Mick Bonner
@mickbonner.bsky.social
Assistant Professor of Cognitive Science at Johns Hopkins. My lab studies human vision using cognitive neuroscience and machine learning. bonnerlab.org
Pinned
Dimensionality reduction may be the wrong approach to understanding neural representations. Our new paper shows that across human visual cortex, dimensionality is unbounded and scales with dataset size—we show this across nearly four orders of magnitude. journals.plos.org/ploscompbiol...
Reposted by Mick Bonner
Now out in #JNeurosci -- we found changes in medial parietal cortex after manual exploration of everyday real-world objects
doi.org/10.1523/JNEU...
with Beth Rispoli, Vinai Roopchansingh & @cibaker.bsky.social
doi.org/10.1523/JNEU...
with Beth Rispoli, Vinai Roopchansingh & @cibaker.bsky.social
December 11, 2025 at 5:13 PM
Now out in #JNeurosci -- we found changes in medial parietal cortex after manual exploration of everyday real-world objects
doi.org/10.1523/JNEU...
with Beth Rispoli, Vinai Roopchansingh & @cibaker.bsky.social
doi.org/10.1523/JNEU...
with Beth Rispoli, Vinai Roopchansingh & @cibaker.bsky.social
Dimensionality reduction may be the wrong approach to understanding neural representations. Our new paper shows that across human visual cortex, dimensionality is unbounded and scales with dataset size—we show this across nearly four orders of magnitude. journals.plos.org/ploscompbiol...
December 11, 2025 at 3:32 PM
Dimensionality reduction may be the wrong approach to understanding neural representations. Our new paper shows that across human visual cortex, dimensionality is unbounded and scales with dataset size—we show this across nearly four orders of magnitude. journals.plos.org/ploscompbiol...