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norbert-fortin.bsky.social

@norbert-fortin.bsky.social
20 followers 30 following 1 posts

Neuroscientist, techie, and foodie.

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Reposted by norbert-fortin.bsky.social
Keiland Cooper @kwcooper.bsky.social · 29/04/2026
Importantly, we must balance such massive scale in data, and the benefits of recording large neural yields with strong hypotheses, models, and rigorous statistical approaches to ensure we aren’t just "data-rich" but gaining knowledge.
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Reposted by norbert-fortin.bsky.social
Keiland Cooper @kwcooper.bsky.social · 29/04/2026
What’s next? We outline a future defined by "big science" collaborations inspired by fields like Astronomy. We’re approaching terabyte-scale data, and will see more multimodal datasets. We envision a "team science" approach as the path forward.
A plot that illustrates the increasing scale of neural recording yield, which has been proposed to double roughly every 7 years.
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Reposted by norbert-fortin.bsky.social
Keiland Cooper @kwcooper.bsky.social · 29/04/2026
Today, we’ve moved from single neurons to the ensemble era. Researchers need to bridge brain-activity and behavior by interpreting activity from thousands of neurons simultaneously by leveraging spike sorting, dimensionality reduction, machine learning, and neural decoding.
An illustration of systems neuroscience recording methods and analysis techniques: tetrode hyperdrives, silicon probes, and optical imaging.
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Reposted by norbert-fortin.bsky.social
Keiland Cooper @kwcooper.bsky.social · 29/04/2026
Early work was often bottlenecked by analysis: E.g., in the 1930s, Fourier transforms were painstakingly calculated by hand until mechanical "automated" devices were invented. This history shows that analytical tools often lag behind recording tech, a gap we’re still facing
A visual schematic of an EEG "analyzing-system", from Grass and Gibbs, which shows a mechanical device to calculate the Fourier transform.
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norbert-fortin.bsky.social @norbert-fortin.bsky.social · 05/05/2026
A massive thank you and congratulations to you, Keiland, for leading this humongous project. We hope this review paper is a fun and useful read to those interested in data analysis of neural activity data.
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