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Activity during Learning and the Nonlinear Differentiation of Experience
Yuri I Alexandrov1, Andrei K Krylov2, Karina R Arutyunova2
1Institute of Psychology, Russian Academy of Sciences, Moscow, Russia, and Department of Psychology, National Research University Higher School of Economics, Moscow, Russia.
Nonlinear Dynamics, Psychology, and Life Sciences
|September 20, 2017
Summary
This study explores how individual activity and perception-action cycles shape experience. Computer modeling reveals nonlinear dynamics in how we learn and develop consciousness and emotion.
Area of Science:
- Cognitive Science
- Neuroscience
- Computational Modeling
Background:
- Traditional views emphasize stimulus-reaction and machine metaphors.
- Walter Freeman highlighted individual activity and intentionality.
- Neuroscience links behavior to specialized neural activity.
Purpose of the Study:
- To model the nonlinear dynamics of experience.
- To understand the perception-action cycle as a behavioral continuum.
- To explore how active learning differentiates individual experience.
Main Methods:
- Computer modeling of perception-action cycles.
- Analysis of neuroscientific research on behaviorally specialized neurons.
- Examination of active learning's role in neural differentiation.
Main Results:
- Perception-action cycles generate nonlinear dynamics of experience.
- Active learning drives differentiation of individual experience through neural specialization.
- Consciousness and emotion emerge as dynamic characteristics at different differentiation levels.
Conclusions:
- Individual experience is a nonlinear, multi-level process.
- Consciousness and emotion are dynamic features of systemic differentiation.
- This work moves beyond stimulus-reaction models to dynamic experience.
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