I am a generalist, reading the discoveries and insights of others, putting them together with a few thoughts, stitching them into broader patterns. My interest in thinking and how the mind functions bridges neuroscience, cognitive science, and philosophy.
Sometimes, it’s hard to trace where an interest arises, but my interest in the human brain and its relation to physical reality has certain high points that I’d like to mention.
In 1979, sitting at my work desk faced with a large sheet of blank paper, I mulled over my off-the-cuff comment to a fellow programmer: “It’s a mark of intelligence if a person can figure out a word if he only sees part of the word.”
I floated a bunch of ideas on the blank page, but was frustrated at the chaos. I ripped that out and started from scratch. Figure 2.1 is a later version of those early attempts to understand the relationship between external reality and internal worldview.
Everything we know starts with sense data. Creativity is needed to proceed from partial external sense data to our internal mental interpretation. But what mechanism provided this creativity eluded me! I also wondered why some people are so rigid in their interpretations of reality and others so free. I wanted to know.
Column and Row Summation
I tried to figure out how to condense the mass of raw visual data, but all my attempts failed. I set my notes into a project folder, until …
Neural Networks, Artificial
In 1992, I took a class on Artificial Intelligence at The Johns Hopkins Applied Physics Lab. It showed me a new way to condense information.
Backpropagation sort of worked, but it demanded an overseer, a set of good answers to calculate the errors to be propagated backward. That was interesting, but exceedingly unlikely as an explanation of how the human brain works; however, the outlines of some ideas were starting to emerge. At work, I gave a presentation on neural networks to technical staff. I stressed the observed phenomenon of the brain, like speed of neurons, since I didn’t know a neural mechanism that could account for processing the raw sense data.
Caudill and Butler had other types of neural networks, but I was busy with work and home. I filed a folder labelled “Artificial Neural Networks.”
The Mind in the Net
My interest never flagged. I avidly read the latest books on neuroscience, cognitive science, and biological science. The works that affected me most are in the references. Early in 2006, I bought Manfred Spitzer’s The Mind in the Net. Spitzer introduced me to semantic maps, Kohonen artificial neural networks with their self-organizing property, and a sober development of brain processes.
The Finite Mind
I slowly developed the idea that, although the brain has billions of neurons with thousands of interconnections between them, the existence of a limited working storage meant that thoughts went through a narrow sieve at times. Although our brains could hold and remember vast amounts of information, when it came to making decisions, only a subset of that information was available at any time. Another aspect is the locus of interest a person has, through which attention rotates. The Finite Mind is briefly mentioned in the main argument of Mental Construction. It is discussed further in this post.
In 2011, now retired, I went through my hanging folders, getting excited once again about how the flux of external reality becomes stable objects in my mental world. When I tried to bring my ideas into sharper focus, I saw how much I had to learn. But now I finally had time.
As I mentioned above, I am a generalist, not a specialist in any of the areas discussed here—neuroscience, cognitive science, philosophy, or psychology. I am not consumed with the latest research questions unique to a specialty. I am fascinated with how the operation of the human mind relates to issues in biology, psychology, and philosophy.
My blog can be found at Burning Thoughts