Akademik Veri Yönetim Sistemi
Biomedical Signal Processing and Control, cilt.76, 2022 (SCI-Expanded, Scopus)
https://www.sciencedirect.com/science/article/pii/S1746809422001483
ABSTRACT
The goal of the present study is to propose the use of
global connectivity measures as quantitative indicators of long-term medication
in pediatric patients with Attention-Deficit-Hyperactivity Disorder, combined
type (ADHD-C). For this purpose, graph theoretical brain connectivity indices
are computed from connectivity estimations across eyes-opened resting-state EEG
recordings measured before and after the treatment with osmotic release oral
system-methylphenidate for a month in 18 boys (aged between 7–12 years). In
order to present the reliable results, neurofunctional correlations are firstly
estimated in time (Pearson Correlation (PC), Spearman Correlation), frequency
(Directed Transfer Function, Partial Directed Coherence) and phase (Phase
Locking Value, Phase Lag Index) domains in between short segments of 2sec over
single trials of 1min. Later, transitivity, clustering coefficients,
assortativity, global efficiency and modularity are computed from EEG based
connectivity matrices produced by each approach. Since the highest
classification accuracy of 83.79% is provided by PC, statistical tests (one-way
Anova, pair-wise multiple comparison) and step-wise logistic regression
modelling are all examined to detect significant differences between pre- and
post- treatment relevant connectivity measures. Statistical boxplots are also
shown, as well. Overall results reveal that global brain connectivity can be
increased by long-term medication in pediatric ADHD-C in terms of increased
segregation & resilience. This is the first study to demonstrate that
long-term medication can normalize the functional brain connectivity in ADHD,
which is characterized by decreased connectivity compared to controls.
DISCISION AND CONCLUSION
In the present study,
resting-state eyes-opened EEG series were recorded from 18 boys diagnosed with
ADHD-C before medication phase. They had a specified treatment as OROS-MPH for
a month. Then post-treatment resting-state eyes-opened EEG series were also
recorded from them. Graph Theoretic brain network indices were estimated from
both pre- and post-treatment related EEG recordings with respect to un-directed
weighted adjacency matrixes that are extracted from brain dependency and
connectivity estimations by PC, SC, PLV, PLI, DTF and PDC. In obtaining
adjacency matrixes, threshold was 60% of maximum value in dependency matrix of
interest in each short EEG segment of 2sec over trial
of 1min.
The resulting
estimations were investigated through both classifications with SVMs and statistical
tests including one-way Anova and pair-wise multiple comparison. Finally,
graphical box-plots of brain network indices were shown in pre- and
post-treatment recordings in accordance with PC that provided superior results.
Regarding step-wise logistic regression modelling, brain modularity (Q) is
found to be less sensitive to treatment with OROS-MPH. The highest
classification performance of 83.79% was obtained
when three brain network indices (𝑇,CC and r) were combined as feature set.
The lowest statistical p-values were obtained for these three indices.
Combining
quantitative results reveal that functional brain segregation (T and CC)
and resilience (r) indices are mostly influenced by OROS-MPH, while
integration and modularity indices are less affected by medication in boys with
ADHD-C. However, the statistical box-plots on brain network indices showed the
following brief results:
·
increased T indicates
stronger connectivity of cortical regions to neighbors,
From methodological
point of view, statistical correlation method, PC provided the best results to
compute brain dependency values that provide strong estimations in brain
network measures from resting state eyes-opened surface EEG series. PC is found
to be superior to both phase domain functional synchronization methods (PLV,
PLI) and frequency domain effective connectivity methods (DTF, PDC).
In conclusion, our
hypothesis is confirmed by the current results obtained by using time-domain
dependency approach, PC in full-band eyes-opened resting state EEG segments.
The past neuroimaging studies comparing patients and controls have a common
emphasis on the decreased connectivity of the brain in ADHD. Therefore, the
present findings are important contributions to the literature to show that the
long-term medication increases functional connectivity in boys with
ADHD-C. Moreover, graph theoretical analysis driven by default-mode EEG based
statistical correlations have provided more insight to global connectivity in
terms of integration, segregation, modularity and resilience in observing the
impact of OROS-MPH in ADHD-C. Both segregation and resilience are increased by
medication in accordance with the best results. From computational psychiatric
point of view, quantitative visual results reveal that OROS-MPH clearly
influence functional brain segregation and resilience in boys with ADHD-C. In
detail, OROS-MPH provide the followings: (1) functional connectivity between cortical
regions becomes more stronger, (2) neuronal undirected information flow becomes
more efficient and (3) the number of interconnected regional neural populations
that are required to form a resilient that provides information spread across the
whole cortex. In future work, we are plan to record emotional EEG series from
three groups of the patients (ADHD-I, ADHD-HI, ADHD-C) in response to affective
static pictures (unpleasant vs pleasant) in both pre- and post- treatment
periods in estimating brain network measures.
In the present study,
pre- and post-treatment related resting-state EEG based global connectivity
measures are estimated in several domains and then the best results are
discussed with respect to specified network functions defined as segregation,
integration and resilience assuming that functional connectivity is decreased
in ADHD according to the past findings in ADHD research. Studies on how
OROS-MPH changes regional FC in children with ADHD, supported by functional neuroimaging modalities, have
shown that treatment normalizes the brain [56]. Unlike several structural studies, numerous fMRI
studies have been conducted on MPH’s effects [57]. These
studies can be divided into those investigating resting-state brain activation and
those investigating task-related brain activation. Task-related studies have
identified specific areas of activation with MPH treatment in the parietal
areas during tasks involving attention, error monitoring, and interference inhibition [58], in the
inferior frontal cortex during selective attention and response
inhibition [59], and in
the striatum during tasks involving reward and response inhibition [60]. Studies
with tasks evaluating cognitive control have
shown that MPH improves the ability to inhibit inappropriate responses in
favour of more appropriate ones by increasing activation in frontostriatal
circuits and ultimately normalizes brain activation patterns and executive
functions during the task in children with ADHD with MPH treatment [61], [62]. One
study performed with fMRI during the Stroop test showed that MPH treatment
improved suppression of DMN activity
in the ventral anterior cingulate and posterior cingulate cortices [63]. There is
enough evidence to suggest that the poorly switched of mind-wandering functions
of DMN at the time of cognitive task may be a cause of distractibility
and impulsivity in
children with ADHD and that increasing in DMN deactivation may play a role in
the clinical improvement achieved with MPH treatment [64], [65], [56]. In the light of all these data, it can be
concluded that MPH treatment has a clear protective and normalizing effect on
the brain. Functional positive changes observed with MPH treatment, especially
in the prefrontal cortex, and the improvement in DMN deactivation at the time
of cognitive loading can be considered as evidence of the normalizing effect.
The present study can minimize the relative factors that led to several
inconsistency among the findings in the literature such that EEG based graph
theoretical analysis of default-mode brain network is independent of both total
number of electrodes and electrode placement on scalp surface.