Catalyzing next-generation Artificial Intelligence through NeuroAI
#neuroscience #AI #neuroAI #ML #DL #neuralnetworks
https://doi.org/10.1038/s41467-023-37180-x

Save the date of our next UCL #NeuroAI online seminar, where we are excited to be hosting Prof. Jakob Macke @jakhmack (University of Tübingen) for a talk on "Bridging machine learning and mechanistic modelling"

🗓 Wednesday 15 March 2023
⏰ 2-3pm GMT
ℹ Find out more and register here:

https://www.ucl.ac.uk/research/domains/events/2023/mar/ucl-neuroai-talk-series-professor-jakob-macke

Choice blindness. What!?

Learned about this in a new book by @summerfieldlab:

One fascinating instance of this is the phenomenon known as choice blindness. In a study conducted in Sweden, people were asked to fill out question- naires about their political views. After submitting their answers, they received them back and were asked to verbally explain their views. Unbeknownst to participants, researchers switched the answer sheets, so that left-leaning people received right-leaning answers back, and vice versa. Of the 75% who failed to notice, many were happy to provide elaborate justifications for political positions opposing their own, apparently blind to the choices they had just made. Similar effects have been described with preferences about facial attractiveness and the taste of tea or jam. Choice blindness is an instance of post hoc rationalization, the tendency to invent motives in the light of actions, rather than choosing actions to satisfy motives.

See (Hall et al. 2010), (Johansson et al. 2005), and (Strandberg et al. 2020).

https://global.oup.com/academic/product/natural-general-intelligence-9780192843883?cc=us&lang=en&

#neuroscience #psychology #neuroAI

For the next UCL #NeuroAI online seminar, we are excited to be hosting Prof. Malcolm MacIver (Northwestern University)

🗓 Wednesday 15 February 2023
⏰ 2-3pm GMT
ℹ Find out more and register here:

https://www.ucl.ac.uk/research/domains/events/2023/feb/ucl-neuroai-talk-series-professor-malcolm-maciver

I've realized that Big Ideas about the brain tend to be a chaotic mix of:

• Big Ideas about how we think the brain works,
• Big Ideas about how to figure the brain out (tools, approaches and the like),
• Big Ideas about what we'll do with knowledge about the brain once we have it (like therapeutic approaches).

For example, I jumbled them all up here in the #BrainIdeasCountdown
https://neuromatch.social/@NicoleCRust/109557289393362842

Now that I see the potential for order in Big Idea chaos, I'm obsessed with putting everything that I read and hear (here and elsewhere) in these conceptual buckets. Most notably, I find myself thinking a lot:

"That's a very nice tool and all, but What have/will we learn with it?

#BigBrainIdeas #neuroscience #cognition #neuroAI

Inspired by @LenoreBlum, I'm excited to help celebrate the many diverse voices of "systems neuroscience and general intelligence".
(Everyone): I'm a bit time limited today and can't do this group full justice, so please help me out by adding to the list. Thank you!

Doris Tsao, Berkeley. MacArthur genius, NAS member, HHMI investigator. Doris studies visual perception in primates in order to understand how the brain creates our sense of reality. She's deeply interested in questions about visual awareness, intelligence and consciousness.
https://vcresearch.berkeley.edu/faculty/doris-tsao

Dani Bassett, UPenn. MacArthur genius and so many other awards, author of over 300 publications and one of the most highly cited researchers via web of science. They study a host of intelligence-related topics including how humans learn graphs of related concepts and how brain connectivity reflects cognitive capacities and changes during adolescent development.
https://live-sas-physics.pantheon.sas.upenn.edu/people/standing-faculty/danielle-bassett

Tirin Moore, Stanford. NAS Pradel Research award winner, NAS member, HHMI investigator. Tirin uses systems neuroscience approaches to investigate the neural basis of cognition with an emphasis on attention, a fundamental component of visual awareness.
https://profiles.stanford.edu/tirin-moore

Marlene Cohen, UChicago. @marlenecohen. Troland award from NAS and many others; executive committee on the Simon's Foundation for the Global Brain. Marlene uses systems neuroscience approaches to study visual cognition and visual attention/awareness. She's a leader in the application of population-based approaches including subspace communication and topological approaches.

Emery Brown, MIT
Winner of the 2022 Gruber award, along with so many others; NAS member. A large slice of Emery's work focuses on quantifying consciousness level in awake an anesthesia states.
https://www.neurostat.mit.edu/

Megan Peters, UC Irvine. Rising star in consciousness research who uses neuroimaging, computational modeling, machine learning and neural stimulation techniques to reveal how the brain represents and uses uncertainty, and performs adaptive computations based on noisy, incomplete information. Key member of a group funded by the Templeton Foundation to focus "On adversarial collaboration to test predictions of first-order and higher-order
theories of consciousness"
https://faculty.sites.uci.edu/cnclab/

What's inspiring this list? This exciting upcoming meeting:
https://researcher.watson.ibm.com/researcher/view_group_subpage.php?id=11048

#neuroscience #neuroAI #psychology #cognition #AI
#consciousness

@summerfieldlab
February 15th. Exciting!

#NeuroAI #neuroscience #psychology #cognition

https://global.oup.com/academic/product/natural-general-intelligence-9780192843883?cc=us&lang=en&

What are your favorite recent papers on *memory and space* in #neuroscience #computational #neuroAI #psychology #AI #behavioral fields?

🚨​We are excited to be hosting Dr Carsen Stringer (@Computingnature, HHMI Janelia) for our next online #NeuroAI seminar.

🗓️​Wednesday 11 January 2023 (in two days!)

🕑​2-3pm GMT

Find out more and register at bit.ly/3ifXMti

A big thanks to @kendmiller + for helping the #neuroscience community get its hashtag act together!

https://neuromatch.social/@kendmiller@qoto.org/109645950754401219

For neuro paper threads: sigmoid.social/about/more has already claimed #PaperThread and #NewPaper (the latter announcing a paper without a thread) for the AI community. I enjoy seeing their papers too, but we need a distinct tag for neuro papers. For a thread, ... maybe we want something simple like #NeuroPaperThread and #NeuroNewPaper?

Great idea Ken - let's do this.

➡️​​EVERYONE: BOOKMARK THIS! ⬅️​ and follow those hashtags. And then don't hold back. After all, it's what we all show up here for: to hear what you've figured out and learn from you.

#neuroscience #neuroAI #psychology

Hi all!

A quick #introduction -
We foster collaborations and discussion between the #Neuroscience and #AI communities within University College London (#ucl), other academic institutes and industry.

Follow to discover upcoming events (including many hybrid ones), general #NeuroAI news, and other opportunities.

Visit our website for further details and recordings of previous talks.

#arxivfeed :

"Plasticity Neural Network Based on Astrocytic effects at Critical Period, Synaptic Competition and Strength Rebalance by Current and Mnemonic Brain Plasticity and Synapse Formation"
https://arxiv.org/abs/2203.11740

#MachineLearning #NeuroAI #NeuralNetworks #Synapse #Plasticity

2022 saw a whirlwind of #neuroAI research. Brain Dall-E. Neurons in a dish playing pong. GPT predicts how brains process language. I read through a bunch of papers so you don't have to. Read my review of 2022. Featuring the work of @kordinglab , @tyrell_turing , @TimKietzmann and many others.

https://xcorr.net/2023/01/01/2022-in-review-neuroai-comes-of-age/

My end-of-year review of #neuroAI is in the can: it will be released at noon Eastern tomorrow. Hope you enjoy taking in the New Year by reading rambling 3,700 word blog posts.

The bittersweet lesson: data-rich models narrow the behavioural gap to human vision (Geirhos et al): https://jov.arvojournals.org/article.aspx?articleid=2784043

The questions raised at the end of this VSS abstract are interesting and quite important for #NeuroAI research.

"In the light of these findings, it is hard to avoid drawing parallels to the "bitter lesson" formulated by Rich Sutton, who argued that "building in how we think we think does not work in the long run" "

"Should we, perhaps, worry less about biologically faithful implementations and more about the algorithmic similarities between human and machine vision induced by training on large-scale datasets?"

Also see Geirhos et al NeurIPS 2021 for a more detailed version of the findings mentioned in the VSS abstract: https://proceedings.neurips.cc/paper/2021/hash/c8877cff22082a16395a57e97232bb6f-Abstract.html

I wanted to do a narrative review of papers from last year in #NeuroAI, but I think I nerd-sniped myself. Instead, you're going to get a dozen cool papers from last year and a UMAP of the last year in neuroAI.

#arxivfeed :

"Inductive biases of neural networks for generalization in spatial navigation"
https://www.biorxiv.org/content/10.1101/2022.12.07.519515v1

#MachineLearning #ReinforcementLearning #DeepLearning #Neuroscience #Neuro #NeuroAI

Gotta up my mastodon game by including the #neuroAI hashtag... ^^^

#introduction : I am a computer scientist, and I do AI for #neurosience (#NeuroAI).

My work is most well known for:
1) comparing #machinelearning and models of brain #plasticity,

2) optimization in networks of #spiking neurons.

I am currently doing my postdoc with Wulfram Gerster at #epfl

The #neuro and #NeuroAI communities have more or less all migrated here from 🐦. But we’re still missing a good number of #AI folks.