@NeuroTMA

Neuro-inspired Theory, Modeling, and Applications research group led by Mihai A. Petrovici @unibern https://xitter.cf/t.co/0CxlkIIcQo

 Bern, Switzerland
physiologie.unibe.ch/~petrovici/group/
Joined September 2020
  • Tweets476
  • Following337
  • Followers427
61Media
NeuroTMA Lab retweeted
CLaE
@leafs_s6 May 2024
eLife Learning cortical representations through perturbed and adversarial dreaming elifesciences.org/articles/7…

Learning cortical representations through perturbed and adversarial dreaming

A cortical model inspired by cognitive theories and deep learning demonstrates how the combination of wakefulness, non-rapid eye movement (NREM), and REM dreams leads to the emergence of robust and...

elifesciences.org
10
2
45
5,729
NeuroTMA Lab retweeted
Arturo Deza
@ArtDeza6 Feb 2022
An Exciting New Dataset! 🤯
This Post is from an account that no longer exists. Learn more
2
6
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: arxiv.org/abs/2201.12123 leave a comment if you have thoughts!

DELAUNAY: a dataset of abstract art for psychophysical and machine...

Image datasets are commonly used in psychophysical experiments and in machine learning research. Most publicly available datasets are comprised of images of realistic and natural objects. However,...

arxiv.org
1
3
365
Check our new perspective article led by @Mario_Senden about building large-scale brain models published in @NSR_Family 👇 academic.oup.com/nsr/advance… @HumanBrainProj @HBPNeurorobotic
4
5
426
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 bit.ly/3p5dGzs
3
3
208
🟣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 bit.ly/3p5dGzs #bioelectronics
3
1
167
Gradient-based methods for spiking physical systems. arxiv.org/abs/2309.10823

Gradient-based methods for spiking physical systems

Recent efforts have fostered significant progress towards deep learning in spiking networks, both theoretical and in silico. Here, we discuss several different approaches, including a tentative...

arxiv.org
1
1
93
Emulating insect brains for neuromorphic navigation. arxiv.org/abs/2401.00473
1
1
43
Backpropagation through space, time, and the brain. arxiv.org/abs/2403.16933

Backpropagation through space, time, and the brain

How physical networks of neurons, bound by spatio-temporal locality constraints, can perform efficient credit assignment, remains, to a large extent, an open question. In machine learning, the...

arxiv.org
2
9
309
what are the ethical problems specific to neuroAI? arxiv.org/pdf/2305.10938.pdf
1
4
14
4,702
Curious about brain-inspired #AI, #neuroscience and #neuroethics? Take a look at this week's #HBPSummerSchool blog post featuring @MicheleFarisco's presentation on #aiethics! ethicsdialogues.eu/2023/08/2…
1
4
1
9
952
On the same topic also available a preprint: arxiv.org/abs/2305.10938 #AI #AIethics #brain
HBP & Society@HBPSociety23 Aug 2023
Curious about brain-inspired #AI, #neuroscience and #neuroethics? Take a look at this week's #HBPSummerSchool blog post featuring @MicheleFarisco's presentation on #aiethics! ethicsdialogues.eu/2023/08/2…
1
4
3
515
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 🧠 dx.doi.org/10.1007/s10462-02…
2
2
140
Replying to @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 biorxiv.org/content/10.1101/…

A Neuronal Least-Action Principle for Real-Time Learning in Cortical Circuits

One of the most fundamental laws of physics is the principle of least action. Motivated by its predictive power, we introduce a neural least-action principle that we apply to motor control. The...

biorxiv.org
2
9
360
Increased perceptual reliability reduces membrane potential variability in cortical neurons biorxiv.org/cgi/content/shor… #biorxiv_neursci
2
3
1,433
Prospective and retrospective coding in cortical neurons. arxiv.org/abs/2405.14810
4
6
366
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. 💡 doi.org/10.48550/arXiv.2405.…
2
2
206
Prospective and retrospective coding in cortical neurons. arxiv.org/abs/2405.14810
3
2
120
NeuroTMA Lab retweeted
bioRxiv@biorxivpreprint24 Feb 2024
#PeerReview from @eLife of 👉🏿 Uncertainty-modulated prediction errors in cortical microcircuits biorxiv.org/content/10.1101/… #biorxiv #reviewedpreprint
2
2
1,841
#PeerReview from @eLife of 👉🏿 Uncertainty-modulated prediction errors in cortical microcircuits biorxiv.org/content/10.1101/… #biorxiv_neursci #reviewedpreprint
1
6
2,176
Load more