top of page

Interview with Ben Cuthbert

Updated: Sep 9, 2020

📷 Ben Cuthbert

Journalist: Emily O’Halloran

Interviewer: So we're joined today with Ben Cuthbert who is a PhD student in computational neuroscience at Queens University welcome.

Ben: Hi.

Interviewer: So do you think you could give us kind of an overview of what it is specifically that you're researching right now?

Ben: Yup so I'm going to computational neuroscience lab where we use techniques from engineering computer science to study the brain uh specifically I study working memory which a lot of people refer to as short term memory and uh I use a combination of experiments and uh computer modeling to try to understand how that works

Interviewer: Very cool So what kind of experiment do you do to understand the short term memory and working memory?

Ben: Um the earlier on my PhD Anna my Masters we did a lot of behavioral experiments with humans so we get people to sit in a chair and remember things on the computer screen try to make predictions about how that goes down now on my current project I'm working on data from experiments done with monkeys or we actually have electrodes stuck into certain brain areas and we record the neural activity as they remember things.

Interviewer: Wow so do you expect that there will be like any similarities between the ways that monkeys remember things in the ways that humans other things?

Ben: Yeah I mean the idea of that approach is that these monkeys we use rhesus macaques the idea is that their brains are really really similar to humans as good as it gets without having an actual human brain so hopefully they're pretty similar.

Interviewer: wow very cool and why do you choose to use monkeys like is it an invasive procedure?

Ben: Yeah and you can't stick an electrode into a human brain have to do things there are some exceptions like sometimes seizure patients or Parkinson patients things like that they'll have electrodes in there in their brains already for stimulation other purposes and we can occasionally record from there but it's really rare and most of the time we're stuck with other monkeys or mice or another model Organism

Interviewer: Right, so how did you get into this whole field of computational neuroscience and modeling the brain?

Ben: I did my undergrad in life science thought I wanted to go to Med school and then in fourth year I was fortunate enough to end up in a computational neuroscience lab for my thesis and realized that I loved programming and I love math and this is a good way to sort of build on my life science skills while getting into a little more computational research

Interviewer: Right cool so what is it that makes you passionate about this field of research?

Ben: Um I think maybe I shouldn't speak for other people but I think what personally for me and some people that I know what hooks us into computational neuroscience is that it allows me to have a little bit of a philosophy about the brain like there are a lot of kind of questions that you can try to tackle with math that are also easy to have sort of armchair theories about and you can really really everyday as you walk around is constantly thinking about why am I doing this why is my brain doing this how are other people behaving things like that it just kind of the more I think about it it kind of works its way into your everyday life and I think that keeps me interested.

Interviewer: That's so true it's constantly impeccable no matter what you're doing. So what is it that makes your current research important in the grand scheme of things?

Ben: Um so my research project it doesn't have like immediate clinical applications or applications in industry or anything like that so it's kind of a hard question but we do basic research and I think maybe something that's under appreciated by people haven't thought about this that much is is how basic research just really asking simple questions about how the world works really forms a foundation for other discoveries or developments that come out later that can have a sort of a big impact on the world.

Interviewer: Yeah this is a stepping like a fundamental building block for understanding have you seen any significant advancements in the neuroscience field since beginning your research 'cause you said you began in your 4th year of your undergrad but now you're part way through your PhD have there been any major advancements you've seen?

Ben: So in the past three years to be honest it's mainly been like playing catch up you know I'm constantly reading finding papers from the 90s or 80s or whatever that seems shockingly relevant today I wouldn't say there are specific like groundbreaking discoveries in the sense that some people might imagine happen but for me there's definitely trends that I'm excited about and I think are interesting.

Interviewer: So what trends are those?

Ben: Something that I think people are getting more interested in now is investigating true causal relationships as opposed to correlations in the past people have been really focused on correlating neural responses so their response of a brain cell to for example a specific stimulation and correlating that with behavior and formulating theories based on those correlations in recent years or at least in the circles that I hang out with people seem to be a little bit more concerned about causality and not just correlation so there are a lot of techniques that are being developed like brain stimulation because if you go in and you stimulate the brain for example something like transcranial stimulation which is just giving a little bit of current across the skull to a specific brain area by stimulating the brain you can be sure that the effects you're seeing are actually the result of your actions and that you actually understand the mechanism and you're not just you know witnessing a correlation or something that's not causal.

Interviewer: Like a direct more direct method kind of.

Ben: Yeah perturbation is is the word that people would use for that and I think I think there's definitely a big call for people to have more causal mechanisms and really be more rigorous in their experiments less hand wavey about explaining away their data.

Interviewer: Yeah that's great I I wouldn't even think of that that's fantastic so do you think you kind of say what research you've done so far like what different projects you've had and what have been your favourites what have been the takeaways from those.

Ben: The brain is really complicated if you big takeaway it's pretty common for people to say that um you know before basically once you're done your Masters you realize that you don't know anything and then once you finish your PhD you realize that nobody knows anything as like a common setting in academia and I'd say that's kind of been my biggest takeaway is not nobody like there are a lot of really smart people make doing really great work but really realizing just like how incredibly complicated the brain is and people people who claim they understand how the brain works most of the time are pulling the wool over your eyes 'cause it's really really tough problem.

Interviewer: Wow interesting do you know what you're going to do once you finish your PhD do you think you will remain in academia? Do you think you'll take it to more medical related field? Or yeah do you have any ideas?

Ben: It's tough question depending on the day I usually answer that question differently or when I'm talking to you but I'm pretty likely to do a postdoc if there's a cool opportunity in a cool city somewhere with work that I'm interested in I'll probably do something like that for a year or two my second option after that would actually not be medical but going into industry our field has a lot of overlap with sort of machine learning data science applications and I think for people in my lab or my fields that's a pretty common option more common than academia for sure.

Interviewer: interesting so would you be I guess you know obviously by employing your coding skills that you've learned through this lab would there be any use of like would you be using your neuroscience understanding in the machine learning field?

Ben: I think there are some opportunities I haven't haven't done a lot of query search so far but there are some opportunities with businesses or companies that actually study the brain and are using AI to do so but that's pretty rare I would say most likely I would end up just using general data analysis experience maybe some of the algorithms or methods that I use with crossover but the main the main skill that are developed is being able to read like dense technical writing and learn it quickly so that probably no important my biggest strength we’ll see when I hit the job market.

Interviewer: So you're talking about you know more causal experiments and correlation experiments what are some experimental techniques that you have seen so you said stimulation of the brain are there any other causal experiments that you can.

Ben: Yeah so there they're mostly mostly stimulation and the one that I've mentioned before is called transcranial direct current stimulation which means sending current across the skull through the scalp in the skull in the hair and everything it's kind of messy because you have to go through all these different layers you're not sure exactly where the currents going there are other techniques that involve using magnetism there's transcranial magnetic stimulation is another example of that some people are actually doing in brain tissue they can do microsimulation so there's sticking actual electrodes in and directly stimulating the cells with that issue lots of other examples like that I guess is also inactivation some people will use coils sort of cooling coils in monkey brains not humans and you can deactivate selectively certain parts of the brain superficially and make predictions about what that will do so those are kind of examples of causal interventions that you can do most of them are pretty difficult

most are invasive trans cranial and despite how scary it sounds it's actually not that invasive then we actually do a turn not to ourselves but to each other quite a bit.

Interviewer: Neat very neat so what does a typical day look like for you in this you know in this PhD life that you're living?

Ben: I mean aside from like sort of the um administrative email stuff I do in the morning I usually start my day by reading a few papers so either papers I have a gigantic back lot of papers that I'm supposed to be reading and usually I ignore that backlog and find some shiny new paper on Twitter or something and read that so usually couple hours a day at least reading papers and then the rest of the day will be spent either sitting in my chair trying to figure out some math or implementing code that I like implementing algorithms or models that I'm reading about and trying to apply it to my own data.

Interviewer: Wow that is so cool.

Ben: Some people think programming schools some people don’t.

Interviewer: I think the world thinks program is pretty cool it's kind of the way everything is going well thank you so much that was Ben Cuthbert thanks for joining us.


bottom of page