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Poster Session A: Tuesday, August 12, 1:30 – 4:30 pm, de Brug & E‑Hall

Emergent oscillations in a cortical column model of predictive coding with multiple interneuron types

Kwangjun Lee¹, Cyriel Pennartz, Jorge Mejias¹; ¹University of Amsterdam

Presenter: Kwangjun Lee

We propose a biologically grounded computational model of predictive coding (PC) that integrates a neuroanatomically informed hierarchy of cortical areas with laminar organization and cell-type-specific connectivity. The model performs PC on naturalistic images through Hebbian learning and prediction error minimization. The model assumes that stereotypical pyramidal-PV-SST-VIP circuits with the same structure but different bottom-up and top-down inputs compute positive and negative prediction errors. Sensory inference in the model generates neural oscillations, with simulations of optogenetic inactivation revealing distinct roles for PV, SST, and VIP cells in these dynamics. Furthermore, the model exhibits mismatch negativity-like responses to deviant stimuli. This work offers a biologically plausible framework for understanding the neural circuits underlying PC in the cortex.

Topic Area: Brain Networks & Neural Dynamics

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