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Using simultaneous recordings of electrophysiology, respiration, and resting-state fMRI, a respiration-associated neural network is identified.

Topographic maps can gradually increase the fidelity of sensory representations and improve signal-to-noise ratio across multiple cortical circuits, a generic architectural feature that depends solely on the modularity of topographic projections and recurrent inhibition.

A new type of biologically constrained spiking neural network model applied to the dorsal raphe nucleus shows that the output of the serotonin system reflects not just its raw input, but mainly how quickly its input changes over time.

BrainPy presents a general-purpose programming framework that enables efficient implementation, simulation, training, and analysis of brain dynamics models across multiple organization scales, ultimately facilitating the understanding of the complex neural mechanisms underlying brain functions.

Changes in the interpretation of specific scenes in a narrative trigger corresponding updates in the neural patterns evoked by those scenes in the default mode network.