SIGNAL DETECTION APPROACH IN MODELING CONSCIOUSNESS – EMOTION INTERACTIONS
Marta Korendo
Acta Neuropsychologica March 12, 2017 DOI: 10.5604/12321966.1238143 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Citations | 1 |
| Key points | Argues that signal-detection theory can capture consciousness–emotion interactions underlying emotional experience. The author reports that a hierarchical SDT model can estimate levels of the hierarchical organization of emotional experience, and that a threshold SDT model predicts emotion experience requires a discrete decision space, implying neural representations of emotion are mediated by thresholds to be experienced consciously. |
Abstract
Contemporary cognitive science attempts to provide computational models that describe how consciousness and emotion constitute adaptive behavior. Given the recent neurobiological view that highlights the fact that the cognitive and emotional regions of the brain work together to achieve conscious behavior, it was shown that signal-detection theory (SDT) can effectively capture the notion of the consciousness–emotion interactions that underlie emotional experience. In particular, I have demonstrated that the hierarchical SDT model is capable of estimating different levels of the hierarchical organization of emotional experience. I have also shown that the threshold SDT model predicts that the formation of emotion experience requires a discrete decision space, which implies that the neural representations of emotion are mediated by thresholds to be experienced consciously. The application of both computational SDT models seems to be a promising advance for studying consciousness–emotion interactions.