Key result
Affective emotional stimuli linked to substantially higher functional connectivity network semi-metric percentages versus neutral stimuli.
Why the study?
Network redundancy features via semi-metric analysis had not been considered in conventional fNIRS-based functional connectivity analyses.
Cross-Sectional (n=38)
No
Semi-metric analysis can be generalized and extended to fNIRS-based functional connectivity estimation to detect emotional state differences during decision making.
May differentiate affective states in nurse decision-making; leaves open generalizability of semi-metric fNIRS FC analysis.
This study aims to investigate the generalizability of the semi-metric analysis of the functional connectivity (FC) for functional near-infrared spectroscopy (fNIRS) by applying it to detect the dichotomy in differential FC under affective and neutral emotional states in nursing students and registered nurses during decision making. The proposed method employs wavelet transform coherence to construct FC networks and explores semi-metric analysis to extract network redundancy features, which has not been considered in conventional fNIRS-based FC analyses. The trials of the proposed method were performed on 19 nursing students and 19 registered nurses via a decision-making task under different emotional states induced by affective and neutral emotional stimuli. The cognitive activities were recorded using fNIRS, and the emotional stimuli were adopted from the International Affective Digitized Sound System (IADS). The induction of emotional effects was validated by heart rate variability (HRV) analysis. The experimental results by the proposed method showed significant difference (FDR-adjusted p = 0.004) in the nursing students' cognitive FC network under the two different emotional conditions, and the semi-metric percentage (SMP) of the right prefrontal cortex (PFC) was found to be significantly higher than the left PFC (FDR-adjusted p = 0.036). The benchmark method (a typical weighted graph theory analysis) gave no significant results. In essence, the results support that the semi-metric analysis can be generalized and extended to fNIRS-based functional connectivity estimation.
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Chong et al. (2020) conducted a cross-sectional in Healthy (Decision making under emotional states) (n=38). Affective emotional stimuli vs. Neutral emotional stimuli was evaluated on Global semi-metric percentage (SMP) of the functional connectivity network in nursing students (Cohen's d 0.895, p=0.004). Affective emotional stimuli significantly increased the global semi-metric percentage of the functional connectivity network compared to neutral stimuli in nursing students (Cohen's d 0.895, p=0.004).
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