[Eeglablist] EEG-Based Biomarkers for Dementia

Francesca Miraglia fra.miraglia at gmail.com
Wed Nov 22 03:00:50 PST 2017

Dear colleagues,
is now online the call for Papers for a special issue on EEG-Based
Biomarkers for Dementia, published on Disease Markers (Impact Factor 2.348)

Call for Papers

The diagnosis and treatment of dementia has become a growing and worrying
public health problem in both developed and developing countries. Research
to identify reliable markers is very active and there is currently a
consensus among scientists that a presymptomatic variable duration stage is
characteristic of most dementias. Starting treatment only when the symptoms
appear is probably too late to have full effectiveness of medications able
to control disease progression. Consequently, there is a pressing need for
low-cost, high-sensitive, and high-specific biomarkers for early
identification of individuals at risk of developing dementia within a few
years. The analysis of electroencephalographic signals is potentially one
of the best candidates because EEG equipment is cheap and safe. More
importantly, EEG markers may probe the neurophysiological “reserve” in
patients with dementing disorders. It was defined as the residual ability
of the brain to ensure the synchronization of neural activity at different
spatial scales and frequencies from small cellular populations to large
regions and the coordination of that synchronization across subcortical and
cortical neural networks. Unfortunately, the vast majority of the
scientific community does not accept EEG signal analysis as a reliable
topographic marker for dementia, although a growing number of published
studies show the opposite. Such wary attitude could be due to the fact that
even though there is a wide range of innovative approaches to signal
analysis; so far there has been little effort to explore their
complementarity and integrate them all in a stronger and more reliable

To step up the discussion on EEG markers and dementia, the present special
issue will solicit manuscripts reporting studies aimed at advancing the
field of EEG-based biomarkers along different paths. Submissions related to
the assessment of the neurophysiological “reserve” are especially welcome,
mainly those markers derived from resting state EEG rhythms. The submission
of studies aiming to probe the cortical neural
synchronization/desynchronization at given frequency bands and reflecting
neurophysiological mechanisms underpinning local cortical arousal in quiet
wakefulness and vigilance will be particularly appreciated. Likewise,
manuscripts supporting the importance of dementia biomarkers based on
task-related EEG are also welcome, as well as those exploring functional
cortical connectivity in both resting state and task-related EEG. Finally,
submission of review articles describing the current state of the art is
highly encouraged and even judiciously designed studies show negative

Potential topics include but are not limited to the following:

   - New dementia EEG biomarkers
   - Innovations in low-cost EEG measurement for dementia diagnostics
   - Unsupervised or semisupervised extraction of EEG biomarkers
   - Multimodal (EEG + other modalities) biomarkers
   - Biomarkers of MCI progression to AD
   - Confounding factors in EEG biomarker research
   - Biomarker-based neurofeedback for mental training
   - EEG-based correlates of treatment outcome/progress prediction
   - Multimarker strategy (EEG, circulating biomarkers, and clinical
   variables) for dementia
   - Diagnostic role and predictive value of EEG and other imaging
   modalities for dementia

Authors can submit their manuscripts through the Manuscript Tracking System
Submission Deadline Friday, 20 April 2018
Publication Date September 2018

Papers are published upon acceptance, regardless of the Special Issue
publication date.

Impact Factor 2.348


Ing. Francesca Miraglia, PhD

BCLab Brain Connectivity LABoratory for cognitive neurosciences
IRCCS San Raffaele Pisana Roma

Via Val Cannuta, 247 -  00166 Roma
+39 0652253767
+39 3281512811
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