Cortical oscillations to measure anti-epileptic drug activity in clinical trials

2021 ◽  
Author(s):  
Andrea Biondi ◽  
Lorenzo Rocchi ◽  
Viviana Santoro ◽  
Gregory Beatch ◽  
Pierre Rossini ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Brain Activity ◽  
Systematic Evaluation ◽  
Alpha Power ◽  
Brain Oscillations ◽  
Cortical Oscillations ◽  
Anti Epileptic Drug ◽  
Beta Power ◽  
Gamma Power

Abstract The frequency analysis of electroencephalographic (EEG) activity, either spontaneous or evoked by transcranial magnetic stimulation (TMS-EEG), is a powerful tool to investigate changes in brain activity and excitability following the administration of antiepileptic drugs (AEDs). However, a systematic evaluation of the effect of AEDs on spontaneous and TMS-induced brain oscillations has not yet been provided. We studied the effects of lamotrigine, levetiracetam, and of a novel potassium channel opener (XEN1101) on TMS-induced and spontaneous brain oscillations in a group of healthy volunteers. Levetiracetam suppressed TMS-induced theta, alpha and beta power, whereas lamotrigine increased TMS-induced alpha power. XEN1101 decreased TMS-induced delta, theta and beta power. Resting-state EEG showed a decrease of theta band power after lamotrigine intake. Levetiracetam increased theta, beta and gamma power, while XEN1101 produced an increase of delta, theta, beta and gamma power. Different AEDs induce specific patterns of power changes in spontaneous and TMS-induced brain oscillations. Spontaneous and TMS-induced cortical oscillations represent a powerful tool to characterize the effect of AEDs on in vivo brain activity. Spectral fingerprints of specific AEDs should be further investigated to provide robust and objective biomarkers of biological effect in human clinical trials.

scholarly journals Effects of familiarity with musical style on music-evoked emotions: An EEG study

2021 ◽  
Author(s):  
Gladys Jiamin Heng ◽  
Quek Hiok Chai ◽  
SH Annabel Chen
Keyword(s):  
Brain Activity ◽  
Treatment Plan ◽  
Brain Regions ◽  
Alpha Power ◽  
Musical Style ◽  
Learning Mechanisms ◽  
Behavioral Ratings ◽  
Eyes Closed ◽  
Beta Power ◽  
Musical Excerpts

Learning mechanisms have been postulated to be one of the primary reasons why different individuals have similar or different emotional responses to music. While existing studies have largely examined mechanisms related to learning in terms of cultural familiarity or recognition, few studies have conceptualized it in terms of an individual’s level of familiarity with musical style, which could be a better reflection of an individual’s composite musical experiences. Therefore, the current study aimed to bridge this research gap by investigating the electrophysiological correlates of the effects of familiarity with musical style on music-evoked emotions. 49 non-musicians listened to 12 musical excerpts of a familiar musical style (Japanese animation soundtracks) and eight musical excerpts of an unfamiliar musical style (Greek Laïkó music) with their eyes closed as electroencephalography is being recorded. Participants rated their felt emotions after each musical excerpt is played. Behavioral ratings showed that music of the familiar musical style was felt as significantly more pleasant as compared to the unfamiliar musical style while no significant differences in arousal were observed. In terms of brain activity, music of the unfamiliar musical style elicited higher (1) theta power in all brain regions (including frontal midline), (2) alpha power in frontal region, and (3) beta power in fronto-temporo-occipital regions as compared to the familiar musical style. This is interpreted to reflect the need for greater attentional resources when listening to music of an unfamiliar style, where listeners are less familiar with the syntax and structure of the music as compared to music of a familiar style. In addition, classification analysis showed that unfamiliar and familiar musical styles can be distinguished with 67.86% accuracy, Thus, clinicians should consider the musical profile of the client when choosing an appropriate selection of music in the treatment plan, so as to achieve better efficacy.

scholarly journals Understanding the neurological mechanism involved in enhanced memory recall task following binaural beat: a pilot study

2021 ◽  
Author(s):  
Muhammad Danish Mujib ◽  
Muhammad Abul Hasan ◽  
Saad Ahmed Qazi ◽  
Aleksandra Vuckovic
Keyword(s):  
Short Term Memory ◽  
Brain Activity ◽  
Digit Span ◽  
Memory Task ◽  
Neural Mechanism ◽  
Alpha Power ◽  
Before And After ◽  
Gamma Power ◽  
Group A ◽  
Oscillatory Brain Activity

AbstractBinaural beat (BB) is a promising technique for memory improvement in elderly or people with neurological conditions. However, the related modulation of cortical networks followed by behavioral changes has not been investigated. The objective of this study is to establish a relationship between BB oscillatory brain activity evoked by stimulation and a behavioral response in a short term memory task. Three Groups A, B, and C of 20 participants each received alpha (10 Hz), beta (14 Hz), and gamma (30 Hz) BB, respectively, for 15 min. Their EEG was recorded in pre, during, and post BB states. Participants performed a digit span test before and after a BB session. A significant increase in the cognitive score was found only for Group A while a significant decrease in reaction time was noted for Groups A and C. Group A had a significant decrease of theta and increase of alpha power, and a significant increase of theta and decrease of gamma imaginary coherence (ICH) post BB. Group C had a significant increase in theta and gamma power accompanied by the increase of theta and gamma ICH post BB. The effectiveness of BB depends on the frequency of stimulation. A putative neural mechanism involves an increase in theta ICH in parieto-frontal and interhemispheric frontal networks.

scholarly journals Interactions between motor thalamic field potentials and single unit spiking predict behavior in rats

2019 ◽  
Author(s):  
Matt Gaidica ◽  
Amy Hurst ◽  
Christopher Cyr ◽  
Daniel K. Leventhal
Keyword(s):  
Task Performance ◽  
Brain Activity ◽  
Field Potential ◽  
Spike Timing ◽  
Delta Phase ◽  
Beta Power ◽  
High Gamma ◽  
Gamma Power ◽  
Complex Relationships ◽  
And Behavior

AbstractThe thalamus plays a central role in generating circuit-level neural oscillations believed to coordinate brain activity over large spatiotemporal scales. Such thalamic influences are well-documented for sleep rhythms and in sensory systems, but the relationship between thalamic activity, motor circuit local field potential (LFP) oscillations, and behavior is unknown. We recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced choice task. The power of delta (1−4 Hz), beta (13−30 Hz), low gamma (30−70 Hz), and high gamma (70−200 Hz) oscillations were strongly modulated by task performance. As in cortex, delta phase predicted beta/low gamma power and reaction time. Furthermore, delta phase differentially predicted spike timing in functionally distinct populations of Mthal neurons, which also predicted task performance and beta power. These complex relationships suggest mechanisms for commonly observed LFP-LFP and spike-LFP interactions, as well as subcortical influences on motor output.

scholarly journals Cortical Oscillatory Dysrhythmias in Visual Snow Syndrome: A MEG Study

2021 ◽  
Author(s):  
Jenny L Hepschke ◽  
Robert A Seymour ◽  
Wei A He ◽  
Andrew Etchell ◽  
Paul F Sowman ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Brain Activity ◽  
Peak Frequency ◽  
Alpha Phase ◽  
Alpha Power ◽  
Gamma Peak ◽  
Gamma Power ◽  
Early Visual Cortex ◽  
Phase Amplitude

Visual Snow (VS) refers to the persistent visual experience of static in the whole visual field of both eyes. It is often reported by patients with migraine and co-occurs with conditions like tinnitus and tremor. The underlying pathophysiology of the condition is poorly understood. Previously we hypothesised, that VSS may be characterised by disruptions to rhythmical activity within the visual system. To test this, data from 18 patients diagnosed with visual snow syndrome (VSS), and 16 matched controls, were acquired using Magnetoencephalography (MEG). Participants were presented with visual grating stimuli, known to elicit decreases in alpha-band (8-13Hz) power and increases in gamma-band power (40-70Hz). Data were mapped to source-space using a beamformer. Across both groups, decreased alpha power and increased gamma power localised to early visual cortex. Data from primary visual cortex (V1) were compared between groups. No differences were found in either alpha or gamma peak frequency or the magnitude of alpha power, p>.05. However, compared with controls, our VSS cohort displayed significantly increased V1 gamma power, p=.035. This new electromagnetic finding concurs with previous fMRI and PET findings suggesting that in VSS, the visual cortex is hyper-excitable. The coupling of alpha-phase to gamma amplitude (i.e., phase-amplitude coupling, PAC) within V1 was also quantified. Compared with controls, the VSS group had significantly reduced alpha-gamma PAC, p<.05, indicating a potential excitation-inhibition imbalance in VSS, as well as a potential disruption to top-down 'noise-cancellation' mechanisms. Overall, these results suggest that rhythmical brain activity in primary visual cortex is both hyperexcitable and disorganised in VSS, consistent with visual snow being a condition of thalamocortical dysrhythmia.

scholarly journals The role of brain oscillations in predicting the sensory consequences of your actions

2016 ◽  
Author(s):  
Liyu Cao ◽  
Gregor Thut ◽  
Joachim Gross
Keyword(s):  
Phase Locking ◽  
Beta Phase ◽  
General Mechanism ◽  
Normal Brain ◽  
Alpha Power ◽  
Brain Oscillations ◽  
Neural Information ◽  
Gamma Power ◽  
Alpha Beta

Being able to predict self-generated sensory consequences is an important feature of normal brain functioning. In the auditory domain, self-generated sounds lead to smaller brain responses compared to externally generated sounds. Here we investigated the role of brain oscillations underlying this effect. With magnetoencephalography, we show that self-generated sounds are associated with increased pre-stimulus alpha power and decreased post-stimulus gamma power and alpha/beta phase locking in auditory cortex. All these oscillatory changes are correlated with changes in evoked responses. Furthermore, they correlate with each other across participants, supporting the idea that they constitute a neural information processing sequence for self-generated sounds, with pre-stimulus alpha power representing prediction and post-stimulus gamma power representing prediction error, which is further processed with post-stimulus alpha/beta phase resetting. Additional cross-trial analysis provides further support for the proposed sequence that might reflect a general mechanism for the prediction of self-generated sensory input.

scholarly journals Heading for Personalized rTMS in Tinnitus: Reliability of Individualized Stimulation Protocols in Behavioral and Electrophysiological Responses

2021 ◽  
Vol 11 (6) ◽  
pp. 536
Author(s):  
Stefan Schoisswohl ◽  
Berthold Langguth ◽  
Tobias Hebel ◽  
Mohamed A. Abdelnaim ◽  
Gregor Volberg ◽  
...  
Keyword(s):  
Repetitive Transcranial Magnetic Stimulation ◽  
Brain Activity ◽  
Clinical Effectiveness ◽  
Individual Variability ◽  
Alpha Power ◽  
Group Level ◽  
Electrophysiological Responses ◽  
Before And After ◽  
Gamma Power ◽  
Oscillatory Brain Activity

Background: Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation tool potentially modulating pathological brain activity. Its clinical effectiveness is hampered by varying results and characterized by inter-individual variability in treatment responses. RTMS individualization might constitute a useful strategy to overcome this variability. A precondition for this approach would be that repeatedly applied protocols result in reliable effects. The condition tinnitus provides the advantage of immediate behavioral consequences (tinnitus loudness changes) after interventions and thus offers an excellent model to exemplify TMS personalization. Objective: The aim was to investigate the test–retest reliability of short rTMS stimulations in modifying tinnitus loudness and oscillatory brain activity as well as to examine the feasibility of rTMS individualization in tinnitus. Methods: Three short verum (1, 10, 20 Hz; 200 pulses) and one sham (0.1 Hz; 20 pulses) rTMS protocol were administered on two different days in 22 tinnitus patients. Before and after each protocol, oscillatory brain activity was recorded with electroencephalography (EEG), together with behavioral tinnitus loudness ratings. RTMS individualization was executed on the basis of behavioral and electrophysiological responses. Stimulation responders were identified via consistent sham-superior increases in tinnitus loudness (behavioral responders) and alpha power increases or gamma power decreases (alpha responders/gamma responders) in accordance with the prevalent neurophysiological models for tinnitus. Results: It was feasible to identify individualized rTMS protocols featuring reliable tinnitus loudness changes (55% behavioral responder), alpha increases (91% alpha responder) and gamma decreases (100% gamma responder), respectively. Alpha responses primary occurred over parieto-occipital areas, whereas gamma responses mainly appeared over frontal regions. On the contrary, test–retest correlation analyses per protocol at a group level were not significant neither for behavioral nor for electrophysiological effects. No associations between behavioral and EEG responses were found. Conclusion: RTMS individualization via behavioral and electrophysiological data in tinnitus can be considered as a feasible approach to overcome low reliability at the group level. The present results open the discussion favoring personalization utilizing neurophysiological markers rather than behavioral responses. These insights are not only useful for the rTMS treatment of tinnitus but also for neuromodulation interventions in other pathologies, as our results suggest that the individualization of stimulation protocols is feasible despite absent group-level reliability.

scholarly journals Psychological, Neurophysiological, and Mental Factors Associated With Gamma-Enhancing Neurofeedback Success

2020 ◽  
Vol 11 (5) ◽  
pp. 701-714
Author(s):  
Zeynab Khodakarami ◽  
◽  
Mohammad Firoozabadi ◽  
Keyword(s):  
Fluid Intelligence ◽  
Brain Activity ◽  
Cognitive Task ◽  
Gain Control ◽  
Learning Performance ◽  
Gamma Activity ◽  
Alpha Power ◽  
Neurofeedback Training ◽  
Eyes Closed ◽  
Gamma Power

Introduction: Regarding the neurofeedback training process, previous studies indicate that 10%-50% of subjects cannot gain control over their brain activity even after repeated training sessions. This study is conducted to overcome this problem by investigating inter-individual differences in neurofeedback learning to propose some predictors for the trainability of subjects. Methods: Eight healthy female students took part in 8 (electroencephalography) EEG neurofeedback training sessions for enhancing EEG gamma power at the Oz channel. We studied participants’ preexisting fluid intelligence and EEG frequency sub-bands’ power during 2-min eyes-closed rest and a cognitive task as psychological and neurophysiological factors, concerning neurofeedback learning performance. We also assessed the self-reports of participants about mental strategies used by them during neurofeedback to identify the most effective successful strategies. Results: The results revealed that a significant percentage of individuals (25% in this study) cannot learn how to control their brain gamma activity using neurofeedback. Our findings suggest that fluid intelligence, gamma power during a cognitive task, and alpha power at rest can predict gamma-enhancing neurofeedback performance of individuals. Based on our study, neurofeedback learning is a form of implicit learning. We also found that learning without a user’s mental efforts to find out successful mental strategies, in other words, unconscious learning, lead to more success in gamma-enhancing neurofeedback. Conclusion: Our results may improve gamma neurofeedback efficacy for further clinical usage and studies by giving insight about both non-trainable individuals and effective mental strategies.

scholarly journals Changes in Psychoacoustic Recognition and Brain Activity by Types of Fire Alarm

2021 ◽  
Vol 18 (2) ◽  
pp. 541
Author(s):  
Sunghwa You ◽  
Woojae Han ◽  
Han-Jin Jang ◽  
Ghee-Young Noh
Keyword(s):  
Older Adults ◽  
Brain Activity ◽  
Age Groups ◽  
Alpha Power ◽  
Acoustic Features ◽  
High Arousal ◽  
Fire Alarm ◽  
Age Related ◽  
Significant Difference ◽  
Gamma Power

In public, the role of a fire alarm is to induce a person to a certain recognition of potential danger, resulting in that person taking appropriate evacuation action. Unfortunately, the sound of the fire alarm is not internationally standardized yet, except for recommending the use of a signal with a regular temporal pattern (or T-3 pattern). To identify the effective alarm sound, the present study investigated a relationship between acoustic characteristics of the fire alarm and its subjective psychoacoustic recognition and objective electroencephalography (EEG) responses for 50 young and older listeners. As the stimuli, six different types of alarms were applied: bell, slow whoop, T-3 520 Hz, T-3 3100 Hz, and two simulated T-3 sounds (i.e., 520 and 3100 Hz) to which older adults with age-related hearing loss seemed to hear. While listening to the sounds, the EEG was recorded by each individual. The psychoacoustic recognition was also evaluated by using a questionnaire consisting of three subcategories, i.e., arousal, urgency, and immersion. The subjective responses resulted in a statistically significant difference between the types of sound. In particular, the fire alarms had acoustic features of high frequency or gradually increased frequencies such as T-3 3100 Hz, bell, and slow whoop, representing effective sounds to induce high arousal and urgency, although they also showed a limitation in being widely transmitted and vulnerable to background noise environment. Interestingly, there was a meaningful interaction effect between the sounds and age groups for the urgency and immersion, indicating that the bell was quite highly recognized in older adults. In general, EEG data showed that alpha power was decreased and gamma power was increased in all sounds, which means a relationship with negative emotions such as high arousal and urgency. Based on the current findings, we suggest using fire alarm sounds with acoustic features of high frequencies in indoor and/or public places.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

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