CLINICAL EEG AND NEUROSCIENCE

Scope & Guideline

Pioneering Research in Electroencephalography

Introduction

Welcome to the CLINICAL EEG AND NEUROSCIENCE information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of CLINICAL EEG AND NEUROSCIENCE, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN1550-0594
PublisherSAGE PUBLICATIONS INC
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 1970 to 1985, from 1988 to 2024
AbbreviationCLIN EEG NEUROSCI / Clin. EEG Neurosci.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address2455 TELLER RD, THOUSAND OAKS, CA 91320

Aims and Scopes

The journal 'Clinical EEG and Neuroscience' is dedicated to advancing the understanding and application of electroencephalography (EEG) and related neurophysiological techniques in clinical settings. It focuses on the integration of neuroscience with clinical practice, emphasizing research that contributes to the diagnosis, treatment, and understanding of neurological and psychiatric disorders.
  1. Clinical Applications of EEG:
    The journal emphasizes the clinical utility of EEG in diagnosing and managing neurological disorders, such as epilepsy, traumatic brain injury, and neurodevelopmental disorders.
  2. Neurophysiological Research:
    Research on the neurophysiological underpinnings of cognitive and behavioral disorders, including studies on brain connectivity, neural oscillations, and event-related potentials.
  3. Innovative EEG Methodologies:
    The journal explores advancements in EEG technologies and methodologies, including high-density EEG, quantitative EEG (qEEG), and machine learning approaches for EEG data analysis.
  4. Neurofeedback and Rehabilitation:
    A focus on the therapeutic applications of EEG, particularly in neurofeedback for conditions such as ADHD and depression, along with rehabilitation strategies for brain injury.
  5. Interdisciplinary Perspectives:
    Encouragement of interdisciplinary research that combines EEG with neuroimaging, cognitive psychology, and clinical neuroscience to enrich understanding and treatment of brain disorders.
Recent publications in 'Clinical EEG and Neuroscience' indicate several emerging themes that reflect current trends in research and clinical practice. These themes highlight the journal's responsiveness to new challenges and advancements in the field.
  1. Integration of AI and Machine Learning:
    There is an increasing trend toward using artificial intelligence and machine learning to analyze EEG data, improving diagnostic accuracy and personalizing treatment approaches.
  2. Neurofeedback and Cognitive Enhancement:
    Research on neurofeedback as a therapeutic tool for various conditions, including ADHD, depression, and anxiety, is gaining momentum, reflecting a broader interest in cognitive enhancement and rehabilitation.
  3. Longitudinal Studies and Predictive Modeling:
    An emerging focus on longitudinal studies that track EEG changes over time to predict clinical outcomes, particularly in neurodegenerative diseases and recovery from brain injuries.
  4. Exploration of Comorbidities in Neuropsychiatric Disorders:
    Increasing attention to the comorbidity of neurological and psychiatric disorders, with studies examining how EEG findings correlate with multiple conditions, such as anxiety, depression, and substance use disorders.
  5. Neurophysiological Biomarkers for Mental Health:
    The identification of EEG-based biomarkers for mental health disorders is a growing area of research, aiming to enhance diagnostic precision and inform treatment strategies.

Declining or Waning

While 'Clinical EEG and Neuroscience' has maintained a robust focus on various aspects of EEG and neurophysiology, certain themes have shown a decline in prominence over recent years. This may reflect shifts in research priorities or the evolving landscape of clinical neuroscience.
  1. Traditional EEG Analysis Techniques:
    There appears to be a waning interest in basic, traditional EEG analysis methods as researchers increasingly adopt more sophisticated and computational approaches, such as machine learning and deep learning.
  2. Solely Descriptive Case Studies:
    The journal has seen a decrease in the publication of purely descriptive case studies, moving towards more robust experimental and clinical trial designs that provide stronger evidence for clinical practice.
  3. Focus on Single Disorder Studies:
    There is a decreasing trend in studies focusing on single disorders in isolation. Instead, there is a growing preference for studies that explore comorbidities and the interplay between different neurological and psychiatric conditions.
  4. Basic Neuroscience without Clinical Implications:
    Research that does not directly translate to clinical application or lacks immediate relevance to patient care is becoming less common as the journal seeks to emphasize clinical relevance.

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