  Neurons in the brain continuously process the barrage of sensory inputs they
receive from the environment. A wide array of experimental work has shown that
the collective activity of neural populations encodes and processes this
constant bombardment of information. How these collective patterns of activity
depend on single neuron properties is often unclear. Single-neuron recordings
have shown that individual neural responses to inputs are nonlinear, which
prevents a straightforward extrapolation from single neuron features to
emergent collective states. In this work, we use a field theoretic formulation
of a stochastic leaky integrate-and-fire model to study the impact of nonlinear
intensity functions on macroscopic network activity. We show that the interplay
between nonlinear spike emission and membrane potential resets can i) give rise
to metastable transitions between active firing rate states, and ii) can
enhance or suppress mean firing rates and membrane potentials in opposite
directions.
