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Evaluation and objective characterisation of Brain function by quantitative EEG in normal controls and patients of major Depressive Disorder
Joint Event on 12th International Conference on Vascular Dementia and Dementia & 8th International Conference on Neurological Disorders and Stroke
March 14-16, 2019 | London, UK
Tamal Basak
Kolkata Medical College, India
Posters & Accepted Abstracts : J Brain Neurol
Abstract:
Introduction: EEG Signal Processing: Signal processing is the
enabling technology for the generation, transformation, and
interpretation of information. At different stages of time our
brain reacts differently. These brain signals used for various
purposes so that it is possible to study the functionalities of
brain properly by generating, transforming and interpreting the
collected signal. This process is known as brain signal processing.
Researchers have focused on brain signals since the beginning
of the last century and several attempts to understand and
interpret those signals have been proposed. Characteristics of
EEG Wave Bands: The EEG signal is traditionally divided into
spectral broad frequency bands related to EEG generators and
rhythms: delta, theta, alpha, and beta.
Objective:
• To evaluate and characterise brain electrophysiology by
quantitative EEG in normal controls and patients of major
depressive disorder
• To assess the efficiency of quantitative EEG in studying
brain electrophysiology
• To correlate qEEG parameters with clinical scoring
parameters in assessing brain electrophysiology in major
depressive disorder
• To evaluate the event related potential against visual and
auditory stimuli in major depressive disorder as compared
to normal controls
• To compare qEEG parameters in major depressive disorder
with that of in schizophrenia and obsessive compulsive
disorder
Methodology: Recording procedure: Regular EEG will be
recorded with routine Bipolar and Referential montages.
Along with that, a registry of the long latency event-related
potentials will be carried out with visual and auditory task
(Sternberg paradigm, 1966). Both memory task and reaction
time evaluation should be conducted. Data mining: The digital
data of the subject specific (both Control and Case) EEG time
series were retrieved and archived in specific drive destination,
in ASCII format. They were categorised in accordance with their
independent variable. Descriptive: Analysis of the amplitude,
duration, latency, phase of the different waves were first carried
out manually and with the cursor on the screen, identifying
each one of the waves visually, paying attention to both the
negative as well as positive inflections that occur sequentially
to the stimulation performed, with an analysis window of 1,000
msec from the onset of the visual stimulus. Necessary rejection
of the artefacts was carried out.
Objective: The digital data of the subject specific EEG time
series will be analysed using standard software algorithm in
MATLAB platform. Another option EEGLAB tool box, which is an
open source utility for analysis of EEG dynamics, can be used.
Statistical analysis: The statistical analysis of the results will
be performed by using different statistical designs; depending
upon the characteristics of the variables, and inter-relation
between them. Implications: Quantitative EEG (qEEG) deals
with the evaluation of the brain electrophysiology for objective
characterisation of the wave pattern and extraction of the
embedded information, utilising standard and customised
software tools and mathematical algorithm to undertake
various transformation procedures to decompose the complex
brain signals, both in time-domain and frequency-domain
analysis platform. Major Depressive Disorder (MDD) has
been associated with alterations in cognitive function as well
with memory and attention problems; the neurophysiological
mechanisms of which are still unknown. Characterisation of
brain electrophysiology by qEEG in MDD patients by correlation
of qEEG parameters with clinical scoring parameters will likely
elucidate the underlying mechanism.
Biography:
Tamal Basak is a final year medical student of Medical College, Kolkata, India. He has actively participated in the several health camp organised by South Asian Medical Students’ Association. He has participated in ICMR- STS programme in 2016.
E-mail: tbasak168@gmail.com
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