Firing Up Climate Models

Firing Up in Anticipation

When it comes to nightime routines, we all have our ways to best mark the end to a hectic day. Maybe you enjoy a hot bath or you surf the Internet right up until bedtime. Whatever helps you unplug and wind down, indulging in a cup of tea or milk—or simply drinking a glass of water—is often part of the bedtime ritual. A recent study may be able to explain why. Charles Bourque and colleagues at M...

Stochastic firing rate models

We review a recent approach to the mean-field limits in neural networks that takes into account the stochastic nature of input current and the uncertainty in synaptic coupling. This approach was proved to be a rigorous limit of the network equations in a general setting, and we express here the results in a more customary and simpler framework. We propose a heuristic argument to derive these eq...

Short survey Scaling-up crop models for climate variability applications$

Although most dynamic crop models have been developed and tested for the scale of a homogeneous plot, applications related to climate variability are often at broader spatial scales that can incorporate considerable heterogeneity. This study reviews issues and approaches related to applying crop models at scales larger than the plot. Perfect aggregate prediction at larger scales requires perfec...

Fundamentals of Ocean Climate Models Fundamentals of Ocean Climate Models

Firing-rate Models for Neural Populations

I discuss the construction of models that describe the ring rates of excitatory and inhibitory neurons in biological neural networks. A model is presented that incorporates both slow linear and fast nonlinear inhibition. With the appropriate excitatory-to-excitatory couplings this model can act as an associative memory in which pattern recognition is signalled by resonant ring behavior. Stored ...