Brain and mind researchers of all types: I hope you'll join this conversation at Cognitive Computational Neuroscience (August 6-9, Boston).
There, I'll be zooming out to 40,000 feet to inspire discussion around the question: Why have we been learning so much about the brain and mind for so many decades, but our ability to treat its dysfunction has been so frustrated?
The answer to that question informs what I affectionately call the Grand Plan — a description, in broad strokes, of how brain and mind researchers of all types plan to move from where we are now to societal benefits (including treating brain dysfunction).
I'm envisioning a community-centered conversation unlike any I've seen before; because it's unusual, I unpack it here:
https://www.nicolerust.com/grandplan
I'm grateful to the CCN organizers for providing an opportunity for this. I hope you'll join in!
Fuck it. This was my 2023: getting married, almost dying, learning that the thing about almost dying is that nobody cares except for the people who care so much that it rewrites the world around you, the way that scientists love, the fact that at the end of the day we are our cells, what it means to get caught up inside of #LongCovid while everyone talks about it but nobody listens, the cruelty of doctors, how much we try not to see it all.
“Ideas are getting harder to find” is a pretty bleak thing to believe. It says, “Look around the world. This is pretty much as good as it gets; the returns start diminishing from here. All the problems you see are unlikely to be solved anytime soon, so you better get used to them.” Why would anyone agree to such a thing without putting up a fight?
https://www.experimental-history.com/p/ideas-arent-getting-harder-to-find
@tyrell_turing @DrYohanJohn this is a great question. I've been thinking about it all evening and my answer surprised myself.
When you read a really good and careful experimental paper, and you go through the methods in detail, there's just this staggering attention to detail and willingness to consider all the ways they could be accidentally tricking themselves into seeing what they want to see.
Like, they recorded responses to two different types of stimulus to see the different responses, but then they realised that the ancient PC they were using to generate the stimuli had different levels of fan noise depending which stimuli it was and the PC was in the chamber, so they put the chamber in a sound proof booth. But they didn't stop there, they got high precision calibration equipment to measure the received noise in the booth and it was just still just detectable. So they put the booth on stilts to minimise the vibrations. Then they couldn't detect the noise but they still didn't trust it wasn't there so they filled the room outside with a bunch of PCs generating the same types of stimuli on random uncorrelated schedules to mask the true signal, and so on.
As a computational person it's shameful to say it, but even though this level of attention to detail would be so much easier for us, we just don't do it. I think we're a little bit too willing to allow ourselves to be tricked by our models or simulations and don't put the effort in to stopping it from happening. Our methods sections are just recipes with no explanation as to why 5 layers were used instead of 4, etc.
And to get back to the specifics we were talking about, it's so much easier to trick yourself with a massively complex model with millions of parameters that's so computationally expensive to run that it can only be run a handful of times, and a measure that is so involved we can only guess at what it's actually measuring.
Stop using #Mailchimp.
Mailchimp (a proprietary mailing list and customer CMS platform) has updated its terms of service.
Mailchimp is planning to feed your email content and customer contacts into its AI models.
Mailchimp's email generating AI might spit out content that infringements on another person's copyright. And the new Mailchimp terms of service say you are legally liable for that copyright infringement, not them.
See section 30. Generative AI Features: https://mailchimp.com/legal/terms/preview/
beautiful and lucid reflection of an autistic researcher on her academic journey https://elifesciences.org/articles/93330?utm_source=twitter&utm_medium=social&utm_campaign=organic_features
Congrats to my colleagues Katalin Kariko and Drew Weissman on the Nobel Prize!
My favorite part of this news is knowing that more people (including kids) will get to hear and be inspired by the story behind the science and scientists (especially Kariko).
If you're applying to grad school, reminder that I will be looking for PhD students through the Cognition & Perception (https://as.nyu.edu/departments/psychology/graduate/phd-cognition-perception.html) & Data Science (https://cds.nyu.edu/phd-admissions-req/) programs. Research areas listed below and available here: https://lindsay-lab.github.io
My latest: that guy who's planning to live forever? Yeah he's absolutely going to die. Let's talk about the science of longevity, whether humans have a maximum lifespan, and the philosophical reasons behind why we're so scared of death
https://skepchick.org/2023/09/bryan-johnson-is-going-to-die-sorry/
AoIR will not be using Twitter/X during #AoIR2023. We will be posting here. Please see this announcement for additional information and details. https://aoir.org/aoir2023onmastodon/
We made a robot and landed it on a rock hurtling through space, took samples of that rock, and just this morning, landed the samples safely back on Earth. Scientists will study them for decades. Who knows what they'll learn, about the history of the solar system and the universe. All without endangering human crew or spending the resources needed to support them.
Congratulations to the OSIRIS-REx team and everyone at NASA who has to hear people complain that we don't do amazing things anymore.
Hi All! I just changed instances and feel like this might be a good home for an old neuroscientist like me. A brief introduction: I study the neurobiological underpinnings of episodic memory in rats, pigs and humans, and how they go awry in preclinical models and clinical disorders. I like talking about all things neuroscience, neurocareers and science communication. I am happy to be here and to find some new (and old) SciFriends such as @elduvelle @markgbaxter @alicia_izquierdo and many others!
“Elegant and powerful new result that seriously undermines large language models”
Like I’ve been saying for a while now: LLMs do not think or reason. They are not on the path to AGI. They are extremely limited correlation and text synthesis machines. https://garymarcus.substack.com/p/elegant-and-powerful-new-result-that
Overdue #introduction #1stToot
Hi 👋🏼! I’m a #neuroscience Instructor in Rudebeck’s lab at #MountSinai NY.
Strong focus on animal #learning #DecisionMaking #Reward #valuation and how #prefrontal #subcortical regions represent these and interact at the level of #neurons and #LFP.
Proponent of recording neurons in too many areas simultaneously, and a #Matlab enthusiast (I know.. I complain about it too!).
Off lab, you will find me #biking , pushing a #stroller , and/or enjoying #beers.
#introduction Hi all, I recently switched instances and am getting my profile set up. If you followed me on my old instance I'll not be using that anymore.
I am a PhD candidate in Albert Einstein College of Medicine, working with #intrinsic #manifolds and #decisionmaking , doing some visual cortex research by coincidence.
Am I misunderstanding something?
This appears to be a stunningly irresponsible story in Science, claiming that up to 30% of the scientific literature is fake.
https://www.science.org/content/article/fake-scientific-papers-are-alarmingly-common
Below, the first two paragraphs of the story.
h/t @Hoch
We have moved to neuromatch.social: https://neuromatch.social/@neurofrontiers
We're a neuroscience blog trying to make neuroscience accessible for everyone! Check it out here: https://neurofrontiers.blog