Mathematical Universe Hypothesis
Something a bit different ...
Here are some of the places I stopped along the way.
Something a bit different ...
I review the literature and state of the art of genetic and evolutionary algorithms.
In this lecture I discuss short term synaptic plasticity.
What is it? And what is its purpose?
In this lecture I explain the basic operating principles of the brainstem and the cerebellum. If you prefer to read, the next post is a short article covering this same material.
I finally understood the purpose of the cerebellum, having acquired the prerequisite knowledge of control systems and the brainstem, and so I spent the summer studying the cerebellum and explaining my findings.
In this lecture I explain how the cortex represents information.
In this lecture I introduce the topic of computational neuroscience and then I briefly review the biology and chemistry of the brain.
This program optimizes NMODL files for the NEURON simulator. I wanted to see how much performance was being left on the table: between 5%-15%.
This script sets up the NEURON simulator with a realistic model of action potential propagation. The pyramidal neuron was scanned from layer 5 of a cat's visual cortex.
Lecture about the (Kropff & Treves, 2008) theory of Grid Cells.
This reframes their work in terms of Numenta's HTM theory.
An in-depth analysis of a flaw that I found and fixed in the HTM algorithm.
In this report I demonstrate an unsupervised learning algorithm for recognizing objects and their boundaries. This is a biologically constrained extension of the HTM theory.
In this report I reproduce a computational model of "grid cells," which are a type of neuron that tracks an animal's physical location.
In this report I discuss viewpoint invariance for HTM systems. I introduce the concept of stability, quantify it, and demonstrate a rudimentary method of achieving it.
In this report I reproduce the Spatial Pooler algorithm and experiment with logarithmic boosting and local inhibition. This was my first post on the HTM Forum.
Under the right conditions, science and technology can accelerate its own development.
I took several computer graphics courses in college and I enjoyed them a lot.
This is a python library of graph algorithms that I published in college. Graphs are a mathematical concept and at the time I was quite interested in studying their properties and applications. This library's distinguishing feature is that it operates directly on the user's data structures, whereas all comparable libraries required the user to copy their data into and out of a specific data structure or format. My library accomplishes this using an "adjacency()" function to specify the graph structure. I'm proud of how simple and versatile this API is.
I rendered this animation for a college course, in which I learned that 3D modeling is a difficult skill that I don't have.
Anecdotes from a youth spent wandering the roads at night