Comparative analysis of the electroencephalogram in patients with Alzheimer's disease, diffuse axonal injury patients and healthy controls using LORETA analysis

An Integrative Review about Electrophysiological Biomarkers of Cognitive Impairment in Alzheimer's Disease: A Developing Relationship

Background: Electrophysiological biomarkers are being examined as potential diagnostic measures of cognitive impairment and its manifestations for psychiatric nurses' use in the care of Alzheimer's disease (AD). However, there is no integrative review describing the themes from the current research about electrophysiological biomarkers and the developing relationship among the themes. Characterizing this developing relationship is imperative for any possible integration of biomarkers into the care of AD by psychiatric nurses. Objective: The purpose of this integrative review is to identify themes from the current research about electrophysiological biomarkers of AD and the developing relationship among the themes, the conceivable relational premise for psychiatric nurses to integrate electrophysiological biomarkers into the screening, assessment, diagnosis, and treatment of AD for the care of persons with AD. Methods: A literature search was executed with PUBMED (accessing Medline and Elsevier) and CINAHL databases that focused on studies about electrophysiological biomarkers of AD from 2015 to 2022. Twenty-seven peer-reviewed studies met this review's inclusion criteria. Results: Five themes emerged: (1) assessing/screening, (2) assessment differential, (3) diagnosing, (4) diagnostic accuracy, and (5) treating. These themes related sequentially and linearly, establishing a developing relationship about the risk, the onset, and the progression of AD. Discussion: Electrophysiological biomarkers associated to cognitive impairment in AD, supporting the accepted understanding of the symptoms of AD. Changes in behavior and functioning were not examined, limiting the possible integration of electrophysiological biomarkers. Further investigations are warranted with an expansion of the clinical symptoms and diverse study populations.

EEG resting-state networks in Alzheimer's disease associated with clinical symptoms

Alzheimer's disease (AD) is a progressive neuropsychiatric disease affecting many elderly people and is characterized by progressive cognitive impairment of memory, visuospatial, and executive functions. As the elderly population is growing, the number of AD patients is increasing considerably. There is currently growing interest in determining AD's cognitive dysfunction markers. We used exact low-resolution-brain-electromagnetic-tomography independent-component-analysis (eLORETA-ICA) to assess activities of five electroencephalography resting-state-networks (EEG-RSNs) in 90 drug-free AD patients and 11 drug-free patients with mild-cognitive-impairment due to AD (ADMCI). Compared to 147 healthy subjects, the AD/ADMCI patients showed significantly decreased activities in the memory network and occipital alpha activity, where the age difference between the AD/ADMCI and healthy groups was corrected by linear regression analysis. Furthermore, the age-corrected EEG-RSN activities showed correlations with cognitive function test scores in AD/ADMCI. In particular, decreased memory network activity showed correlations with worse total cognitive scores for both Mini-Mental-State-Examination (MMSE) and Alzheimer's Disease-Assessment-Scale-cognitive-component-Japanese version (ADAS-J cog) including worse sub-scores for orientation, registration, repetition, word recognition and ideational praxis. Our results indicate that AD affects specific EEG-RSNs and deteriorated network activity causes symptoms. Overall, eLORETA-ICA is a useful, non-invasive tool for assessing EEG-functional-network activities and provides better understanding of the neurophysiological mechanisms underlying the disease.

Early Schizophrenia and Bipolar Disorder Patients Display Reduced Neural Prepulse Inhibition

BACKGROUND

Altered sensorimotor gating has been demonstrated by Prepulse Inhibition (PPI) tests in patients with psychosis. Recent advances in signal processing methods allow assessment of neural PPI through electroencephalogram (EEG) recording during acoustic startle response measures (classic muscular PPI). Simultaneous measurements of muscular (eye-blink) and neural gating phenomena during PPI test may help to better understand sensorial processing dysfunctions in psychosis. In this study, we aimed to assess simultaneously muscular and neural PPI in early bipolar disorder and schizophrenia patients.

METHOD

Participants were recruited from a population-based case-control study of first episode psychosis. PPI was measured using electromyography (EMG) and EEG in pulse alone and prepulse + pulse with intervals of 30, 60, and 120 ms in early bipolar disorder (n = 18) and schizophrenia (n = 11) patients. As control group, 15 socio-economically matched healthy subjects were recruited. All subjects were evaluated with Rating Scale, Hamilton Rating Scale for Depression, and Young Mania Rating Scale questionnaires at recruitment and just before PPI test. Wilcoxon ranked sum tests were used to compare PPI test results between groups.

RESULTS

In comparison to healthy participants, neural PPI was significantly reduced in PPI 30 and PPI60 among bipolar and schizophrenia patients, while muscular PPI was reduced in PPI60 and PPI120 intervals only among patients with schizophrenia.

CONCLUSION

The combination of muscular and neural PPI evaluations suggested distinct impairment patterns among schizophrenia and bipolar disorder patients. Simultaneous recording may contribute with novel information in sensory gating investigations.

A Review of Methods of Diagnosis and Complexity Analysis of Alzheimer's Disease Using EEG Signals

This study will concentrate on recent research on EEG signals for Alzheimer's diagnosis, identifying and comparing key steps of EEG-based Alzheimer's disease (AD) detection, such as EEG signal acquisition, preprocessing function extraction, and classification methods. Furthermore, highlighting general approaches, variations, and agreement in the use of EEG identified shortcomings and guidelines for multiple experimental stages ranging from demographic characteristics to outcomes monitoring for future research. Two main targets have been defined based on the article's purpose: (1) discriminative (or detection), i.e., look for differences in EEG-based features across groups, such as MCI, moderate Alzheimer's disease, extreme Alzheimer's disease, other forms of dementia, and stable normal elderly controls; and (2) progression determination, i.e., look for correlations between EEG-based features and clinical markers linked to MCI-to-AD conversion and Alzheimer's disease intensity progression. Limitations mentioned in the reviewed papers were also gathered and explored in this study, with the goal of gaining a better understanding of the problems that need to be addressed in order to advance the use of EEG in Alzheimer's disease science.

Alzheimer's Disease Diagnosis and Severity Level Detection Based on Electroencephalography Modulation Spectral "Patch" Features

Over the last two decades, electroencephalography (EEG) has emerged as a reliable tool for the diagnosis of cortical disorders such as Alzheimer's disease (AD). Typically, resting-state EEG (rsEEG) signals have been used, and traditional frequency bands (delta, theta, alpha, beta and gamma) have been explored. Recent studies, however, have suggested that non-conventional bands may lead to improved diagnostic performance. In this work, we propose a new type of features derived from the 2-dimensional modulation spectral domain representation of the rsEEG signal in order to characterize the neuromodulatory deficit emergent with AD. The proposed features are computed as the power in specific "patches" or regions of interest in the power modulation spectrogram, which are shown to be highly discriminant of AD severity levels. The proposed features were compared with traditional features used in the rsEEG AD monitoring literature. Results showed the proposed features not only achieving improved performance at discriminating between healthy normal elderly controls (Nold) and AD patients with varying severity levels, but also at monitoring severity levels (i.e., mild AD versus moderate AD). Moreover, the proposed features were shown to outperform traditional rsEEG features. Finally, we validated the biological origin of the proposed features by using source localization and comparing the obtained results with ones reported in the AD literature.

Transcranial Photobiomodulation Therapy in the Cognitive Rehabilitation of Patients with Cranioencephalic Trauma

Objective: This research evaluated the hemodynamic conditions before and after the transcranial photobiomodulation therapy (PBMT) and investigated neurocognitive changes before and after treatment. Background: Traumatic brain injury (TBI) is the major cause of morbidity and mortality among individuals 21-60 years old and causes ∼500,000 people to be hospitalized in Brazil annually. Some survivors develop an irreversible decrease in neurological function, and the mortality rate is as high as 70% in severe cases. PBMT is an alternative to treat secondary injuries due to TBI. Methods: This multidisciplinary clinical study was carried out on 10 chronic adult patients with severe TBI, who were treated with PBMT with an optical device containing 13 sets of 4 light emitting diodes, and underwent hemodynamic transcranial Doppler and neuropsychological evaluation at three different times: pre-PBMT, post-PBMT (after a week), and late-PBMT, which occurred 3 months after the last session. The patients received PBMTs three times a week, for 6 weeks. PBMTs were performed for 18 sessions for 6 weeks and 30 min per session. Results: The results found an alteration in the cerebral blood flow (CBF) as well as a consequent increase of the cerebral oxygenation that helped to improve the cerebral function. Conclusions: The PBMT contributed to increased CBF, evidenced mainly by the increased left peak systolic velocity, which consequently increased the hemodynamic response after the PBMT and impacts on the peripheral cerebral perfusion contributing to improved cerebral function.

Global Synchronization Index as an Indicator for Tracking Cognitive Function Changes in a Traumatic Brain Injury Patient: A Case Report

Traumatic brain injury is a main cause of long-term neurological disability, and many patients suffer from cognitive impairment for a lengthy period. Cognitive impairment is a fatal malady to that limits active rehabilitation, and functional recovery in patients with traumatic brain injury. In severe cases, it is impossible to assess cognitive function precisely, and severe cognitive impairment makes it difficult to establish a rehabilitation plan, as well as evaluate the course of rehabilitation. Evaluation of cognitive function is essential for establishing a rehabilitation plan, as well as evaluating the course of rehabilitation. We report a case of the analysis of electroencephalography with global synchronization index and low-resolution brain electromagnetic tomography applied, for evaluation of cognitive function that was difficult with conventional tests, due to severe cognitive impairment in a 77-year-old male patient that experienced traumatic brain injury.