Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons
Figure 1
(A) The network is composed of two populations (1000 interneurons and 4000 pyramidal neurons). The connectivity is random, a synapse being present between any directed pair of neurons with probability 0.2. The size of the arrows represents schematically the strength of single synapses: recurrent interactions are dominated by inhibition. In addition to recurrent interactions, both populations receive an external excitatory input. (B–D) Three types of inputs are delivered to the network. The three panels display (in black) the time-varying rate of Poissonian spike trains representing external inputs to each neuron in the network in a 1 second long interval. All inputs are a superposition of a ‘signal’ and a ‘noise’ component. The ‘signal’ is shown in green. Average value of input is 1.6 spikes/ms in all traces. The noise is modelled as an Ornstein-Uhlenbeck process (see Methods) in all cases while the three signals are different, (B) Signal: constant rate. (C) Signal: oscillatory rate (here shown with 8 Hz frequency and 0.8 spikes/ms amplitude) (D) Signal: taken from MUA recordings of LGN of anesthetized monkeys watching natural movie scenes (see Methods).