Leonardo Dalla Porta
@ldallap.bsky.social
190 followers 500 following 17 posts
Physicist by training working in Neuroscience (PhD). Into brain states and their transitions. Newbie climber https://ldallap.github.io/
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Reposted by Leonardo Dalla Porta
aitormg.bsky.social
Are you at the @cnsorg.bsky.social conference?

Do you like networks? Brain-like networks? Pretty and structure rich networks? 🙇‍♂️🧠🕸

Come to my Poster 204 this afternoon (or anytime today)!!

The poster is right next to the coffee! ☕️ 😉

#CNS2025 #CNS2025Florence 🇮🇹🍝
Brain networks from many animals have nonrandom structure. Including high clustering, short path lengths, heavy tailed weight distributions, and heavy-tailed degree distributions.
ldallap.bsky.social
Great news Dan. All the best!!!
Reposted by Leonardo Dalla Porta
macshine.bsky.social
I recently had the great pleasure of interviewing Michael Bruchas about an absolutely banger recent paper from his group that tracked down cells in the brainstem that subtlety and precisely control the output of the locus coeruleus. Check out my interview here. I hope you like it as much as I did!
Reposted by Leonardo Dalla Porta
Reposted by Leonardo Dalla Porta
chrisbehler.bsky.social
🧠🌡️ New preprint out!

BRAIN TEMPERATURE may be a key factor in understanding and treating Alzheimer’s disease and brain cancer:

doi.org/10.31219/osf...

'Temperature matters: Insights into brain thermoregulation and its impact on neural activity and health'
Reposted by Leonardo Dalla Porta
ungteoriz.bsky.social
Despite species and task differences, timescales of these reward history signals (as well as intrinsic timescales) follow the same pattern of cortical hierarchy across different species.

www.pnas.org/doi/10.1073/...
(B–D) Behavioral task for each species. Matching pennies task for monkeys (B), dynamic foraging task for rats (C), and visual discrimination task for mice (D). (E–G) Correlation between the timescales of neural activity and anatomical hierarchy score in monkeys (E), rats (F), and mice (G). Each dot and error bar, respectively, indicate the median and SE of the timescale within each area. In (F), black and pink dots represent data from the neocortex and hippocampus, respectively. Note that the data from the hippocampus (CA3, CA1, and SUB) do not have a precise hierarchy score. In (G), black and red dots represent data from the neocortex and thalamus, respectively. Blue, green, and yellow shading indicate the regions in the visual, somatomotor, and prefrontal areas, respectively. Dashed lines denote linear regression.
Reposted by Leonardo Dalla Porta
marinopagan.bsky.social
1/7 Our paper on individual variability in decision-making is finally out in @nature.com! Inspired by the classic work by Mante and Sussillo, we trained many rats to solve context-dependent decision-making, and we found that different brains use different neural mechanisms to solve the same task!
Individual variability of neural computations underlying flexible decisions - Nature
Behavioural experiments to study decision-making in response to context-dependent accumulation of evidence provide testable models that are consistent with the heterogeneity in neural signatures among...
www.nature.com
Reposted by Leonardo Dalla Porta
andrewtanyongyi.bsky.social
Trajectories in state space are shown in Figures 3 & 4 of Stable propagation of synchronous spiking in cortical neural networks (Diesmann et al, Nature, 1999).
Stable propagation of synchronous spiking in cortical neural networks - Nature
Nature - Stable propagation of synchronous spiking in cortical neural networks
www.nature.com
Reposted by Leonardo Dalla Porta
carandinilab.net
It's finally out!

Visual experience orthogonalizes visual cortical responses

Training in a visual task changes V1 tuning curves in odd ways. This effect is explained by a simple convex transformation. It orthogonalizes the population, making it easier to decode.

10.1016/j.celrep.2025.115235
Reposted by Leonardo Dalla Porta
pessoabrain.bsky.social
**The ultimate systems #neuroscience paper!**

Recording every spike, every stimulus, every action during person's first half of life to predict second half?

The future of papers and neuro, are we almost there yet? That would great discussion to have online.

www.thetransmitter.org/systems-neur...
Imagining the ultimate systems neuroscience paper
A growing body of papers on systems neuroscience and on giant simulations of neural circuits involves data beyond the point that anyone can reasonably understand end to end. Looking ahead, “paper-bots...
www.thetransmitter.org
Reposted by Leonardo Dalla Porta
mpicbs.bsky.social
The human 🧠 has two halves that make our behaviors and thoughts more efficient. How the asymmetry of the brain halves contributes to human cognition, examined @wanb.bsky.social & @sofievalk.bsky.social in their study in Nature Communications: www.cbs.mpg.de/2316389/2024...
How asymmetry of brain halves contributes to human cognition
How asymmetry of brain halves contributes to human cognition
www.cbs.mpg.de
Reposted by Leonardo Dalla Porta
tyrellturing.bsky.social
Super pumped to say that this paper, which takes us another step closer to a proper foundation model for neural data, will be coming out at #NeurIPS2024. Big thanks to Liam Paninski and @colehurwitz.bsky.social for letting me be a part of this amazing project!
colehurwitz.bsky.social
Ported over from X!

What will a foundation model for the brain look like? 🧠

We argue that it must be able to solve a diverse set of tasks across multiple brain regions and animals.

Check out our NeurIPS paper which introduces a multi-region, multi-animal, multi-task model arxiv.org/abs/2407.14668