#connectome
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In our new preprint we describe the synaptic #connectome of the nerve net in the ctenophore gravisensory organ. https://www.biorxiv.org/content/10.1101/2025.06.26.661250v1 #biology #neuroscience #ctenophore #vEM
What is citizen neuroscience and why does it matter?
Image credit: Ionut Stefan
I started this article with a clear idea: talk to you about cool neuroscience projects that used “the power of the people” to find out something interesting about the brain. In other words, make citizen neuroscience more well-known, since, as the name suggests, it’s supposed to involve citizens and all that. But those who’ve been here before probably know that I like to start my articles with a good definition of what we’re actually discussing, to make sure we’re all on the same page. And more often than not, the concept turns out to be fuzzier than I expected. This time was no exception.
The definition
“C’mon, what can be so complicated about citizen neuroscience?!” Believe me, I had the same thought. In theory, it’s all quite simple: citizen neuroscience is a subfield of citizen science, and that refers to citizens engaged in the process of generating science. But… engaged how? Do they collect data? Formulate hypotheses? Write up results? Are they doing this independently or do they need to collaborate with someone whose official job is to do science? Are they doing this for free or should they be paid? These are just some of the aspects to consider when it comes to defining citizen (neuro)science.
Depending on the project, it can be any combination of the above, and sometimes more. On the one hand, having such a broad and flexible definition is great because it allows citizen science to be inclusive and adaptable. On the other hand, it can be tricky to get a good grasp of the field. In turn, that makes it difficult not only to learn about it, but also to properly catalogue, evaluate, and fund such initiatives.
Still, the flexibility matters more here. So the solution isn’t to come up with an all-encompassing definition, but to stay aware of the fuzziness surrounding it.
The why and the how
Now that we’re somewhat clear on the “what”, we can move on to the finer details. First, why do we need citizen neuroscience in the first place? Why isn’t academic science enough? For today, I’ll focus on two points: the large amount of data and the lack of broad enough data. Secondly, if citizen neuroscience is important, how can we actually make it happen?
More data than manpower
Understanding the brain requires a lot of data. So much data, in fact, that neuroscientists sometimes generate more data than they have the capacity to analyze. And yes, they do try to use AI, but no matter what you might’ve heard, AI isn’t magical and human input is still very much necessary. That’s why data analysis is one area where citizen contributions can be very helpful, provided a couple of conditions are met.
Take Eyewire and FlyWire as examples. They are both projects focused on creating a map of connections between neurons: Eyewire looks at a piece of the human retina, whereas FlyWire recently finished mapping the entire brain of a fruit fly (Drosophila) down to the synapse level. To understand how that works, imagine you have a bundle of braided wires, which you slice into many paper-thin cross-sections and you photograph these slices. What you get is a huge stack of 2D images that you can use to reconstruct individual wires. However, that requires you to go through those images one by one, tracing the path of each wire as it twists, turns, splits, and merges.
That’s how neuron tracing works too. Here, AI can provide an initial guesstimate of the path, but someone still needs to manually go through it and check if it did a good job. Now, to get a sense of the scale: for the fruit fly brain, for example, there were about 7.000 slices to be checked, and about 140.000 neurons that were eventually mapped. That’s an enormous amount and something that wouldn’t have been possible without the contribution of hundreds of citizen scientists.
Eyewire made that possible by turning neuron tracing into a game where players earn points for accurate tracing and where that accuracy is determined based on community consensus. FlyWire built on that, using the data from Eyewire to train its AI, and employing a similar system for its citizen contributors. Both projects are great examples of how citizen neuroscience can work when done right.
Of course, this begs the question: is citizen neuroscience the one true solution to the massive amounts of data in all of neuroscience? Well, not really. It definitely helps, but not all projects tick the boxes that made Eyewire and FlyWire so successful: a low barrier to entry, an engaging task, and strong infrastructure to support both the science and the people doing it. And when human data is involved, access becomes much trickier (for good reason), making such initiatives a lot more difficult to develop.
But although not all analyses lend themselves to this blueprint, that doesn’t mean citizen involvement in neuroscience ends here.
Not enough brains in the data
Which brings us to the second point on the agenda: neuroscience needs even more data than it has at the moment. I know, it seems counterintuitive: if it can’t handle what it already has, why add more? But you see, neuroscience is a heterogeneous field. On the one hand, there are areas like connectomics (what we discussed above) that produce tons of rich data from small sample sizes (only one retina or only one fruit fly brain, for example). On the other hand, there are the areas that try to draw conclusions about humans as a whole. For that, researchers tend to use whatever is at hand, which historically meant 15-20 WEIRD psych undergrads (WEIRD stands for Western, Educated, Industrialized, Rich, Democratic).
Citizen neuroscience projects in this direction allow researchers to expand beyond their immediate surroundings. One such example is the Music Lab, an online platform where you can take part in fun experiments related to music perception (and potentially get hard proof of how bad you are at recognizing tunes, as a certain blog author did). Another one is Neureka, an app-based initiative which allows people to track their mood and behavior over time and which aims to use that information for detecting mental disorders and developing appropriate interventions.
These are behavioural projects, but with the advent of consumer-grade neurotech, the possibility of collecting brain-related data at home isn’t so far-fetched anymore. People are already using actigraphy for sleep tracking. Portable eye trackers can capture real-world gaze behavior. And more tools are on the way.
While I’m really looking forward to seeing how the field will develop, this article wouldn’t be complete without mentioning some of the challenges that still need to be sorted out. From the researchers’ perspective, quality in both data collection and analysis is crucial. From the participants’ perspective, as we hinted above, the task has to be easily accessible and rewarding. Plus, contributions should be properly acknowledged. With respect to the scientific process as a whole, accountability needs to be clearly defined – who’s responsible for the project, for what goes wrong, for how the data is handled and stored, for how the results are published, etc. Finally, a quick glance at the geographic distribution of such projects will tell you that they’re a reflection of the underlying socioeconomic background of the world: they mostly originate in developed Western countries. That’s hardly surprising, but if we want to reach a universal understanding of brain and behavior, then we need to build a system that includes more of the globe.
What to do
So why should care? Because understanding the brain takes more than lab coats and fMRI scans. It needs broader participation, and that includes people who aren’t part of academia.
And what can you do? If you have free time to spare, get involved in an open project (Google is quite helpful, but if you’re in the EU, it’s worth checking out this website first). If you’re a researcher, think about how you could open up your work to wider participation. And if you’re a funding agency: well, someone’s got to pay for all this.
Also, if you’re involved in a cool citizen neuroscience project or know of any such projects, feel free to drop them in the comments below.
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References
Alemanno, M., Di Pompeo, I., Marcaccio, M., Canini, D., Curcio, G., & Migliore, S. (2025). From Gaze to Game: A Systematic Review of Eye Tracking Applications in Basketball. https://doi.org/10.20944/preprints202503.2114.v1
Jafarzadeh Esfahani, M., Sikder, N., Horst, R. ter, Weber, F. D., Daraie, A. H., Appel, K., Bevelander, K., & Dresler, M. (2023). Citizen neuroscience: wearable technology and open software to study the human brain in its natural habitat. https://doi.org/10.31234/osf.io/4mfcd
Vohland, K., Land-Zandstra, A., Ceccaroni, L., Lemmens, R., Perelló, J., Ponti, M., Samson, R., & Wagenknecht, K. (Eds.) (2021). The Science of Citizen Science. Springer. https://doi.org/10.1007/978-3-030-58278-4
@persagen@mastodon.socialThis isn't a galaxy: it's a map of a mouse brain
https://www.cbc.ca/news/science/mouse-brain-map-1.7506699
Scientists mapped a mouse's brain to record how its cells lit up as it watched parts of a movie
#CellBiology #neurobiology #imaging #connectome #neuroscience #MolecularBiology
Scientists created a map of a mouse's brain while it…
CBCSciTech Chronicles. . . . . . . . .Mar 31st, 2025
#nanostructured #Copper-Tantalum-Lithium #stability #strength #Connectome #cortical #thickness #volume #conductor #Faraday #electrostatic #tube #stromatolites #amino-acids #abiogenesis #carbon-nitrogen #AMSAT-OSCAR #AO-7 #NiCd #AE4JC
In the beginning God created data. Then She created…
scitechchron.blogspot.comThe revised version of our #Platynereis #connectome paper is now out:
https://elifesciences.org/reviewed-preprints/97964
Cell-type-level annotation of the whole organisms, including synaptic and desmosomal connectomes. Can be explored with CATMAID here:
https://catmaid-jekelylab.cos.uni-heidelberg.de
#larva #marine #neuroscience #vEM
Getting between universes can be easier than getting to the next star
Latest post in a #Neuro #Science #Fiction #WorldBuilding project
The #Brane #Connectome Project: Vertex
https://neurontosomething.wordpress.com/2025/02/14/brane-connectome-project-vertex/
Strange and exotic matters from alt-physics universes
NeurOnToSomethingHere are my slides from today's talk at the ZooCELL vEM Practical Course.
"Large-volume EM and connectomics - An (incomplete) history of neuronal connectomics"
https://jekelylab.github.io/ZooCell_Connectomics_Intro_Feb2025.html#/title-slide
Enjoy!
#neuroscience #connectome #biology
Here's a #MicroscopyMonday segmentation of some neurons from the optic lobe, or visual processing area of the #Drosophila fruit fly's brain. The #connectome for the full optic lobe was released in 2024 by #HHMIJanelia, Google, and the University of Cambridge, with support from the Wellcome Trust.
On this day 5 years ago #HHMIJanelia and Google released the "hemibrain", a map of neural connections in much of the #Drosophila fly brain. At the time it was the largest such #connectome ever created. Here's a video from the release (polished a bit), showing the interesting shapes of the neurons.
@katchwreck For sure we won't understand how the brain works until the role of astrocytes and other glial cells is fully understood.
The #connectome though is understood as the wiring diagram where neurons are nodes and edges are synaptic connections. For additional interactions there's the "#neuromodulome" for e.g., neuropeptide/neuromodulator vs. the corresponding receptor, like in this paper by Lidia Ripoll-Sánchez et al. 2023 on C. elegans:
"The neuropeptidergic connectome of C. elegans" https://www.cell.com/neuron/fulltext/S0896-6273(23)00756-0
#neuroscience #Celegans #connectomics
i've seen a few papers in the last 10 years demonstrating direct #astrocyte involvement in a variety of brain functions normally associated with #neurons... does this mean that the definition of the #connectome should be somehow augmented with astrocyte topologies, relative to the neuronal ones?
The #Drosophila optic lobe has neural circuits that help the fly respond to its environment. Here's one for detecting motion, identified by Shin-ya Takemura, from an optic lobe #connectome released in April 2024. I made the video with neuVid driving #Blender. Watch for synapses pulsing at the end.
@seeingwithsound@mas.toWith blind adults, the brain's #connectome will be mostly fixed, but this need not apply to the brain-wide (functional) #projectome: sensory substitution for the blind aims to tap into functional rewiring through changes in e.g. dendritic spines, thereby modifying the projectome.
I was reading something the other day about new neurological research suggesting that while the #connectome is the physical foundation of the manifested mind, there may be another level manifested in the electrical fields generated by the synapses firing across the brain. And that’s where the mind lives, in the swirling fields. #AI doesn’t have (yet) an equivalent physical foundation like ours, but when they do, we’re cooked.
PUTTING THE MOUSE BRAIN ON THE MAP A pioneering ‘connectomics’ collaboration is the latest effort to unravel the brain’s myriad functions, bringing neuroscientists into challenging new territory. By Michael Eisenstein
https://media.nature.com/original/magazine-assets/d41586-024-01096-3/d41586-024-01096-3.pdf
This is an amazing story of a complex collaboration to completely map a tiny volume--a cubic mm s "densely packed with tens of thousands of neurons and other cells in a staggeringly complex architectural weave."
@persagen@mastodon.socialHuman molecular map contributes to understanding of disease mechanisms
https://www.sciencedaily.com/releases/2024/09/240911175947.htm
Roadmap to molecular human linking multiomics w. population traits, diabetes subtype
https://www.nature.com/articles/s41467-024-51134-x
6,304 quantitative molec. traits
1,221,345 genetic variants
methylation @ 470,837 DNA CpG sites
gene expression: 57,000 transcripts
#metabolome #connectome #interactome #genotype #phenotype #IndividualVariation #transcriptome #multiomics #omics #disease #MolecularEpidemiology #GeneExpression
Scientists have created an intricate molecular map…
www.sciencedaily.comLong time in the making: @hhmijanelia Group Leader @srinituraga@threads.net, Janne Lappalainen, Jakob Macke from @unituebingen and colleagues reproduce the network dynamics in the part of the fly visual system responsible for motion detection using end-to-end training on plausible high level tasks. Their model uses reasonable neural dynamics and the FlyEM #connectome as a start and figures out the rest, leading to natural network dynamics. Cool!
Finding suitable embeddings for connectomes (spatially embedded complex networks that map neural connections in the brain) is crucial for analyzing and understanding cognitive processes. Recent studies have found two-dimensional hyperbolic embeddings superior to Euclidean embeddings in modeling connectomes across species, especially human connectomes. However, those studies had limitations: geometries other than Euclidean, hyperbolic, or spherical were not considered. Following William Thurston's suggestion that the networks of neurons in the brain could be successfully represented in Solv geometry, we study the goodness-of-fit of the embeddings for 21 connectome networks (8 species). To this end, we suggest an embedding algorithm based on Simulating Annealing that allows us to embed connectomes to Euclidean, Spherical, Hyperbolic, Solv, Nil, and product geometries. Our algorithm tends to find better embeddings than the state-of-the-art, even in the hyperbolic case. Our findings suggest that while three-dimensional hyperbolic embeddings yield the best results in many cases, Solv embeddings perform reasonably well.
Full video: https://www.youtube.com/watch?v=GQKaKF_yOL4 arXiv: http://arxiv.org/abs/2407.16077
#NonEuclideanGeometry #connectome #RogueViz
#Mathematical modeling of #neurological disease: what if we try to apply concepts and methods of #theoretical #physics to #medicine? Maybe this could lead to new #non-invasive research methods. Enjoy!
#complexnetworks #connectome
The brain is a complex network, and diseases can alter…
pubs.aip.org