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Related Concept Videos

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Cognition plays a pivotal role in shaping emotional experiences, as demonstrated by Schachter and Singer’s two-factor theory of emotion. According to this model, emotion arises from a combination of physiological arousal and cognitive interpretation. The body’s physiological response to stimuli is ambiguous and only gains emotional significance through cognitive labeling. For instance, an increased heart rate and adrenaline surge while standing near an attractive person may be...
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Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
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Brain Imaging Investigation of the Neural Correlates of Emotion Regulation
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Exploring the link between emotional states and coding task quality: a pilot study.

Aquib Reshad1, Valentina Nino1, Maria Valero2

  • 1Department of Industrial and Systems Engineering, Kennesaw State University, Marietta, GA, United States.

Frontiers in Human Neuroscience
|December 11, 2025
PubMed
Summary
This summary is machine-generated.

This study explored how emotions affect coding quality. Brain activity (EEG) and self-reports suggest a link between neural emotional markers and programmer performance, though more research is needed.

Keywords:
EEGFrontal Asymmetry Indexemotionsprograming qualityprogrammers

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Software Engineering

Background:

  • Emotions significantly impact cognitive functions, but their role in programming is not well understood.
  • Understanding the emotional-cognitive link in programming can enhance developer productivity and code quality.

Purpose of the Study:

  • To investigate the relationship between emotional states and the quality of coding tasks.
  • To explore the feasibility of using electroencephalography (EEG) to measure emotions during programming.

Main Methods:

  • Ten participants performed a programming task while their brain activity was monitored using EEG.
  • Frontal alpha asymmetry (FAI) was used as a neural indicator of emotional valence.
  • Emotional self-reports were gathered using the Scale of Positive and Negative Experience (SPANE).
  • Coding task quality was assessed using a standardized rubric.

Main Results:

  • Preliminary analysis suggests a potential association between frontal alpha asymmetry (FAI) and coding performance.
  • Self-reported emotional states (SPANE) showed less consistent or weaker correlations with coding quality.
  • The study confirmed the feasibility of integrating EEG-based emotional metrics into software engineering research.

Conclusions:

  • Neural markers of emotion may be more closely linked to coding performance than self-reported feelings.
  • This pilot study provides a foundation for future, larger-scale research on emotions and programming.
  • Integrating neuroscientific methods can offer novel insights into software development processes.