Predictive processing postulates the existence of prediction error neurons in cortex. Neurons
with both negative and positive prediction error response properties have been identified in …

To understand the brain we must relate neurons' functional responses to the circuit
architecture that shapes them. Here, we present a large functional connectomics dataset …

A catalogue of neuronal cell types has often been called a 'parts list'of the brain, and
regarded as a prerequisite for understanding brain function,. In the optic lobe of Drosophila …

The brain functions as a prediction machine, utilizing an internal model of the world to
anticipate sensations and the outcomes of our actions. Discrepancies between expected …

Animal movement is controlled by motor neurons (MNs), which project out of the central
nervous system to activate muscles. MN activity is coordinated by complex premotor …

Complex neocortical functions rely on networks of diverse excitatory and inhibitory neurons.
While local connectivity rules between major neuronal subclasses have been established …

Abstract Advances in Electron Microscopy, image segmentation and computational
infrastructure have given rise to large-scale and richly annotated connectomic datasets …

Understanding the relationship between circuit connectivity and function is crucial for
uncovering how the brain implements computation. In the mouse primary visual cortex (V1) …

Understanding the brain's perception algorithm is a highly intricate problem, as the inherent
complexity of sensory inputs and the brain's nonlinear processing make characterizing …

In recent years, large-scale computational models of the cortex have emerged as a powerful
way to study the multi-scale mechanisms of neural processing. However, due to …