A few examples of my work as a Computational Neuroscientist in the field of decision making. Everything is original, independent work I have completed that has been (or will be) submitted to high impact, peer-reviewed, journals. Feel free to get in touch if you have any questions!
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- Using logistic regression to predict where a monkey will look: Model comparison and feature selection demonstrates we can evaluate items in our peripheral vision to decide where to look.
- Neural networks can encode the value of multiple objects simultaneously: Modelling firing rates using GLMs and statistics reveals neurons in the brain can respond to the value of at least 4 different objects in our peripheral vision, simultaneously.
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- Dimensionality reduction reveals how neural networks encode information: Using PCA and Pearson r, I demonstrate that neurons can rotate their encoding of information to orthogonalize it when necessary.
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- Extracting discrete eye movements from continuous eye tracking data: Processing of noisy eye-tracking data (eye x and y positions recorded at 1 kHz) to extract the discrete eye movements ('saccades') that occur.
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- Standalone Android platform for automated behavioural testing: Android app that allows monkeys to play games in their enclosures. It using facial recognition while they play via a custom-built neural network to identify which monkey is playing when and adjusts the difficulty accordingly. Now used in multiple centres around the world, awarded the UCL 3Rs prize for Innovation and funding to expand the scheme throughout England.