furthermore, this paper attempts to investigate the mechanisms of brain activeness under two scenarios by using a topography technique at the sensor-data level. The results suggest that the active regions at two states is different, which leaves further exploration for future investigations. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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23 pages, 4053 KiB  
Article
Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings
by Gert Dehnen, Marcel S. Kehl, Alana Darcher, Tamara T. Müller, Jakob H. Macke, Valeri Borger, Rainer Surges and Florian Mormann
Brain Sci. 2021, 11(6), 761; https://doi.org/10.3390/brainsci11060761 - 8 Jun 2021
Cited by 4 | Viewed by 3458
Abstract
Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other [...] Read more.
Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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17 pages, 2793 KiB  
Article
Cognitive Effects of Montelukast: A Pharmaco-EEG Study
by Fabian Schwimmbeck, Wolfgang Staffen, Christopher Höhn, Fabio Rossini, Nora Renz, Markus Lobendanz, Peter Reichenpfader, Bernhard Iglseder, Ludwig Aigner, Eugen Trinka and Yvonne Höller
Brain Sci. 2021, 11(5), 547; https://doi.org/10.3390/brainsci11050547 - 27 Apr 2021
Cited by 3 | Viewed by 4516
Abstract
Montelukast is a well-established antiasthmatic drug with little side effects. It is a leukotriene receptor antagonist and recent research suggests cognitive benefits from its anti-inflammatory actions on the central nervous system. However, changes in brain activity were not directly shown so far in [...] Read more.
Montelukast is a well-established antiasthmatic drug with little side effects. It is a leukotriene receptor antagonist and recent research suggests cognitive benefits from its anti-inflammatory actions on the central nervous system. However, changes in brain activity were not directly shown so far in humans. This study aims to document changes in brain activity that are associated with cognitive improvement during treatment with Montelukast. We recorded EEG and conducted neuropsychological tests in 12 asthma-patients aged 38–73 years before and after 8 weeks of treatment with Montelukast. We found no significant changes on neuropsychological scales for memory, attention, and mood. In the EEG, we found decreased entropy at follow up during rest (p < 0.005). During episodic memory acquisition we found decreased entropy (p < 0.01) and acceleration of the background rhythm (p < 0.05). During visual attention performance, we detected an increase in gamma power (p < 0.005) and slowing of the background rhythm (p < 0.05). The study is limited by its small sample size, young age and absence of baseline cognitive impairment of the participants. Unspecific changes in brain activity were not accompanied by cognitive improvement. Future studies should examine elderly patients with cognitive impairment in a double-blind study with longer-term treatment by Montelukast. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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13 pages, 1247 KiB  
Article
Distinction of Physiologic and Epileptic Ripples: An Electrical Stimulation Study
by Jan Schönberger, Anja Knopf, Kerstin Alexandra Klotz, Matthias Dümpelmann, Andreas Schulze-Bonhage and Julia Jacobs
Brain Sci. 2021, 11(5), 538; https://doi.org/10.3390/brainsci11050538 - 24 Apr 2021
Cited by 4 | Viewed by 2411
Abstract
Ripple oscillations (80–250 Hz) are a promising biomarker of epileptic activity, but are also involved in memory consolidation, which impairs their value as a diagnostic tool. Distinguishing physiologic from epileptic ripples has been particularly challenging because usually, invasive recordings are only performed in [...] Read more.
Ripple oscillations (80–250 Hz) are a promising biomarker of epileptic activity, but are also involved in memory consolidation, which impairs their value as a diagnostic tool. Distinguishing physiologic from epileptic ripples has been particularly challenging because usually, invasive recordings are only performed in patients with refractory epilepsy. Here, we identified ‘healthy’ brain areas based on electrical stimulation and hypothesized that these regions specifically generate ‘pure’ ripples not coupled to spikes. Intracranial electroencephalography (EEG) recorded with subdural grid electrodes was retrospectively analyzed in 19 patients with drug-resistant focal epilepsy. Interictal spikes and ripples were automatically detected in slow-wave sleep using the publicly available Delphos software. We found that rates of spikes, ripples and ripples coupled to spikes (‘spike–ripples’) were higher inside the seizure-onset zone (p < 0.001). A comparison of receiver operating characteristic curves revealed that spike–ripples slightly delineated the seizure-onset zone channels, but did this significantly better than spikes (p < 0.001). Ripples were more frequent in the eloquent neocortex than in the remaining non-seizure onset zone areas (p < 0.001). This was due to the higher rates of ‘pure’ ripples (p < 0.001; median rates 3.3/min vs. 1.4/min), whereas spike–ripple rates were not significantly different (p = 0.87). ‘Pure’ ripples identified ‘healthy’ channels significantly better than chance (p < 0.001). Our findings suggest that, in contrast to epileptic spike–ripples, ‘pure’ ripples are mainly physiological. They may be considered, in addition to electrical stimulation, to delineate eloquent cortex in pre-surgical patients. Since we applied open source software for detection, our approach may be generally suited to tackle a variety of research questions in epilepsy and cognitive science. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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14 pages, 1424 KiB  
Article
Elevated and Slowed EEG Oscillations in Patients with Post-Concussive Syndrome and Chronic Pain Following a Motor Vehicle Collision
by Derrick Matthew Buchanan, Tomas Ros and Richard Nahas
Brain Sci. 2021, 11(5), 537; https://doi.org/10.3390/brainsci11050537 - 24 Apr 2021
Cited by 9 | Viewed by 3454
Abstract
(1) Background: Mild traumatic brain injury produces significant changes in neurotransmission including brain oscillations. We investigated potential quantitative electroencephalography biomarkers in 57 patients with post-concussive syndrome and chronic pain following motor vehicle collision, and 54 healthy nearly age- and sex-matched controls. (2) Methods: [...] Read more.
(1) Background: Mild traumatic brain injury produces significant changes in neurotransmission including brain oscillations. We investigated potential quantitative electroencephalography biomarkers in 57 patients with post-concussive syndrome and chronic pain following motor vehicle collision, and 54 healthy nearly age- and sex-matched controls. (2) Methods: Electroencephalography processing was completed in MATLAB, statistical modeling in SPSS, and machine learning modeling in Rapid Miner. Group differences were calculated using current-source density estimation, yielding whole-brain topographical distributions of absolute power, relative power and phase-locking functional connectivity. Groups were compared using independent sample Mann–Whitney U tests. Effect sizes and Pearson correlations were also computed. Machine learning analysis leveraged a post hoc supervised learning support vector non-probabilistic binary linear kernel classification to generate predictive models from the derived EEG signatures. (3) Results: Patients displayed significantly elevated and slowed power compared to controls: delta (p = 0.000000, r = 0.6) and theta power (p < 0.0001, r = 0.4), and relative delta power (p < 0.00001) and decreased relative alpha power (p < 0.001). Absolute delta and theta power together yielded the strongest machine learning classification accuracy (87.6%). Changes in absolute power were moderately correlated with duration and persistence of symptoms in the slow wave frequency spectrum (<15 Hz). (4) Conclusions: Distributed increases in slow wave oscillatory power are concurrent with post-concussive syndrome and chronic pain. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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13 pages, 6363 KiB  
Article
Auditory Beat Stimulation Modulates Memory-Related Single-Neuron Activity in the Human Medial Temporal Lobe
by Marlene Derner, Leila Chaieb, Gert Dehnen, Thomas P. Reber, Valeri Borger, Rainer Surges, Bernhard P. Staresina, Florian Mormann and Juergen Fell
Brain Sci. 2021, 11(3), 364; https://doi.org/10.3390/brainsci11030364 - 12 Mar 2021
Cited by 5 | Viewed by 2750
Abstract
Auditory beats are amplitude-modulated signals (monaural beats) or signals that subjectively cause the perception of an amplitude modulation (binaural beats). We investigated the effects of monaural and binaural 5 Hz beat stimulation on neural activity and memory performance in neurosurgical patients performing an [...] Read more.
Auditory beats are amplitude-modulated signals (monaural beats) or signals that subjectively cause the perception of an amplitude modulation (binaural beats). We investigated the effects of monaural and binaural 5 Hz beat stimulation on neural activity and memory performance in neurosurgical patients performing an associative recognition task. Previously, we had reported that these beat stimulation conditions modulated memory performance in opposite directions. Here, we analyzed data from a patient subgroup, in which microwires were implanted in the amygdala, hippocampus, entorhinal cortex and parahippocampal cortex. We identified neurons responding with firing rate changes to binaural versus monaural 5 Hz beat stimulation. In these neurons, we correlated the differences in firing rates for binaural versus monaural beats to the memory-related differences for remembered versus forgotten items and associations. In the left hemisphere, we detected statistically significant negative correlations between firing rate differences for binaural versus monaural beats and remembered versus forgotten items/associations. Importantly, such negative correlations were also observed between beat stimulation-related firing rate differences in the pre-stimulus window and memory-related firing rate differences in the post-stimulus windows. In line with concepts of homeostatic plasticity, our findings suggest that beat stimulation is linked to memory performance via shifting baseline firing levels. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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24 pages, 2282 KiB  
Article
An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States
by Dalton J. Edwards and Logan T. Trujillo
Brain Sci. 2021, 11(3), 330; https://doi.org/10.3390/brainsci11030330 - 5 Mar 2021
Cited by 6 | Viewed by 2769
Abstract
Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a [...] Read more.
Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4–7 Hz, alpha: 8–13 Hz, low beta: 14–20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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13 pages, 2614 KiB  
Article
Identification of Breathing Patterns through EEG Signal Analysis Using Machine Learning
by Yong-Gi Hong, Hang-Keun Kim, Young-Don Son and Chang-Ki Kang
Brain Sci. 2021, 11(3), 293; https://doi.org/10.3390/brainsci11030293 - 26 Feb 2021
Cited by 5 | Viewed by 2447
Abstract
This study was to investigate the changes in brain function due to lack of oxygen (O2) caused by mouth breathing, and to suggest a method to alleviate the side effects of mouth breathing on brain function through an additional O2 [...] Read more.
This study was to investigate the changes in brain function due to lack of oxygen (O2) caused by mouth breathing, and to suggest a method to alleviate the side effects of mouth breathing on brain function through an additional O2 supply. For this purpose, we classified the breathing patterns according to EEG signals using a machine learning technique and proposed a method to reduce the side effects of mouth breathing on brain function. Twenty subjects participated in this study, and each subject performed three different breathings: nose and mouth breathing and mouth breathing with O2 supply during a working memory task. The results showed that nose breathing guarantees normal O2 supply to the brain, but mouth breathing interrupts the O2 supply to the brain. Therefore, this comparative study of EEG signals using machine learning showed that one of the most important elements distinguishing the effects of mouth and nose breathing on brain function was the difference in O2 supply. These findings have important implications for the workplace environment, suggesting that special care is required for employees who work long hours in confined spaces such as public transport, and that a sufficient O2 supply is needed in the workplace for working efficiency. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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13 pages, 1795 KiB  
Article
Investigating the Effects of Seizures on Procedural Memory Performance in Patients with Epilepsy
by Frank J. van Schalkwijk, Walter R. Gruber, Laurie A. Miller, Eugen Trinka and Yvonne Höller
Brain Sci. 2021, 11(2), 261; https://doi.org/10.3390/brainsci11020261 - 19 Feb 2021
Cited by 4 | Viewed by 3302
Abstract
Memory complaints are frequently reported by patients with epilepsy and are associated with seizure occurrence. Yet, the direct effects of seizures on memory retention are difficult to assess given their unpredictability. Furthermore, previous investigations have predominantly assessed declarative memory. This study evaluated within-subject [...] Read more.
Memory complaints are frequently reported by patients with epilepsy and are associated with seizure occurrence. Yet, the direct effects of seizures on memory retention are difficult to assess given their unpredictability. Furthermore, previous investigations have predominantly assessed declarative memory. This study evaluated within-subject effects of seizure occurrence on retention and consolidation of a procedural motor sequence learning task in patients with epilepsy undergoing continuous monitoring for five consecutive days. Of the total sample of patients considered for analyses (N = 53, Mage = 32.92 ± 13.80 y, range = 18–66 y; 43% male), 15 patients experienced seizures and were used for within-patient analyses. Within-patient contrasts showed general improvements over seizure-free (day + night) and seizure-affected retention periods. Yet, exploratory within-subject contrasts for patients diagnosed with temporal lobe epilepsy (n = 10) showed that only seizure-free retention periods resulted in significant improvements, as no performance changes were observed following seizure-affected retention. These results indicate general performance improvements and offline consolidation of procedural memory during the day and night. Furthermore, these results suggest the relevance of healthy temporal lobe functioning for successful consolidation of procedural information, as well as the importance of seizure control for effective retention and consolidation of procedural memory. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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22 pages, 36907 KiB  
Article
Individual Alpha Peak Frequency, an Important Biomarker for Live Z-Score Training Neurofeedback in Adolescents with Learning Disabilities
by Rubén Pérez-Elvira, Javier Oltra-Cucarella, José Antonio Carrobles, Minodora Teodoru, Ciprian Bacila and Bogdan Neamtu
Brain Sci. 2021, 11(2), 167; https://doi.org/10.3390/brainsci11020167 - 28 Jan 2021
Cited by 20 | Viewed by 6230
Abstract
Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to [...] Read more.
Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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17 pages, 2709 KiB  
Article
Temporo-Frontal Coherences and High-Frequency iEEG Responses during Spatial Navigation in Patients with Drug-Resistant Epilepsy
by Aljoscha Thomschewski, Eugen Trinka and Julia Jacobs
Brain Sci. 2021, 11(2), 162; https://doi.org/10.3390/brainsci11020162 - 26 Jan 2021
Cited by 2 | Viewed by 2340
Abstract
The prefrontal cortex and hippocampus function in tight coordination during multiple cognitive processes. During spatial navigation, prefrontal neurons are linked to hippocampal theta oscillations, presumably in order to enhance communication. Hippocampal ripples have been suggested to reflect spatial memory processes. Whether prefrontal-hippocampal-interaction also [...] Read more.
The prefrontal cortex and hippocampus function in tight coordination during multiple cognitive processes. During spatial navigation, prefrontal neurons are linked to hippocampal theta oscillations, presumably in order to enhance communication. Hippocampal ripples have been suggested to reflect spatial memory processes. Whether prefrontal-hippocampal-interaction also takes place within the ripple band is unknown. This intracranial EEG study aimed to investigate whether ripple band coherences can also be used to show this communication. Twelve patients with epilepsy and intracranial EEG evaluation completed a virtual spatial navigation task. We calculated ordinary coherence between prefrontal and temporal electrodes during retrieval, re-encoding, and pre-task rest. Coherences were compared between the conditions via permutation testing. Additionally, ripples events were automatically detected and changes in occurrence rates were investigated excluding ripples on epileptic spikes. Ripple-band coherences yielded no general effect of the task on coherences across all patients. Furthermore, we did not find significant effects of task conditions on ripple rates. Subsequent analyses pointed to rather short periods of synchrony as opposed to general task-related changes in ripple-band coherence. Specifically designed tasks and adopted measures might be necessary in order to map these interactions in future studies. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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12 pages, 1363 KiB  
Article
How Neuronal Noises Influence the Spiking Neural Networks’s Cognitive Learning Process: A Preliminary Study
by Jing Liu, Xu Yang, Yimeng Zhu, Yunlin Lei, Jian Cai, Miao Wang, Ziyi Huan and Xialv Lin
Brain Sci. 2021, 11(2), 153; https://doi.org/10.3390/brainsci11020153 - 25 Jan 2021
Cited by 2 | Viewed by 2067
Abstract
In neuroscience, the Default Mode Network (DMN), also known as the default network or the default-state network, is a large-scale brain network known to have highly correlated activities that are distinct from other networks in the brain. Many studies have revealed that DMNs [...] Read more.
In neuroscience, the Default Mode Network (DMN), also known as the default network or the default-state network, is a large-scale brain network known to have highly correlated activities that are distinct from other networks in the brain. Many studies have revealed that DMNs can influence other cognitive functions to some extent. This paper is motivated by this idea and intends to further explore on how DMNs could help Spiking Neural Networks (SNNs) on image classification problems through an experimental study. The approach emphasizes the bionic meaning on model selection and parameters settings. For modeling, we select Leaky Integrate-and-Fire (LIF) as the neuron model, Additive White Gaussian Noise (AWGN) as the input DMN, and design the learning algorithm based on Spike-Timing-Dependent Plasticity (STDP). Then, we experiment on a two-layer SNN to evaluate the influence of DMN on classification accuracy, and on a three-layer SNN to examine the influence of DMN on structure evolution, where the results both appear positive. Finally, we discuss possible directions for future works. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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14 pages, 2957 KiB  
Article
Physiological and Medico-Social Research Trends of the Wave P300 and More Late Components of Visual Event-Related Potentials
by Sergey Lytaev and Irina Vatamaniuk
Brain Sci. 2021, 11(1), 125; https://doi.org/10.3390/brainsci11010125 - 18 Jan 2021
Cited by 13 | Viewed by 2561
Abstract
To extend the application of the late waves of the event-related potentials (ERPs) to multiple modalities, devices and software the underlying physiological mechanisms and responses of the brain for a particular sensory system and mental function must be carefully examined. The objective of [...] Read more.
To extend the application of the late waves of the event-related potentials (ERPs) to multiple modalities, devices and software the underlying physiological mechanisms and responses of the brain for a particular sensory system and mental function must be carefully examined. The objective of this study was aimed to study the sensory processes of the “human-computer interaction” model when classifying visual images with an incomplete set of signs based on the analysis of early, middle, late and slow ERPs components. 26 healthy subjects (men) aged 20–26 years were investigated. ERPs in 19 monopolar sites according to the 10/20 system were recorded. Discriminant and factor analyzes (BMDP Statistical Software) were applied. The component N450 is the most specialized indicator of the perception of unrecognizable (oddball) visual images. The amplitude of the ultra-late components N750 and N900 is also higher under conditions of presentation of the oddball image, regardless of the location of the registration points. In brain pathology along with the pronounced asymmetry of the wave distribution, reduction of the N150 wave and lengthening of its peak latency, a line of regularities were noted. These include–a pronounced reduction in peak latency P250 and N350, an increased amplitude of N350 in the frontal and central points of registration, a decrease in the amplitude of N450 in the left frontal cortex and its increase in the occipital registration points, activation of the occipital cortex at a time interval of 400–500 ms, as well as fusion later waves. We called such phenomena of the development of cognitive ERP in brain pathology “the incongruence of ERP components”. The results of the research are discussed in the light of the paradigm of the P300 wave application in brain-computer interface systems, as well as with the peculiarities in brain pathology. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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10 pages, 636 KiB  
Article
Memory Traces Formed in Utero—Newborns’ Autonomic and Neuronal Responses to Prenatal Stimuli and the Maternal Voice
by Adelheid Lang, Peter Ott, Renata del Giudice and Manuel Schabus
Brain Sci. 2020, 10(11), 837; https://doi.org/10.3390/brainsci10110837 - 11 Nov 2020
Cited by 5 | Viewed by 3675
Abstract
In our pilot study, we exposed third-trimester fetuses, from week 34 of gestation onwards, twice daily to a maternal spoken nursery rhyme. Two and five weeks after birth, 34 newborns, who were either familiarized with rhyme stimulation in utero or stimulation naïve, were [...] Read more.
In our pilot study, we exposed third-trimester fetuses, from week 34 of gestation onwards, twice daily to a maternal spoken nursery rhyme. Two and five weeks after birth, 34 newborns, who were either familiarized with rhyme stimulation in utero or stimulation naïve, were (re-)exposed to the familiar, as well as to a novel and unfamiliar, rhyme, both spoken with the maternal and an unfamiliar female voice. For the stimulation-naïve group, both rhymes were unfamiliar. During stimulus presentation, heart rate activity and high-density electroencephalography were collected and newborns’ responses during familiar and unfamiliar stimulation were analyzed. All newborns demonstrated stronger speech–brain coupling at 1 Hz during the presentation of the maternal voice vs. the unfamiliar female voice. Rhyme familiarity originating from prenatal exposure had no effect on speech–brain coupling in experimentally stimulated newborns. Furthermore, only stimulation-naïve newborns demonstrated an increase in heart rate during the presentation of the unfamiliar female voice. The results indicate prenatal familiarization to auditory speech and point to the specific significance of the maternal voice already in two- to five-week-old newborns. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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11 pages, 1070 KiB  
Article
The Cross-Modal Suppressive Role of Visual Context on Speech Intelligibility: An ERP Study
by Stanley Shen, Jess R. Kerlin, Heather Bortfeld and Antoine J. Shahin
Brain Sci. 2020, 10(11), 810; https://doi.org/10.3390/brainsci10110810 - 2 Nov 2020
Cited by 3 | Viewed by 2771
Abstract
The efficacy of audiovisual (AV) integration is reflected in the degree of cross-modal suppression of the auditory event-related potentials (ERPs, P1-N1-P2), while stronger semantic encoding is reflected in enhanced late ERP negativities (e.g., N450). We hypothesized that increasing visual stimulus reliability should lead [...] Read more.
The efficacy of audiovisual (AV) integration is reflected in the degree of cross-modal suppression of the auditory event-related potentials (ERPs, P1-N1-P2), while stronger semantic encoding is reflected in enhanced late ERP negativities (e.g., N450). We hypothesized that increasing visual stimulus reliability should lead to more robust AV-integration and enhanced semantic prediction, reflected in suppression of auditory ERPs and enhanced N450, respectively. EEG was acquired while individuals watched and listened to clear and blurred videos of a speaker uttering intact or highly-intelligible degraded (vocoded) words and made binary judgments about word meaning (animate or inanimate). We found that intact speech evoked larger negativity between 280–527-ms than vocoded speech, suggestive of more robust semantic prediction for the intact signal. For visual reliability, we found that greater cross-modal ERP suppression occurred for clear than blurred videos prior to sound onset and for the P2 ERP. Additionally, the later semantic-related negativity tended to be larger for clear than blurred videos. These results suggest that the cross-modal effect is largely confined to suppression of early auditory networks with weak effect on networks associated with semantic prediction. However, the semantic-related visual effect on the late negativity may have been tempered by the vocoded signal’s high-reliability. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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13 pages, 1237 KiB  
Article
Widespread Reductions of Spontaneous Neurophysiological Activity in Leber’s Disease—An Application of EEG Source Current Density Reconstruction
by Kamil Jonak
Brain Sci. 2020, 10(9), 622; https://doi.org/10.3390/brainsci10090622 - 8 Sep 2020
Cited by 3 | Viewed by 2334
Abstract
Leber’s hereditary optic neuropathy (LHON) is a rare, maternally inherited genetic disease caused by a mutation of mitochondrial DNA. Classical descriptions have highlighted structural abnormalities in various parts of patients’ optic tracts; however, current studies have proved that changes also affect many cortical [...] Read more.
Leber’s hereditary optic neuropathy (LHON) is a rare, maternally inherited genetic disease caused by a mutation of mitochondrial DNA. Classical descriptions have highlighted structural abnormalities in various parts of patients’ optic tracts; however, current studies have proved that changes also affect many cortical and subcortical structures, not only these belonging to the visual system. This study aimed at improving our understanding of neurophysiological impairments in LHON. First of all, we wanted to know if there were any differences between the health control and LHON subjects in the whole-brain source electroencephalography (EEG) analysis. Second, we wanted to investigate the associations between the observed results and some selected aspects of Leber’s disease’s clinical picture. To meet these goals, 20 LHON patients and 20 age-matched healthy control (HC) subjects were examined. To investigate the electrophysiological differences between the HC and LHON groups, a quantitative analysis of the whole-brain current source density was performed. The signal analysis method was based on scalp EEG data and an inverse solution method called low-resolution brain electromagnetic tomography (eLORETA). In comparison with the healthy subjects, LHON participants showed significantly decreased neuronal activity in the alpha and gamma bands; more specifically, in the alpha band, the decrease was mainly found in the occipital lobes and secondary visual cortex, whereas, in the gamma band, the reduced activity occurred in multiple cortical areas. Additionally, a correlation was found between the alpha band activity of the right secondary visual cortex and the averaged thickness of the right retinal nerve fiber layer in the LHON participants. Our study suggests that LHON is associated with widespread cortical de-activation, rather than simply abnormalities of structures constituting the visual system. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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11 pages, 905 KiB  
Article
Sleep, Little Baby: The Calming Effects of Prenatal Speech Exposure on Newborns’ Sleep and Heartrate
by Adelheid Lang, Renata del Giudice and Manuel Schabus
Brain Sci. 2020, 10(8), 511; https://doi.org/10.3390/brainsci10080511 - 2 Aug 2020
Cited by 8 | Viewed by 5390
Abstract
In a pilot study, 34 fetuses were stimulated daily with a maternal spoken nursery rhyme from week 34 of gestation onward and re-exposed two and five weeks after birth to this familiar, as well as to an unfamiliar rhyme, both spoken with the [...] Read more.
In a pilot study, 34 fetuses were stimulated daily with a maternal spoken nursery rhyme from week 34 of gestation onward and re-exposed two and five weeks after birth to this familiar, as well as to an unfamiliar rhyme, both spoken with the maternal and an unfamiliar female voice. During auditory stimulation, newborns were continuously monitored with polysomnography using video-monitored hdEEG. Afterward, changes in sleep–wake-state proportions during familiar and unfamiliar voice stimulation were analyzed. Our preliminary results demonstrate a general calming effect of auditory stimulation exclusively in infants who were prenatally “familiarized” with a spoken nursery rhyme, as evidenced by less waking states, more time spent in quiet (deep) sleep, and lower heartrates. A stimulation naïve group, on the other hand, demonstrated no such effects. Stimulus-specific effects related to the familiarity of the prenatally replayed voice or rhyme were not evident in newborns. Together, these results suggest “fetal learning” at a basic level and point to a familiarization with auditory stimuli prior to birth, which is evident in the first weeks of life in behavioral states and heartrate physiology of the newborn. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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Review

Jump to: Editorial, Research

40 pages, 946 KiB  
Review
Narrative Review: Quantitative EEG in Disorders of Consciousness
by Betty Wutzl, Stefan M. Golaszewski, Kenji Leibnitz, Patrick B. Langthaler, Alexander B. Kunz, Stefan Leis, Kerstin Schwenker, Aljoscha Thomschewski, Jürgen Bergmann and Eugen Trinka
Brain Sci. 2021, 11(6), 697; https://doi.org/10.3390/brainsci11060697 - 25 May 2021
Cited by 28 | Viewed by 5482
Abstract
In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of [...] Read more.
In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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16 pages, 5648 KiB  
Review
TMS–EEG Co-Registration in Patients with Mild Cognitive Impairment, Alzheimer’s Disease and Other Dementias: A Systematic Review
by Raffaele Nardone, Luca Sebastianelli, Viviana Versace, Davide Ferrazzoli, Leopold Saltuari and Eugen Trinka
Brain Sci. 2021, 11(3), 303; https://doi.org/10.3390/brainsci11030303 - 27 Feb 2021
Cited by 17 | Viewed by 4399
Abstract
An established method to assess effective brain connectivity is the combined use of transcranial magnetic stimulation with simultaneous electroencephalography (TMS–EEG) because TMS-induced cortical responses propagate to distant anatomically connected brain areas. Alzheimer’s disease (AD) and other dementias are associated with changes in brain [...] Read more.
An established method to assess effective brain connectivity is the combined use of transcranial magnetic stimulation with simultaneous electroencephalography (TMS–EEG) because TMS-induced cortical responses propagate to distant anatomically connected brain areas. Alzheimer’s disease (AD) and other dementias are associated with changes in brain networks and connectivity, but the underlying pathophysiology of these processes is poorly defined. We performed here a systematic review of the studies employing TMS–EEG co-registration in patients with dementias. TMS–EEG studies targeting the motor cortex have revealed a significantly reduced TMS-evoked P30 in AD patients in the temporo-parietal cortex ipsilateral to stimulation side as well as in the contralateral fronto-central area, and we have demonstrated a deep rearrangement of the sensorimotor system even in mild AD patients. TMS–EEG studies targeting other cortical areas showed alterations of effective dorsolateral prefrontal cortex connectivity as well as an inverse correlation between prefrontal-to-parietal connectivity and cognitive impairment. Moreover, TMS–EEG analysis showed a selective increase in precuneus neural activity. TMS–EEG co-registrations can also been used to investigate whether different drugs may affect cognitive functions in patients with dementias. Full article
(This article belongs to the Special Issue Quantitative EEG and Cognitive Neuroscience)
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