RE: https://fediscience.org/@eLife/115871742804185192
Cool example of #theory meeting #biology: shows that efficient coding principles survive when models include realistic circuitry, noise, and metabolic constraints. A reminder that good theory does not require oversimplification.
🧠 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.
🧠 New paper by Safaai et al. (2025): parietal #cortex output populations show highly structured, task-dependent population geometry. Using multi-area recordings and circuit modeling, they show that #parietal populations display organized task-related patterns rather than uniform mixed coding, and that distinct output groups shape how decisions are routed to downstream targets:
🌍 https://doi.org/10.1038/s41593-025-02095-x
#Neuroscience #NeuralCoding #ParietalCortex #PopulationDynamics #DecisionMaking
🧠 New preprint by Ruff, Markman, Kim & Cohen (2025): #NeuralPopulation formatting matters for function. In monkeys combining motion and reward, both middle temporal area (#MT) & dorsolateral prefrontal #cortex (#dlPFC) encode both signals. But MT formats them separately, dlPFC integrates them. A recurrent #RNN model predicted, and microstimulation confirmed, distinct #behavioral impacts.
🌍 https://www.biorxiv.org/content/10.1101/2025.01.03.631242v1
Fabrizio Musacchio
Fabrizio Musacchio