The Mind/Brain Connection
The idea the subjective or experiential mind and the physical brain are closely related is well-established. In fact, the whole point of having a brain — other than to regulate the body — is to create our mental states and processes. These include sensation and perception (sight, sound, feeling…), recognition, meaning, thought, thinking (creating meaning, understanding, comparing, synthesizing, analyzing, arguing…), emotions, the self, goals, attention, intention, motor control, and learning. And combinations of the above.
Not only that, the main goal of the field of cognitive neuroscience is to clarify this connection. A strong mind-brain connection has been well-established by cognitive neuroscience experimentally.
I argue brain state and activity essentially mirrors that of the mind. If it didn’t, then how could motor control be instantaneously responsive to thought, via the motor cortex? How could goals, attention and motivation affect movement? How could a thought to “move my right arm two feet forward, slowly and gracefully” produce that exact same movement via the efferent (away from the brain) signal?
A strong mind/brain connection is great news. The mind now becomes a viable path to understand the brain. Defining the mind, as it acts through space and time in the brain, represents a functional map of the meaning of the brain’s activity. A brain model based on a mind model shows what the brain is enabling, when and where. This is a mind-centered way to understand brain activity and signal. It gives not only cognitive neuroscience but all of brain science a new tool to enhance their work, by grounding brain signal encoding and decoding in subjective meaning.
There’s a big hurdle to overcome though. The mind is currently poorly understood. There’s no agreed-upon definition of what the conscious or unconscious mind is. What are its “parts” or its cognitive ontology? How do these act and interact through space and time? And how does this activation vary across context: people, environments, situations, time, learning, recent life events etc.?
A second unsolved problem is the so-called “easy problem of consciousness.” How do mind and brain connect? How is the mind represented inside this electrochemical organ? How do mental states and processes connect to neural activity? What is the neural correlate of a given instance of perception, recognition, goal formation, imagination, intention, prediction etc.?
The easy problem of consciousness remains unsolved also. The exact nature of the mind’s relationship to the brain is poorly understood (Bassett & Gazzaniga, 2011). There are a number of very difficult problems standing in the way of defining the mind, and mapping it to the brain (Poldrack & Yarkoni, 2016).
The good news is there are clues we can use to solve these two problems, and thereby understand the system. First, most agree the human mind exists. We all see, hear, feel, think, recognize, understand and so on. Our mental states and processes exist and operate continuously through every moment of the day. This is clear for ourselves (and assumed for everyone else).
The second clue is all aspects of the mind are connected to brain activity. This is obvious given the mind’s location. How could an aspect of it operate from, or be manifest within, the brain — without being connected to it? Indeed cognitive neuroscience has found neural correlates of everything they have looked for: any type of sensation and perception, recognition, emotion, motivation, thought, inner speech, executive control, imagination, goals, working memory, pain & pleasure, belief in God and thousands of other mental phenomena.
Human movement clearly demonstrates the mind operates within the brain. Our thoughts and intentions control our movement. This is done by their influence on the efferent (away from the brain) signal. The efferent signal is sent from the basal ganglia and motor cortex, down the spine to the body. This electrical signal is affected by a combination of sensation and perception, and movement-related goals & intentions (conscious & unconscious).
Less directly, the efferent signal is affected by the rest of the mind. This includes what a person recognizes, identifies, understands, thinks, feels, is motivated by, attends to and so on. His or her body language and movement is a continual, real-time reflection of their mind as it operates inside their brain. The body mirrors (much of) the mind, via the brain. The movement of the eyes, facial muscles, arms, hands, torso etc. is controlled by the mind, continually. Human movement demonstrates the mind/brain connection in a 100% physical way.
If all of the mind has a neural correlate, and the evidence for this I argue is overwhelming, this is great news. It means the former, once defined with accuracy and precision, can be used to construct functional maps of the latter. The easy problem of consciousness can, in theory at least, be solved — by using a mind model as the basis for understanding, defining and labeling its neural counterpart.
Brain Signal Decoding
The mind is critical to decode the brain signal. To decode a brain signal is to ascribe meaning to it, as it operates during a particular task. Meaning is represented by categories or labels, comprised of word sequences. Labels represent the subject’s components of mind — his or her mental states and processes assumed active at that time. The more accurate and precise the labels, the more accurate and precise the decoding can be.
For example, imagine a set of neural activity data that’s labeled as the mental task “remember what a ‘pear’ is.” Is it enough to label this activity as such? It’s a start. But a number of sub-labels are needed for more complete and precise definition. These include “recall from (long term) memory,” “pear shape/color/taste/texture,” “fruit,” “juicy,” “desire,” “bite into,” “nutrition,” “grows on trees” “a favorite food of mine” and so on. The more accurately the labels represent the mind during a mental command, the more accurate the decoding (meaning ascribing) that neural activity can be.
A rich variety of subjective or experiential content — perceptual, intellectual, and emotional — is manifest continuously during any task, or activity. Recognizing this fact is the first step toward optimal brain activity & signal decoding.
Beyond Materialism, to a Mind Model
If the subjective mind is critical to not only decode the brain signal, but understand the brain generally, what should be done? The first step is to acknowledge the mind/brain problem as real. Strangely enough, a hard core materialist might beg to differ. They might try to ignore the mind, or minimize it as much as possible. One tactic is to label consciousness a hallucination or epiphenomenon. Another common materialist tactic is to “reduce” the mind to some aspect of the brain (such as coordinated patterns of neural activity or their “computation”). And materialism is a popular position to take within brain science.
Materialism does have some truth to it. It starts with the idea that everything in our physical universe must take a physical form. And since the mind is immaterial, and inside the brain, it can be “reduced” to it. Once reduced, the mind essentially disappears. The mind is now “the brain.” After all, how could the immaterial exist within, or as part of, a physical entity?
Materialism I argue is partly correct. The human mind depends on a healthy working brain. However it’s only half the story. Subjective awareness exists as well. In fact it occurs every moment of the waking day. Therefore, both the mind and neural activity exist — inside the brain.
Once the unavoidable reality of the subjective is acknowledged, the second step is work toward (or be open to learning) an accurate definition of it. In other words, work toward an accurate mind model. This may involve a rethinking of the mind on a conceptual basis, from the ground up. This may sound distasteful to a brain scientist who leans toward strict materialism. But the current brain-centered paradigm has yet to yield a mind model, a brain model, or anything approaching either.
To be clear, great work is being done without a mind model. Valuable experimental data and knowledge continues to accumulate. Tremendous progress toward understanding the brain has been made. Yet seeing the brain as physical only — and minimizing or ignoring the mental — is an unbalanced approach.
The Value of a Mind/Brain Model
Being able to define the meaning of, and categorize, brain function accurately, in real time, would be of great value. And the stakes are high. A mind/brain model would enhance not only academia but applied neuroscience. This includes CNS biomarkers, neurotech, AGI, knowledge representation, NLP and many other fields. The potential to help humanity is great. For example, BCI technology has the potential to greatly enhance communication and movement for those suffering from paralysis.
Yet with BCI and most of applied neuroscience, real-world applications to date have been minimal. BCI devices remain unreliable and scarcely used outside the lab (Chavarriaga et. al., 2016). BCI’s are not yet a viable commercial technology (Chaudhary et. al., 2021)
I argue the main problem is not technological. Though engineering challenges remain, the major obstacle to reliable, robust BCI performance is not lack of technology, engineering, brain data or knowledge. It’s the inability to define the user’s mind during device operation, and then decode and classify the corresponding brain signal. This is required for thoughts to control an external device accurately, reliably and robustly.
Here a mind/brain model has great potential. Consider neuroprosthetics. As the user attempts to move an artificial limb, an intention to move in a particular way enters her mind. Motor intention (MI) has become the dominant force in the user’s mind, and brain.
However, the psychological mechanisms underlying motor intention are poorly understood (O’Shea & Moran, 2017). Therefore the brain signals corresponding to this, or any, intention will be poorly-understood. If not understood well, how could they be labeled well? Inaccurate labeling means the signal will be decoded and classified sub-optimally.
A mind/brain model can solve this problem. It allows accurate and precise labeling of the content of the user’s mind in real time, and prediction of it’s activation in the brain. Neuroimaging of this (labeled) expression, as it repeats, yields mind, and corresponding brain signal, “signatures.” These can be used as classifiers, to decode & classify future brain signals. Classifiers of aspects of mind (perception, emotion, prediction…) associated with MI can also be developed. A classifier could accurately represent a MI + associated mind components via its signal characteristics: (ranges of) frequency, location, amplitude, band power etc.
For instance, defining the neural activity involved in the intention “reach forward to pick up that glass” rests on labeled subjective components. These include the perception, imagination, and prediction of “(artificial) arm & hand, motion toward a glass, left/right/up/down error correction, fingers in grasp position, and grasp.” Also includes are associated fatigue, frustration, impatience or any other emotion, positive or negative. Arguably dozens of components of mind are active during this (or any) intention. These mind components once acknowledged, can be included in a classifier or not, depending upon their predicted level of activity.
The Mind is a Blind Spot
Despite its obvious importance, the subjective mind is the single largest blind spot within the brain science community. This actually makes a lot of sense. After all, understanding it seems to be a remote goal to be achieved in the distant future. Why pursue a problem which seems to have no resolution, or clear path toward one? Also, current efforts to understand the brain are making (very slow, but steady) progress. Therefore neuroscience has put the issue on the back burner, and turned its focus almost exclusively to the physical brain. The hope is the continued accumulation of brain data and knowledge will some day add up to a brain theory.
However pursuing a brain theory, i.e. a true understanding of how it enables the mind, using brain study alone I argue is a lost cause. The only way to accurately and precisely decoding brain activity is to first define the mind to which it connects, 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., Chander, B. S., Ohry, A., Jaramillo-Gonzalez, A., Lule, D., Birbaumer, N. (2021). Brain Computer Interfaces for Assisted Communication in Paralysis and Quality of Life. International Journal of Neural Systems v. 31. https://doi.org/10.1142/S0129065721300035
Chavarriaga, R., Fried, O., Kleih, S., Lotte, F., Scherer, R. (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: informatics and the search for mental structure. Annual Review of Psychology, 67, 587.