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Related Experiment Video

Updated: Oct 5, 2025

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
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The Algorithms of Mindfulness.

Johannes Bruder1,2

  • 1Institute of Experimental Design and Media Cultures/Critical Media Lab, FHNW Academy of Art and Design, Basel, Switzerland.

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Summary

This study explores "algorithms of mindfulness" and rest reframing in psychology, neuroscience, and computing. It examines how artificial neural networks can challenge pathological cognition concepts by leveraging cognitive principles.

Keywords:
artificial intelligenceattentioncognitive neuroscienceinformation overloadrestsleep

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Area of Science:

  • Interdisciplinary research at the intersection of psychology, neuroscience, and computing.
  • Focus on optimized cognition, emotional resilience, and creative cognition.

Background:

  • Corporate mindfulness programs and artificial neural network designs reframe rest to augment cognitive capacities.
  • Neuroscience research on brain activity during rest informs both human training and AI development.
  • Stress is often viewed as a driver of success, leading to techniques aimed at preventing psychopathologies.

Purpose of the Study:

  • To analyze models of optimized cognition and the concept of "algorithms of mindfulness."
  • To investigate how artificial intelligence, specifically machine learning systems, can be utilized to question and potentially redefine the notion of pathological cognition.

Main Methods:

  • Analysis of mindfulness trainings and their reliance on neuroscience.
  • Examination of artificial neural network designs that incorporate principles of brain cognition.
  • Conceptual exploration of machine learning's potential to challenge existing frameworks of cognitive pathology.

Main Results:

  • Mindfulness practices and AI designs share a common reframing of rest to enhance cognitive function and resilience.
  • Neuroscience findings on resting brains are co-opted for both human self-improvement and machine learning resilience.
  • Algorithmic techniques are currently geared towards preventing stress-induced pathologies.

Conclusions:

  • The concept of "algorithms of mindfulness" offers a framework for algorithmic self-techniques aimed at emotional and creative enhancement.
  • Artificial intelligence presents novel avenues for unsettling established concepts of pathological cognition.
  • Further research into machine learning applications could lead to a paradigm shift in understanding cognitive health and illness.