Jacob Bakermans
@bakermansjjw.bsky.social
88 followers 15 following 10 posts
Postdoc in compneuro with Alex Pouget in Geneva
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Reposted by Jacob Bakermans
vdplasthijs.bsky.social
In our latest perspective article, we outline how ML can overcome 4 current obstacles for large-scale, high-resolution monitoring of protected areas.

doi.org/10.1002/2688...

Hope this stimulates the conversation and provides a pathway of how ML research can be applied for monitoring PAs at scale.
bakermansjjw.bsky.social
Finally we thank the reviewers who encouraged us to test our predictions and you for reading! The double dactyl poem summary didn’t make it past the editor so you’ll find it in the preprint – or here. 9/9
bakermansjjw.bsky.social
We are extremely grateful to Brad Pfeiffer and David Foster for sharing their data to enable these results. And to Éléonore Duvelle, @roddy-grieves.bsky.social and @hugospiers.bsky.social who shared another amazing dataset for us to reanalyse. doi.org/10.25493/7NJ... 8/9
EBRAINS
EBRAINS is building the platform needed to enable a new era in brain research.
doi.org
bakermansjjw.bsky.social
If these memories combine reusable codes, these cells should generalise their response when the cheese moves. We find cells like that too: if the cheese moves, the firing field moves accordingly. 7/9
bakermansjjw.bsky.social
Looks like it is! This cell has a new field in the bottom left after a replay. That’s the exact same location of this cell’s spike within the replayed trajectory. If you calculate the ratemap change, it peaks at the replay spike. 6/9
bakermansjjw.bsky.social
Or even better: hippocampus encodes those memories in replay. That builds a map for getting to cheese in locations without even going there, so they can be retrieved at that location later. These are memories of the future! 4/9
bakermansjjw.bsky.social
Crucially, these maps don’t need to be learned from scratch, but can be constructed from reusable grid (“you’re here”) and object-vector (“cheese-over-there”) codes. Hippocampus combines them in memory for the current environment. 3/9
bakermansjjw.bsky.social
If I’m a mouse that just discovered cheese, I’d like to know how to return to that cheese later. Instead of learning a plan, we propose building a map that comes with a plan for free. That solves planning in representation instead of computation. 2/9