What tags are you all following?
Here are mine but I’d like to add some more, particularly science-related:
#FediTips #Hippocampus #PlaceCells #Tetrodes #NatureIsBeautiful (yes… I’m the only one using it for now) #NeuroPaper #NeuroPaperThread #Neuroscience
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
Hot off the press! 🔥
https://doi.org/10.1016/j.neubiorev.2023.105042
We performed a meta-analysis of neuroimaging studies looking at interpersonal neural synchronization (INS) and contextualized the results using diverse public databases to develop new hypotheses on physiological processes potentially involved in INS.
What is he talking about, you ask? See below ⏬
1/9
#NewPaper #PaperThread #NeuroPaper #NeuroPaperThread #NewNeuroPaper #NeuroScience #Neuro #Psych #Psychiatry #Psychology #Cognition #Brain #Communication #Science #Research #DataViz #DataScience
@neuroscience @neuro @cognition @fmri @phdstudents @academicchatter
First #bioRxiv submission since joining here 🎉🎉
Follow the incredible lead author ( @zachzeisler1 ) and his #NeuroPaperThread here:
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:
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:
@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
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
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
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
@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
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
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
#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
3) 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
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 🧵👇
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 👀
@NicoleCRust field-specific hashtags for paper announcements and threads might not work so well for those of us with poor memories and interests across multiple fields, because we would have to remember the specific hashtags for each field.
The Mastodon advanced web interface allows you to follow combinations of hashtags (instructions here: https://blog.djnavarro.net/posts/2022-11-03_what-i-know-about-mastodon/#tracking-hashtags) but it doesn't appear to allow for (#neuroscience AND (#NewPaper OR #PaperThread)), plus I think I found a bug.
For now, I think I will follow (#PaperThread OR #NewPaper OR #NeuroPaperThread OR #NeuroNewPaper OR ...).
Plus, I'm copying in @cogsci #CogSci and #CompCogSci because this is an issue that needs to be discussed in all research communities.
