Quantum propensities in the brain cortex and free will
Not on the map. Why?
Abstract (arXiv)
Capacity of conscious agents to perform genuine choices among future alternatives is a prerequisite for moral responsibility. Determinism that pervades classical physics, however, forbids free will, undermines the foundations of ethics, and precludes meaningful quantification of personal biases. To resolve that impasse, we utilize the characteristic indeterminism of quantum physics and derive a quantitative measure for the amount of free will manifested by the brain cortical network. The interaction between the central nervous system and the surrounding environment is shown to perform a quantum measurement upon the neural constituents, which actualize a single measurement outcome selected from the resulting quantum probability distribution. Inherent biases in the quantum propensities for alternative physical outcomes provide varying amounts of free will, which can be quantified with the expected information gain from learning the actual course of action chosen by the nervous system. For example, neuronal electric spikes evoke deterministic synaptic vesicle release in the synapses of sensory or somatomotor pathways, with no free will manifested. In cortical synapses, however, vesicle release is triggered indeterministically with probability of 0.35 per spike. This grants the brain cortex, with its over 100 trillion synapses, an amount of free will exceeding 96 terabytes per second. Although reliable deterministic transmission of sensory or somatomotor information ensures robust adaptation of animals to their physical environment, unpredictability of behavioral responses initiated by decisions made by the brain cortex is evolutionary advantageous for avoiding predators. Thus, free will may have a survival value and could be optimized through natural selection.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jul 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.
- 2024Quantum-tunnelling deep neural network for optical illusion recognitioncited by 6
- 2023Exploring Cognitive Paradoxes in Video Games: A Quantum Mechanical Perspectivecited by 2
- 2025Transforming Traditional Neural Networks into Neuromorphic Quantum-Cognitive Models: A Tutorial with Applicationscited by 0
- 2025Transforming Traditional Neural Networks into Neuromorphic Quantum-Cognitive Models: A Tutorial with Applications10 Mar 2025
- 2024Quantum-tunnelling deep neural network for optical illusion recognition26 Jun 2024
- 2023Exploring Cognitive Paradoxes in Video Games: A Quantum Mechanical Perspective23 Jun 2023