Stefano Fusi

Center for Theoretical Neuroscience, Columbia University

[Lorenzo Posani @LorenzoPosani]

For a neural circuit to be "specialized", does it need specialized neurons? In our new work - now out in @NatureNeuro - we address this question in the BLA, using representational geometry to propose a new population-centric way of defining circuit specialization. 🧵�� 1/

[Stefano Fusi @StefanoFusi2]

Specialized readouts are also possible when most neurons are not specialized. Another great work with D. Salzman's lab: led by Pia O'Neill and @LorenzoPosani, who did a wonderful job

[Lorenzo Posani @LorenzoPosani]

Fin/ check out the publication at https://t.co/ja9zFmcSa3. Huge thanks to Pia O'Neill (new assistant prof at Dartmouth https://t.co/5kw5MHJ4Al) for leading this project, and to @StefanoFusi2 and D Salzman for the fantastic collaboration! Cover artwork https://t.co/GoncjBpBNJ

[Columbia University's Zuckerman Institute @ZuckermanBrain]

Scientists have long debated whether neurons are jacks of all trades or tend to specialize in one thing. Now @StefanoFusi2 @LorenzoPosani & Liam Paninski present new evidence in @Nature favoring generalist neurons and shedding light on how the brain performs complex tasks.

https://t.co/UjqFTVTyJH

[Stefano Fusi @StefanoFusi2]

From a great collaboration with @LorenzoPosani , Shuqi Wang, Samuel Muscinelli, Liam Paninski, now in Nature: https://t.co/MifaNPSZbA

[Stefano Fusi @StefanoFusi2]

The geometry of biased decisions! A great collaboration with @RNogueiraNeuro, Saleh Esteki and @roozbeh_kiani

[Ramon Nogueira @RNogueiraNeuro]

We are very excited to announce that our new preprint with Saleh Esteki, @StefanoFusi2, and @roozbeh_kiani is now available on biorxiv: https://t.co/oV5RjZF9O7. We investigated how reward context is learned, represented, and updated to bias decisions. Thread 🧵👇! 1/13

[Stefano Fusi @StefanoFusi2]

@wjeffjohnston is starting a new lab at UCSF! He is looking for postdocs: https://t.co/u6xtLY8WUb Strongly recommended!

[Earl K. Miller @MillerLabMIT]

Thanks! And check out our new review on mixed selectivity, please and thanks.
https://t.co/WR2X5xNx3V
https://t.co/eLYVwy99In

[The Italian Academy @ItalianAcademy]

Oct 30, 4:30
"How does the Geometry of Brain Activity Shape Behavior?"
@VFascianelli ; moderator Stefano Fusi, Zuckerman Institute, Columbia. Open seminars series; register here: https://t.co/fbz7N0jH3h
@StefanoFusi2, @ZuckermanBrain, @Columbia

[Ramon Nogueira @RNogueiraNeuro]

Two days left to apply!

[Valeria Fascianelli @VFascianelli]

Excited to speak at the Davide Giri Talks at the Consulate General of Italy in New York!
We’ll be discussing complex systems: from atoms, to people, to machines. @s_y_chung @AIRIcercaNY

[Ramon Nogueira @RNogueiraNeuro]

The Grossman Center at UChicago is hiring Center Postdocs! Great scientific environment in a great city. Competitive salaries and freedom to work with any of the center PIs. The deadline is May 1st. DM me if you have any questions. https://t.co/gSCFUJ4pf3

[Stefano Fusi @StefanoFusi2]

We always see that: 1) neural responses are very diverse 2) the shattering dimensionality is as high as it can be. Now also in an extensive analysis of the IBL dataset. Wonderful collaboration with @LorenzoPosani , Shuqi Wang, Samuel Muscinelli, Liam Paninski. Many new analyses

[Lorenzo Posani @LorenzoPosani]

Long-overdue thread on our latest work using the IBL data to reveal the shared organizational principles of the neural code in the cortex.
A systematic analysis of categoricality 🧱 and dimensionality 📐 of the neural code across 40+ regions.
https://t.co/42Z2KwUkYS
👇 1/n

[Stefano Fusi @StefanoFusi2]

The geometry of adaptation! My first excursion in the V1 territory. Great collaboration with @MarioDipoppa
@MatteoCarandini and many others

[Mario Dipoppa @MarioDipoppa]

New results! Visual adaptation changes the geometry of V1 population activity: frequent stimuli elicit smaller responses but become more discriminable, consistent with our efficient coding model. You can find me on the "new neurotwitter" at mariodipoppa. https://t.co/Mf58zzYrgq

[Stefano Fusi @StefanoFusi2]

A beautiful work with a wonderful team! A lot of new ideas and a huge number of elegant experiments

[Frances Xia @_fxia]

Excited to share our new paper out now @Nature, where we identified neural signatures of stress susceptibility and resilience in the amygdala-ventral hippocampal network to enable control of anhedonia! <https://t.co/8sd31UV0Ng>

Thread below:

[Stefano Fusi @StefanoFusi2]

Modularity can emerge also in the absence of anatomical and metabolic constraints. What are the computational reasons? A new great theoretical study with @wjeffjohnston

[Jeff Johnston @wjeffjohnston]

When does modular structure emerge in neural networks?
What are the consequences of this structure for learning and behavior?

New work with @StefanoFusi2 answers these questions and more: https://t.co/IyEZoSR7Gb

see 🧵below (1/11)

[Stefano Fusi @StefanoFusi2]

And finally, here are some ideas from our group about the formation of abstract representations:
https://t.co/81ov8Wh3KR
https://t.co/Ik4xon70Qo

[Stefano Fusi @StefanoFusi2]

Abstract disentangled representations are observed in multiple brain areas of rodents, human and non-human primates:
https://t.co/PihomooOeJ
https://t.co/S5djyFyelQ
https://t.co/guzcsMzl5T
https://t.co/OHgOwOO3ZI

[Stefano Fusi @StefanoFusi2]

These geometries are also similar to those that correspond to the axis code of @doristsao https://t.co/dICApoVuri(see also: https://t.co/7VxLbQkyq1). Indeed, these are disentangled representations: https://t.co/nQymPTY19f

[Stefano Fusi @StefanoFusi2]

For a similar experiment on non-human primates and more about the conceptual framework of abstract representations, see https://t.co/S5djyFyelQ

[Stefano Fusi @StefanoFusi2]

Observing the birth of an abstract representation with disentangled variables in human HPC!!
Now published in Nature. Great collaboration with @courellis @JMinxha @amamelak @UeliRutishauser and others

[Ueli Rutishauser @UeliRutishauser]

Delighted our latest finding! We discovered that abstract representations emerge in the human hippocampus when learning to perform inference. This change in neural geometry is due to disentanglement of discovered latent and observable variables. @Nature https://t.co/Kr7ClRd95I

[Stefano Fusi @StefanoFusi2]

And this is the unstructured geometry when the subjects cannot do inference

[Stefano Fusi @StefanoFusi2]

And this is the real data when the subjects can perform inference (neural recordings from single units in the human hippocampus). Notice the parallelism of the red lines