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. Everything we know starts with sense data. Creativity is needed to proceed from partial external sense data to our internal mental. But what mechanism provided this creativity eluded me! And why were some people 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 my every attempt led nowhere. I set my notes into a project folder, until …
Neural Networks, Artificial
In 1992, I took a class in 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 propagate backward. That was interesting, but exceedingly unlikely as a means of how the human brain word; however, the edges of some ideas were starting. At work, I gave a presentation on neural networks to two groups of 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’s had other types of neural networks, but I was busy with work and home. I filed a folder, “Artificial Neural Networks.”
The Mind in the Net
My interest never flagged. I steadily 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 each, that 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 stores of information, when it came to making decisions only a subset of that information is available at any time. Bringing my software architect frame of reference, I thought …
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 had time.
I am a generalist, not a specialist in one of the areas – neuroscience, cognitive science, philosophy, or psychology. I am not consumed with the latest research questions unique to a specialty. I am consumed with how the operation of the human mind relates to issues in biology, psychology, and philosophy.
My blog can be found at Burning Thoughts