There are two pyramidal cell groups (A and B), each of which is selective to one of the two stimuli (mimicking motion to the right or left). Within each pyramidal neural group there is strong recurrent excitatory connections that can sustain persistent activity triggered by a transient preferred stimulus. The two pyramidal groups compete through feedback inhibition from interneurons.
Figure 2: Model input
Top: the inputs are Poisson rates that vary in time and obey Gaussian distributions, with means muA and muB and with standard deviation sigma. The means muA and muB depend on the coherence level linearly (insert). Bottom: an example of stochastic inputs to neural groups A and B with mu0 = 40 and sigma=10 in Hz, coherence=6.4%. At every 50 ms, the two stimuli are independently resampled using their Gaussian distributions, so that the inputs vary stochastically in time. If sigma = 0, the two inputs would be constant in time.
Submodules (click to view and edit)
Pyramidal population - Pyramidal neuron population containing subpopulations of task-selective cells.
The model consists of two populations of pyramidal cells representing the available response options. Each population receives task-related inputs signaling the perceived evidence for each response option. The difference between the inputs varies inversely with the difficulty of the task. In difficult trials each input fires at approximately the same rate, while in easy trials one input fires at a high rate while the other fires at a very low rate. The pyramidal populations are reciprocally connected and mutually inhibit each other via a common pool of inhibitory interneurons. This pattern of connectivity gives rise to winner-take-all behavior in which the firing rate of one pyramidal population (typically the one receiving the strongest inputs) increases and that of the other is suppressed, indicating the decision.
Summaries of Experimental Data (SEDs) and Simulation Results (SSRs) (Show)