This PLOS Computational Biology neurotheory paper with Christopher Rozell and Ilya Nemenman was my first step into neuroscience and has a special place in my heart. For context, neurons come in two main types: excitatory and inhibitory. The interplay between these types of neurons shapes computation in the brain. Despite brain sizes varying by several orders of magnitude across species, the ratio of excitatory and inhibitory sub-populations (E:I ratio) remains relatively constant, and we don’t know why. This paper offers a potential answer to this puzzle. We use a computational model which simulates the visual brain (visual cortex) and which contains both excitatory and inhibitory neurons. We limit the total number of neurons (i.e., brain volume) available to the model and simulate it at different E:I ratios (including those that cannot be found in nature and thus experimentally studied) and track its performance across different measures that capture how well it encodes visual information and how much metabolic energy the neurons consume (i.e., ATP molecules). The performance of our model at different E:I ratios reveals an optimal E:I ratio, where performance is optimal concurrently for both performance measures (best encoding of visual information, lowest metabolic energy consumption). Let’s unpack what we did and what we found…
Completed neuroscience research projects are described here in layperson friendly posts. Active research projects are best gleaned from the publications page.
I worked on this project during my final semester (Spring 2016) as a Masters student at Georgia Tech under the guidance of Professor Garett Stanley and in support of Michael Bolus and Adam Willats’ research. The project’s broad objective is to control the activity (firing rate trajectories) of light sensitive (ChR2) neurons in a mouse brain’s whisker region (barrel cortex) with optical stimulation (i.e. shining a light onto the exposed mouse brain) in real time using math (control theoretic techniques). For laypersons, normal mammals do not have light sensitive neurons/brains and the mice in question are genetically engineered for scientific research. My contribution to the project was engineering oriented. Click below for a couple of paragraphs explaining the scientific relevance of this work, what I did and how it fit into the bigger picture.