Hybrid meetings and distributed local meetups: the good, the bad and the ugly

The Covid-19 pandemic has propelled the scientific community into a world devoid of in-person conferences. Traditional ‘legacy’ conferences, which have long been the mainstay of academic networking and crucial for catching the latest science, have been largely replaced with virtual events. Moving conferences online is pandemic-proof, and brings myriad other advantages: reduced cost and travel-related carbon emissions, global reach, and increased accessibility for diverse groups. For instance, virtual conferences remove barriers caused by visa restrictions, expensive travel, disabilities, and caring responsibilities. Taken together, these factors can increase the virtual meetings’ diversity, from including students and young parents to attracting scientists from low-income countries and from adjacent research fields.

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2021 in review

I’m a sucker for end-of-year reflections, and this year brought no shortage of memorable events, unanticipated challenges and new life chapters. So here goes: my year in review, in pseudorandom order of my associative memory.

Good things

  • Survived a global pandemic
  • Kept a small, embodied biological neural network alive, fed and mostly happy. Motor control going well, language will be next
  • Bought a house
  • Awarded a Veni grant from NWO, to pursue my research on neural and behavioral noise in ageing
  • Saw my temporary contract turn permanent, thanks to a new national collective labour agreement
  • Published 9 papers and preprints
    • I’m especially happy to have finally submitted the last paper from my PhD, which I started in 2013. Hopefully 2022 will see it published!
  • Co-organized my first conference: very proud of having made a small contribution to NeuroMatch 4.0
  • Spoke at 2 virtual conferences, 1 summer school and 1 panel, and gave 9 virtual talks.
  • Reviewed 8 papers
  • Started supervising 3 student projects
  • Served as an examiner for four PhD theses
  • Designed and taught my first course

Not so good things

  • Survived a global pandemic
  • Increasingly desperate about the point of neuroscience in a world on fire
  • Spent several months so sleep-deprived I could hardly think
  • Failed to make any meaningful progress on analyzing all the beautiful postdoc data I collected
  • Rarely found time to read in depth
  • Wrote five grant proposals that were rejected
  • Registered for too many virtual meetings that I then failed to attend (or tried to catch up on half-heartedly)
  • Bid on four different houses, each time losing out from someone who put more money on the table
  • Promised to take a proper summer holiday, but got interrupted to write a rebuttal to grant reviewers
Not a bad year! Here’s me with some champagne, celebrating after I heard that I’d been awarded the Veni grant. For completeness, note the background with its mess of drying laundry and toys strewn around.

Note-taking 101: from Evernote to Obsidian

Over the years, I’ve accumulated thousands of notes and a personalized GTD system (with tags and notebooks) in Evernote. I use my own flavor of the Zen to Done method, where I capture pretty much everything (from recipes to articles to read, and from project notes to grant deadlines). I’ve come to heavily rely on this second brain, both professionally and personally.

Evernote has served me well for almost a decade. However, the latest update is so annoying (app is super slow, note export to html gone, ) I’m planning to abandon ship. For now, I’ve downgraded to the last useable version on my devices (thanks, reddit!). Getting some great advice from Twitter, I decided that this is the time to invest in a note-taking solution that’s sustainable for the future.

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Post-postdoc acknowledgments and sentiments

Writing the acknowledgment section of my PhD thesis felt like a reward at the end of a long journey: taking the time to highlight everyone who contributed, and appreciating the importance of humanity in science. While there is no such thing as a postdoc thesis, it feels just as significant to wrap up the last 2.5 years of my life and career. Since I’m a sucker for end-of-year lists and reflections, these December days of 2020 (what a year it’s been) seems like as good an opportunity as any to reflect on the many people who shaped my postdoc years. Here goes.

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Brain hats

I’m a long-term fan of inventor Ellen McHenry’s brain hat: print out a simple template, cut and fold, and wear neuroanatomy on your head! Ideal for those who are not as brave as Nancy Kanwisher.

The photos below show me, with the brain hat I made during my studies at ENS Paris. I’ve asked students who attended my lecture on neuroanatomy to send me theirs, and I’ll update this page as responses (hopefully) come in.

NeuroMatchAcademy self-organized slow pods

Since Tweets tend to get lost/unfindable, I’m putting the links for self-organized NMA material study groups here.

I’d be happy to hear back (comment on this post) if you’ve found a pod. How are your experiences going through the materials?

Being the RNG

How would you generate a sequence of random numbers, if you didn’t have a computer or calculator? Each time you typ rng default or random.randint, numbers get drawn from precise observations of some natural process or special algorithms to produce sequences of numbers with certain properties of randomness. But what if your laptop died, your phone had no reception, or you’d suddenly find yourself transported 50 years back in time? How could you approximate random sampling from different distributions just using pen, paper, and whatever you could find in your house?

I thought of three categories (to start with): A. human-made randomization gadgets, B. measurement, C. just you in an empty room.
Rules: Please share your best guesses and intuitions and limitations of each method. If you know what exact distribution can be approximated with each process, please let me know – I’ll update the post as more ideas come in. Do not Google (or be honest if you did). Let’s play!

Update: see the Twitter thread for a bunch of interesting responses and suggestions – I’ve copied some of those into the list of suggestions below (no guarantees).

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#ShutDownSTEM; fighting racism in academia

The last few weeks in the US have been a political and emotional tornado. As protests spread around the country and beyond, I compulsively read the news, went to a local protest and watched Ava DuVernay’s chilling documentary 13th. I also thought a lot about the different ways in which societal and systemic racism manifests itself in the US vs. in Europe. I’m most familiar with the situation in The Netherlands, where (after some initial squabbling about social distancing during a large Amsterdam protest) there has been a more serious conversation about structural obstacles facing people of color and those without traditional Dutch last names (see e.g. here and here).

After a week or so, the conversation among academic on Twitter rightfully shifted. People went from focusing their outrage at police brutality, to examining the many problems with racism that take place in our own professional spheres. On Twitter, #BlackInTheIvoryTower launched a much-needed, painfully honest conversation about the many ways racism pervades academic culture.

I’m here sharing my thoughts, personal commitments to fighting racism in science, and resources.

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Climate action for (neuro)scientists: a concrete guide

Update [19-11-2021]: see the new Green Neuroscience page for more writings, recorded talks, and slide decks on this topic. I’m no longer updating this blog, but the information is still highly relevant.

Note [December 2020]: this blogpost led to an SfN petition, and then to an opinion paper that lays out in more detail what neuroscientists can do against climate catastrophe. If you prefer something with a doi, that one’s for you.

Climate change is the most urgent problem currently facing humanity – including a subset who call themselves (neuro)scientists. While many academics still consider (political) activism far outside their comfort zone, the broader scientific community is slowly waking up to the urgency of the situation and the role we can play as a community of evidence-minded individuals. I believe there are few excuses for not engaging with this issue, and there are many ways to productively do so.

Since many scientists seem reluctant to speak up or unsure where to start, I’m collecting a short list of concrete things you can do (in approximate order of effort/difficulty). Pick one, get started and join the global effort necessary to tackle this problem; after all, aren’t we problem-solvers?

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