Shervin Safavi

Thank you for having me on BrainInspired, Paul @braininspired.bsky.social! It was such an honor to be on my favorite show—a rare place where we can leisurely talk about manifolds, latent circuits, power laws, and other esoteric ideas, and still be taken seriously in knowing they are all real.

Will start in ~45min ;)

In our Learning Club @cmc-lab.bsky.social today (Dec 4, Thu, 2pm CET), @hritz.bsky.social will tell us about his recent paper (👇) [joint work w/ Jonathan Cohen lab]. Want to attend, send an empty email to virtual talk-link-request@cmclab.org to get the link!

Postdoc & PhD positions
How intrinsic motivation underlies intelligent, open-ended and embodied behavior in natural and artificial agents
Apply if interested
sites.google.com/view/morenob...

Cool PI, great lab, vibrant city for science! What else one needs!

Finally got the job ad—looking for 2 PhD students to start spring next year:

www.gao-unit.com/join-us/

If comp neuro, ML, and AI4Neuro is your thing, or you just nerd out over brain recordings, apply!

I'm at neurips. DM me here / on the conference app or email if you want to meet 🏖️🌮

We are excited to announce that the Cognitive Computational Neuroscience meeting (CCN 2026) will be held at New York University from August 3–6, 2026.
2026.ccneuro.org

Please help spread the word! All contributions tax deductible!

Please repost: another kind of Black-Friday deal!

Exemplary analysis pipeline for respiratory data

'Robust circular cluster-based statistics
for respiration-brain coupling'

New preprint, and what a way to welcome @teresaberther.bsky.social to the #neuroskyence community. With @eliobalestrieri.bsky.social, she developed CBPT for circular #bodybrain analyses.

Paper: osf.io/preprints/ps...

🧵🔽

Evolution of taste processing shifts dietary preference - Nature Calcium imaging of taste neurons and the ventral brain provides insight into evolutionary divergence of food choice in Drosophila species, supporting a role of sensorimotor processing in addition to p...

Thrilled to share our new paper!
With @tomtom-auer.bsky.social team, we asked how #evolution reshapes what animals #eat to match their ecological niches. Using pan-neuronal Ca2+ imaging, we show that the changes are in how the brain processes #taste.
Link @nature.com: www.nature.com/articles/s41...

🚀 We are hiring! 🚀

🔍 Join us as a Postdoctoral Researcher (fully-funded) at the Helmholtz Institute for Human-Centered AI in Munich.

📣🔥Thrilled to announce that 2026 Computational Psychiatry Conference will take place in New Haven, CT, btw July 14-16 -
www.cpconf.org

@robbrutledge.bsky.social @drrickadams.bsky.social @tobiasuhauser.bsky.social @docqhuys.bsky.social @clairegillan.bsky.social Sonia Bishop

More info to come soon!

There are 3 Oxford-based post doc positions for this Wellcome Trust project that will be advertised soon!

If you have experinece in neurostimulation (tms/tus) and/or modelling of cogneuro data in humans do contact one of us (me, @mkflugge.bsky.social @lilweb.bsky.social, Jacinta OShea) to discuss!

Different learning algorithms achieve shared optimal outcomes in humans, rats, and mice Animals must exploit environmental regularities to make adaptive decisions, yet the learning algorithms that enabels this flexibility remain unclear. A central question across neuroscience, cognitive science, and machine learning, is whether learning relies on generative or discriminative strategies. Generative learners build internal models the sensory world itself, capturing its statistical structure; discriminative learners map stimuli directly onto choices, ignoring input statistics. These strategies rely on fundamentally different internal representations and entail distinct computational trade-offs: generative learning supports flexible generalisation and transfer, whereas discriminative learning is efficient but task-specific. We compared humans, rats, and mice performing the same auditory categorisation task, where category boundaries and rewards were fixed but sensory statistics varied. All species adapted their behaviour near-optimally, consistent with a normative observer constrained by sensory and decision noise. Yet their underlying algorithms diverged: humans predominantly relied on generative representations, mice on discriminative boundary-tracking, and rats spanned both regimes. Crucially, end-point performance concealed these differences, only learning trajectories and trial-to-trial updates revealed the divergence. These results show that similar near-optimal behaviour can mask fundamentally different internal representations, establishing a comparative framework for uncovering the hidden strategies that support statistical learning. ### Competing Interest Statement The authors have declared no competing interest. Wellcome Trust, https://ror.org/029chgv08, 219880/Z/19/Z, 225438/Z/22/Z, 219627/Z/19/Z Gatsby Charitable Foundation, GAT3755 UK Research and Innovation, https://ror.org/001aqnf71, EP/Z000599/1

paper🚨
When we learn a category, do we learn the structure of the world, or just where to draw the line? In a cross-species study, we show that humans, rats & mice adapt optimally to changing sensory statistics, yet rely on fundamentally different learning algorithms.
www.biorxiv.org/content/10.1...

Cardiac-vagal rhythm echoes on the heartbeat’s mechanosensory imprint in the brain - Communications Biology Vagal-driven heart rhythm fluctuations modulate the heartbeat strength sensed in the head, linking cardiac rhythms to brain mechanosensation. These findings highlight vagal tone’s role in shaping brai...

Out now in Communications Biology 🧠 🫀We show that cardiac oscillations associated with vagal tone influence the strength of the heartbeat as sensed at brain level. We hypothesize that the heart may send information to the brain, encoded by the heartbeat strength doi.org/10.1038/s420...

A remarkable journey of resilience and transformation, from the chaotic corridors of group homes to the halls of Columbia and Stanford, EMERGENCE is a coming-of-age tale where heartbreak and humor meet the scientific wonder of modern artificial intelligence.

🔗 Preorder: tinyurl.com/fzcxb5ea

Time, space, memory and brain–body rhythms - Nature Reviews Neuroscience Understanding how the brain represents experienced time and how representations of space and time are integrated to form episodic memories has been a goal of much neuroscientific research. In this Per...

🧠🫀 🫁 💯

Time, space, memory and brain–body rhythms
György Buzsáki
(2025)

Physical time is measured using arbitrary units whereas experienced time is linked to a hierarchy of brain–body rhythms... these rhythms, may be the source of our subjective feeling of time. 👇💥

www.nature.com/articles/s41...

Top: Experimental set up. Single pulses of TMS were applied to the hand area of the right primary motor cortex with an inter-pulse interval randomized between 6 and 10 s. Simultaneously, the neuronavigated coil position (yellow), electrocardiogram (red), respiratory signal (blue), electrogastrogram (green), and electromyography from the left hand (gray) were recorded. The figure shows traces of a 20-s time segment from one participant of the cardiac (raw), respiratory (filtered), gastric (filtered), and EMG (raw) signals. The experimental measure was the Motor Evoked Potential amplitude measured on a hand muscle (first dorsal interosseous), analyzed against the phase of the cardiac, respiratory, and gastric rhythms. Note that the three rhythms have very different periods (~1 s for the heart, ~ 5 s for respiration, and ~20 s for the gastric rhythm). Bottom: Artwork illustrating how rhythms of the internal organs interact with the moment-to-moment fluctuations observed in corticospinal motor excitability. Image depicts an outline of a brain with representations of the three rhythmic organs influencing the motor system: the heart, lungs, and stomach. Image credit: Tahnée Engelen.

How do internal bodily rhythms influence #brain activity & motor function? @tahnee-engelen.bsky.social &co show that #cardiac, #respiratory & #gastric rhythms independently modulate motor excitability, revealing distinct #interoceptive profiles across individuals @plosbiology.org 🧪 plos.io/4nMtpLT

🗓️ Mark your calendars: the next #BernsteinConference will take place September 28 to October 1, 2026, in Frankfurt am Main!

Follow the link below to meet the first confirmed speakers. More to come!

👉 bernstein-network.de/bernstein-co...

#BernsteinNetwork #CompNeuro

🧪Preprint!
How foragers depart from optimal models can tell us a lot about how they compute their decisions.

A strong but underexplored departure is that foragers widely vary when they leave identical patches.

A 🧵
doi.org/10.1101/2025...

With
@emmavscholey.bsky.social @brainapps.bsky.social

Our next paper on comparing dynamical systems (with special interest to artificial and biological neural networks) is out!! Joint work with @annhuang42.bsky.social , as well as @satpreetsingh.bsky.social , @leokoz8.bsky.social , Ila Fiete, and @kanakarajanphd.bsky.social : arxiv.org/pdf/2510.25943

Yann LeCun on X: "It won't be AGI unless it uses Emacs." / X It won't be AGI unless it uses Emacs.

You should go for Emacs (half kidding)!

x.com/ylecun/statu...

🚨Registration for Mechanistic Basis of Foraging 2025 closes October 20th 🚨

Speakers
@mkflugge.bsky.social @aaronbornstein.bsky.social @benhayden.bsky.social @ellileadbeater.bsky.social
@davidrobbe.bsky.social @dlbarack.bsky.social @becketebs.bsky.social

uobevents.eventsair.com/the-mechanis...

Very much looking forward to this exciting lineup!

Also excited about presenting our work on how timescales of environmental dynamics affect foraging decisions (Wednesday), a work together w/ Tiffany Ona, @neuroprinciplist.bsky.social, Bruno Cruz, @xindipoo.bsky.social and Peter Dayan

Our call for ELBE Visiting Faculty at the Center for Systems Biology Dresden is live with deadline 30 November: www.csbdresden.de/join-us/as-a... Please visit us during your sabbatical!
@mpi-cbg.de @math-mpicbg.bsky.social @csbdresden.bsky.social

We are doing it again!!!!

Save the date for the next in-person #AstrocyteCafe next June 3-5 (2026) in Pamplona (Spain)!

We can’t wait to see many of you in person again, thanks so much to the main local organizer @maitesolas.bsky.social ♥️

If you missed this event and you want to catch the replay, videos are up at this link:
www.nationalacademies.org/en/event/451...

See this thread for Day 1 highlights, and the next post for Day 2.

Reminder everyone that #SNUFA is next week! Make sure to register in advance to get emailed the link to join.

Pleased to share that our survey "Getting aligned on representational alignment" — on representational alignment across cognitive (neuro)science and machine learning — is now published in TMLR! openreview.net/forum?id=Hiq...
Kudos to @sucholutsky.bsky.social @lukasmut.bsky.social for leading this!