I read Dan Brown’s “Origin” and was so intrigued by Santiago Ramo’n Cajal, the father of modern neuroscience, Nobel laureate, artist, and the fact that he perceived neurons, proven in the 1950’s by microscopy
half a century after his work. So taken with his work I ordered “The Beautiful Brain” which has his drawings.
Thank you for sharing your brain and amazing posts that so beautifully illuminate and educate, easily accessible with no microscopy required, just diligent research that is accessible and well written.
Thank you Cathie. Cajal is one of my intellectual heroes, maybe the most inspiring, from such humble beginnings and a troubled youth, military, close to death and to go on to such an incredible career - his illustrations are magical. This is one of my posts about him - https://onepercentrule.substack.com/p/the-fascinating-life-of-santiago
“The Beautiful Brain” is a magnificent work. I carry his research book, Advice for a Young Investigator in my work bag at all times. And his biography is by my bed for regular refresh! He was such an Inspiring human.
"Their focus was cerebral localization: not a speculative endeavor but a brutal one, involving chemical strychninization of monkey cortices to chart neurophysiological function...It was an attempt to reduce the mind-body problem to observable, recordable pulses".
Cruel, but they didn't have an fMRI.
.
"They proposed that neurons, understood as binary threshold units (on or off)"
"McCulloch turned instead toward many-valued logics, recursive paradoxes, and the impossibility of a complete description of perception from within perception itself".
That just might be the distinction between artificial intelligence and real intelligence.
Thanks for this really insightful comment! Those are several key points here.
You are absolutely right. The strychnine experiments sound brutal to our modern ears, and they were. It’s a stark reminder of the limitations they faced without tools like fMRI. What’s fascinating from a historical perspective is that this method was considered more "precise" and even less invasive than the common alternative at the time, which involved surgically removing parts of the brain (extirpation) . It really underscores their drive to find any empirical handle, however crude, on the mind-body problem.
"The original transistor", that's a perfect analogy. That conceptual leap of simplifying the neuron to a binary, all-or-none switch is precisely what allowed McCulloch and Pitts to build a formal logic for the brain and bridge biology with the new world of computation. It was a powerfully creative act of reduction.
The size comparison is amazing and highlights the incredible progress in microelectronics. It also points to a deeper difference. A transistor is a beautifully simple switch, but a neuron is a fantastically complex living cell. McCulloch and Pitts's binary model was a strategic simplification, but McCulloch himself spent his later years moving away from it, recognizing that the brain's "messiness", its analog nature and vast connectivity, wasn't just noise but a core part of its function.
I think your last point is the most profound and gets to the heart of McCulloch's paradox. You said, "That just might be the distinction between artificial intelligence and real intelligence." I couldn't agree more. McCulloch’s turn toward paradox, self-reference, and the limits of formal systems was his way of grappling with what he felt the simple logical models left out. He saw the brain not as a perfect computer, but as a system that had to make value judgments in an ambiguous world. In many ways, his entire career was a journey to, and then away from, the very ideas that would form the foundation of classical AI.
"...to make value judgments in an ambiguous world".
This really gets to the heart of the matter. AI is, if nothing else, a quantitative analysis system attempting to emulate a >qualitative< analysis system - that is, the brain. There's only so much we can do with math.
Amazing content, Colin!
I read Dan Brown’s “Origin” and was so intrigued by Santiago Ramo’n Cajal, the father of modern neuroscience, Nobel laureate, artist, and the fact that he perceived neurons, proven in the 1950’s by microscopy
half a century after his work. So taken with his work I ordered “The Beautiful Brain” which has his drawings.
Thank you for sharing your brain and amazing posts that so beautifully illuminate and educate, easily accessible with no microscopy required, just diligent research that is accessible and well written.
Thank you Cathie. Cajal is one of my intellectual heroes, maybe the most inspiring, from such humble beginnings and a troubled youth, military, close to death and to go on to such an incredible career - his illustrations are magical. This is one of my posts about him - https://onepercentrule.substack.com/p/the-fascinating-life-of-santiago
“The Beautiful Brain” is a magnificent work. I carry his research book, Advice for a Young Investigator in my work bag at all times. And his biography is by my bed for regular refresh! He was such an Inspiring human.
Found my unread “Advice for a Young Investigator”!!
"Their focus was cerebral localization: not a speculative endeavor but a brutal one, involving chemical strychninization of monkey cortices to chart neurophysiological function...It was an attempt to reduce the mind-body problem to observable, recordable pulses".
Cruel, but they didn't have an fMRI.
.
"They proposed that neurons, understood as binary threshold units (on or off)"
The original transistor.
.
"For instance, the soma of a neuron can vary from 4 to 100 micrometers in diameter" https://en.wikipedia.org/wiki/Neuron
Meanwhile, Chinese researchers have created a transistor with a gate length about 1/3nm https://spectrum.ieee.org/smallest-transistor-one-carbon-atom
.
"McCulloch turned instead toward many-valued logics, recursive paradoxes, and the impossibility of a complete description of perception from within perception itself".
That just might be the distinction between artificial intelligence and real intelligence.
Thanks for this really insightful comment! Those are several key points here.
You are absolutely right. The strychnine experiments sound brutal to our modern ears, and they were. It’s a stark reminder of the limitations they faced without tools like fMRI. What’s fascinating from a historical perspective is that this method was considered more "precise" and even less invasive than the common alternative at the time, which involved surgically removing parts of the brain (extirpation) . It really underscores their drive to find any empirical handle, however crude, on the mind-body problem.
"The original transistor", that's a perfect analogy. That conceptual leap of simplifying the neuron to a binary, all-or-none switch is precisely what allowed McCulloch and Pitts to build a formal logic for the brain and bridge biology with the new world of computation. It was a powerfully creative act of reduction.
The size comparison is amazing and highlights the incredible progress in microelectronics. It also points to a deeper difference. A transistor is a beautifully simple switch, but a neuron is a fantastically complex living cell. McCulloch and Pitts's binary model was a strategic simplification, but McCulloch himself spent his later years moving away from it, recognizing that the brain's "messiness", its analog nature and vast connectivity, wasn't just noise but a core part of its function.
I think your last point is the most profound and gets to the heart of McCulloch's paradox. You said, "That just might be the distinction between artificial intelligence and real intelligence." I couldn't agree more. McCulloch’s turn toward paradox, self-reference, and the limits of formal systems was his way of grappling with what he felt the simple logical models left out. He saw the brain not as a perfect computer, but as a system that had to make value judgments in an ambiguous world. In many ways, his entire career was a journey to, and then away from, the very ideas that would form the foundation of classical AI.
"...to make value judgments in an ambiguous world".
This really gets to the heart of the matter. AI is, if nothing else, a quantitative analysis system attempting to emulate a >qualitative< analysis system - that is, the brain. There's only so much we can do with math.