Mind and Brain

The Mind/Brain Connection

The immaterial mind and the physical brain are closely related. The primary purpose of the brain — beyond regulating the body — is to create our mental states and processes. These include sensation and perception, recognition, meaning, thought and thinking, emotions, the self, goals, attention, intention, motor control, learning, and any combination of the above.

Cognitive neuroscience aims to clarify this connection, and experiments have established a strong mind-brain relationship.

Brain activity mirrors the mind. The efferent neural signal and resulting movement respond almost instantly to thought, goals, attention, motivation, emotion, fatigue, and other mental states. Body language and movement provide a continuous physical reflection of the mind operating inside the brain.

This strong connection is excellent news. It means the mind itself offers a powerful pathway to understanding the brain. By defining mental components and their activity through space and time, we can create functional maps of corresponding brain activity. This mind-centered approach significantly improves brain signal decoding, classification, neurotechnology, and biomarker development.

However, a major hurdle remains: the mind is poorly understood and largely ignored. There is no widely accepted definition of the conscious or unconscious mind, its core components (cognitive ontology), or how those components interact across tasks and contexts.

This gap relates directly to the “easy problem of consciousness” — how subjective awareness and mental processes connect to neural activity in the brain. The exact nature of this relationship remains unclear.

Fortunately, we have strong clues. The mind clearly exists as subjective experience, and cognitive neuroscience has identified neural correlates for nearly every mental phenomenon studied. Once the mind is accurately defined, it can serve as a roadmap for mapping and labeling brain activity.

Brain Signal Decoding

Accurate brain signal decoding requires precise labels for the mental states active during a task. These labels give meaning to the neural data. For example, the task “remember what a ‘pear’ is” involves many sub-components: recall from memory, sensory qualities (shape, color, taste), associated ideas (fruit, nutrition, personal preference), and emotional responses. Rich, detailed subjective labeling leads to far more accurate decoding.

Beyond Materialism, to a Mind Model

If the subjective mind is critical to understanding the brain, what should be done? The first step is to acknowledge that the mind exists and that the mind/brain problem is real. Materialism often tries to minimize or reduce the mind to brain activity or computation, treating it as a hallucination, epiphenomenon, or something that disappears once “reduced.”

Materialism has partial truth — the mind depends on a healthy brain. However, it is only half the story. Subjective awareness exists. Both the mind and neural activity coexist inside the brain.

Once the reality of the mind is acknowledged, the next step is to develop a clear, accurate mind model. Although valuable data continues to accumulate, a purely brain-centered approach has significant limitations.

The Value of a Mind/Brain Model

A robust mind/brain model would benefit academia and applied fields including biomarkers, neurotech, AGI, and BCI. Current BCI systems remain unreliable and limited outside the lab, largely due to challenges in defining the user’s mental states in real time.

A solid model would enable better labeling of intentions (such as motor imagery) and associated mental components, leading to more accurate classifiers and real-world performance.

The Mind is a Blind Spot

The subjective mind remains brain science’s largest blind spot. While focusing solely on the physical brain has produced useful data, a true understanding of how the brain enables the mind requires starting with the mind itself. Understanding it seems distant, so the field has focused almost exclusively on the physical brain. However, pursuing a brain theory through brain study alone is very limited. The most effective path is to define the mind first — accurately and precisely. The good news is this can be done — right now.

References

Bassett, D.S., & Gazzaniga, M.S. (2011). Understanding complexity in the human brain. Trends in Cognitive Sciences, 15, 200-209.
Chaudhary, U., et al. (2021). Brain Computer Interfaces for Assisted Communication in Paralysis and Quality of Life. International Journal of Neural Systems. https://doi.org/10.1142/S0129065721300035
Chavarriaga, R., et al. (2016). Heading for new shores! Overcoming pitfalls in BCI design. Brain-Computer Interfaces, 4, 60.
O’Shea, H., & Moran, A. (2017). Does motor simulation theory explain the cognitive mechanisms underlying motor imagery? Frontiers in Human Neuroscience, 17, 1.
Poldrack, R.A., & Yarkoni, T. (2016). From brain maps to cognitive ontologies. Annual Review of Psychology, 67, 587.