Recurrently connected networks of spiking neurons underlie the astounding information
processing capabilities of the brain. Yet in spite of extensive research, how they can learn …

Recurrent networks of spiking neurons (RSNNs) underlie the astounding computing and
learning capabilities of the brain. But computing and learning capabilities of RSNN models …

Understanding the diversity of cell types in the brain has been an enduring challenge and
requires detailed characterization of individual neurons in multiple dimensions. To …

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of
underlying causes. However, determining which model parameters agree with complex and …

Structural rules underlying functional properties of cortical circuits are poorly understood. To
explore these rules systematically, we integrated information from extensive literature …

Neurons and glial cells are endowed with membranes that express a rich repertoire of ion
channels, transporters, and receptors. The constant flux of ions across the neuronal and glial …

There is a high diversity of neuronal types in the mammalian neocortex. To facilitate
construction of system models with multiple cell types, we generate a database of point …

Abstract The Hodgkin–Huxley model of action potential generation and propagation,
published in the Journal of Physiology in 1952, initiated the field of biophysically detailed …

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing
and disparate experimental datasets at multiple scales. The NetPyNE tool (www. netpyne …

Gene expression studies suggest that differential ion channel expression contributes to
differences in rodent versus human neuronal physiology. We tested whether h-channels …