Mind Causality: A Computational Neuroscience Approach

Area of Science:

• Neuroscience
• Philosophy of Mind
• Computational Neuroscience

Background:

• The mind-brain problem has historically been approached through dualism or reductionism.
• A new neuroscience-based framework views mental states as computations occurring at multiple brain levels simultaneously.

Purpose of the Study:

• To propose a novel computational neuroscience approach to understanding the mind-brain relationship.
• To redefine causality in the context of brain function and mental events.
• To move beyond traditional dualistic and reductionist perspectives.

Main Methods:

• Developing a theoretical framework for mind-brain interactions.
• Analyzing causality at sub-neuronal, neuronal, and network levels.
• Proposing conditions for establishing causality in brain events.

Main Results:

• Mental and brain events are simultaneous computations, linked by non-causal supervenience.
• Causality is best understood as operating within specific levels of explanation in the brain.
• Brain-level causal accounts may be more accurate than mental-level accounts, avoiding confabulation.

Conclusions:

• This computational neuroscience model offers a way to understand mind-brain relations without resorting to Cartesian dualism or physical reductionism.
• Downward causation can be explained within a within-levels causality framework.
• The proposed model reframes causality as operating within, not between, different explanatory levels of brain function.