CISC499 projects for Fall 2016/Winter 2017


Although there are 5 project suggestions listed below, please understand that realistically, I can only supervise only a few of them.


Any of the projects listed below will be led by the Poppenk Computational Cognitive Neuroscience (POPMEM) lab, a new NSERC-funded research group focused on understanding the nature of memory and the contributions of neural structures to its function. Students will work directly with the leader of this group, Dr. Jordan Poppenk, who is a Tier 2 Canada Research Chair in Cognitive Neuroimaging cross-appointed to CISC.


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1. Open-source brains: a cognitive neuroimaging experiment database for Python


Our research group has developed an exciting Matlab toolbox for gathering, managing and analyzing data in cognitive neuroimaging experiments called "SuperPsychToolbox" [1]. It logs user behaviour into extremely thorough data files that facilitate integration of brain data with records of what actually happened during the brain-scanning session. Using this toolbox, we aim to change the way that psychologists, neuroscientists and others around the world conduct experiments and analyze the resulting data. Its features and API are described at


We have a problem: in association with Intel, our closest collaborators are developing important new neuroimaging tools optimized for Intel hardware. However, they are pursuing this development entirely in Python. We need a way to convert our complex experimental data files, which are currently saved in the proprietary Matlab format with a variety of complex data types, into Python. Because the same data structures are not available in Python, a key challenge of this project would be to develop an efficient Python structure for storing our scientific data. A tool is then needed to convert our saved Matlab data files into this new Python format, and to convert back again from the Python to Matlab format. Beyond serving as a conversion tool, this work will serve as the backbone of a longer-term effort to port our own toolbox code into Python.


An optional goal will be to create a simple function that uses the Python toolbox PsychoPy to sample keypresses and log them to this database, to demonstrate that the data format is flexible enough to efficiently accommodate new data.


This project is most suitable for a student with an interest in databases, Neuroscience, and/or Psychology.





2. Lifeblogging (telemetry)


An interesting and active topic in human memory research is the way that the human brain represents space at different spatial scales [1]. To address this, some research groups have incorporated “lifeblogging” into their work, a procedure in which participants carry a cell-phone around in a way that it can gather lots of images and other data to be used as stimulus materials. The materials are later presented to participants as they lie in a brain scanner [2] to investigate the neural basis of the individual’s response to the memories.


Along these lines, we wish to create a custom lifeblogging app to securely gather data from participating mobile users. The app would use the user’s phone sensors to gather image, time, audio (obfuscated), GPS, accelerometer, and orientation information throughout the day. This data would be automatically transmitted to our server using an HTTPS POST request whenever the phone was connected to wifi. The app would receive images from the server (gathered from other users) for periodic memory tests (was this your own experience, or someone else’s?). It would also administer memory tests by presenting Google Street View images from the user’s route, and the route of others.


An optional goal would be to prepare this app for use with smart-watches, in which case additional sensors could be deployed (e.g., heart rate).


This project is most suitable for a student with an interest in mobile development, telemetry, Neuroscience, and/or Psychology.






3. Video games for science: A city in flux (procedural city models)


It’s not easy to test memory for space; how do you “really know” how good a person’s memory is for a particular location? One possibility is to manipulate the environment and observe whether the person notices. But you usually can’t change the world like this, and tweaking photographs is time-consuming, often conspicuous, and limited in terms of which manipulations are possible. What is needed is an environment over which the user has sufficient experimental control.


A lot of work has been done in recent years on developing procedural urban modeling tools. With help from Rob Harrap (faculty in Geology), who has worked with procedural generation and GIS as well as on urban modeling at a range of scales, you will adapt and develop tools that generate streetscape environments in Unity3d. The user of the tool is required to learn by navigating, and the tool will then modify the environments, and we will test whether the user can detect the changes. The research question for us is: we hope to use these tools in an experiment that will help us develop an understanding of how people learn to navigate their environments, and how elements of that spatial representation get stronger (or perhaps in some cases weaker) with experience. The development question is: how do you effectively deploy a tool that can build and then modify - by applying rules - a streetscape and then track the details of a user interacting with that space.


As an optional goal, the game would be implemented as a mobile app that prompts requires the user to perform a short navigation twice a day (analogous to an ongoing “commute”).


This project is most suitable for a student with an interest in game design, geographic modeling, and/or Psychology.



4. Video games for science: Queen’s tri-(dimension) pride (photosphere mapping)


How well do you know your way around Queen's campus? That's a question my laboratory wants to ask new and returning Queen’s students using a Unity-based video game that’s based on real campus imagery. We want to learn how spatial representations of our campus change while people get to know it better. We’re also interested in how the neural representations of memories migrate as they age, from one part of the hippocampus (an important brain structure for memory) to another [1].


If you've ever used Google’s Street View, you'll be familiar with the concept of a "Photosphere": a 360° panorama that allows you to pivot your view in any direction [e.g., 2]. In this project, using special camera equipment, we’ll gather photospheres at strategic points around campus; then, using software, we’ll stitch them together, import the images and their geotags into Unity, and build a simple experiment that uses the spheres to test the memory of Queen’s students.


We’ll deploy the “game” both on a desktop and mobile platform that will be used by both new and seasoned undergraduates, staff, faculty, and even alumni; and we’ll eventually gather brain scans to predict which individuals have the best memories in this task.


This project is most suitable for a student with an interest in game design, photography, Geography, Psychology, and/or their campus.






5. Video games for science: like a rat in a virtual maze (VR)


To learn about human spatial memory, our lab has recently started to incorporate 3D virtual worlds into our experiments. We also have recently prepared a VR room with top-end equipment, including a commercial HTC Vive [1], NVIDIA 1080 gtx card, a Unity environment customized for Psychological experimentation, and a complete memory game "experiment" in which human participants experience what it’s like to be a rodent finding its way around a virtual water maze (for early examples of how this has been used in Psychology, see [1]).


We need your help to bring our “virtual water maze” experiment to VR! Doing so will help us address questions related to the way we form spatial maps in embodied vs. video screen spaces. The experiment will also serve as a platform for many future experiments on our VR system.


This will project entail 1) adapting our existing Unity memory game to our HTC VIVE environment using available software tools; and then 2) adding levels to the game that better take advantage of embodied virtual navigation, for instance, allowing you to take note of spatial information in multiple dimensions. The levels you develop will be widely used and promoted, and may also one day be used in a brain imaging study. Prior experience with Unity is an asset, but not strictly required.


This project is most suitable for a student with an interest in game design, VR, and/or Psychology.