Explaining Locus Coeruleus’ Impact on Anterior Cingulate Cortex Through Neuron Network Models

Zaini in front of computers

Students

2020
Engineering and Applied Sciences

Faculty

Professor

Project Summary

The locus coeruleus (LC) is the primary source of norepinephrine (NE) in the central nervous system. Previous research has suggested that this NE influences the firing rate of the anterior cingulate cortex (ACC), in addition to other areas of the brain. Other studies conducted in rodent models identified that NE nonmonotonically regulated the conductance density of an ohmic potassium current. The concentration of NE was found to be inversely proportional to the conductance of the potassium channel. The aim of my experiment was to connect these two findings and test if they could explain each other in a simulated neuron. I therefore investigated whether the activity of neurons in the ACC with respect to spikes in the LC could be explained via the changes in the conductivity of the potassium channel.

Using my knowledge in computer science, I worked on a mathematical neuron model using Matlab with Dr. Joshi in an attempt to explain the correlation found in previous publications. We implemented and tested a leaky integrate-and-fire neuron model and then studied the effect of simulated change in LC activity on the model neuron. We found that changing LC input had a range of effects on the model neuron, and ongoing work is aimed at refining the model to mimic realistic experimental conditions. These findings now help steer our future models as a correlation was found to be consistent between LC and ACC spike rates in the model, and future work could potentially help us come up with a more concrete explanation for how these parts of the brain affect each other. 

I relished working alongside Dr. Gold and Dr. Joshi who exposed me to the latest neuroscience breakthroughs and captivated my interest. Having never taken a neuroscience course before, I was excited to learn, and there was no better way to explore a new field than jumping into it head first. I was able to learn theories from recently published papers, and then minutes later go on and apply what I just learned to my actual research plan. This was vital to my experience since it gave me the opportunity to solidify my understanding of theory by applying this knowledge in our experiment. One of the most fascinating things I learned this summer was that I could apply the knowledge I learned in my electricity and magnetism physics class to this project and model a neuron based on an RC Circuit. This proved to me that knowledge can be applied almost anywhere. Ultimately, I am grateful for the enjoyable summer I spent fascinated by the brain, and this experience encouraged me to go out and take more neuroscience classes so that I can continue researching the brain.