Exploring electroencephalography with a model inspired by quantum mechanics
| Autor: | Bobby Stojanoski, Colin Metrow, Geoffrey Laforge, Adrian M. Owen, Andrea Soddu, Nicholas J. M. Popiel |
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| Přispěvatelé: | Apollo - University of Cambridge Repository |
| Rok vydání: | 2021 |
| Předmět: |
Uncertainty principle
Science 1.1 Normal biological development and functioning 5202 Biological Psychology Bioengineering Electroencephalography Cognitive neuroscience Quantum mechanics Article Task (project management) medicine 5204 Cognitive and Computational Psychology 1 Underpinning research Quantum Multidisciplinary medicine.diagnostic_test FOS: Clinical medicine Computational science Neurosciences Human brain Rotation formalisms in three dimensions Brain Disorders medicine.anatomical_structure 52 Psychology Neurological Medicine Mental health Constant (mathematics) 51 Physical Sciences |
| Zdroj: | Scientific Reports Brain and Mind Institute Researchers' Publications Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021) |
| Popis: | An outstanding issue in cognitive neuroscience concerns how the brain is organized across different conditions. For instance, during the resting-state condition, the brain can be clustered into reliable and reproducible networks (e.g., sensory, default, executive networks). Interestingly, the same networks emerge during active conditions in response to various tasks. If similar patterns of neural activity have been found across diverse conditions, and therefore, different underlying processes and experiences of the environment, is the brain organized by a fundamental organizational principle? To test this, we applied mathematical formalisms borrowed from quantum mechanisms to model electroencephalogram (EEG) data. We uncovered a tendency for EEG signals to be localized in anterior regions of the brain during “rest”, and more uniformly distributed while engaged in a task (i.e., watching a movie). Moreover, we found analogous values to the Heisenberg uncertainty principle, suggesting a common underlying architecture of human brain activity in resting and task conditions. This underlying architecture manifests itself in the novel constant KBrain, which is extracted from the brain state with the least uncertainty. We would like to state that we are using the mathematics of quantum mechanics, but not claiming that the brain behaves as a quantum object. |
| Databáze: | OpenAIRE |
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