NeuroTMA Lab

Neuro-inspired Theory, Modeling, and Applications research group led by Mihai A. Petrovici @unibern

[CLaE @leafs_s]

eLife

Learning cortical representations through perturbed and adversarial dreaming
https://t.co/wVI4s8gjkP

[Arturo Deza @ArtDeza]

An Exciting New Dataset! 🤯

[Brando Miranda @BrandoHablando]

I feel not enough people know about the abstract arts dataset Delaunay. I'm using it for my comparison of pre-training vs MAML in my upcoming work and wanted to share it: https://t.co/Z5tU8uwx3v leave a comment if you have thoughts!

[Pablo Lanillos (🤖🧠) @PLanillos]

Check our new perspective article led by @Mario_Senden about building large-scale brain models published in @NSR_Family
👇
https://t.co/DY3n6PvHCW

@HumanBrainProj @HBPNeurorobotic

[Research Directions @CUP_RDirections]

Is neuromorphic computing disruptive enough to advance our understanding of the brain & make the design & working of (bio)electronic devices efficient & scalable? ask Samit Chakrabarty @sc_laboratories & Mihai A. Petrovici @NeuroTMA for #RDBioelectronics

https://t.co/9ZdLsyYlr4

[Research Directions @CUP_RDirections]

🟣Is neuromorphic computing disruptive enough to advance our understanding of the brain & make the design & working of (bio)electronic devices efficient & scalable? ask Samit Chakrabarty @sc_laboratories & @NeuroTMA for #RDBioelectronics

https://t.co/mXb0xmkde8

#bioelectronics

[Quantitative Biology (Neurons and Cognition) @BioPapers]

Gradient-based methods for spiking physical systems. https://t.co/C9TXV28Sdw

[Neural and Evolutionary Computing Papers @TAL]

Emulating insect brains for neuromorphic navigation. https://t.co/1fUDaRCcN6

[Quantitative Biology (Neurons and Cognition) @BioPapers]

Backpropagation through space, time, and the brain. https://t.co/5uexh9Y9PA

[Kording Lab 🦖 @KordingLab]

what are the ethical problems specific to neuroAI? https://t.co/4awcQxeekl

[HBP & Society @HBPSociety]

Curious about brain-inspired #AI, #neuroscience and #neuroethics? Take a look at this week's #HBPSummerSchool blog post featuring @MicheleFarisco's presentation on #aiethics!
https://t.co/IGqiESgT7v

[Michele Farisco @MicheleFarisco]

On the same topic also available a preprint: https://t.co/D8g4yP4bjl #AI #AIethics #brain

[Centre for Research Ethics & Bioethics @crb_uu]

Curious to learn more about brain-inspired #AI? Take a look at this study which examines conceptual, technical, and ethical issues raised by the development and use of brain-inspired AI #CRBSummerRead 🧠

https://t.co/SrlgI0Okf4

[fellow ⚚ traveler ❤️‍🔥 @architectonyx]

@fchollet a cool recent paper on cortical circuit function is this one, Bengio was actually a co-author on it

has cool ties with predictive coding, biologically plausible/backprop free learning

https://t.co/ZDdwCMYm5w

[bioRxiv Neuroscience @biorxiv_neursci]

Increased perceptual reliability reduces membrane potential variability in cortical neurons https://t.co/vEhwsTrBC1 #biorxiv_neursci

[Quantitative Biology (Neurons and Cognition) @BioPapers]

Prospective and retrospective coding in cortical neurons. https://t.co/T2T9JlN2OD

[Emerson F. Harkin @efharkin_]

What’s the point of strong spike frequency adaptation in serotonin neurons?

This new work offers a clue: adaptation lets neurons broadcast a prediction of their future output, preventing slow downstream regions from lagging behind. 💡

https://t.co/4ZnEIfJGHN

[Quantitative Biology (Neurons and Cognition) @BioPapers]

Prospective and retrospective coding in cortical neurons. https://t.co/T2T9JlN2OD

[bioRxiv @biorxivpreprint]

#PeerReview from @eLife of 👉🏿 Uncertainty-modulated prediction errors in cortical microcircuits https://t.co/cJV5ozy3gm #biorxiv #reviewedpreprint

[bioRxiv Neuroscience @biorxiv_neursci]

#PeerReview from @eLife of 👉🏿 Uncertainty-modulated prediction errors in cortical microcircuits https://t.co/NXLUVJgvQC #biorxiv_neursci #reviewedpreprint