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 Hz, delta: 0.5−4 Hz, theta: 4.5−8 Hz, alpha: 8.5−12.5 Hz,
beta: 13−30 Hz, gamma: 30.5−40.5 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).