#NeuroNewPaper

Thrilled to share our paper "Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity" now out at #NatureCommunications

https://www.nature.com/articles/s41467-023-37613-7

We have added interesting new analyses to our preprint version (thanks to the reviewers!),
so here goes a new summary:

#NeuroNewPaper
#NeuroPaperThread
# Timescale #Attention #visualcortex #connectivity

New preprint: Didhiti shows that there is crossmodal plasticity in the pre-critical period. Early enucleation in mice leads to changes in the auditory cortex before ear opening.

https://www.biorxiv.org/content/10.1101/2023.02.21.529453v1

#neuroscience #crossmodal #blind #hearing #neuronewpaper #auditory #cortex

What better way to introduce myself on this Neuromatch server than to announce that my first paper is out on bioRxiv!

We used MAPseq to characterize the branching patterns of single macaque amygdala neurons, finding that they often innervate multiple distinct areas in frontal cortex and form dissociable networks. Brief thread to follow:

#NeuroPaperThread #NeuroNewPaper

https://www.biorxiv.org/content/10.1101/2023.01.18.524407v1

RT from Manuel Beiran on the blue bird about his new paper on parametric control of low-dimensional manifolds (a joint work with @nicognitive, Srdjan Ostojic, Mehrdad Jazayeri and Hansem Sohn out in Neuron last week).

Here is the open-access link:
https://t.co/uqgTApyAID

What neural mechanisms support generalization in temporal tasks? How can neural dynamics be controllable by inputs? Thread reproduced here:

#mastoprint #paper #Neuropaperthread #neuronewpaper

Our new work with @TimGollisch and team is now out as a @biorxivpreprint!

We found that gaze shifts in natural movies drive concerted responses in populations of retinal ganglion cells. We think that these concerted responses violate the decorrelation prediction of efficient coding in a cell-type-specific manner in both marmosets and mice.

Check the manuscript for more details!

https://www.biorxiv.org/content/10.1101/2023.01.10.523412v1?rss=1

#NeuroNewPaper
#neuroscience

Null-findings are important, but more difficult to prove and publish. Here is a null-finding #NewPaper / #NeuroNewPaper.

Line-scanning functional #MRI has both high spatial and high temporal resolutions, about 200 micrometers and 200 milliseconds. This is achieved by sacrificing spatial coverage, akin to a virtual BOLD electrode through the brain. Previously, we implemented a human line-scanning sequence using gradient-echo #BOLD #fMRI at 7T.

Spin-echo MRI sequences offer several advantages over gradient-echo MRI sequences, for example much improved spatial line-selection and microvascular specificity. However, despite many efforts, especially from the lead-author Luisa Raimondo, spin-echo line-scanning currently lacks adequate sensitivity for #neuroscience applications.

https://link.springer.com/article/10.1007/s10334-022-01059-7

@summerfieldlab Welcome! Good places to start are these hashtags (which can be followed, just like following people): #neuroscience #NeuroNewPaper #NeuroPaperThread ... and so many more. Tags are the way to discover what's going on without following a thousand people.

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

Shortly, mice were trained to discriminate between concave and convex shapes using only their whiskers. They accumulated touches across time and whiskers to perform the discrimination task

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

7) We realized that instead of a random and disorganized mixed code, the geometry of representations in S1 was best characterized by a low-dimensional scaffold with small perturbations towards higher dimensions. An approximately disentangled representation in orthogonal subspaces

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

5) We built a simulation of the task and changed the general parameters of the shapes. Linear integration was also sufficient for a variety of shapes, distances, angles, and sizes. Non-linear integration of touches was necessary for tasks with complex semantics of groups of shapes

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

6) Populations of S1 neurons were fit with encoding models of varying degrees of flexibility. We found that S1 activity was best explained by models that allowed for non-linear mixed selectivity rather than pure or linear mixed selectivity

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

9) Finally, we fit RNNs to perform an artificial equivalent of the task and found that the geometry of the representations is determined by the difficulty of the task, and RNNs trained on complex tasks can still form representations that can generalize to unseen conditions

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

11) Also, I am on the job market this year, so please do not hesitate to reach out if you think I could be a good fit for a theoretical/computational faculty position in your department!

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

10) Thanks for reading until the end. Many more details in the main article and supplementary figures. Thanks for the support from our many funding agencies and to the
Center for Theoretical Neuroscience, and the Zuckerman Brain at Columbia University. Please reach out if you have any questions or suggestions!

@chrisXrodgers @StefanoFusi #NeuroPaperThread #NeuroNewPaper

8) This organization was not a simple consequence of somatotopy because all whiskers were represented in all columns (see also Rodgers et al 2021). This representational geometry can be useful for balancing generalization and flexible behavior

#NeuroPaperThread
#NeuroNewPaper
@chrisXrodgers @StefanoFusi

4) We monitored whisker movement and contacts and used linear and non-linear classifiers to decode the identity of the shape and the choice of the animal on a trial-by-trial basis. We found that linear integration is sufficient for both shape’s identity and the animals’ choice

@chrisXrodgers @StefanoFusi
#NeuroPaperThread #NeuroNewPaper

2) This deep dive into neural representations follows a previous study led by
@chrisXrodgers
at the Randy Bruno lab, where the task and neural recordings are described in depth, and very interesting results about task dependency are presented https://www.sciencedirect.com/science/article/pii/S089662732100372X

#NeuroPaperThread #NeuroNewPaper

1) Our article “The geometry of cortical representations of touch in rodents” with @chrisXrodgers Randy Bruno and @StefanoFusi is finally out! In brief, we found that whisker contacts in mice S1 are represented in approximately orthogonal subspaces https://www.nature.com/articles/s41593-022-01237-9 ​​

Visual cortex is affected by sounds. Does this mean it is multisensory? Does it represent sounds?

Today in Nature #Neuroscience (https://doi.org/10.1038/s41593-022-01227-x) Célian Bimbard and team find otherwise.

Sound-evoked activity in visual cortex was similar across neurons. Even neurons in hippocampus. It persisted after we cut fibers from auditory cortex!

This activity was predicted by… subtle body movements evoked by the sounds. It reflects brainwide state and behavior signals.

#NeuroNewPaper

@NicoleCRust @kendmiller

I’d be in on #NeuroPaperThread and #NeuroNewPaper. Although I’d prefer #NewNeuroPaper bc grammar .

And I am not sure how much sense it makes to let a single field „claim“ a very general tag such as #PaperThread. It would be more elegant to establish a convention for all fields, i.e., #PaperThread for field-independent use, #MLPaperThread or #AIPaperThread for the Sigmoidians. Sorry folks