Akademik Veri Yönetim Sistemi
COGNITIVE NEURODYNAMICS, cilt.17, sa.2, ss.331-344, 2023 (SCI-Expanded)
https://link.springer.com/article/10.1007/s11571-022-09843-w
ABSTRACT:
In
the present study, new findings reveal the close association between graph
theoretic global brain connectivity measures and cognitive abilities the
ability to manage and regulate negative emotions in healthy adults. Functional
brain connectivity measures have been estimated from both eyes-opened and
eyes-closed resting-state EEG recordings in four groups including individuals
who use opposite Emotion Regulation Strategies (ERS) as follow: While 20
individuals who frequently use two opposing strategies, such as rumination and
cognitive distraction, are included in 1st group, 20 individuals who don't use
these cognitive strategies are included in 2nd group. In 3rd and 4th groups,
there are matched individuals who use both Expressive Suppression and Cognitive
Reappraisal strategies together frequently and never use them, respectively.
EEG measurements and psychometric scores of individuals were both downloaded
from a public dataset LEMON. Since it is not sensitive to volume conduction,
Directed Transfer Function has been applied to 62-channel recordings to obtain
cortical connectivity estimations across the whole cortex. Regarding well
defined threshold, connectivity estimations have been transformed into binary
numbers for implementation of Brain Connectivity Toolbox. The groups are
compared to each other through both statistical logistic regression models and
deep learning models driven by frequency band specific network measures
referring segregation, integration and modularity of the brain. Overall results
show that high classification accuracies of 96.05% (1st vs 2nd) and 89.66% (3rd
vs 4th) are obtained in analyzing full-band (0.5 - 45 Hz) EEG. In conclusion,
negative strategies may upset the balance between segregation and integration.
In particular, graphical results show that frequent use of rumination induces
the decrease in assortativity referring network resilience. The psychometric
scores are found to be highly correlated with brain network measures of global
efficiency, local efficiency, clustering coefficient, transitivity and
assortativity in even resting-state.
Discussion and conclusion
In
the present study, healthy adults having different cognitive abilities in
management of negative emotions in daily life were identified by resting-state
Graph Theoretic network measures in both EO and EC states. The individuals were
grouped according to their use of positive or negative cognitive/behavioral
ERS. For each group, connectivity matrices were estimated by examining DTF
based on Granger causality insensitive to volume conduction. BCT was used to
compute the network measures from adjacency matrices, i.e. binary
transformation of connectivity matrices according to non-overlapped short EEG
segments across 61-channel recordings (VEOG recordings were not included in
connectivity estimations). The groups were firstly classified by using LSTMNs
driven by six different network measures together (CC, LE, GE, T, Q, r)
with respect to both states (EO, EC) and frequency band intervals (full-band:0.5−40.5 Hz0.5−40.5 Hz, delta:0.5−4 Hz0.5−4 Hz, theta:4.5−8 Hz4.5−8 Hz,
alpha:8.5−12.5 Hz8.5−12.5 Hz, beta:13−30Hz13−30Hz, gamma:30.5−40.5 Hz30.5−40.5 Hz).
In comparing both cognitive and behavioral opposing ERS, the highest
classification performance was provided by full-band specific measures in EC
state that refer the default mode network (DMN) of the brain. Eyes-opening can
induce significant neural activities due to many external stimuli
(Gorantla 2020). Therefore,
eyes-closed resting-state can be conducive to understanding the dynamic
characteristics of the brain (Liu and Wu 2020). The current results
are compatible with these DMN research.
Regarding
EC state, the main full-band specific findings are discussed in following
items:
In
conclusion, Graph Theoretical global connectivity measures are found to be
useful in discriminating opposing ERS in resting-state. In other words, the
scores of the psychological metrics can be correlated with full-band network
measures by means of segregation, integration and modularity of the brain. In
particular, both segregation and integration are found to be highly sensitive
to not only frequency band interval but also cognitive abilities, while the
resilience represented as network assortativity is found to be almost
insensitive to frequency interval. Since the brain is composed of spatially
embedded complex sub-networks, there must be a balance between integration and
segregation of neural information flow result in cognition and behavior in
healthy brains (Bullmore and Sporns 2009). The later studies
show that the number and strength of neural connections can change with aging,
but the optimal balance occurred between neuronal wiring costs and
communication efficiency (Bullmore and Sporns 2012; Cao 2014). Thus, the current
overall findings can be concluded that cortico-functional balance is impaired
by the presence of ruminative and negative thoughts. The present new findings
are also compatible with the more recent neuro-imaging studies including
structural connectivity analysis based on fMRI (Wang et al. 2021).