On July 6, 1924, the pioneering German psychiatrist Hans Berger, credited as the inventor of human electroencephalography (EEG), conducted the human EEG recording during a neurosurgical operation on a 17-year-old patient. The introduction of EEG marked a significant milestone in the progress of neuroscience, neurology, and psychiatry.
EEG is a cost-effective, secure, and user-friendly technique in clinical applications. With the continuous evolution of digitalization methods, quantitative EEG (qEEG) has emerged as an enticing tool in precision psychiatry. Precision psychiatry aims to formulate therapeutic strategies tailored to individuals with specific combinations of health issues, characteristics, strengths, and symptoms. This approach integrates basic and clinical neuroscience insights, clinical practice, and population-level data.
In commemorating the imminent 100th anniversary of Hans Berger's groundbreaking human EEG recording, this Research Topic is dedicated to spotlighting the clinical applications of EEG, evoked potentials, and related techniques as essential tools in daily psychiatric practice. The primary objective is to assemble a comprehensive body of research that elucidates the current evidence regarding using quantitative EEG in precision psychiatry.
Anticipated research papers are expected to provide an evidence-based foundation for incorporating these measures into the clinical evaluation of psychiatric patients. This includes differential diagnosis, identifying patient subgroups or treatment responders, monitoring, and integrating therapeutic modalities like TMS and neurofeedback. We aim to enhance our understanding of how quantitative EEG can contribute to more precise and effective psychiatric care.
The topics may include:
1. Diagnostic Accuracy Enhancement with QEEG: Investigating the extent to which the accuracy of psychiatric diagnoses improves through the integration of QEEG into daily psychiatric practice.
2. QEEG Changes in Response to Treatment: Examining alterations in QEEG, both resting and event-related potentials, following various treatments such as pharmacotherapy, psychotherapy, neurostimulation, and other EEG-based therapeutic interventions. Assessing whether these QEEG variables normalize with therapy.
3. Role of QEEG in Understanding Organic Etiology: Exploring how QEEG contributes to understanding the organic causes of psychiatric disorders, particularly in delineating medical and neurological factors underlying psychiatric symptoms.
4. QEEG- or ERP-Based Biomarkers: Identifying QEEG-based biomarkers for applications such as diagnosis and differential diagnosis and determining diagnostic sub-groups treatment responders from non-responders.
5. Pharmaco-EEG and Pharmacogenetic Profiles: Exploring the pharmaco-EEG area reflects the pharmacodynamic profile of medications, with a welcome integration of pharmacogenetic profiles.
6. Integration of Other Neuroimaging Techniques: Accepting analyses incorporating other neuroimaging techniques, such as MRI, fMRI, and PET, as long as QEEG is a central component of the study.
7. Computational Methods: Applications in psychiatric disorders of EEG non-linear and complexity analysis and Implementations of machine learning and deep learning to the EEG from psychiatric disorders as tools for diagnosis, prognosis, and treatment individualization.
A diverse range of contributions is encouraged, including Original Research, Systematic Review, Review, Clinical Trial, Case Report and Brief Research Report.
On July 6, 1924, the pioneering German psychiatrist Hans Berger, credited as the inventor of human electroencephalography (EEG), conducted the human EEG recording during a neurosurgical operation on a 17-year-old patient. The introduction of EEG marked a significant milestone in the progress of neuroscience, neurology, and psychiatry.
EEG is a cost-effective, secure, and user-friendly technique in clinical applications. With the continuous evolution of digitalization methods, quantitative EEG (qEEG) has emerged as an enticing tool in precision psychiatry. Precision psychiatry aims to formulate therapeutic strategies tailored to individuals with specific combinations of health issues, characteristics, strengths, and symptoms. This approach integrates basic and clinical neuroscience insights, clinical practice, and population-level data.
In commemorating the imminent 100th anniversary of Hans Berger's groundbreaking human EEG recording, this Research Topic is dedicated to spotlighting the clinical applications of EEG, evoked potentials, and related techniques as essential tools in daily psychiatric practice. The primary objective is to assemble a comprehensive body of research that elucidates the current evidence regarding using quantitative EEG in precision psychiatry.
Anticipated research papers are expected to provide an evidence-based foundation for incorporating these measures into the clinical evaluation of psychiatric patients. This includes differential diagnosis, identifying patient subgroups or treatment responders, monitoring, and integrating therapeutic modalities like TMS and neurofeedback. We aim to enhance our understanding of how quantitative EEG can contribute to more precise and effective psychiatric care.
The topics may include:
1. Diagnostic Accuracy Enhancement with QEEG: Investigating the extent to which the accuracy of psychiatric diagnoses improves through the integration of QEEG into daily psychiatric practice.
2. QEEG Changes in Response to Treatment: Examining alterations in QEEG, both resting and event-related potentials, following various treatments such as pharmacotherapy, psychotherapy, neurostimulation, and other EEG-based therapeutic interventions. Assessing whether these QEEG variables normalize with therapy.
3. Role of QEEG in Understanding Organic Etiology: Exploring how QEEG contributes to understanding the organic causes of psychiatric disorders, particularly in delineating medical and neurological factors underlying psychiatric symptoms.
4. QEEG- or ERP-Based Biomarkers: Identifying QEEG-based biomarkers for applications such as diagnosis and differential diagnosis and determining diagnostic sub-groups treatment responders from non-responders.
5. Pharmaco-EEG and Pharmacogenetic Profiles: Exploring the pharmaco-EEG area reflects the pharmacodynamic profile of medications, with a welcome integration of pharmacogenetic profiles.
6. Integration of Other Neuroimaging Techniques: Accepting analyses incorporating other neuroimaging techniques, such as MRI, fMRI, and PET, as long as QEEG is a central component of the study.
7. Computational Methods: Applications in psychiatric disorders of EEG non-linear and complexity analysis and Implementations of machine learning and deep learning to the EEG from psychiatric disorders as tools for diagnosis, prognosis, and treatment individualization.
A diverse range of contributions is encouraged, including Original Research, Systematic Review, Review, Clinical Trial, Case Report and Brief Research Report.