Seeing the Mind: Spectacular Images from Neuroscience, and What They Reveal about Our Neuronal Selves by Stanislas Dehaene, 2023
A lavishly illustrated and accessibly explained deep dive into the major new findings from cognitive neuroscience.
Who are we? To this age-old question, contemporary neuroscience gives a simple answer: we are exquisite neuronal machines.
"Schreckstoff: It takes two to panic", a dispatch by @MarcusStensmyr 2024
"Schreckstoff (fear substance) is an alarm signal released by injured fish that induces a fear response. Its chemical nature has long been debated. A new study finds that zebrafish Schreckstoff is composed of at least three components, two of which elicit the fear response only in combination."
Happy birthday to #neurologist Santiago Ramón y Cajal (1852 - 1934), here in front of Purkinje and granule cells from a pigeon, based on one of his own drawings! Cajal &Golgi won the Nobel in 1906, "in recognition of their work on the structure of the nervous system". He was as much of an artist as he was a scientist & his 100s of drawings are still used for teaching purposes.
🧵1/n
#sciart#linocut#printmaking#histstm#PurkinjeCell#neuroscience#MastoArt
Spanish neuroscientist Santiago Ramón y Cajal was born #OTD in 1852.
His most significant contribution to science was his work on the structure of the nervous system. Through meticulous microscopic observations, he proposed that the nervous system is made up of "neurons". His drawings highlighted the complex arborizations of these cells, effectively mapping various parts of the brain & spinal cord, demonstrating the directional flow of nerve impulses in neurons.
If you’ve ever been out in the woods and sworn you’ve heard someone call your name, you might not be going crazy — just experiencing a condition called “auditory pareidolia.” Live Science explains more about this phenomenon of hearing intelligible voices or sounds in meaningless background noise. https://flip.it/KbQ8o- #Science#Hearing#Health#Mind#NeuroScience
Great write-up by @annaleen on the modern history of the pseudoscience of "brainwashing" and how it has been (/tried to be) used for mostly nefarious ends.
We can say this "psychopolitics" is part and parcel of what the great political scientist Richard Hofstadter termed the "paranoid style in American politics".
Awesome to see a mention of Liang Qichao and how his term "xinao" (wash-brain) which meant modernization was usurped and became a negative connotation. He was one of the great early reformers who wanted to modernize Chinese philosophy by seeking a radical break from Confucianism. Pankaj Mishra's "From the ruins of empire" does a great job of his intellectual response to western imperialism in remaking Asia.
First time also hearing/reading about "stochastic terrorism".
How the insect centre for learning and memory, the mushroom body, evolves. By Farnworth et al. 2024, using the example of "the Heliconiini (Nymphalidae), which show extensive variation in mushroom body size over comparatively short phylogenetic timescales, linked to specific changes in foraging ecology, life history and cognition."
Some key findings:
number of GABA cells change, concomitant with increase in Kenyon Cell number;
The honeybee brain hosts over 600,000 neurons, at a density higher than that of mammalian brains:
"Our estimate of total brain cell number for the European honeybee (Apis mellifera;
≈ 6.13 × 10^5, s = 1.28 × 10^5; ...) was lower than the existing estimate from brain sections ≈ 8.5 × 10^5"
"the highest neuron densities have been found in the smallest respective species examined (smoky shrews in mammals; 2.08 × 10^5 neurons mg^−1 [14] and goldcrests in birds; 4.9 × 10^5 neurons mg^−1 [16]). The Hymenoptera in our sample have on average higher cell densities than vertebrates (5.94 × 10^5 cells mg^−1; n = 30 species)."
Ants, on the other hand ...
"ants stand out from bees and wasps as having particularly small brains by measures of mass and cell number."
I'm happy to present the last paper from my thesis!
Lisa Li and I set out to build a model of fly walking which is based on 3D kinematics data, handles perturbations, and includes sensorimotor delays. (This was supervised by Bing Brunton and @tuthill )
We set up a new modeling framework, generated fly walking with kinematics matched to real data, a simple metric for quantifying similarity of trajectories, and found constraints on delays for robust walking!
The screenshot below features Patrick Lichtsteiner and his work on mimicking retinal circuits in the design of the dynamic vision sensor (DVS), an event-based camera where the log difference of light intensity at time t and t-1 is emitted (the event), rather than a typical camera frame. This has extraordinary implications for visual processing, data transfer bandwidth and data storage.
Having determined that the DVS pixel noise is limited to 2x the shot noise, Tobi's group built a "Scientific DVS" targetting e.g., very fast imaging of neural activity with low noise. They've done it by tweaking the DVS pixel circuit and also binning 4 pixels together for spatial integration.
The result: 10x more sensitive.
Looking forward to seeing applications in neuronal activity imaging, which seems ideally suited for event-based imaging: large fields of view where largely nothing changes, with few, very sparse but fast changing pixels – where neurons are active.
“Feeding-state dependent modulation of reciprocally interconnected inhibitory neurons biases sensorimotor decisions in Drosophila”, by Eloise de Tredern et al. 2024 (Tihana Jovanic’s lab) https://doi.org/10.1101/2023.12.26.573306
“the competition between different aversive responses to mechanical cues is biased by feeding state changes. We found that this is achieved by differential modulation of two different types of reciprocally connected inhibitory neurons promoting opposing actions” … and via homologues of the vertebrates’ neuropeptide Y.
[1/2] Surprising findings in brain research 🧠: As a team from #CharitéBerlin shows in #Science, thoughts in the human neocortex flow in one direction ⬆️, as opposed to the loops seen in mice 🔄. That makes processing information extra efficient. These discoveries could further the development of artificial neural networks.
the last thing i would do is blame neuroscientists for the disfunctional US federal budgeting process that funds basic research at pennies on the dollar compared to war and subsidizing the rich. at the same time I also think we would probably have an easier time communicating to the public at large and building a political case for funding neuroscience if we focused less on publishing discrete papers and more on making our work into larger, cumulative projects that we could point to as a direct consequence of our funding. We should be able to say "here are all the things the BRAIN initiative funds and how they relate to one another" instead of having NIH Reporter and a handful of summary PDFs as the best resource at hand.
the Brain Initiative Cell Atlas Network, which is pioneering single-cell atlases for the human brain and the mouse brain, and the FlyWire Connectome project, which mapped every neuron in the fruit fly brain and spinal cord.
BICAN, which has a ton of work that you can point to, is great, eg the "knowledge explorer" but even then it suffers from public intelligibility even though i know there's a lot more there - eg. the "tools" link from the homepage - https://www.portal.brain-bican.org/ - goes to some unintelligible RRID page. FlyWire is great ( https://codex.flywire.ai/ ) but the dependence on google infra and identity is just a pointless footgun.
point being, scientific infrastructure isn't just a matter of 'nice to have,' but is probably increasingly important to the survival of the discipline. If we can't point to what we've done as a coherent picture, it's very easy to cut funding and have it fly under the radar.