When Haider Raiz arrived at McGill, he wasn’t sure if he was going to be involved in research. Any doubt he had has clearly been removed; this year he will be publishing his second article in the McGill Science Undergraduate Research Journal (MSURJ) Riaz published a biophysics paper later year, and his fascination with groundbreaking discoveries in physics sparked a desire to conduct research of his own. “I was in physics and started reading about people like Feynman and other notable physicists… I thought their curiosity and intuition for understanding certain topics was cool,” Riaz explained. This, in combination with his preexisting interest in biology, drew him toward the field of biophysics. “[In the Resiner Lab,] we looked at transverse fluctuation of a DNA polymer in a nano pit system. Specifically, DNA that was trapped between two slits in this system and we investigated models that would describe the fluctuations of the trapped DNA.”
Riaz found another research opportunity after his first PHGY 209 lecture, when Professor Erik Cook announced that he was looking for undergraduates to work in his lab. After completing coding courses to meet the prerequisites to work in Cook’s lab, he began research in the Department of Physiology, ultimately completing a 396 research project course. His 396 project was to analyze the strategy that the brain employs when forming perception by listening to neurons across two separate sensory patches. The purpose of his experiment was “[…to determine if] the brain listens to all neurons equally, if it is weighted towards more reliable neurons, towards the neurons that have the tightest link to behaviour, the neurons that are correlated with neurons from the other sensory pools, or some combination of this.”
As the semester-long project was drawing to a close, Cook asked him if he would like to continue working on the project over the summer. Riaz accepted, and continued his work on microsaccade analysis – which led to his latest publication. Riaz notes that his data is not only valuable on its own: “The microsaccade analysis is only one component of the entire experiment. The primary component is to see whether microstimulating neurons in the MT area can you cause perception in the monkey. And then can you ultimately influence behavior.”
Data was collected by using microelectrodes implanted into the MT area of the brain. Microstimulation was then applied to explore the neural systems that control visual fixation and microssaccades. The experimental design started with two random dot motion patches and a monkey releasing a lever based on the coherence of the random dot motion matches. The monkey’s eye movements were simultaneously recorded using a camera and microelectrodes were used to see if microstimulation lead to any effects in perception. Riaz noted that collecting the data was very difficult – it took almost a year and a half to get the data he needed! However, the work paid off, and Riaz got positive results. In this case, positive results meant that there were more microsaccades on trials with microstimulation. Riaz described the challenge in analyzing the results from the experiment, “My professor had told me to do an analysis called a spike triggered average. The peer reviewers told me to call it a microsaccades triggered average because of the use of microsaccades instead of spikes, and they were right.” He continued to explain his analysis by coming to a conclusion of wider significance, “our results showed that an increase in microsaccade is caused by a microstimuation. This means that somewhere back in time, there should be a temporal link between the microstimulation and the microsaccade.” Although the microsaccade-triggered average showed this link, the low level of significance worries Riaz. With a statistically-stronger result, Riaz feels that the research would receive more attention and others would start to replicate it. Beyond this, others would perform further studies about the optimal level of microstimulation that would cause more microsaccades. However, he concluded by saying that “the results do show an increase and it can be replicated to see if there is a temporal link.”
MSURJ owes a Ph.D. student thanks for directing Riaz to the journal as a place to publish his work. He noted, “When I first started research, I was collaborating with a PhD student. I didn’t know where to publish and he suggested MSURJ as an excellent publication. I have found the feedback from the editorial staff and the peer-reviewers to be especially helpful and detailed.”
This summer, Riaz plans to further explore one of his diverse interests in the Ruthazer lab at the McConnell Brain Imaging Centre. There, he will be porting an image de-noising algorithm – which is currently written in MATLAB, with C++ components compiled in Mex – over to Java for integration into ImageJ as a plug-in. Clearly, this will not be the last publication that Riaz is involved in. Riaz has clearly become involved with research at McGill – and perhaps will continue with research beyond the Roddick Gates.
With files from Sapan Patel
You can read Riaz’s article here*.
*Links to the original research articles will be available as soon as the journal is uploaded online at msurj.mcgill.ca