Classification of Parkinson's disease with dementia using phase locking factor of event-related oscillations to visual and auditory stimuli.

In the last decades, machine learning approaches have been widely used to distinguish Parkinson's disease (PD) and many other neuropsychiatric diseases. They also speed up the clinicians and facilitate decision-making for several conditions with similar clinical symptoms. The current study attempts to detect PD with dementia (PDD) by event-related oscillations (EROs) during cognitive processing in two modalities, i.

Does transcranial direct current stimulation enhance cognitive performance in Parkinson's disease mild cognitive impairment? An event-related potentials and neuropsychological assessment study.

Background: Parkinson's disease-mild cognitive impairment (PD-MCI) is garnering attention as a key interventional period for cognitive impairment. Currently, there are no approved treatments for PD-MCI and encouraging results of transcranial direct current stimulation (tDCS) combined with other interventions have been proposed, though the efficacy and neural mechanisms of tDCS alone have not been studied in PD-MCI yet.

Objectives: The present double-blind, randomized, sham-controlled study assessed the effects of tDCS over the dorsolateral prefrontal cortex on cognitive functions via neuropsychological and electrophysiological evaluations in individuals with PD-MCI for the first time.

Evoked and induced EEG oscillations to visual targets reveal a differential pattern of change along the spectrum of cognitive decline in Alzheimer's Disease.

In recent years, quantitative variables derived from the electroencephalogram (EEG) attract an increasing interest for the evaluation of neurodegenerative diseases, as EEG registers the neuro-electric activity with a high temporal resolution and provides a cost-effective and easily accessible, non-invasive method. Event-related oscillations (EROs) as oscillatory responses in the EEG to specific events further provide the possibility to track the cognitive decline in a task-specific manner. Current study in search for potential ERO biomarkers to distinguish different stages of cognitive decline along the Alzheimer's Disease (AD) continuum re-analyzed a combined set of data collected and analyzed in previous studies by Başar and coworkers.

Prediction of treatment resistance in obsessive compulsive disorder patients based on EEG complexity as a biomarker.

Objective: This study aimed to identify an Electroencephalography (EEG) complexity biomarker that could predict treatment resistance in Obsessive compulsive disorder (OCD) patients. Additionally, the statistical differences between EEG complexity values in treatment-resistant and treatment-responsive patients were determined. Moreover, the existence of correlations between EEG complexity and Yale-Brown Obsessive Compulsive Scale (YBOCS) score were evaluated.

Predictive Value of Slow and Fast EEG Oscillations for Methylphenidate Response in ADHD.

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder and is characterized by symptoms of inattention and/or hyperactivity and impulsivity. In the current study, we obtained quantitative EEG (QEEG) recordings of 51 children aged between 6 and 12 years before the initiation of methylphenidate treatment. The relationship between changes in the scores of ADHD symptoms and initial QEEG features (power/power ratios values) were assessed.

High Frequencies in QEEG Are Related to the Level of Insight in Patients With Schizophrenia.

Lack of insight is a neurocognitive problem commonly encountered in patients with psychotic disorders that negatively affects treatment compliance and prognosis. Measurement of insight is based on self-report scales, which are limited due to subjectivity. This study aimed to determine the correlation between resting state beta and gamma power in 23 patients with schizophrenia and insight.

Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion.

Lithium excessively enhances event related beta oscillations in patients with bipolar disorder.

Background: Previous resting-state electroencephalography studies have consistently shown that lithium enhances delta and theta oscillations in default mode networks. Cognitive task based networks differ from resting-state networks and this is the first study to investigate effects of lithium on evoked and event-related beta oscillatory responses of patients with bipolar disorder.

Methods: The study included 16 euthymic patients with bipolar disorder on lithium monotherapy, 22 euthymic medication-free patients with bipolar disorder and 21 healthy participants.