The Mind/Brain Connection
The immaterial mind and the physical brain are closely related. This is well-established. 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, touch…), recognition, meaning, thought, thinking (understanding, comparing & contrasting, synthesizing, arguing…), emotions, the self, goals, attention, intention, motor control, and learning. And any combination of the above, in imagination or reality.
In fact the main goal of cognitive neuroscience is to clarify this connection. So far a strong if not 1-to-1 mind-brain connection has been well-established by cognitive neuroscience, experimentally.
I argue brain activity mirrors that of the mind. If not, how could the efferent (away from the brain) neural signal and movement respond to thought instantly? How could not only movement goals & subgoals, but attention, motivation, pain & pleasure, desire, fatigue, anxiety, confidence, cognitive workload and other mental states 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 signal?
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.
A strong mind/brain connection is great news. The mind is now a viable path to understand the brain. It’s components and their activity can be used to functionally map corresponding brain activity. Defining the mind, as it acts through space and time in the brain, and you can define a corresponding brain’s activity “signature” that carries the label (and meaning) OF those mental components. A brain model based on a mind model shows WHAT the brain is enabling, when and where. This mind-centered approach to brain understanding, model building and brain signal classification is a powerful tool to enhance signal decoding, classification, neurotech and CNS biomarker development.
There’s a big hurdle to overcome though. The mind is poorly understood and mostly ignored by the brain science community. There’s no agreed-upon definition of what the (conscious and/or unconscious) mind is. What are its “parts” i.e. 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.?
Related to lack of mind understanding is the so-called “easy problem of consciousness.” How does the mind connect to the brain, and vice-versa? How is subjective awareness and the mental processes involved with it (perception, thought, emotion, sense of self or executive control…) represented or computed inside this electrochemical organ? How do these states and processes connect to neural activity? What is the neural correlate of a given instance of perception, recognition, goal formation, imagination, 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. First, it’s widely agreed the human mind exists. We all see, hear, feel, think, recognize, understand and so on. Our mental states and processes exist and operate continuously — AS subjective phenomena — through every moment of the day. This is clear for ourselves, and assumed for everyone else.
The second clue is that all aspects of the mind are, or can be, associated with a given brain activity. This is obvious, given the mind’s location. How could a condition of the mind 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.
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 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 as existing, and the mind/brain problem as real. Strangely enough, a hard core materialist might beg to differ. In their view it’s best to ignore the mind as much as possible. One common tactic is to label consciousness a “hallucination” or “epiphenomenon” (secondary effect or by-product of brain activity). 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”. If mind is brain activity or computation, then does it really exist in and of itself?
Materialism does have some truth to it. Everything in the physical universe takes a physical form, by definition. And since the mind is immaterial, and inside the brain, it would seem it could be so “reduced.” Once reduced, the mind disappears. The mind is now “the brain.” Good riddance — how after all could the immaterial exist within, or as part of, a physical entity?!
I would argue materialism is partly correct. The human mind does depend on a healthy working brain. However it’s only half the story. Subjective awareness exists as well. If you don’t believe this, go ahead and hit your thumb with a hammer, and don’t worry because pain doesn’t exist, nor your thoughts about this idea.
In fact awareness, consciousness, and unconscious mental states & processes occur every moment of the waking day. Therefore, both the mind and neural activity exist — inside of the brain.
Once the reality of the mind 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 materialist, or to most brain scientists. However the current brain-centered paradigm has yet to yield a mind model, a brain model or theory, 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 (certain aspects of) the brain has been made. Yet seeing the brain as physical only while minimizing the mind is an unbalanced and untenable 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 the inability to define the user’s mind during device operation, and then decode and classify the corresponding brain signal. A mind/brain model is required for thoughts to control an external device accurately, reliably and robustly.
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.