scholarly journals A novel approach for combining task-dependent gamma with alpha and beta power modulation for enhanced identification of eloquent cortical areas using ECoG in patients with medical-refractory epilepsy

2019 ◽  
Author(s):  
M.E. Archila-Meléndez ◽  
G. Valente ◽  
E. Gommer ◽  
R.P.W. Rouhl ◽  
O.E.M.G. Schijns ◽  
...  
Keyword(s):  
Refractory Epilepsy ◽  
Low Frequency ◽  
Cognitive Testing ◽  
Gamma Activity ◽  
Beta Band ◽  
Diagnostic Ability ◽  
Eloquent Areas ◽  
Cortical Areas ◽  
Beta Power ◽  
Band Activity

AbstractElectrical stimulation mapping (ESM) is the gold standard for identification of “eloquent” areas prior to resection of epileptogenic tissue, however, it is time consuming and may cause side effects, especially stimulation-induced seizures and after-discharges. Broadband gamma activity (55 – 200 Hz) recorded with subdural electrocorticography (ECoG) during cognitive tasks has been proposed as an attractive tool for mapping cortical areas with specific function but until now has not proven definitive clinical value. Fewer studies have addressed whether the alpha (8 – 12 Hz) and beta (15 – 25 Hz) band activity could also be used to improve eloquent cortex identification. We compared alpha, beta and broadband gamma activity, and their combination for the identification of eloquent cortical areas defined by ESM. Ten patients participated in a delayed-match-to-sample task, where syllable sounds were matched to visually presented letters and responses given by keyboard. We used a generalized linear model (GLM) approach to find the optimal weighting of low frequency bands and broadband gamma power to predict the ESM categories. Broadband gamma activity increased more in eloquent areas than in non-eloquent areas and this difference had a diagnostic ability (area under (AU) the receiving operating characteristic curve - AUROC) of ∼70%. Both alpha and beta power decreased more in eloquent areas. Alpha power had lower AUROC than broadband gamma while beta had similar AUROC. AUROC was enhanced by the combination of alpha and broadband gamma (3% improvement) and by the combination of beta and broadband gamma (7% improvement) over the use of broadband gamma alone. Further analysis showed that the relative performance of broadband gamma and low frequency bands depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patient’s attention to the stimulus. However, the combination of beta band and broadband gamma always gave the best performance. We show how ECoG power modulation from cognitive testing periods can be used to map the probability of eloquence by ESM and how this probability can be used as an aid for optimal ESM planning. We conclude that low frequency power during cognitive testing can contribute to the identification of eloquent areas in patients with focal refractory epilepsy improving its precision but does not replace the need of ESM.HighlightsGamma, alpha and beta band activity has significant diagnostic ability to identify ESM defined eloquent cortical areas.We present a novel method to combine gamma and low frequency activity for enhanced identification.We quantify how identification is dependent on analysis time window, cortical function, and patient’s attentional engagement.With further development, this approach may offer an alternative to ESM mapping with reduced burden for patients.

scholarly journals Combining Gamma With Alpha and Beta Power Modulation for Enhanced Cortical Mapping in Patients With Focal Epilepsy

2020 ◽  
Vol 14 ◽  
Author(s):  
Mario E. Archila-Meléndez ◽  
Giancarlo Valente ◽  
Erik D. Gommer ◽  
João M. Correia ◽  
Sanne ten Oever ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Cognitive Task ◽  
Cognitive Testing ◽  
Gamma Activity ◽  
Cortical Mapping ◽  
Beta Activity ◽  
Diagnostic Ability ◽  
Power Modulation ◽  
Eloquent Areas ◽  
Beta Power

About one third of patients with epilepsy have seizures refractory to the medical treatment. Electrical stimulation mapping (ESM) is the gold standard for the identification of “eloquent” areas prior to resection of epileptogenic tissue. However, it is time-consuming and may cause undesired side effects. Broadband gamma activity (55–200 Hz) recorded with extraoperative electrocorticography (ECoG) during cognitive tasks may be an alternative to ESM but until now has not proven of definitive clinical value. Considering their role in cognition, the alpha (8–12 Hz) and beta (15–25 Hz) bands could further improve the identification of eloquent cortex. We compared gamma, alpha and beta activity, and their combinations for the identification of eloquent cortical areas defined by ESM. Ten patients with intractable focal epilepsy (age: 35.9 ± 9.1 years, range: 22–48, 8 females, 9 right handed) participated in a delayed-match-to-sample task, where syllable sounds were compared to visually presented letters. We used a generalized linear model (GLM) approach to find the optimal weighting of each band for predicting ESM-defined categories and estimated the diagnostic ability by calculating the area under the receiver operating characteristic (ROC) curve. Gamma activity increased more in eloquent than in non-eloquent areas, whereas alpha and beta power decreased more in eloquent areas. Diagnostic ability of each band was close to 0.7 for all bands but depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patient’s degree of attention to the stimulus. We show that diagnostic ability can be increased by 3–5% by combining gamma and alpha and by 7.5–11% when gamma and beta were combined. We then show how ECoG power modulation from cognitive testing can be used to map the probability of eloquence in individual patients and how this probability map can be used in clinical settings to optimize ESM planning. We conclude that the combination of gamma and beta power modulation during cognitive testing can contribute to the identification of eloquent areas prior to ESM in patients with refractory focal epilepsy.

scholarly journals Effects of beta- and gamma-band rhythmic stimulation on motor inhibition

2020 ◽  
Author(s):  
Inge Leunissen ◽  
Manon Van Steenkiste ◽  
Kirstin Heise ◽  
Thiago Santos Monteiro ◽  
Kyle Dunovan ◽  
...  
Keyword(s):  
Gamma Oscillations ◽  
Gamma Band ◽  
Stop Signal ◽  
Gamma Activity ◽  
Oscillatory Activity ◽  
Beta Activity ◽  
Motor Inhibition ◽  
Beta Band ◽  
Beta Power ◽  
Transcranial Alternating Current Stimulation

Voluntary movements are accompanied by an increase in gamma-band oscillatory activity (60-100Hz) and a strong desynchronization of beta-band activity (13-30Hz) in the motor system at both the cortical and subcortical level. Conversely, successful motor inhibition is associated with increased beta power in a fronto-basal-ganglia network. Intriguingly, gamma activity also increases in response to a stop-signal. In this study, we used transcranial alternating current stimulation to drive beta and gamma oscillations to investigate whether these frequencies are causally related to motor inhibition. We found that 20Hz stimulation targeted at the pre-supplementary motor area enhanced inhibition and increased beta oscillatory activity around the time of the stop-signal in trials directly following stimulation. In contrast, 70Hz stimulation seemed to slow down the braking process, and predominantly affected go task performance. These results demonstrate that the effects of tACS are state-dependent and that especially fronto-central beta activity is a functional marker for successful motor inhibition.

scholarly journals Intracranial Recordings and Computational Modeling of Music Reveal the Time Course of Prediction Error Signaling in Frontal and Temporal Cortices

2019 ◽  
Vol 31 (6) ◽  
pp. 855-873 ◽  
Author(s):  
Diana Omigie ◽  
Marcus Pearce ◽  
Katia Lehongre ◽  
Dominique Hasboun ◽  
Vincent Navarro ◽  
...  
Keyword(s):  
Prediction Error ◽  
Time Course ◽  
Inferior Frontal Gyrus ◽  
Low Frequency ◽  
Anterior Cingulate ◽  
Predictive Processing ◽  
Gamma Activity ◽  
Oscillatory Activity ◽  
Middle Temporal Gyrus ◽  
Beta Power

Prediction is held to be a fundamental process underpinning perception, action, and cognition. To examine the time course of prediction error signaling, we recorded intracranial EEG activity from nine presurgical epileptic patients while they listened to melodies whose information theoretical predictability had been characterized using a computational model. We examined oscillatory activity in the superior temporal gyrus (STG), the middle temporal gyrus (MTG), and the pars orbitalis of the inferior frontal gyrus, lateral cortical areas previously implicated in auditory predictive processing. We also examined activity in anterior cingulate gyrus (ACG), insula, and amygdala to determine whether signatures of prediction error signaling may also be observable in these subcortical areas. Our results demonstrate that the information content (a measure of unexpectedness) of musical notes modulates the amplitude of low-frequency oscillatory activity (theta to beta power) in bilateral STG and right MTG from within 100 and 200 msec of note onset, respectively. Our results also show this cortical activity to be accompanied by low-frequency oscillatory modulation in ACG and insula—areas previously associated with mediating physiological arousal. Finally, we showed that modulation of low-frequency activity is followed by that of high-frequency (gamma) power from approximately 200 msec in the STG, between 300 and 400 msec in the left insula, and between 400 and 500 msec in the ACG. We discuss these results with respect to models of neural processing that emphasize gamma activity as an index of prediction error signaling and highlight the usefulness of musical stimuli in revealing the wide-reaching neural consequences of predictive processing.

scholarly journals Daytime Neurophysiological Hyperarousal in Chronic Insomnia: A Study of qEEG

2020 ◽  
Vol 9 (11) ◽  
pp. 3425
Author(s):  
Da Young Oh ◽  
Su Mi Park ◽  
Sung Won Choi
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Chronic Insomnia ◽  
Beta Band ◽  
Eyes Closed ◽  
Eyes Open ◽  
Quantitative Electroencephalogram ◽  
High Beta ◽  
Insomnia Symptoms ◽  
Band Activity

Background: The hyperarousal model demonstrates that instability of sleep-wake regulation leads to insomnia symptoms and various neurophysiological hyperarousal states. Previous studies have shown that hyperarousal states that appear in chronic insomnia patients are not limited to sleep at nighttime but are stable characteristics that extend into the daytime. However, this phenomenon is mainly measured at bedtime, so it hard to determine whether it is maintained throughout a 24 h cycle or if it just appears at bedtime. Methods: We examined the resting state qEEG (quantitative electroencephalogram) and ECG (electrocardiogram) of chronic insomnia patients (n = 24) compared to good sleepers (n = 22) during the daytime. Results: As compared with controls, participants with insomnia showed a clearly high beta band activity in eyes closed condition at all brain areas. They showed a low frequency band at the frontal area; high frequency bands at the central and parietal areas were found in eyes open condition. Significantly higher heart rates were also found in the chronic insomnia group. Conclusion: These findings suggest that chronic insomnia patients were in a state of neurophysiological hyperarousal during the middle of the day due to abnormal arousal regulation.

scholarly journals Task performance changes the amplitude and timing of the BOLD signal

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Atae Akhrif ◽  
Maximilian J. Geiger ◽  
Marcel Romanos ◽  
Katharina Domschke ◽  
Susanne Neufang
Keyword(s):  
Task Performance ◽  
Temporal Dynamics ◽  
Brain Activation ◽  
Bold Signal ◽  
Bold Response ◽  
Imaging Data ◽  
Neural Firing ◽  
Beta Band ◽  
Beta Power ◽  
Band Activity

AbstractTranslational studies comparing imaging data of animals and humans have gained increasing scientific interests. With this upcoming translational approach, however, identifying harmonized statistical analysis as well as shared data acquisition protocols and/or combined statistical approaches is necessary. Following this idea, we applied Bayesian Adaptive Regression Splines (BARS), which have until now mainly been used to model neural responses of electrophysiological recordings from rodent data, on human hemodynamic responses as measured via fMRI. Forty-seven healthy subjects were investigated while performing the Attention Network Task in the MRI scanner. Fluctuations in the amplitude and timing of the BOLD response were determined and validated externally with brain activation using GLM and also ecologically with the influence of task performance (i.e. good vs. bad performers). In terms of brain activation, bad performers presented reduced activation bilaterally in the parietal lobules, right prefrontal cortex (PFC) and striatum. This was accompanied by an enhanced left PFC recruitment. With regard to the amplitude of the BOLD-signal, bad performers showed enhanced values in the left PFC. In addition, in the regions of reduced activation such as the parietal and striatal regions, the temporal dynamics were higher in bad performers. Based on the relation between BOLD response and neural firing with the amplitude of the BOLD signal reflecting gamma power and timing dynamics beta power, we argue that in bad performers, an enhanced left PFC recruitment hints towards an enhanced functioning of gamma-band activity in a compensatory manner. This was accompanied by reduced parieto-striatal activity, associated with increased and potentially conflicting beta-band activity.

scholarly journals Bilaterally Reduced Rolandic Beta Band Activity in Minor Stroke Patients

2021 ◽  
Author(s):  
Joshua P Kulasingham ◽  
Christian Brodbeck ◽  
Sheena Khan ◽  
Elisabeth B Marsh ◽  
Jonathan Z Simon
Keyword(s):  
Sensorimotor Cortex ◽  
Reaction Times ◽  
Minor Stroke ◽  
Button Press ◽  
Beta Band ◽  
Stroke Patients ◽  
Potential Biomarker ◽  
Beta Power ◽  
Motor Dexterity ◽  
Band Activity

Objective: Stroke patients with hemiparesis display decreased beta band (13-25 Hz) rolandic activity, correlating to impaired motor function. However, patients without significant weakness, with small lesions far from sensorimotor cortex, nevertheless exhibit bilateral decreased motor dexterity and slowed reaction times. We investigate whether these minor stroke patients also display abnormal beta band activity. Methods: Magnetoencephalographic (MEG) data were collected from nine minor stroke patients (NIHSS < 4) without significant hemiparesis, at ~1 and ~6 months postinfarct, and eight age-similar controls. Rolandic relative beta power during matching tasks and resting state, and Beta Event Related (De)Synchronization (ERD/ERS) during button press responses were analyzed. Results: Regardless of lesion location, patients had significantly reduced relative beta power and ERS compared to controls. Abnormalities persisted over visits, and were present in both ipsi- and contra-lesional hemispheres, consistent with bilateral impairments in motor dexterity and speed. Conclusions: Minor stroke patients without severe weakness display reduced rolandic beta band activity in both hemispheres, which may be linked to bilaterally impaired dexterity and processing speed, implicating global connectivity dysfunction affecting sensorimotor cortex. Significance: Rolandic beta band activity may be a potential biomarker and treatment target, even for minor stroke patients with small lesions far from sensorimotor areas.

scholarly journals Minimal phrase composition revealed by intracranial recordings

2021 ◽  
Author(s):  
Elliot Murphy ◽  
Oscar Woolnough ◽  
Patrick S Rollo ◽  
Zachary J Roccaforte ◽  
Katrien Segaert ◽  
...  
Keyword(s):  
Low Frequency ◽  
Phrase Structure ◽  
Superior Temporal Gyrus ◽  
Gamma Activity ◽  
Middle Temporal Gyrus ◽  
Beta Band ◽  
Pars Triangularis ◽  
Human Participants ◽  
Intracranial Electrode ◽  
Intracranial Recordings

The ability to comprehend meaningful phrases is an essential component of language. Here we evaluate a minimal compositional scheme - the 'red-boat' paradigm - using intracranial recordings to map the process of semantic composition in phrase structure comprehension. 18 human participants, implanted with penetrating depth or surface subdural intracranial electrode for the evaluation of medically refractory epilepsy, were presented with auditory recordings of adjective-noun, pseudoword-noun and adjective-pseudoword phrases before being presented with a colored drawing, and were asked to judge whether the phrase matched the object presented. Significantly greater broadband gamma activity (70-150Hz) occurred in temporo-occipital junction (TOJ) and posterior middle temporal gyrus (pMTG) for pseudowords over words (300-700ms post-onset) in both first- and second-word positions. Greater inter-trial phase coherence (8-12Hz) was found for words than for pseudowords in posterior superior temporal gyrus (pSTG). Isolating phrase structure sensitivity, we identified a portion of TOJ and posterior superior temporal sulcus (pSTS) that showed increased gamma activity for phrase composition than for non-composition, while left anterior temporal lobe (ATL) showed greater low frequency (2-15Hz) activity for phrase composition, likely coordinating distributed semantic representations. Greater functional connectivity between pSTS-TOJ and pars triangularis, and between pSTS-TOJ and ATL, was also found for phrase composition. STG, ATL and pars triangularis were found to encode anticipation of composition in the beta band (15-30Hz), and alpha (8-12Hz) power increases in ATL were also linked to anticipation. These results indicate that pSTS-TOJ appears to be crucial hub in the network responsible for the retrieval and computation of minimal phrases, and that anticipation of such composition is encoded in fronto-temporal regions.

scholarly journals Subthalamic beta-targeted neurofeedback speeds up movement initiation but increases tremor in Parkinsonian patients

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Shenghong He ◽  
Abteen Mostofi ◽  
Emilie Syed ◽  
Flavie Torrecillos ◽  
Gerd Tinkhauser ◽  
...  
Keyword(s):  
Reaction Times ◽  
Gamma Activity ◽  
Neurofeedback Training ◽  
Theta Band ◽  
Beta Band ◽  
Movement Initiation ◽  
Parkinsonian Tremor ◽  
Frequency Interaction ◽  
Motor Initiation ◽  
Band Activity

Previous studies have explored neurofeedback training for Parkinsonian patients to suppress beta oscillations in the subthalamic nucleus (STN). However, its impacts on movements and Parkinsonian tremor are unclear. We developed a neurofeedback paradigm targeting STN beta bursts and investigated whether neurofeedback training could improve motor initiation in Parkinson’s disease compared to passive observation. Our task additionally allowed us to test which endogenous changes in oscillatory STN activities are associated with trial-to-trial motor performance. Neurofeedback training reduced beta synchrony and increased gamma activity within the STN, and reduced beta band coupling between the STN and motor cortex. These changes were accompanied by reduced reaction times in subsequently cued movements. However, in Parkinsonian patients with pre-existing symptoms of tremor, successful volitional beta suppression was associated with an amplification of tremor which correlated with theta band activity in STN local field potentials, suggesting an additional cross-frequency interaction between STN beta and theta activities.

scholarly journals Adaptive Parameter Modulation of Deep Brain Stimulation Based on Improved Supervisory Algorithm

2021 ◽  
Vol 15 ◽  
Author(s):  
Yulin Zhu ◽  
Jiang Wang ◽  
Huiyan Li ◽  
Chen Liu ◽  
Warren M. Grill
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Supervisory Control ◽  
Control Algorithm ◽  
Beta Band ◽  
Rbf Network ◽  
Stimulation Parameters ◽  
Beta Power ◽  
Band Activity ◽  
Deep Brain

Clinically deployed deep brain stimulation (DBS) for the treatment of Parkinson’s disease operates in an open loop with fixed stimulation parameters, and this may result in high energy consumption and suboptimal therapy. The objective of this manuscript is to establish, through simulation in a computational model, a closed-loop control system that can automatically adjust the stimulation parameters to recover normal activity in model neurons. Exaggerated beta band activity is recognized as a hallmark of Parkinson’s disease and beta band activity in model neurons of the globus pallidus internus (GPi) was used as the feedback signal to control DBS of the GPi. Traditional proportional controller and proportional-integral controller were not effective in eliminating the error between the target level of beta power and the beta power under Parkinsonian conditions. To overcome the difficulties in tuning the controller parameters and improve tracking performance in the case of changes in the plant, a supervisory control algorithm was implemented by introducing a Radial Basis Function (RBF) network to build the inverse model of the plant. Simulation results show the successful tracking of target beta power in the presence of changes in Parkinsonian state as well as during dynamic changes in the target level of beta power. Our computational study suggests the feasibility of the RBF network-driven supervisory control algorithm for real-time modulation of DBS parameters for the treatment of Parkinson’s disease.

Changes in the Total Power of Beta and Theta Bands When Using EEG Biofeedback in Primary School-Age Children Having Difficulties with Voluntary Regulation

2020 ◽  
pp. 331-340
Author(s):  
Yuliya S. Dzhos ◽  
◽  
Irina A. Men’shikova ◽  
Keyword(s):  
Left Hemisphere ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
School Age Children ◽  
Total Power ◽  
Eeg Biofeedback ◽  
Beta Band ◽  
Bioelectric Activity ◽  
Voluntary Regulation ◽  
The Brain

This article presents the results of the study on spectral electroencephalogram (EEG) characteristics in 7–10-year-old children (8 girls and 22 boys) having difficulties with voluntary regulation of activity after 10 and 20 neurofeedback sessions using beta-activating training. Brain bioelectric activity was recorded in 16 standard leads using the Neuron-Spectrum-4/VPM complex. The dynamics was assessed by EEG beta and theta bands during neurofeedback. An increase in the total power of beta band oscillations was established both after 10 and after 20 sessions of EEG biofeedback in the frontal (p ≤ 0.001), left parietal (p ≤ 0.036), and temporal (p ≤ 0.003) areas of the brain. A decrease in the spectral characteristics of theta band oscillations was detected: after 10 neurofeedback sessions in the frontal (p ≤ 0.008) and temporal (p ≤ 0.006) areas of both hemispheres, as well as in the parietal area of the left hemisphere (p ≤ 0.005); after 20 sessions, in the central (p ≤ 0.004), frontal (p ≤ 0.001) and temporal (p ≤ 0.001) areas of both hemispheres, as well as in the occipital (p ≤ 0.047) and parietal (p ≤ 0.001) areas of the left hemisphere. The study into the dynamics of bioelectric activity during biofeedback using EEG parameters in 7–10-year-old children with impaired voluntary regulation of higher mental functions allowed us to prove the advisability of 20 sessions, as the increase in high-frequency activity and decrease in low-frequency activity do not stop with the 10th session. Changes in these parameters after 10 EEG biofeedback sessions are expressed mainly in the frontotemporal areas of both hemispheres, while after a course of 20 sessions, in both the frontotemporal and central parietal areas of the brain.

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