These university cash “deals” to restore federal funding are worrisome. They seem more naïve than pragmatic. Please no more.

Preprint posted for Kevin Zhou's awesome development in the Waller Lab of a gigapixel-scale microscope using a low-cost sensor array, along with Muneki Ikeda.
www.focolab.org/post/large-s...

We built StarDist to detect cells in volumetric microscopy and jointly infer closed curved parametric surfaces for each cell. It's an example of an interpretable machine learning approach. More detail in the blog post and preprint.

www.focolab.org/post/surfdis...

Here’s a nice Nature news article on efforts to establish the tardigrade as a new model organism for neuroscience.

www.focolab.org/post/nature-...

An instant classic by Zheng and Meister ‪(@mameister4.bsky.social‬): www.cell.com/neuron/fullt...

"...1⁢0^8... the ratio between peripheral information processing and the overall throughput of the brain. Numerically speaking, this may be the largest unexplained number in brain science. "

so glad websites are back.

Here's a curious result we found from modeling human problem solving as the composition of past remembered dynamical systems. www.focolab.org/post/recombi...

Here's a nice article on our tardigrade work in the Transmitter: www.focolab.org/post/article...

Congrats to the Kavli Institute for Fundamental Neuroscience at UCSF Collaborative Awardees!

🔬 @focolab.bsky.social, Christoph Kirst: AI-driven 3D tracking of object perception in C.elegans

🧠 Robert Stroud, Robert Edwards, James Holton: Mapping SVs w/ cryo-ET #KavliNeuro
kavliifn.ucsf.edu/grants

kleptokakistocracy

Data contamination (validation data leaking into training data) is a critical problem for the whole approach of (static) performance benchmarks to test large AI models. This issue needs to be surfaced more. This article for example, completely neglects it. www.nytimes.com/2025/01/23/t...

Prediction: AI will ultimately drive the renaissance of the fourth estate, the press, as we seek authoritative sources of information and trusted interpretation.

effect size? without any effect size claims, it is impossible to gauge importance of such findings.

It has become impossible to distinguish real newspaper headlines from Onion headlines. We need a name for this era

Our paper on WormID is out. Moral: building a multi-lab data corpus boosts generalization and performance of ML labeling algorithms. We extended the Neurodata Without Borders format to support this. Resource at wormid.org. www.focolab.org/post/our-pap...

and congrats to first author, postdoc Ana Lyons!

For our inaugural post on bsky, we're happy to share our preprint on tardigrades as a new model organism for neuroscience. Exciting times for these little critters! www.focolab.org/post/our-pre...