Category: Uncategorized
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Learning weights between a pair of neurons: a long way past Hebb
While many artificial neural nets use a rule to update their weights that does not involve time, It has been found in the brain that Spike-timing-dependent plasticity (STDP) is common. Here, it is not enough to say that neuron A fires at the same time as neuron B and therefore increases the weight between them. […]
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A ‘family-tree’ of words from a recurrent net
Back in 1990 (28 years ago now), Jeffrey Elman wrote an interesting paper titled “Finding Structure in Time”. He took a standard backpropagation net, with one hidden layer, and fed that layer back into the inputs. To review what a backpropagation net is: it’s just a way of learning associations between a group of inputs […]
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A Brain that works on Images – Where the Images are Neurotransmitter Maps
Professor Douglas Greer has some original ideas on how the cortex works, and he has made a working program based on them, the source-code of which you can get for free. The most revolutionary idea is that instead of looking at the firing of a group of neurons as a representation of an object, we […]
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Ogma Corp’s Feynman Machine – it learns Attractors and can drive a car.
In a previous post, I wrote about Numenta, a company that attempts to model just one region of the cortex. Since cortex looks very similar whether it is used for hearing, seeing, or other purposes, they believe there is a general basic algorithm that is used everywhere, and it makes sense to study the building […]
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The “Tunnel vision” brain, and the “Big picture” brain.
Iain McGilchrist is a former psychiatrist living on the Isle of Skye, in Scotland. He wrote a book about the two cerebral hemispheres in 2009, titled “The Master and his Emissary“. In that book he describes the two ways of thinking of the two hemispheres as complementary and both necessary. He believes that the […]
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Getting past the “Deep Learning” neuron
If you learn about machine learning methods such as “deep learning”, you learn a neural model that does a remarkably simple calculation – it receives inputs from many sources, multiplies each input by a weight, takes a sum of the products, subtracts a threshold, and applies a function. That model has led to amazing progress […]
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Learning about the mind from Stephan Guyenet’s “The Hungry Brain”
The Hungry Brain is a new (2017) book by Stephan Guyunet on how to “outsmart” the instincts that make us overeat. “Outsmart” is a good word, because he doesn’t advocate pure willpower as the answer. There were a few observations that I found of special interest. 1) Leptin is a protein that’s made in the […]
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A free program from Northwestern University that understands your drawings
Cogsketch is a program that understands sketches (the type the people draw with pen and paper). You can download it for free, from the Qualitative Reasoning Group at Northwestern University. Cogsketch is an impressive achievement, one reason being that people draw things in many different ways, and make mistakes (which Cogsketch can often advise them […]
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Numenta and Spaun – A hobbyist’s guide to reverse-engineering the brain.
Neural net models that are loosely inspired by animal nervous systems have been around for many years. They are made up of many nodes (neurons) that do a computation of some kind on the sum of the signals coming in to them. The incoming signals travel along connections that are weighted, so some signals are […]
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