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Are any computer scientists here on Mastodon working in Visual Computing, or Computer Vision? I'm looking for a collaborator to work on the visualisation of medieval handwriting as movement. Would be grateful for re-posts!

One of my papers got declined today by the journal I submitted it to, with a polite letter saying that while they found the paper interesting, it was not a good fit for the journal. In truth, I largely agreed with their conclusions, and the paper is now submitted to a different (and hopefully more appropriate) journal.

Rejection is actually a relatively common occurrence for me, happening once or twice a year on average. I occasionally mention this fact to my students and colleagues, who are sometimes surprised that my rejection rate is far from zero. I have belatedly realized our profession is far more willing to announce successful accomplishments (such as having a paper accepted, or a result proved) than unsuccessful ones (such as a paper rejected, or a proof attempt not working), except when the failures are somehow controversial. Because of this, a perception can be created that all of one's peers are achieving either success or controversy, with one's own personal career ending up becoming the only known source of examples of "mundane" failure. I speculate that this may be a contributor to the "impostor syndrome" that is prevalent in this field (though, again, not widely disseminated, due to the aforementioned reporting bias, and perhaps also due to some stigma regarding the topic). So I decided to report this (rather routine) rejection as a token gesture towards more accurate disclosure. (1/2)

Fascinating experiments done with humans and ants.

"Unsurprisingly, the cognitive abilities of humans gave them an edge in the individual challenge, in which they resorted to calculated, strategic planning, easily outperforming the ants.

In the group challenge, however, the picture was completely different, especially for the larger groups. Not only did groups of ants perform better than individual ants, but in some cases they did better than humans."

phys.org/news/2024-12-ants-sup

#science #ants

Through monitoring a large group of marmosets, researchers have categorised their behaviours to find baselines for typical and atypical responses that can help us study psychiatric disorders.
elifesciences.org/reviewed-pre

@eliocamp Not sure about the implementation of R, but probably these coefficients are the linear combination weights that lead to a variable that maximally correlates with the measurement you want to predict. Aren't those what you are looking for?

@eliocamp another thing to check is canonical correlation analysis

Say you take all 12 eggs out of an egg carton, randomly permute them, and put them back in. How many eggs come back to their original place, on average?

One!

What's the probability that exactly one gets back to its original place? This is a lot harder, because unlike the first question it really depends on the number "12". But the answer is close to 1/e. And if we did it for 100 eggs, or a million, the answer would get even closer to 1/e.

What's the probability that exactly n eggs each get back to their original place? Now things get really interesting. The answer is complicated, but again it simplifies a lot in the limit where we permute a huge number of eggs. Then the answer approaches 1/e divided by n factorial.

What's interesting about that? It's the same as the answer to *this* question: if you're standing in the rain, and on average one raindrop lands on your head every second, what's the probability that in one second exactly n raindrops land on your head? At least this is true if raindrops are falling randomly in the most reasonable way - a so-called 'Poisson distribution'.

So random permutations are connected to Poisson distributions. And the connection goes a lot further than I've explained so far.

I've been trying to understand this better and better. The formulas I'm trying to understand are already known, but I've been proving them using category theory:

golem.ph.utexas.edu/category/2

This gives a deeper outlook: instead of just proving an equation about probabilities, we can show that two categories are equivalent, and this has the equation as an easy spinoff. All the fun facts I just listed, and more, become facts about categories!

I never heard of these whole ass deeply evolutionarily preserved organelles in my cell bio class. Anyone know what these dang things are?
en.m.wikipedia.org/wiki/Vault_

We are pleased to announce the 2025 Paris Spring School in Optical Imaging and Electrophysiological Recording in Neuroscience. AKA the Paris Neuro Course.

The course will run 14-27 May 2025.

parisneuro.ovh/

Please boost (with apologies for duplicates).

I wonder if the tools of digital stylometry can detect what people seem to sense when presented with AI-generated text. I don't mean using deep learning to have built up an internalised semantic picture of what type of text LLMs generate, but just purely examining style with eg the count of function words, the use of starting sentences with linking adverbs ("However,..."), having paragraphs all about the same length made of sentences of fairly homogeneous style and so on. This type of analysis doesn't return an informative yes/no, but all kinds of comparative statistics, which people can then iterate on, or drill into, and make judgements about—that is, the software doesn't tell you if a piece of text is AI-generated, it merely unpacks a description of the text that isn't obvious on surface reading. Maybe all this happens under the hood on tools that use ML to classify text, but I much prefer seeing the actual data, not the opaque "answer".

Data-driven synapse classification reveals a logic of glutamate receptor composition biorxiv.org/content/10.1101/20

Data-driven synapse classification reveals a logic of glutamate receptor composition

The rich diversity of synapses facilitates the capacity of neural circuits to transmit, process and store information. Here, we used multiplex super-resolution proteometric imaging through array tomography to define features of single synapses in the adult mouse neocortex. We find that glutamatergic synapses cluster into subclasses that parallel the distinct biochemical and functional categories of receptor subunits: GluA1/4, GluA2/3 and GluN1/GluN2B. Two of these subclasses align with physiological expectations based on synaptic plasticity: large AMPAR-rich synapses may represent potentiated synapses, whereas small NMDAR-rich synapses suggest "silent" synapses. The NMDA receptor content of large synapses correlates with spine neck diameter, and thus the potential for coupling to the parent dendrite. Conjugate array tomography's rigorous registration of immunofluorescence with electron microscopy provides validation for future super-resolution imaging studies in other systems. No barriers prevent generalization of this approach to other species, laying a foundation for future studies of human disorders and therapeutics. ### Competing Interest Statement K.D.M. and S.J.S. have founder's equity interests in Aratome, LLC (Menlo Park, CA), an enterprise that licenses high-multiplex immunostaining materials, and are also listed as inventors on two United States patents on array tomography methods that have been issued to Stanford University (United States patents 7,767,414 and 9,008,378). All other authors declare no competing interests.

bioRxiv

Looks like I will have some funding to hire a computational tech for ~6 months, starting super duper soon! Can be done remotely. Looking for good computational & programming skills with a strong interest in or knowledge of systems neuroscience/hippocampus. PLS SHARE + RT!

I was interviewed on the podcast The One You Feed with Eric Zimmer. We discuss #morality, #addiction, and the general structure of #DecisionMaking.

check it out!

oneyoufeed.net/changing-how-we

🥳 BIG NEWS for the lab! 🥳 I'm excited to join the Göttingen neuroscience community and the excellence cluster
@MBExC_de as a tenure-track group leader at the European Neuroscience Institute (ENI-G), where we will continue neural circuit research in a great research environment!
mbexc.de/the-mbexc-welcomes-ju

Every time I heard that the vertebrate retina does not receive any feedback from the central brain I expressed scepticism, and was told repeatedly that no, feedback fibers running backwards along the optic nerve were never found.

Now*, Sylvia Schröder et al. reports that:

"Arousal modulates retinal output", Schröder et al. 2020 cell.com/neuron/fulltext/S0896

Recordings with neuropixels probes on the optic tract of the mouse showed changes in retinal ganglion cell (RGC) activity (the output neurons of the retina whose axons make up the optical tract) in concordance with the arousal state of the mouse. They also measured activity of RGC axon boutons in the superior colliculus.

What a fantastic piece of work.

* for long values of "now".

#neuroscience #neuropixels #vision #retina #mouse

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