CNS 2018
In the neurosciences, there exists a veritable orgy of data – but is that what we need?
Will the colossal datasets we now enjoy solve the questions we seek to answer, or do we need more ‘big theory’ to provide the necessary intellectual infrastructure?
Four leading researchers, with expertise in neurophysiology, neuroimaging, artificial intelligence, language, and computation debated these big questions in “Big Data Versus Big Theory,” a special session at this year’s 25th annual CNS meeting in Boston:
- Alona Fyshe (University in Victoria, British Columbia): Data Driven Everything
- Eve Marder (Brandeis): The Important of the Small for Understanding the Big
- Gary Marcus (NYU): Neuroscience, Deep Learning, and the Urgent Need for an Enriched Set of Computational Primitives
- Jack Gallant (University of California, Berkeley): Which Presents the Biggest Obstacle to Advances in Cognitive Neuroscience Today: Lack of Theory or Lack of Data?
Watch their talks here (will play all 4 talks back-to-back plus the intro, debate, and Q&A/group discussion):
Some highlights:
Grand Ballroom is filling in for Big Theory v. Big Data. Join us for the debate! #CNS2018 @davidpoeppel pic.twitter.com/EOuCqA8J1V
— CNS News (@CogNeuroNews) March 24, 2018
.@davidpoeppel introducing a “wonderful cast of heroes for the epic battle” #CNS2018 #sciencedebate #Neuroscience pic.twitter.com/fY2mr8iTCX
— CNS News (@CogNeuroNews) March 24, 2018
.@MarderLab on the continuing importance of the small for understanding the big #CNS2018 pic.twitter.com/gCtigWGv7O
— CNS News (@CogNeuroNews) March 24, 2018
But building models of large numbers of neurons means either using reduced models that sacrifice biological accuracy or building models incomprehensible for real brain –@MarderLab #CNS2018#sciencedebate
— CNS News (@CogNeuroNews) March 24, 2018
.@alonamarie a computer scientist — I think we can play well together, I think data and theory can go hand in hand #CNS2018 pic.twitter.com/poNT74isuw
— CNS News (@CogNeuroNews) March 24, 2018
“If you have the data, you don’t have to have a strict theory that puts you in a corner” –@alonamarie #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
“Let the data kill our little darlings” – nice ending from @alonamarie that merges computer science with neuroscience with #scicomm and writing 🙂 #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
.@GaryMarcus on “The original sin: the misguided search for the one circuit that rules them all” #CNS2018 pic.twitter.com/PWzEnJnkZh
— CNS News (@CogNeuroNews) March 24, 2018
If we know nothing else about biology and the brain, it’s that biology is tremendously diverse at every level that we look –@GaryMarcus #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
There’s been some progress with deep learning on perception but nothing else that goes into cognition –@GaryMarcus #cns2018#AI #ArtificialInteligence
— CNS News (@CogNeuroNews) March 24, 2018
.@gallantlab “This debate is silly” #CNS2018 pic.twitter.com/cpT7tKI0xa
— CNS News (@CogNeuroNews) March 24, 2018
The question isn’t big theory v. big data but which is the more limiting factor in progress in cognitive neuroscience right now –@gallantlab #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
For those who can’t do these experimental designs, @gallantlab is building a tool to interrogate naturalistic data https://t.co/dERYD3PPRR #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
Now the debate part! @davidpoeppel @MarderLab @gallantlab @alonamarie @GaryMarcus #CNS2018 pic.twitter.com/Brf44qoHmW
— CNS News (@CogNeuroNews) March 24, 2018
Unlike a brain, there’s no structure to the way a computer is run –@alonamarie #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
Software and hardware are intertwined in the brain, unlike in a computer –@gallantlab #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
“Chance favors prepared mind”… Mendel identified genetic factors, based on top-down, and then when others found the molecular mechanism, they could map to the factors –@GaryMarcus #cns2018
— CNS News (@CogNeuroNews) March 24, 2018
It’s getting really heated here. Roughly as heated as in a microprocessor running without a fan, stuck on some local minimum computation. @CogNeuroNews #CNS2018 with @davidpoeppel @gallantlab @GaryMarcus eve Marder and @Alina marie pic.twitter.com/Xb1mvqR8dU
— Jonas Obleser (@jonasobleser) March 24, 2018
This sums up the last exchange@gallantlab v. @GaryMarcus #CNS2018 pic.twitter.com/bGEQcf5jg7
— CNS News (@CogNeuroNews) March 24, 2018
