Abstract:
Populations of neurons in the brain can produce distinctive, rhythmic activity 
observable in extracellular recordings.  Activity in the ~30-90 Hz frequency band 
of these recordings has been the subject of much attention and is known as gamma 
rhythm.  It has been found in the visual cortex, for example, where power in the 
gamma band is modulated by the orientation and contrast of visual stimuli.  
Whether it performs a specific function in the brain or is merely a side-effect of 
neural computation is not yet settled.  My aim will be to discuss the mechanism 
that produces gamma rhythm.

As gamma rhythm is thought to be locally produced, I will begin by introducing a 
spiking network model of a generic local population of neurons in the brain, where 
biophysical parameters and network structure are chosen to reflect data where 
possible.  When the network is driven, an emergent spike pattern appears consisting 
of the briefly coordinated spiking activity of small groups of neurons followed by 
relative lulls in activity.  The frequency and size of these events are consistent 
with gamma rhythm.  I will explain the mechanism of these events, their statistics, 
and how synaptic parameters influence their size and inter-event times.

Next I will show how such rhythms appear in a semi-realistic model of the visual 
cortex.  The model covers a small patch of monkey V1 and reproduces many of its known 
phenomena.  Driven now by visual stimuli, a gamma rhythm is again produced in a way 
that is graded with stimulus features like contrast and orientation.  The more 
detailed and realistic model benchmarked against different forms of experimental data 
increases our confidence in the mechanism for gamma rhythm production, and allows us 
to relate dynamics to the network’s visual functions and response statistics.  This 
is joint work with Lai-Sang Young and Robert Shapley.