Can the Brain understand the Brain: Incompleteness, Uncertainty and Strange Loops

To make the human brain better, humans first have to understand how the brain functions.  However, that task is much more difficult than what it seems like on the surface.

Besides the great difficulties in investigating higher mental functions, which are common with all epistemology, we are faced with some unique challenges when the brain tries to study itself.  These difficulties have more in common with investigations in mathematics and physics, where problems of measuring and describing a system while being within the system itself have been studied in more detail.  These difficulties are – 1) Is it possible for an observer within the system to study and understand the system wholly and accurately; 2) Is it possible for an observer in the system to study the system without changing it; 3) How can a system reflect upon itself?

Kurt Godel described the limits of a logical system to fully understand itself in his Incompleteness Theorem: a system with self-evident assumptions (axioms) will always contain unanswerable questions if consistent and if all questions can be answered, some of the answers may not be accurate and the system will be inconsistent.   In the case of the brain, by definition, any starting point of investigation regarding the brain about itself is a  ‘self-evident’ property.  Therefore, even questions about its basic functions may be unanswerable.  This may be a reason why even the salient properties of the brain such as volition, consciousness, emotions, self-identity, and abstract thinking are so difficult to conceptualize and study. Despite decades of research, very little is known about mechanisms behind these functions.  Keeping Godel’s theorems in mind, the only way a true understanding of brain function may arise is if something outside the system would study the brain.  At present, there are two possible candidates to conduct such an investigation – an artificial entity or an alien life force. In the case of an artificial entity, the limitation would be that the artificial entity is likely to be developed by humans and so may suffer the same limitations of logical accuracy and consistency as the human brain itself.  The case of an alien life force is purely speculative and assumes that even if such an entity exists it has some interest in studying the human brain.

A second limitation of the brain studying the brain arises from the principle of physics that an observer while studying a system changes the system.  Also known as the Heisenberg’s Uncertainty Principle, this phenomenon becomes very pertinent to the brain even if the investigation is merely thinking about itself.  Descartes’ “I think therefore I am’  is not entirely accurate if as soon as somebody starts thinking about themselves, they induce a change in the ‘I am’.  Furthermore, the current methods of conducting human brain research are so intrusive and uncontrolled that the investigator or observer changes the system dramatically.  A common method is to study brain function is to use a brain scanner, e.g., a PET scan or a structural or functional MRI scan.  At present, the technology of obtaining neurochemical and physiological measures of brain function is primitive in nature and most images are noisy and distorted.   Beside brain imaging artifacts, scan testing is usually anxiety provoking, and it is difficult to translate findings from a person while lying in a scanner to a person while going about in real life.  Ethical issues of studying living human brain function lead to further confounds of subject selection, adequate controls, and confounding factors such as medications or drug use.  In this scenario, obtaining objective knowledge regarding brain functioning free of observer bias or effect seems to be quite impossible.  Quantification and statistical analyses of these images have been unable to provide any deep understanding of higher brain function in health and disease despite decades of research.  The Uncertainty Principle is difficult to get around by definition, so all that can be done is to reduce its impact as much as possible.  This requires an exponential increase in the technology to study the living brain so that information can be obtained with minimal artifacts and with the least amount of disturbance to the system.

Finally, the very process of brain delving deeper and deeper into itself, parsing its functioning and physiology into smaller bits and then coming back to how that knowledge determines behavior, identity and consciousness seems like very strange endeavor. Douglas Hofstadter has coined the term – ‘strange loop’ in which delving deeper into levels leads to coming up to the starting level again.  At present, a strange  loop seems to exist in neuroscience research between system-level neural circuit oscillations as the basis of human behavior and reductionist-formulations of a single gene or molecule determining behavior.  Brain function is thought to arise from neuronal firings which are then related to subgroups firing, then to membrane electrical potential changes, then to molecular changes such as protein changes or gene expression changes. However, this reductionist approach has not yielded any particular molecular or gene expression abnormality related to higher mental function.  Therefore, it has to be postulated that a pattern of interaction between genes or molecular changes may explain the behavior.  To test this out, dynamic pattern of changes at the molecular level need to be looped back to neuronal firing and oscillations and group of neurons firing.  Most of neuroscience research at present follows one arm of the loop: from behavior to single molecule or brain region abnormality. Even though this reductionist approach has not led to any major findings in terms of the basis for higher level mental function, it remains the dominant paradigm in neuroscience investigations.  This may be due to a stubborn reductionist philosophy in science, a byproduct of how funding mechanisms reward research into the identification of single discrete findings, and publication bias which also caters to the same biases. The other arm of the strange loop – starting from dynamic relationship of molecular changes and working up towards neuronal level firings and networks changes has not been pursued as much. Whether following the full loop will increase our understanding of the brain or such scientific investigation will meaninglessly keep on looping back on itself remains unclear at this stage.