Dimos Karamanlis @dimokaramanlis@qoto.org

Back in the 90s, when I was in grad school, sensory decisions were analyzed with “signal detection theory”. Since then, many have found it more fruitful to use logistic classification: the observer weighs the factors, uses their sum to bias a coin, and flips the coin.

However, a student starting today would find the relevant information scattered around. To fix this, I wrote “Sensory decisions as logistic classification": https://www.biorxiv.org/content/10.1101/2024.01.17.576029v1. If you have suggestions, please let me know!

Looking for paper suggestions!

I'm teaching a class in Neuroecology for first year PhD students and part of it is a journal club.

I'm looking for additional, pure behavior papers that study "natural" / ecological behaviors, if possible not in mice.
And also for rather short papers that perform any form of brain recordings during natural /ecological behaviors (plus points if not in mice).

Any suggestions?
#Neuroecology #behaviors #neuroscience #teaching

Crazy read: detecting positions of players in Counterstrike by *listening to their GPU over a microphone*

https://faculty.cc.gatech.edu/~genkin/papers/lendear.pdf

I guess we do #introduction posts over here? I work on the #neuroscience (am I doing those hashtags right!?) of learning and memory, specifically how we learn while we navigate space and context. To do this, I take in vivo recordings (currently calcium imaging but ephys has my heart) of freely moving rats! After that, I use computational and mathematical approaches to analyze their neural activity! I am currently a BRAIN Initiative K99/R00 postdoc at Northwestern working with John Disterhoft and Sara Solla. I was trained at MIT with Matt Wilson, where I got my PhD in biology, and my BS is from Carnegie Mellon. Welcome!

@manisha @alicia_izquierdo @dimokaramanlis
@jonny

Loving the discussion in this thread. For dendritic tiling, one candidate would be clustered protocadherins, a group of 60 cell-surface genes in 3 clusters, some with weird split-promoters.

Their expression is randomized, and thought to form a combinatorial code that allows self-avoidance and (potentially) other-recognition.

In Retina:
https://www.jneurosci.org/content/38/11/2713.full

Structural interaction:
https://elifesciences.org/articles/72416

Review:
https://link.springer.com/article/10.1007/s12264-020-00578-4

I wrote about the cerebellum for Current Biology … check it out if you’d like to learn more about “the little brain” [link provides free access through February]
https://authors.elsevier.com/a/1iOZX3QW8S2T6A

Just getting a chance now to look at @strawman 's new system for following and keeping in focus flying insects with a telescope, including from a drone. The videos are amazing. There's surprisingly limited video of insects flying with the spatiotemporal resolution to track and analyze their wing and body movements.
Andrew's post on this work:
https://social.coop/@strawman@sciencemastodon.com/111624685212157804
Paper on bioRxiv: https://www.biorxiv.org/content/10.1101/2023.12.20.572558v1
Check out the videos in the supplement there, sneak peak gif:

Who did it better?

I'm a neuroscientist and group leader of the Flexibility in Circuits and Behaviour lab at SISSA, Italy. My lab studies how innate behaviours can be flexibly adjusted to contextual information, and how this correlates with changes in visual and behavioural encoding. We're a systems neuro lab with a neuroethological angle, and aim to identify general principles of how essential, very fast and stereotyped behaviours/circuits can be flexibly and quickly modulated. 🐁
www.reinhardlab.org

The mastodon community seems to have grown, so I'm giving it another try and hope for many stimulating inputs and discussions! 🧠😊

Conda is moving our social media presence from Twitter/X to Mastodon and LinkedIn at the start of 2024. It's past time to move into spaces that are welcoming and more in line with our community values. Going forward, you can find us at
🐘 @conda (https://fosstodon.org/@conda) on Mastodon
🔗 Conda Community (https://linkedin.com/company/condacommunity) on LinkedIn

Announcement: https://conda.org/blog/2023-12-27-social-move
We hope to see you on Mastodon and LinkedIn in 2024!

#introduction , hi , I'm a junior group leader at the Institute of Cellular and Integrative Neuroscience in Stasbourg. I am interested in multi-regional optical imaging (such as multi-fiber photometry and wide -field imaging). I use these approaches to study adaptation of multi-regional calcium dynamics and release of norepinephrine during learning and sleep.

#Retinas in awake mice respond more quickly and strongly than isolated tissue samples, highlighting the importance of studying them in live animals. #Neuroscience https://elifesciences.org/digests/78005/the-eye-of-the-beholder?utm_source=mastodon&utm_medium=social&utm_campaign=organic

A quick selection of interesting papers from this year:

1) A level-headed intro to neural manifolds and how they tie into our current scientific project
https://nature.com/articles/s41583-023-00693-x by Langdon et al.

2) A review on brain circuits of spatial navigation in fruit flies and other insects.
https://annualreviews.org/doi/abs/10.1146/annurev-neuro-110920-032645 by Wilson.

3) A philosophical treatment of constraint, which is a form of non-causal explanation that's kind of trendy right now.
https://link.springer.com/article/10.1007/s11229-023-04281-5 by Ross.

4) A sharp piece on the computational capacities of neural oscillations, and what they can and can't do for syntactical processing.
https://nature.com/articles/s41583-022-00659-5 by Kazanina & Tavano

(My 2c: https://sandervanbree.com/posts/1497-the-scope-and-limits-of-oscillations-in-language-comprehension)

5) A prudent analysis on how neural oscillations relate to representation, leveraging the always useful causal/constitutive distinction.
https://philpapers.org/rec/MARNOA-7 by Martínez & Artiga.

6) A model of space and concept learning with both algorithmic and neural commitments.
https://science.org/doi/full/10.1126/sciadv.ade6903 by Mok & Love

Neural activity across cortex is high-dimensional and ... complicated. Still, those fine neural features can be predicted from orofacial behaviors in mice! Great work by Atika Syeda et al in the lab!

Try out the all-new keypoint-based #facemap, paper here: https://www.nature.com/articles/s41593-023-01490-6

Our model for prediction mismatch responses in cortex is now on biorxiv.
We predict that the mismatch size influences the latency of the response, which would not be expected for error neurons in previous predictive coding models.
doi.org/10.1101/2023.11.16.567335

For the larger context, see your perspective paper
doi.org/10.1016/j.tins.2022.09.007

Congratulations to Kjartan van Driel to his first paper submitted!
And thanks to Lucas Rudelt and Fabian Mikulasch for designing this project!

@Neurograce @tyrell_turing @DrYohanJohn the comparison to psychology is good actually, and arguably we could learn from their experience. I do sometimes feel like our current approach is a bit like a scientist in the mid 20th century randomly picking 10 people, measuring their height and IQ, noting that they correlate fairly well and concluding that the study of height is a promising avenue for throwing light on intelligence.