Author/Authors :
khosrowabadi, reza Institute for Cognitive and Brain Sciences - Shahid Beheshti University, Tehran, Iran
Abstract :
Introduction: Long-term stressful situations can drastically influence one’s mental life.
However, the effect of mental stress on recognition of emotional stimuli needs to be explored.
In this study, recognition of emotional stimuli in a stressful situation was investigated. Four
emotional conditions, including positive and negative states in both low and high levels of
arousal were analyzed.
Methods: Twenty-six healthy right-handed university students were recruited within or after
examination period. Participants’ stress conditions were measured using the Perceived Stress
Scale-14 (PSS-14). All participants were exposed to some audio-visual emotional stimuli while
their brains responses’ were measured using the Electroencephalography (EEG) technique.
During the experiment, the subject’s perception of emotional stimuli is evaluated using the Self-
Assessment Manikin (SAM) questionnaire. After recording, EEG signatures of emotional states
were estimated from connectivity patterns among 8 brain regions. Connectivity patterns were
calculated using Phase Slope Index (PSI), Directed Transfer Function (DTF), and Generalized
Partial Direct Coherence (GPDC) methods. The EEG-based connectivity features were then
labeled with SAM responses. Subsequently, the labeled features were categorized using two
different classifiers. Classification accuracy of the system was validated by leave-one-out method.
Results: As expected, performance of the system is significantly improved by grouping the
subjects to stressed and stress-free groups. EEG-based connectivity pattern was influenced by
mental stress level.
Conclusion: Changes in connectivity patterns related to long-term mental stress have overlapped
with changes caused by emotional stimuli. Interestingly, these changes are detectable from EEG
data in eyes-closed condition.
Keywords :
Long-term stress , Effective connectivity , Electroencephalography (EEG) , Emotion