Abstract
Learning in chemistry and other areas of science involves developing one's mental models of invisible processes and manipulating temporal and spatial domains during visual information processing. While some aspects learning have been well studied by EEG (e.g., theta and gamma oscillations), the role of spontaneous and scale-free brain activity remains unclear. We used a continuous chemistry learning EEG paradigm to explore how scale-free brain activity is related learning. We found a learning effect in participants (N = 22) with an increase in test accuracy (learning gain) and decrease in test question response times in a counterbalanced pre/post-test experiment. In the brain we found increased overall (mixed) broadband power (1–50 Hz) during learning compared to rest. We then used the IRASA method to separate oscillatory and fractal (i.e. scale-free) spectral components and observed an increase in low-frequency oscillatory band powers during learning. More importantly, we found that fractal power increased during the learning sessions relative to oscillatory power. Finally, the structure of the fractal power spectra (PLE) correlated to the individual participants’ learning gains. These findings support the importance of scale-free activity for learning from a complex visual paradigm. We tentatively hypothesize that this fractal component is involved in integrating the different time scales of the learning material with those of the spontaneous activity during learning and mental model shaping.
Original language | English |
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Pages (from-to) | 165-177 |
Number of pages | 13 |
Journal | Neuroscience Research |
Volume | 156 |
DOIs | |
Publication status | Published - Jul 2020 |
Externally published | Yes |
Keywords
- Brain dynamics
- Electroencephalography
- Learning
- Mind, brain, and education
- Oscillology
- Power-law distribution
- Power-law exponent
- Scale-free brain activity
ASJC Scopus subject areas
- Neuroscience(all)