You can find a full list of my articles in my Google Scholar profile. I comment here on a selection of articles and research that I was a part of.

During my Ph.D., I researched how adding neural properties with some further biological realism affected the results of simulations with the popular grid cell network-level theory of continuous attractor networks. I primarily sourced the detailed neural properties from the knowledge base of the lab I work in named hippocampome.org.

Sutton, N. M., Gutiérrez-Guzmán, B. E., Dannenberg, H., & Ascoli, G. A. (2024). A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology. International Journal of Molecular Sciences.

I researched what the are the popular methods used to model cognitive functions in a brain region of interest to me. The results of that work was the creation of a literature review and knowledge base of spiking neural network computational models of cognitive functions that are a part of hippocampal formation activity. Methods identified in this work were used in my simulation work.

Sutton, N. M., & Ascoli, G. A. (2021). Spiking neural networks and hippocampal function: A web-accessible survey of simulations, modeling methods, and underlying theories. Cognitive Systems Research.

In my Ph.D., I collaborated on a variety of different articles. I used synapse probabilities as a constraint on the properties included in my simulation. I worked on the web-based graphical interface, database, and probabilities tool in that work.

Tecuatl, C., Wheeler, D. W., Sutton, N., & Ascoli, G. A. (2021). Comprehensive estimates of potential synaptic connections in local circuits of the rodent hippocampal formation by axonal-dendritic overlap. Journal of Neuroscience.

I analyzed rhythmic neural activity in my simulations and gained knowledge about such activity though my work on helping to report rhythm-related activities in hippocampal formation neuron types. I contributed to the web-based graphical interface and database in this work.

Sanchez-Aguilera, A., … Sutton, N., … Ascoli, G. A. (2021). An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo. PLoS biology.

Work with the high-performance computing neural network simulation toolkit CARLsim was included in my modeling. I contributed to testing and debugging the software’s compatibility with state-of-the-art hardware at its article’s time of release. I also assisted in benchmarking the software’s improvements in speed performance of modeling large scale biological neural networks compared to prior software versions.

Niedermeier, L., … Sutton, N., … Krichmar, J. L. (2022). CARLsim 6: an open source library for large-scale, biologically detailed spiking neural network simulation. In 2022 International Joint Conference on Neural Networks (IJCNN) IEEE.

Hippocampome.org was a major source of neural evidence used for parameter values in my simulation and I contributed to the release of the second version of the site. I aided in work on the front- and back-end of the site. I also created a mock-up of my spatial navigation modeling as a preview of results before the article for that work was released.

Wheeler, D. W., … Sutton, N., … Ascoli, G. A. (2024). Hippocampome.org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits. Elife.

I built software that measures grid cell firing pattern metrics to aid with investigations in an article on a theory that the movement trajectory of animals caused the firing patterns of grid cells to be formed. I also used this software to measure firing patterns in my simulation work.

Rebecca, R. G., Ascoli, G. A., Sutton, N. M., & Dannenberg, H. (2024). Spatial periodicity in grid cell firing is explained by a neural sequence code of 2-D trajectories. eLife.

Work prior to my doctoral program:

Reinforcement learning with Spiking Neural Networks

In collaboration with Ignacio Tartavull, M.Sc. Image based classification of characters using spiking neural networks with reinforcement learning. Reimplemented simulation based on published work. This work includes active dendrites and direct to soma signaling signal processing neuron dynamics, lateral Inhibition, use of a learning rate in computations, and the Brian 2 toolkit. This work was released as open source but not yet submitted for publication. Results Website | Github

MazeRunner: Rodent Spatial Memory Simulation

A model of grid and place cells, and theta rhythms is implemented based on published models such as attractor networks for spatial awareness from Dr. Matthew Nolan’s lab and others. A state of the art game engine, Unreal Engine 4, is used to simulate the maze. Github

3d Graphical Simulation of Biophysics, Open Worm Project

In collaboration with the Open Worm Project including Dr. Stephen Larson and Dr. Sergey Khayrulin. Using C++, OpenCL, and Python OpenGL code was created to import 3d models from blender and generate a physics simulation of their activity. Existing code was expanded on and collaborative discussions with original developers were done to advance the work. I created work for potential use in the Sibernetic simulator. Results Page

Memory Module: Hippocampus Neural Network Simulation

Experimental recordings from rat hippocampus areas were modeled in a spiking neural net. Open access data from Dr. György Buzsáki’s lab at NYU was the data source. Izhikevich neurons with pyramidal parameters were used. Functions derived from experimental data optimized synapse weights. Jupyter Notebook

Visual Receptor Fields 3d Simulation

Center-surround and other fields generating firing responses to image patterns were simulated. Visual system equations included the Gabor filter and differences of Gaussians. Custom C++ graphics created 3d images or videos of space-time fields and stimuli changing over time and the effect of that
in fields. Results Page | Github

Emotion Neuropsychology Experiment Software Development

In collaboration with Dr. Yuwen Hung who was researching as a postdoc at MIT. Work with MATLAB’s Psychtoolbox toolkit was integrated for functions like recording subjects’ keypress reactions. Data and metadata was stored to accommodate analysis of synchronized neural image recordings. Existing code was expanded on to present images as emotion stimulus with precise timing, format, and multiple random and pseudorandom ordering methods. Details

Kadlec, K., Hung, Y., Sutton, N., Goncalves, M., Ghosh, S., Uchida, M., Biederman, J., WoodWorth, H, Whitefield-Gabrieli, S., & Gabrieli, J. D. E. (2016). Neural biomarkers of risk factors for pediatric mood disorders. Poster, MIT Summer Research Program in Biology, Brain and Cognitive Sciences and Center for Brains, Minds & Machines Summer Programs Conference. Cambridge, Ma

Natural Language Processing Corpus and Analysis of Gene-Drug Interactions

Work was in the lab of Dr. Graciela Gonzalez at Arizona State University. Java programming using original code, open source programs, and reimplemented programs for a project which researched automatic extraction of text descriptions of gene and drug interactions. Large scale data from a science article database was programmatically processed. The software was optimized for statistical analyses with an open source machine learning tool. I lead and trained a team of coworkers in the work.

Sutton, N., Wojtulewicz, L., Mehta, N., & Gonzalez, G. (2012). Automatic approaches for gene-drug interaction extraction from biomedical text: corpus and comparative evaluation. In BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing (pp. 214-222).

Computational Biology projects done during and after my master’s degree:

10/09 – 11/09, 01/10 – 04/10 Worked on a tool for automating science experiments using Apache Tomcat, Html, the Liferay web portal, CSS, and briefly Java including servelets with JDBC, MySql, and PostgreSQL.

02/10 – 03/10 Compiled a genetic pattern recognition program from source code in Linux and worked with that to perform population genetics research. Advanced statistics such as some information on principle components analysis were learned for the work. A tool used was Eigenstrat.

03/10 – 06/10 Worked on a project using Java Script, Java, and html to graphically show population genetics statistics. Graphical presentations of underlying statistics were dynamically generated in web pages.

03/10 – 05/10 Used MySQL and Visual Basic for Applications (VBA) on Excel to create an interactive report of genomic disease association analyses.

07/10, 10/10 – 12/10 Installed and tested in Linux next generation sequencing software on a local computer and remote cluster computing machine.

08/10 – 09/10 Performed database management of genome sequences using MySQL including integration with Perl scripting. Created sequence alignment analyses using private and public databases.

08/10 – 12/10 Created a plug-in in Java for a genetic analysis workbench program. A Java GUI was created to allow user interaction with the program. The program interfaced with a web utility API for collection of scientific literature data. The project involved a simulated full software development lifecycle, along with documentation including modeling, presentations, team collaboration, and more attributes.

12/10 – 04/11 Used Java and Perl to manipulate portions of genetic sequences for genetic transcription factor research. XML was processed in Java using JDom for drug reaction research. Data from multiple public databases were utilized and a variety of open source programs were integrated into the research. Eclipse and a limited degree of MATLAB were utilized.

04/11 – 06/11 Public databases were analyzed using Java in Eclipse to create comparisons of disease studies’ results. MySQL queries were used to map genetic regions to each other. Advanced queries were performed using SQL. Processing was done to compare data from multiple databases together.

08/12 Java in Eclipse was used to contribute to a project on extracting relationships between entities in medical records. A combination of open source Java code and original programming was used.

06/11 – 08/12 Worked in text mining where programs were created or reimplemented in Java for the identification of text in scientific articles describing genes and drugs interacting together.

02/13 – 03/13, 06/13, 08/13 Contribution of software features to the Biopython.org open source project. Added Matplotlib plotting options, C++ to Python wrapping, and a series of tests. Some technologies worked with include Python, Matplotlib, Eclipse with Pydev, Fasttree, and others.

06/13 – 07/13 Built a bioinformatics web application. Some technologies worked with include Python, Matplotlib, Django, Eclipse with Pydev, MySQL, Openshift, Html, Css, Java Script, Plink, and others.

01/14 – 02/14 Web development at Arizona State University. Contributed to a backend redesign of a science lab site including security, file, and user management. Github