It has been a long time since I last posted about my research. I have been avoiding putting too much online until it's ready (a different approach than my master's research, which was an open source software project). I still have a lot of work ahead, but things having been progressing very well. I seem to be finding answers to all of my big questions at a fairly constant rate.
Again, my goal is to build an intelligent machine based on the structure and computational functions of the mammalian brain. My general approach is to implement models of what I consider the core computational structures of the brain: the posterior cerebral cortex, the motor cortex, the prefrontal cortex, the hippocampus, the basal ganglia, and the cerebellum. I have been studying each of these elements at a time, attempting to extract its core function and purpose within the brain as a whole. For each one I am going through a series of phases: studying biological evidence, developing a computational model, implementing the model in software, and testing the implementation. Once I complete these phases for each component, I will begin a series of whole-system tests.
Testing these models has become a pretty involved process. You can't debug a hippocampus model implementation in a debugger like most other software; there are just too many variables to watch at once. Instead, I have to design a custom testing program for each component. For the case of the hippocampus model, I made an electronic music program where you can play notes on the computer keyboard. This lets you present songs to the hippocampus, allowing it to learn temporal patterns, and later recall songs from small pieces of the same songs. The end result is that by using the medium of sound/music, I can study the system's capabilities much easier than by watching huge arrays of variables in a standard debugger.
The following is a summary my current status. Obviously it's impossible to quantify these things exactly, but this is my best estimate.