In the same session, also make sure to visit poster [3-135] by @weijiazh.bsky.social , who’s presenting joint work with @neurokim.bsky.social and Josh Jacobs showing that Human Single Neurons and Predictive Models Remap Differently in Reward and Transition Relearning
Thank you! 😊🥰
@tomdonoghue.bsky.social @qasimetal.bsky.social @neurojosh.bsky.social
By disentangling methods from biology, we move toward more robust cross-species insights into spatial coding!
This methodological lens point us to biological patterns:
🐀 Rats showed a wide range of spatial responses.
👩 Humans showed weaker but consistent tuning.
Importantly, these consistent responses overlap across species and may serve similar computational roles in flexible memory and generalization.
We compared the most common approaches: Spatial Information (SI) and ANOVA-based tests, across 🐀 rat, 👩 human, and 💻 simulations. We found these methods emphasize distinct properties:
SI highlights the contrast between peak and average firing.
ANOVA emphasizes consistency across trials.
🚀 New Preprint from our team: comparing place cells across species!
Disentangling methods from biology provides a roadmap for cross-species insights into spatial coding 🌍
👉 www.biorxiv.org/content/10.1...
