1. Synaptic background activity.
Synaptic background activity. A, In the point conductance model of Destexhe et al., (2001), synaptic background activity is modeled by two noisy conductance trains. One represents excitatory input, and the other represents inhibitory input; both are generated by Ornstein–Uhlenbeck processes. Each train is normally distributed (middle) and is correlated at short times (right; the power spectrum goes like 1/f2 for higher frequencies). B, Without background activity, the model cell has a flat membrane potential (left) that is almost constant (middle); its input resistance is large (right). Adding in vivo–like background activity depolarizes the membrane, introduces membrane potential fluctuations, and reduces the input resistance. The vertical scale of the middle histogram is truncated so that the membrane potential distribution in the active state is easier to see. C, Varying the mean (g, in nanoSiemens) and standard deviation (s, in nanoSiemens) of the excitatory and inhibitory conductances produced the predicted changes in total conductance (top) and membrane potential fluctuations (bottom). The added conductance is expected to equal the sum of gE and gI. The numerical estimates of standard deviation were calculated by simulating the model cell. When sE and sI were varied, gE and gI were held fixed at 4 nS.
Niraj S. Desai et al. eNeuro 2017;4:ENEURO
©2017 by Society for Neuroscience