#NeuronalPopulation

Fabrizio MusacchioFabMusacchio
2026-01-07

🧠 New paper by Ishida et al who show how in the central complex implement vector inversion via spikes.

A single can flip the sign of its encoded vector by switching biophysical modes, enabling coordinate transformations through rather than circuit switching.

Cool as it shows that computation is not imposed by the circuit, but emerges from the neuron’s own dynamics.

🌍doi.org/10.1016/j.cell.2025.11

Diagram showing how single neuron activity influences population activity, with vectors, signals, and neural pathways. Graphical abstract of the paper.
Fabrizio Musacchiopixeltracker@sigmoid.social
2025-12-01

🧠 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.

🌍 doi.org/10.1101/2025.11.12.688

#CompNeuro #Neuroscience #NeuralCoding #PopulationDynamics

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.

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