The importance of neuronal morphology in brain function has been recognized for over a
century. The broad applicability of" digital reconstructions" of neuron morphology across …

Synaptic plasticity is thought to underlie learning and memory, but the complexity of the
interactions between the ion channels, enzymes and genes that are involved in synaptic …

Computational neuroscience has produced a diversity of software for simulations of
networks of spiking neurons, with both negative and positive consequences. On the one …

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network
simulations using biologically realistic connectivity. This simulation environment enables the …

Biologically detailed single neuron and network models are important for understanding
how ion channels, synapses and anatomical connectivity underlie the complex electrical …

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

At many scales in neuroscience, appropriate mathematical models take the form of complex
dynamical systems. Parameterizing such models to conform to the multitude of available …

Recordings of extracellular electrical, and later also magnetic, brain signals have been the
dominant technique for measuring brain activity for decades. The interpretation of such …

Excitation-inhibition (EI) balance controls excitability, dynamic range, and input gating in
many brain circuits. Subsets of synaptic input can be selected or'gated'by precise …

Scientific models are abstractions that aim to explain natural phenomena. A successful
model shows how a complex phenomenon arises from relatively simple principles while …