Dimos Karamanlis @dimokaramanlis@qoto.org

Come work at @SWC_Neuro with us (@neuroinformatics) and scientific computing to help us manage and share lots and lots of cool neuroscience data.

https://www.sainsburywellcome.org/web/content/current-vacancies

Something big happened this weekend. Everyone is talking about it, wondering what the implications will be.

That's right: I finished writing my new book "What is Entropy?" It's just 120 pages long. It has lots of short sections, mostly one page each, each based on a tweet. This is just a draft, and I'm still fixing lots of typos and other mistakes. So grab a copy - and if you catch errors, please let me know, either here or on my blog!

It is not a pop book: it's an introduction that assumes you know calculus. But it's about a lot of big, bold concepts, and I try to really get to the bottom of them:

• information
• Shannon entropy and Gibbs entropy
• the principle of maximum entropy
• the Boltzmann distribution
• temperature and coolness
• the relation between entropy, expected energy and temperature
• the equipartition theorem
• the partition function
• the relation between entropy, free energy and expected energy
• the entropy of a classical harmonic oscillator
• the entropy of a classical particle in a box
• the entropy of a classical ideal gas

I learned a lot by trying to explain in words what people often say only in equations.

https://johncarlosbaez.wordpress.com/2024/07/20/what-is-entropy/

Could we decide if a simulated spiking neural network uses spike timing or not? Given that we have full access to the state of the network and can simulate perturbations. Ideas for how we could decide? Would everyone agree? #neuroscience #SpikingNeuralNetworks #computationalneuroscience #compneuro

At #Fens2024 tomorrow (Wednesday 26/June) - Check out our poster comparing how representations change in #hippocampus, dorsolateral #striatum, and #prefrontal cortex in rats making decisions as environmental complexity changes.

U. Mugan et al. Poster number 211. In poster session 02: prefrontal decision-making

Some really cool results looking at interactions between decision-making systems!

How are events segmented and organized in time? And how might this impact our perception and memory of time?

Check out our work here on how neural trajectories in the lateral entorhinal cortex inherently drift over time, but abruptly shift at event boundaries to discretize a continuous experience.

https://www.biorxiv.org/content/10.1101/2024.06.17.599402v1

https://x.com/EdvardMoser/status/1802967173196808557

#Events #Time #Memory #Dynamics #Experience #Circuits #EntorhinalCortex #Hippocampus #AnimalBehavior #Preprint

Meet our Neuroinformatics Unit! Driven by an open science ethos, the team of research software engineers work closely with SWC and @GatsbyUCL researchers to build tools that improve data organisation, refine analysis pipelines, and more: https://www.sainsburywellcome.org/web/blog/neuroinformatics-unit-paves-way-open-science-initiatives

@BorisBarbour as I said I don't have any objection to people using hypothesis testing as one small part of the process, I have an objection to making it central to the process. As you say, it's about drawing a conclusion. My assertion would be that 99.9% of the time or more it would be inappropriate to draw a conclusion from any given experiment, but that this doesn't make those experiments bad, failed or not useful. Designing everything around an approach to analysis that is rarely the most appropriate is inefficient and distorting. And secondarily, and less contentiously I guess, applying this framework to modelling work is just flat out wrong.

How do neural circuits generate flexible, cognitive behaviours? The Duan and @jerlich labs are looking for 2️⃣ excellent postdoctoral research fellows to join the team. Check out the vacancies and apply by 25 May: https://www.sainsburywellcome.org/web/content/current-vacancies#research-fellow-senior-research-fellow-two-posts

Spike sorting with #Kilosort in #python w/ #pytorch + @pyqtgraph
!
>>> pip install kilosort[gui]

To learn more, check out the paper (https://www.nature.com/articles/s41592-024-02232-7), the docs (https://kilosort.readthedocs.io/en/latest/ by Jacob Pennington), or watch the talk (https://youtube.com/watch?v=LTSmoACr918 by @marius10p )

I'm trying to make it a habit to post some thoughts about neuroscience papers that I like on my blog.

Here 3 papers from computational neuroscience:

1. The Neuron as a Direct Data-Driven Controller from Dmitri Chklovskii's Lab

2. A Learning Algorithm beyond Backpropagation from Rafal Bogacz' Lab

3. Continuous vs. Discrete Representations in a Recurrent Network from Rainer Friedrich's Lab

https://gcamp6f.com/2024/03/26/three-recent-interesting-papers-on-computational-neuroscience/

In a new paper, published today in Current Biology, we analyse the genome of renowned composer Ludwig van Beethoven using a polygenic index related to musicality, as a way to illustrate the limits of genetic predictions at the individual level. Beethoven, one of the most celebrated musicians in history, scored unremarkably, ranking between the 9th & 11th percentile based on modern samples. We explain why this is no surprise & how it can provide a valuable teaching moment on the complex relationships between DNA & behaviour.
An interdisciplinary collaboration across two Max Planck Institutes (Psycholinguistics in Nijmegen & Empirical Aesthetics in Frankfurt), University of Amsterdam, Karolinska Institute, Vanderbilt University and others.
#MastodonScience #science #music #genetics #genomics
@mpi_nl @maxplanckgesellschaft

https://authors.elsevier.com/sd/article/S0960982224000253

Wondering about the current state of affairs of data science and data management in neuroscience collaborations? Wondering where your tax dollars go? Well, wonder no more! Edgar Walker, Guoqiang Yu and myself collected some data! And opinions :-) https://www.biorxiv.org/content/10.1101/2024.03.20.585936v1

Representing data through music makes it possible to spot patterns that link behavior, neural activity and hemodynamic activity in an awake mouse. Neural activity is represented as piano notes, whereas hemodynamic activity is encoded as violin chords.

By Calli McMurray

https://www.thetransmitter.org/methods/getting-musical-to-spot-patterns-in-whole-brain-imaging-data-qa-with-elizabeth-hillman/?utm_source=mastodon&utm_medium=org-social&utm_campaign=2024221-getting-musical

Suppose an agent (such as an individual, organization, or an AI) needs to choose between two options A and B. One can try to influence this choice by offering incentives ("carrots") or disincentives ("sticks") to try to nudge that agent towards one's preferred choice. For instance, if one prefers that the agent choose A over B, one can offer praise if A is chosen, and criticism if B is chosen. Assuming the agent does not possess contrarian motivations and acts rationally, the probability of the agent selecting your preferred outcome is then monotone in the incentives in the natural fashion: the more one praises the selection of A, or the more one condemns the selection of B, the more likely the agent would select A over B.

However, this monotonicity can break down if there are three or more options: trying to influence an agent to select a desirable (to you) option A by criticizing option B may end up causing the person to select an even less desirable option C instead. For instance, suppose one wants to improve safety conditions for workers in some industry. One natural approach is to criticise any company in the industry that makes the news due to an workplace accident. This is disincentivizing option B ("Allow workplace accidents to make the news") in the hope of encouraging option A ("Implement policies to make the workplace safer"). However, if this criticism is driven solely by media coverage, it can perversely incentivize companies to pursue option C ("Conceal workplace accidents from making the news"), which many would consider an even worse outcome than option B. (1/2)

#Cellpose 3! Not all images are perfect. Restore your images with Cellpose3 to get better segmentations. @marius10p https://www.biorxiv.org/content/10.1101/2024.02.10.579780v1

(click to play gif)

@nsmarkov for example at the annual workshop I run, we the organisers don't choose which abstracts get to be talks and which posters, instead all the participants say which anonymous abstracts they'd like to hear as talks and we pick those that maximise the potential audience. Works well. Small step, but in the right direction.

How did birds evolve wings?

A partial wing is of no use for flying, but natural selection can't plan ahead and allow a species to gradually evolve toward wings that are actually useful for flying.

Evolutionary biologists suspect that wings originally evolved for some purpose other than flight, and then later were coopted for flying.

Researchers have proposed a wide range of possible original purposes for wings, ranging from thermoregulation to knocking down insects to running up hills.

I have never considered the design of #DB 's official #ICE and #IC network map convincing. This was my motivation to create my own 🇩🇪 long-distance rail map a few years ago. It focuses more on systematic connections and their frequencies for better understanding rather than just showing every line.

The 2024 map is finally online 🥳
https://larstransportmaps.com/germany-2024/

Boost appreciated.

Official Map: https://assets.static-bahn.de/dam/jcr:a2ed983a-36e1-4533-a4ee-8b85daf684c2/231127_Liniennetz%20ICE%20IC%202024.pdf