__Below I provide a list of papers, each of which could form the basis of a project in this course. You may choose your own paper, but must discuss this with me ahead of time. As stated on the syllabus, by Fri Mar 20 at 11am, you must email me a one page proposal telling me the paper you've chosen, the mathematical work and computational experiments you will perform, and the research question(s) you will ask and answer. I encourage you to meet with me as you're developing your proposal, so you can be sure to identify interesting and realistic goals for your project. The proposal should list the members of the project group: you may work individually or in groups of two or three. Each group only needs to submit one proposal. Each group should plan on meeting weekly with me over zoom from Apr 8 to 29 to discuss their project progress. Email me to setup a time to meet, or we can meet during zoom office hours.__

## APPM 4370/5370: Projects

By Wed Apr 29 at 11am, you will either email me your final report (10-15 page paper or jupyter notebook) or email me a link to a 15-25 minute video presentation of a slide talk (e.g. Powerpoint, Keynote, or beamer). As part of the report or presentation you must thoroughly read the paper (several times), summarize it, recreate two results figures, and create two new results figures which are extensions of the work in the paper. The report/presentation should be structured to include an introduction, methods, results, and discussion section.

**Introduction:**Provide a detailed summary and motivation of the work in the paper (2-3 pages/slides).

**Methods:**Explain in detail the mathematical model the paper examines, defining all terms, and provide some details on the mathematical methods they use, and any new methods you will use to extend results in your paper (2-3 pages/slides).

**Results:**Recreate two results figures in the paper and explain what they mean and then produce two new figures which are interesting extensions of the results already presented in the paper. Provide a detailed explanation of what all the plots you provide mean and explain what you learn from them (4-6 pages/slides).

**Discussion:**Provide a neurobiological interpretation of your findings from the paper and suggest any future studies or analyses that would be interesting to consider (2-3 pages/slides).

The goals for the project are for you to learn about ongoing research in computational neuroscience, demonstrate understanding of its value, and gain experience asking/answering your own relevant research questions. The paper/presentation should demonstrate you have done all this.

A simple growth model constructs critical avalanche networks by LF Abbott & R Rohrkemper (2007)

Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity by C Borgers & N Kopell (2003)

Generative models of cortical oscillations: neurobiological implications of the Kuramoto model by M Breakspear et al (2010)

Directed intermittent search for hidden targets by PC Bressloff & J Newby (2009)

Neutral stability, rate propagation, and critical branching in feedforward networks by NA Cayco-Gajic & E Shea-Brown (2013)

Delays in activity-based neural networks by S Coombes & C Laing (2009)

Traveling waves of excitation in neural field models: Equivalence of rate descriptions and integrate-and-fire dynamics by D Cremers & AVM Herz (2002)

Ghostbursting: A novel neuronal burst mechanism by B Doiron et al (2002)

Beyond a pacemakerâ€™s entrainment limit: phase walk-through by GB Ermentrout & J Rinzel

Normative evidence accumulation in unpredictable environments by C Glaze et al (2015)

A spiking neuron model for binocular rivalry by C Laing & CC Chow (2002)

Dynamics of spiking neurons connected by both inhibitory and electrical coupling by T Lewis & J Rinzel (2003)

Modelling autonomous oscillations in the human pupil light eye reflex using nonlinear delay-differential equations by A Longtin & J Milton (1989)

Epilepsy in small-world networks by Netoff et al (2004)

Network model of spontaneous activity exhibiting synchronous transitions between up and down states by N Parga & LF Abbott (2007)

Similar network activity from disparate circuit parameters by AA Prinz et al (2004)

Dynamical characteristics common to neuronal competition models by A Shpiro et al (2007)

Human sleep and circadian rhythms: a simple model based on two coupled oscillators by S Strogatz (1987)

Generating coherent patterns of activity from chaotic neural networks by D Sussillo & LF Abbott (2009)

Neural networks with dynamic synapses by M Tsodyks et al (1998)

On the structure of cortical microcircuits inferred from small sample sizes by M Vegue et al (2017)

Neural circuit dynamics underlying accumulation of time-varying evidence during perceptual decision making by KF Wong et al (2007)

Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: A theory by K Zhang (1996)