Quantitative Electroencephalogram Standardization: A Sex- and Age-Differentiated Normative Database

We describe the utility of a standardized index (Z-score) in quantitative EEG (QEEG) capable of when referenced to a resting-state, sex- and age-differentiated QEEG normative database (ISB-NormDB). Our ISB-NormDB comprises data for 1,289 subjects (553 males, 736 females) ages 4.5 to 81 years that met strict normative data criteria. A de-noising process allowed stratification based on QEEG variability between normal healthy men and women at various age ranges. The ISB-NormDB data set that is stratified by sex provides a unique, highly accurate ISB-NormDB model (ISB-NormDB: ISB-NormDB-Male, ISB-NormDB-Female). To evaluate the trends and accuracy of the ISB-NormDB, we used actual data to compare Z-scores obtained through the ISB-NormDB with those obtained through a traditional QEEG normative database to confirm that basic trends are maintained in most bands and are sensitive to abnormal test data. Finally, we demonstrate the value of our standardized index of QEEG, and highlight it’s capacity to minimize the confounding variables of sex and age in any analysis.

501 - Prediction of Mild Cognitive Impairment (MCI) progression to Alzheimer Disease (AD) or Dementia with Lewy Bodies (DLB): Is this possible neuropsychologically?

Objective:Aim of the present review study was to describe and compare the neurocognitive features of MCI which could predict its progression to DLB vs AD.Background:Progression of MCI to AD or DLB is a relatively recent field of study with emphasis on the clinical or neuropsychological features of MCI which could potentially predict its progression to specific types of dementia.Methods:A literature review in the Pubmed database has been made, after the year 2005, using the key- words: neuropsychological assessment; MCI; AD; DLB; progression to dementia. Seventeen relevant articles have been found.Results:Data from most studies supports that, in MCI, impairment in executive, attentional and visuospatial functions, as well as letter fluency and fluctuating concentration are mainly related to progression to DLB. In contrast, prominent episodic and recognition memory deficits are mostly found in MCI which progresses in AD. Furthermore, non-amnestic MCI has been related most often to progression in DLB, whereas the amnestic type to AD, although memory loss may not necessarily predict the development of AD. Nevertheless, fewer studies suggest that MCI-DLB is related to cognitive profile similar to that of MCI-AD, while cognitive scoring alone does not accurately predict MCI-DLB vs MCI-AD. Interestingly, quantitative electroencephalogram has been found to help in predicting the progression of MCI to DLB, while preservation of hippocampal volume is associated with increased risk of DLB vs AD, especially in non-amnestic MCI. Moreover, specific patterns on neuroimaging MCI may predict progression to AD in contrast to DLB.Conclusions:Predicting the progression of MCI to AD or DLB based on neuropsychological profiles is challenging and useful for early therapeutic interventions. More studies are needed, since there are some conflicting findings and, at present, the combination of clinical symptoms with neurocognitive assessment and neuroimaging is the ideal method for the prediction of MCI progression to various types of dementia.

Quantifying Conventional Electroencephalogram Recordings and Examining its Output Computation with a Quantitative Electroencephalogram

Quantitative electroencephalogram enables mathematical analysis of neurological recordings while conventional electroencephalogram lacks the mathematical output; hence, its usage is limited to neurological experts. This study was to determine if quantified conventional electroencephalogram recordings were compatible and comparable with quantitative electroencephalogram recordings. A group of post-call doctors was recruited and subjected to an EEG recording using a conventional electroencephalogram followed by a quantitative electroencephalogram device. The patterns and quantified recording results were compared. A comparative analysis of the two recording sets did not find differences in the recording patterns and statistical analysis. The findings promoted the use of a readily available conventional electroencephalogram in quantitative brain wave studies and have cleared potential compatibility bias towards data merging.

Quantitative Electroencephalogram in Pediatric Intensive Care Unit in Three Different Clinical Scenarios

Although clinical judgement and sedation scales are primarily used in intensive care units (ICUs) to manage sedation, adjunctive data are needed to direct therapy with sedative and hypnotic agents to prevent side effects and long-term sequelae. In this report, we describe three cases where we used quantitative electroencephalogram (qEEG) data in a pediatric ICU (PICU); to manage these specific clinical situations and to identify the limitations of the qEEG data, two patients were admitted for post–cardiac arrest care and the third was admitted for status epilepticus. In post–cardiac arrest patients, qEEG was mainly used for monitoring depth of sedation and drug titration. Unnecessary use of high-drug doses was prevented, and monitoring also helped to guide clinical intervention for the management of seizure activity. In the patient with status epilepticus, qEEG data on burst suppression and depth of sedation were used. In this report, we describe three different cases where we used qEEG data in a PICU, to give insight on the use of data in specific clinical situations and to describe the limitations of the qEEG data monitoring system.

Improving Clinical, Cognitive, and Psychosocial Dysfunctions in Patients with Schizophrenia: A Neurofeedback Randomized Control Trial

Objectives. The aim of this study was to use neurofeedback (NF) training as the add-on therapy in patients with schizophrenia to improve their clinical, cognitive, and psychosocial condition. The study, thanks to the monitoring of various conditions, quantitative electroencephalogram (QEEG) and brain-derived neurotrophic factor (BDNF), was supposed to give an insight into mechanisms underlying NF training results. Methods. Forty-four male patients with schizophrenia, currently in a stable, incomplete remission, were recruited into two, 3-month rehabilitation programs, with standard rehabilitation as a control group (R) or with add-on NF training (NF). Pre- and posttherapy primary outcomes were compared: clinical (Positive and Negative Syndrome Scale (PANSS)), cognitive (Color Trails Test (CTT), d2 test), psychosocial functioning (General Self-Efficacy Scale (GSES), Beck Cognitive Insight Scale (BCIS), and Acceptance of Illness Scale (AIS)), quantitative electroencephalogram (QEEG), auditory event-related potentials (ERPs), and serum level of BDNF. Results. Both groups R and NF improved significantly in clinical ratings (Positive and Negative Syndrome Scale (PANSS)). In-between analyses unveiled some advantages of add-on NF therapy over standard rehabilitation. GSES scores improved significantly, giving the NF group of patients greater ability to cope with stressful or difficult social demands. Also, the serum-level BDNF increased significantly more in the NF group. Post hoc analyses indicated the possibility of creating a separate PANSS subsyndrome, specifically related to cognitive, psychosocial, and BDNF effects of NF therapy. Conclusions. Neurofeedback can be effectively used as the add-on therapy in schizophrenia rehabilitation programs. The method requires further research regarding its clinical specificity and understanding mechanisms of action.

Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination

This paper aimed to explore the clinical value of combined adoption of magnetic resonance diffusion tensor imaging (DTI) and quantitative electroencephalogram (QEEG) in assessing microstructure changes and mild neurocognitive dysfunction in patients with white matter demyelination. 128 cases of white matter demyelination admitted to the hospital from October 2018 to October 2019 were rolled into the research group, and 100 healthy patients physically examined during the same period were rolled into the control (ctrl) group. QEEG and magnetic resonance DTI examinations were performed for all patients. The wave power of δ, θ, α, and β and the ratio of α/θ and (δ + θ)/(α + β) were recorded. The FA values of white matter fibers in different brain areas were measured, and the Montreal Cognitive Assessment (MoCA) and Addenbrooke Cognitive Evaluation rating (ACE-R) were adopted to assess the neurocognitive function of patients. It was found that the dominant frequency of each brain area in the research group was 8-9 Hz slow α wave. In contrast with the ctrl, the α wave and α/θ values in the research group were lower, while θ wave and δ + θ/α + β values were higher ( P < 0.05 ); the scores of ACE-R and MoCA were lower ( P < 0.01 ); the fractional anisotropy (FA) values of the right frontal lobe white matter (0.335 ± 0.068), the left temporal lobe white matter (0.391 ± 0.032), and the corpus callosum knee white matter (0.658 ± 0.053) were lower ( P < 0.05 ). The FA values of these three areas were positively correlated with attention and calculation, memory, and memory of MoCA scale, respectively ( P < 0.05 ). The FA value of the right frontal white matter was positively correlated with the attention and calculation score of the ACE-R scale ( P < 0.05 ). In conclusion, magnetic resonance DTI combined with QEEG could reflect the microstructural changes of white matter, which may be associated with mild neurocognitive impairment. The primary objective of the study was to explore the clinical value of combined adoption of magnetic resonance DTI and QEEG in assessing microstructure changes and mild neurocognitive dysfunction in patients with white matter demyelination, expected to provide a theoretical basis for the treatment of white matter demyelination.