Thrilled to join UIUC as Prof of
Computational Neuroscience! Lets figure the brain out before we're dead! Recruiting PhDs via CS, ECE & Psych. We study stats methods, mechanistic model inference (w/ connectomics), sensory coding & more. Reach out! [email protected]
These features are more robustly encoded (higher SNR) and more easily characterized than single neuron tuning (higher R2 by classic models, corrected for SNR) —suggesting studying population visual representations may prove more tractable than studying single neuron tuning. (5/6)
Prior work concluded that the eigenvalues of mouse primary visual cortex responses to natural images followed a power-law with a slope of 1 (go.nature.com/3TcQITc). They argued this was a critical balance between representation smoothness and efficiency. (2/6)
We find that the estimator (cvPCA) used to determine this slope was biased and we propose a novel approach (MEME) to inferring eigenvalues that is robust to noise correlation and can even infer eigenvalues beyond the rank of the data. (3/6)
there is a face in the center of the drosophila ellipsoid body diagram in Figure 17b of Hulse et al 2022(iiif.elifesciences.org/lax:66039%2F...).
who is it? is this an easter egg?
If you are interested in eigenvalues consider applying MEME: github.com/dapospisil/r...
Special thanks to @computingnature.bsky.social for practicing open science and feedback!
And if you want to work on high-d estimators (or connectomes, mechanistic model inference) come join me at UIUC! (6/6)
We find that instead mouse visual cortex follows a piecewise power-law with slopes of 0.5 and then 1.2. Thus the visual representation is less complex than previously thought—10 image features can explain 30% of the representation. (4/6)
New paper out at PNAS: www.pnas.org/doi/10.1073/...
Revisiting the high-dimensional geometry of population responses in the visual cortex with @jpillowtime.bsky.social. The review took forever because a reviewer was doubtful our new estimator can infer eigenvalues beyond the rank of the data! (1/6)
I've wanted to write this article for years. About my and other's struggles to even survive sometime in #academia. Thank you to the amazing editors at @plosbiology.org that gave me the forum to write this piece. #science
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
That image is from 1961 and an idealization. Here is an actual trajectory of fixational eye movements. The dots are 2 ms apart. If a midget ganglion cell, with single-cone receptive field, fires at 100 Hz, then every spike reports about a different cone. How can we ever read anything?
Dr Craig R McClain
Markus Meister
From student to researcher, a career in science can come with a high price tag. This Perspective explores how persistent financial barriers limit who can succeed in science, revealing how wealth shape...
