Features of brain electrical activity in adult patients with POLG-related disorders

Introduction. Epilepsy is a common feature of mitochondrial disorders, including those associated with mutations in the POLG gene. Nevertheless, brain electrical activity features of POLG-related disorders in adult patients have not been adequately studied. Objective. To study the features and characteristics of the electroencephalography (EEG) pattern in adult patients with POLG-related disorders. Material and methods. Eight patients were examined: 7 with SANDO (Sensory Ataxic Neuropathy, Dysarthria, Ophthalmoparesis) syndrome, and 1 with MEMSA (Myoclonic Epilepsy Myopathy Sensory Ataxia) syndrome; median age was 32.5 years. All patients underwent routine EEG monitoring using a 19-channel electroencephalograph according to the generally accepted method. Results. Epileptic seizures were found in 3 patients, for 2 of them – as the first manifestation of the disease. In 6 patients, theta waves predominated in the occipital regions. Of those 6 patients, in 5 bilateral synchronous bursts of theta and delta wave groups were identified being more prominent in the frontocentral regions; 4 patients had transient non-lateralized delta activity in the occipital and parieto-occipital brain regions. In all patients, opening eyes led to the depression of rhythms and burst suppression. After photostimulation, in 2 cases bilateral synchronous bursts of delta and theta wave groups were recorded predominantly in frontal lobes. In 3 patients during hyperventilation an increase in delta activity in the occipital lobes and bilateral synchronous bursts of delta wave groups were observed. Epileptiform activity was recorded in 2 cases. Conclusion. In adult patients with POLG-related disorders, regardless of the clinical manifestation, typical EEG features include generalized background slowing, theta and delta bursts in occipital lobes with their suppression by opening eyes.

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Effect of sevoflurane on high-frequency brain electrical activity

Translational Medicine ◽

10.18705/2311-4495-2019-6-6-23-28 ◽

2020 ◽

Vol 6 (6) ◽

pp. 23-28

Author(s):

N. B. Arkhipova ◽

M. V. Aleksandrov

Keyword(s):

Electrical Activity ◽

High Frequency ◽

Slow Wave Sleep ◽

Epileptiform Activity ◽

Temporal Cortex ◽

Epileptogenic Zone ◽

Brain Electrical Activity ◽

Surgery Outcome ◽

Wide Range ◽

Deep Brain

Background. In 30 % of cases with epilepsy, it qualifies as medically intractable and requires surgical treatment. The need for improvement of epilepsy surgery effectiveness demands updating of the preoperative assessment protocols. Intraoperative wide-range electrocorticography is a novel technique for defining resection volume in focal structural epilepsy. Combined analysis of high-frequency and epileptiform activity provides additional information and allows prognosticating of surgery outcome. However, consistent evaluation of intraoperative monitoring results is only possible when general anesthetic effect on brain electrical activity is taken into account.Objective. This study was aimed at evaluation of anesthetic gas sevoflurane effect on high-frequency brain electrical activity, recorded directly from the cortex or deep brain structures.Design and methods. Eight patients were included in this study (2 females, 6 males), aged 19 to 47, with a long-term epilepsy (disease duration 15 to 38 years). Prolonged electrocorticographic monitoring was indicated to these patients, combined with eloquent zones mapping in some cases. Patients were implanted with grid electrodes on frontal and temporal cortex, and deep brain Spencer electrodes into the mesial temporal lobe. Wide-range electrocorticography was recorded during slow-wave sleep and intraoperatively under sevoflurane anesthesia. Pathological high-frequency oscillations (pHFOs) rate was counted.Results. In seven patients pHFOs were recorded extraoperatively. Pathological HFO rate varied between 13 and 30 % (mean — 19 %). Distribution of pHFO did not change due to anesthesia effects. Mean background noise amplitude was significantly decreased intraoperatively (z = 2.45; p = 0.014). This effect facilitated visual marking of pHFOs. There were no trends in comparison between extraoperative and intraoperative pHFO rate.Conclusion. Well-controlled levels of general anesthesia obtained with sevoflurane (0,9-1,1 MAC) showed minimal effect on high-frequency brain electrical activity. This allows thorough analysis of wide-range electrocorticogiaphy without waking the patient and provides more information about the extension of the epileptogenic zone and its resection rate intraoperatively.

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Neurocortical electrical activity tomography in chronic schizophrenics

Arquivos de Neuro-Psiquiatria ◽

10.1590/s0004-282x2003000500002 ◽

2003 ◽

Vol 61 (3B) ◽

pp. 712-717 ◽

Cited By ~ 28

Author(s):

Heloisa Veiga ◽

Andréa Deslandes ◽

Mauricio Cagy ◽

Adriana Fiszman ◽

Roberto Airthon M. Piedade ◽

...

Keyword(s):

Electrical Activity ◽

Inferior Frontal Gyrus ◽

Statistical Parametric Mapping ◽

Brain Regions ◽

Brain State ◽

High Temporal Resolution ◽

Brain Electrical Activity ◽

Frequency Bands ◽

Theta Frequency ◽

The Right

Functional imaging of brain electrical activity was performed in 25 chronic medicated schizophrenics and 40 controls, analyzing the classical frequency bands (delta, theta, alpha, and beta) of 19-channel EEG during resting state to identify brain regions with deviant activity of different functional significances, using LORETA (Low Resolution Tomography) and SPM99 (Statistical Parametric Mapping). Patients differed from controls due to an excess of slow activity comprising delta + theta frequency bands (inhibitory pattern) located at the right middle frontal gyrus, right inferior frontal gyrus, and right insula, as well as at the bilateral anterior cingulum with a left preponderance. The high temporal resolution of EEG enables the specification of the deviations not only as an excess or a deficit of brain electrical activity, but also as inhibitory (delta, theta), normal (alpha), and excitatory (beta) activities. These deviations point out to an impaired functional brain state consisting of inhibited frontal and prefrontal areas that may result in inadequate treatment of externally or internally generated information.

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Fit Vs Faint: Assessing Work Causation in “Idiopathic Fall” Cases

Guides Newsletter ◽

10.1001/amaguidesnewsletters.2014.sepoct01 ◽

2014 ◽

Vol 19 (5) ◽

pp. 3-12

Author(s):

Lorne Direnfeld ◽

David B. Torrey ◽

Jim Black ◽

LuAnn Haley ◽

Christopher R. Brigham

Keyword(s):

Blood Flow ◽

Electrical Activity ◽

Loss Of Consciousness ◽

Brain Electrical Activity ◽

Medical Terminology ◽

Scientific Analysis ◽

Medical Causation ◽

The Individual ◽

The Brain ◽

Current Science

Abstract When an individual falls due to a nonwork-related episode of dizziness, hits their head and sustains injury, do workers’ compensation laws consider such injuries to be compensable? Bearing in mind that each state makes its own laws, the answer depends on what caused the loss of consciousness, and the second asks specifically what happened in the fall that caused the injury? The first question speaks to medical causation, which applies scientific analysis to determine the cause of the problem. The second question addresses legal causation: Under what factual circumstances are injuries of this type potentially covered under the law? Much nuance attends this analysis. The authors discuss idiopathic falls, which in this context means “unique to the individual” as opposed to “of unknown cause,” which is the familiar medical terminology. The article presents three detailed case studies that describe falls that had their genesis in episodes of loss of consciousness, followed by analyses by lawyer or judge authors who address the issue of compensability, including three scenarios from Arizona, California, and Pennsylvania. A medical (scientific) analysis must be thorough and must determine the facts regarding the fall and what occurred: Was the fall due to a fit (eg, a seizure with loss of consciousness attributable to anormal brain electrical activity) or a faint (eg, loss of consciousness attributable to a decrease in blood flow to the brain? The evaluator should be able to fully explain the basis for the conclusions, including references to current science.

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Identification of Brain Electrical Activity Related to Head Yaw Rotations

Sensors ◽

10.3390/s21103345 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3345

Author(s):

Enrico Zero ◽

Chiara Bersani ◽

Roberto Sacile

Keyword(s):

Electrical Activity ◽

Electrical Stimulus ◽

Head Movements ◽

Brain Electrical Activity ◽

Output Function ◽

Input Output ◽

Eeg Signals ◽

Head Turning ◽

Identification Technique ◽

The Brain

Automatizing the identification of human brain stimuli during head movements could lead towards a significant step forward for human computer interaction (HCI), with important applications for severely impaired people and for robotics. In this paper, a neural network-based identification technique is presented to recognize, by EEG signals, the participant’s head yaw rotations when they are subjected to visual stimulus. The goal is to identify an input-output function between the brain electrical activity and the head movement triggered by switching on/off a light on the participant’s left/right hand side. This identification process is based on “Levenberg–Marquardt” backpropagation algorithm. The results obtained on ten participants, spanning more than two hours of experiments, show the ability of the proposed approach in identifying the brain electrical stimulus associate with head turning. A first analysis is computed to the EEG signals associated to each experiment for each participant. The accuracy of prediction is demonstrated by a significant correlation between training and test trials of the same file, which, in the best case, reaches value r = 0.98 with MSE = 0.02. In a second analysis, the input output function trained on the EEG signals of one participant is tested on the EEG signals by other participants. In this case, the low correlation coefficient values demonstrated that the classifier performances decreases when it is trained and tested on different subjects.

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