I’ve been at UofT and CAMH for over five years now, and it’s been a truly incredible time. If someone had told me when I started the lab just how successful it would be today, I wouldn’t have believed it. I’m so proud of my lab, our science, and the great friends and colleagues we’ve made. Most of all, I’m proud of the fantastic individuals I’ve been lucky enough to train and watch become legit scientists.

I’m writing this at a major life juncture: my wife and I are mere days to weeks away from welcoming our first child, a baby girl, into our lives (which is the major reason this post is so late).

These yearly posts can be a bit of a humblebrag as I look back on our successes. This year, I want to contrast my expectations for the lab with its reality today and reflect on how much I got right versus what I was completely wrong about.

The Science

I couldn’t have started my lab at a better time, right as the single-cell revolution was beginning to crest. A few months into my position, I organized a symposium on single-cell biology and the brain at the annual Canadian Association for Neuroscience meeting with Mark Cembrowski. This put my lab on the map in Toronto and across Canada as a lab with the bioinformatics expertise to make sense of these complex data.

This happened just as Corina Nagy, Rebecca Hodge, and others figured out the magic of nucleus dissociation—how, for some weird reason, brain nuclei survive long-term freezing with plenty of mRNA left in them for characterization. This single technical advance is what has made cell-type-specific analyses of the human brain, which power my lab, broadly accessible.

In the early days, I put a ton of effort into doubling down on human analyses. I would tell myself and anyone who would listen that humans are the new model organism. A lot of this focus came from the gentle prodding of my dearly departed former Centre Director, Sean Hill. Sean instilled in us the mandate that our research needed to impact human health—not in 20 years, but tomorrow. I found this hard initially. Sean, Etay, and so many others, including myself, cut our teeth studying rodents. How was I, a neuroinformatics and ephys guy, going to make such a pivot?

We figured it out. Basically, I took the attitude to bet hard on anything involving humans. I was super stoked to work closely with Taufik and his incredibly talented colleague, Homeira. One of the papers I’m most proud of from those early years is the labor of love Homeira and I put together on characterizing ephys from human neocortical biopsies from Taufik’s epilepsy patients (paper link). As we worked on human cells, I was surprised how much a solid understanding of rodent brain cell types, gained from my years curating NeuroElectro.org, more or less directly translated. My enthusiasm for studying the living human brain really paid off. I even got on the local news during our first open house, likely because I was just so into what we were doing.

On the omics side, we’ve gotten so much mileage out of the incredible single-cell genomics resources from the Allen Institute, using them to help interpret other datasets. We do a lot of cell type deconvolution using archived bulk brain tissue, with the goal of figuring out what’s happening in brain disorders.

What I Got Wrong

I’m shocked by how little time my lab has spent curating databases. I expected that great datasets would remain rare, creating a huge need to collect, curate, and share them for meta-analysis. The opposite happened. Data, especially omics data, became cheap, and what mattered most was how recently it had been collected, thanks to the Moore’s Law-like improvements in technology.

The other thing that happened was the absolute demolishing of most other neuroscience fields by omics. Who cared about patching 50 cells when you could sequence the mRNA of 500,000? Hard-core patch-clampers would come to me and ask how to retrain as bioinformatics people. In my lab, this meant that more projects became solid bioinformatics or even epidemiology projects, while my love and bread-and-butter of ephys and cellular neuro became a bit of an afterthought. I think this is a little sad; neuroscience is still waiting for its “omics moment” for physiology.

The last thing I was wrong about was the value of large-scale population cohorts like UK Biobank, ROSMAP, or PsychENCODE. When you have good, multi-modal public data from half a million people, everyone is an epidemiologist.

The Lab

The most important thing about a lab is its people. Over five-plus years, the lab has evolved completely—from just me, to me plus undergrads, to grads plus lots of postdocs, to its current mix of staff, graduate students, post-docs, and undergrads.

I’m convinced that my most important role is to set the lab’s culture. And relatedly, to hire people who best fit that culture. The thing I think about most is how to cultivate an environment where lab members feel mutually invested in each other’s success and where asking questions—even “dumb” questions—is encouraged. These days, our culture is probably my greatest hiring tool. My scientific advice is good, but the collective advice of the lab is unmatched.

A piece of advice I received early on was to have lab meetings as soon as possible, even if it was just me and a couple of undergrads. I’m so grateful we take group meetings seriously. More than anything else, they have created a culture that promotes communication. As I get ready to go on parental leave, I’ve tried to create more subgroup meetings so people can mutually advise each other. It’s been great to see lab members, even the undergrads, ask each other the same kinds of questions I would ask.

The hardest thing is that the lab is constantly changing. A single person can completely change the dynamic, for better or worse. The hardest day of my job was when my first hire, Sonny, and my first grad student, Isabel, told me on the same day that they were leaving. They had both defined the culture of my lab; they were incredible teachers who helped everyone else. It took almost a year to recover from their departure.

These days, I think of the lab as a role-playing game strategy campaign. Each member is seeking their own goals for glory and self-discovery, but we’re on a shared quest together. I am more intentional now about having social events, at least one every couple of months. And I try to be mindful about celebrating our successes—from great lab meetings to graduations and when people leave for greener pastures.

Me

My first couple of years were defined by imposter syndrome. I didn’t think I’d be successful, or I thought any success would be attributed to my circumstances and not to me. As a child of immigrants, I was taught that I’d have to be ten times as successful to be taken as seriously as my native-born colleagues. I think this has resulted in a feeling that no amount of success is ever enough, but it’s also been a boon, as I keep working and striving, even as I’ve been lucky enough to accrue a relative degree of success.

These days, I don’t worry so much about the outcome of any particular thing, like where a paper ends up. Instead, I think more about the big picture. Am I happy with the process? Are we having fun? Are we learning? A body of research is defined over years, not by any one paper or student.

What’s it going to be like running a lab as a new father? I have no idea, but I can’t wait to meet my daughter.