Discussion
Loading...

#Tag

Log in
  • About
  • Code of conduct
  • Privacy
  • Users
  • Instances
  • About Bonfire
Fabrizio Musacchio
Fabrizio Musacchio
@FabMusacchio@mastodon.social  ·  activity timestamp yesterday

Syeda, …, @computingnature et al., bioRxiv (2026) find that #NeuralActivity in #mouse #VisualCortex is dominated by #orofacial movements, not eye movements. Across darkness and visual stimulation, eye movements explain only a small fraction of neural variance and are largely correlated with whisking and sniffing. Movement signals thus strongly shape #V1 activity during free viewing.

📄 https://doi.org/10.64898/2026.02.04.703800

#Neuroscience

Diagram showing face view and eye tracking data, including keypoints, eye movement, and gaze direction analysis.
Diagram showing face view and eye tracking data, including keypoints, eye movement, and gaze direction analysis.
Diagram showing face view and eye tracking data, including keypoints, eye movement, and gaze direction analysis.
  • Copy link
  • Flag this post
  • Block
Fabrizio Musacchio
Fabrizio Musacchio
@pixeltracker@sigmoid.social  ·  activity timestamp 2 months ago

🧠 New preprint by Tilbury et al: Characterizing #NeuronalPopulation geometry with #AI equation discovery

The approach generates & evaluates 100s of candidate equations, finding "peaky" non-Gaussian tuning functions whose Fourier structure matches power-law dimensionality observed in real #V1 pops. Links shape of single- #neuron tuning to #PopulationLevel geometry using both data fits & analytical derivations.

🌍 https://doi.org/10.1101/2025.11.12.688086

#CompNeuro #Neuroscience #NeuralCoding #PopulationDynamics

2 media
Fig. 1. Oriented stimuli produce a high-dimensional population code not captured by standard tuning curve models.
Fig. 1. Oriented stimuli produce a high-dimensional population code not captured by standard tuning curve models.
Fig. 1. Oriented stimuli produce a high-dimensional population code not captured by standard tuning curve models.
Fig. 5. Effect of tuning peakiness on a simulated hyperacuity task.
Fig. 5. Effect of tuning peakiness on a simulated hyperacuity task.
Fig. 5. Effect of tuning peakiness on a simulated hyperacuity task.

Characterizing neuronal population geometry with AI equation discovery

  • Copy link
  • Flag this post
  • Block

bonfire.cafe

A space for Bonfire maintainers and contributors to communicate

bonfire.cafe: About · Code of conduct · Privacy · Users · Instances
Bonfire social · 1.0.2-alpha.22 no JS en
Automatic federation enabled
Log in
  • Explore
  • About
  • Members
  • Code of Conduct