2026/06/17 by Will Greedy, Heng Wei Zhu, Alexia Duriez +4 · 2 voices
Neuroscience · #Neural dynamics and brain function #Neuroscience and Neuropharmacology Research #Memory and Neural Mechanisms
paper · doi:10.64898/2026.06.16.732595
Abstract Learning is thought to arise from synaptic modifications embedded in brain-wide circuits 1–3 , yet how such circuits coordinate plasticity to support complex behaviour is not known 4,5 . Inspired by deep learning, we propose a theory in which pathway-specific cortical feedback drives dendrite-dependent burst plasticity across cortical hierarchies. We show that this mechanism enables online hierarchical credit assignment and learning of complex image recognition and reward-driven tasks. This theory links credit assignment to cell-type-specific control of dendritic excitation–inhibition balance. In doing so, it provides a unified account of cell-type-specific modulation of synaptic plasticity, learning-dependent changes in interneurons, and neuron-specific dendritic error signals. The theory further predicts that interneurons constrain the dimensionality of error-related feedback, offering a functional rationale for cortex-wide gradients in interneuron density. Taken together, these findings indicate that distinct cortical cell types jointly coordinate learning across hierarchical circuits, connecting synaptic plasticity, circuit-level computation, and behaviour.