Processing Rat Brain Neuronal Signals Using A Hadoop Computing Cluster – Part I by Jadin C. Jackson, PhD & Bradley S. Rubin, PhD.
From the introduction:
In this three-part series of posts, we will share our experiences tackling a scientific computing challenge that may serve as a useful practical example for those readers considering Hadoop and Hive as an option to meet their growing technical and scientific computing needs. This first part describes some of the background behind our application and the advantages of Hadoop that make it an attractive framework in which to implement our solution. Part II dives into the technical details of the data we aimed to analyze and of our solution. Finally, we wrap up this series in Part III with a description of some of our main results, and most importantly perhaps, a list of things we learned along the way, as well as future possibilities for improvements.
Prior to starting this work, Jadin had data previously gathered by himself and from neuroscience researchers who are interested in the role of the brain region called the hippocampus. In both rats and humans, this region is responsible for both spatial processing and memory storage and retrieval. For example, as a rat runs a maze, neurons in the hippocampus, each representing a point in space, fire in sequence. When the rat revisits a path, and pauses to make decisions about how to proceed, those same neurons fire in similar sequences as the rat considers the previous consequences of taking one path versus another. In addition to this binary-like firing of neurons, brain waves, produced by ensembles of neurons, are present in different frequency bands. These act somewhat like clock signals, and the phase relationships of these signals correlate to specific brain signal pathways that provide input to this sub-region of the hippocampus.
The goal of the underlying neuroscience research is to correlate the physical state of the rat with specific characteristics of the signals coming from the neural circuitry in the hippocampus. Those signal differences reflect the origin of signals to the hippocampus. Signals that arise within the hippocampus indicate actions based on memory input, such as reencountering previously encountered situations. Signals that arise outside the hippocampus correspond to other cognitive processing. In this work, we digitally signal process the individual neuronal signal output and turn it into spectral information related to the brain region of origin for the signal input.
If this doesn’t sound like a topic map related problem on your first read, what would you call the “…brain region of origin for the signal input[?]”
That is if you wanted to say something about it. Or wanted to associate information, oh, I don’t know, captured from a signal processing application with it?
Hmmm, that’s what I thought too.
Besides, it is a good opportunity for you to exercise your Hadoop skills. Never a bad thing to work on the unfamiliar.