Neuroscience phd

Matthew s. creamer

Interests

I am a computational and experimental neuroscientist with experience in analyzing high-dimensional neural time series data using probabilistic models coded in Python. During my PhD, I built machine-vision models of Drosophila visual motion based on measurements of the brain’s activity. During my postdoc, I coded a probabilistic latent linear dynamical systems model of the C. elegans brain and used it to explain how the brain responds to perturbation. During this time, I also developed a novel algorithm for correcting motion artifacts using Gaussian processes and validated the method by showing that it nearly doubled performance over previous methods.

RESEARCH EXPERIENCE

C. V. Starr Fellow – Princeton University

Princeton, NJ, beginning August 2019
Advisor: Andrew M. Leifer and Jonathan W. Pillow

• Developed a code base for implementing and training dynamical systems models with sparsity constraints.

• Created a method that corrects motion artifacts in neural activity using Gaussian processes and Bayesian inference. Performance nearly double relative to earlier methods when decoding behavior from neural activity.

• Designed and implemented custom Python pipelines for neural data preprocessing, statistical analysis, and model validation.

PhD – Yale University

New Haven, CT, 2012-2018
Advisor: Damon A. Clark

• Built machine vision models of Drosophila constrained by neural and behavioral measurements.

• Measured neural activity and behavioral responses to visual stimuli on a custom designed virtual reality experimental system for Drosophila.

Research Assistant – Ludwig Institute for Cancer Research

Melbourne, Australia, 2011-2012
Advisor: Antony W. Burgess

• Built mass action kinetics model of a cancer signalling pathway which allowed researchers to predict protein concentration and modification over time (Matlab)

• Parameterized the model by measuring protein concentration in tissue culture

Helios Scholar Internship – Translational Genomics Research Institute

Phoenix, Arizona, June-August 2011
Advisor: Richard G. Posner and Edward C. Stites

Undergraduate Researcher – Northern Arizona University

Flagstaff, Arizona, 2008-2011
Advisor: Richard G. Posner

• Built mass action kinetic model of large cell signalling pathway to demonstrate that it is possible to create models with arbitrarily large numbers of complexes [10]

PUBLICATIONS - featured (See full list here)

Creamer, M.S., Leifer, A.M., Pillow, J.W. (2024). Bridging the gap between the connectome and whole-brain activity in C. elegans. BioRxiv. https://doi.org/10.1101/2024.09.22.614271

Creamer, M.S., Chen, K.S., Leifer, A.M. (2022). Correcting motion-induced fluorescence artifacts in two-channel neural imaging. PLoS Comp Bio. https://doi.org/10.1371/journal.pcbi.1010421

Creamer, M.S., Mano, O., and Clark, D.A. (2018). Visual Control of Walking Speed in Drosophila. Neuron 100: 1460–1473. https://doi.org/10.1016/j.neuron.2018.10.028
Video abstract: https://youtu.be/LdJRfc6PCi4