Topic: excitatory pyramidal cells

The remarkable ability of neural networks to make predictions about the immediate future and recognize unexpected events is a ubiquitous hallmark of intelligent life. In recent years, researchers have begun to unravel the neural substrates underlying this predictive information processing [1]. An integral part of predictive processing is a subset of excitatory neurons that encode prediction errors: while negative prediction-error (nPE) neurons are only activated when sensory signals are weaker than predicted, positive prediction-error (pPE) neurons respond only when sensory signals exceed the

The function of the cerebral cortex relies on the precise integration of diverse neuronal populations during development, which is regulated by dynamic fine-tuning mechanisms maintaining the balance between excitation and inhibition. For instance, the development of excitatory pyramidal cells is simultaneously and precisely counterbalanced by the formation of inhibitory synapses during the maturation of neuronal circuits. Although this process relies on neuronal activity, different types of pyramidal cells likely respond to changes in activity through the expression of cell-specific genes. How