Are Neurons all Alike?

Written By Frank Coyle

thoughts after reading McCulloch: Why the Mind is in the Head

current neuron networks assume uniformity across neurons which works for symmetric processing. what’s missing in the ai models are different computational units operating at different time scales. what we get, as Lorente de No says, a conception of the brain as an integrated whole. the role of chemicals adds to the complexity - cholinergic vs adrenergic with different effects. the prevalence of the chemicals that interact with the surfaces of the neurons and effect firing patterns where connected cells don’t carry the signal. so control may occur on the surface of the neuron supporting a huge number of chemical configurations. Also in attendance with McCulloch, deNo, - John von Neumann - memory not a place. often the memory comes to us - the memory size exceeds the capacity of the swithcing system where there are priorities - parts may get moved from less accessible to more accessible. seems like emotion can keep the memory in the ready to review section. resolving the emotion generating issue may reduce the memory as well as its emotional component.

Frank Coyle

My journey into the mechanics of intelligence and consciousness began during a summer internship at Modesto State Hospital in California. Observing the limitations of traditional psychology in treating severely disturbed patients sparked a four-decade quest to understand how the mind truly functions—and how to better support its complexities.

This pursuit evolved into a rigorous academic path, from psychology at Fordham to the neuroscience labs at Emory. There, I transitioned from dissecting biological brains to discovering the mathematical elegance of McCulloch-Pitts neurons. The arrival of the PDP-8 computer in our lab served as a catalyst; I recognized the same neural patterns I was studying in biological systems mirrored in early computational architecture.

Following a 31-year tenure as a Professor of Computer Science at SMU (where I was known as "Dr. C"), I am now at UC Berkeley, focusing on the frontier of Generative AI and Large Language Models (LLMs). I bring a unique "brain-to-bits" perspective to the classroom, helping students bridge the gap between biological intelligence and modern technology.

My teaching philosophy is guided by the wisdom of avant-garde composer John Cage:

Nothing is a Mistake
There is no win; no lose

Only MAKE!

https://frank-coyle.ai
Next

RAG vs CAG: Understanding When to Use Each