| Facilitation-depression model | A stimulation instantaneously activates a fraction Use of synaptic resources r, Which then inactivates With a time constant Time and recovers With a time constant rm In the simulations, at time t = tstl-m, r and e respectively decreases and increases by the value User. |
| Kir4.1 channel contribution to neuronal firing and extracellular K+ levels | Recovery time constant |
| Kir4.1 channel contribution to neuronal firing and extracellular K+ levels | Inactivation time constant |
| Numerical implementations and fitting procedures | Approximation of time constants . |
| Numerical implementations and fitting procedures | Time constants T of simulated extracellular K+ transients were fitted to curves using a single exponential (e‘i) (Fig. |
| Numerical implementations and fitting procedures | Time constants T of experimental and simulated astroglial membrane potentials were calculated by computing the rise and decay times between 20% and 80% of the maximal peak amplitude responses (Fig. |
| The long-lasting astrocytic potassium uptake is due in part to the slow Kir4.1 conductance dynamics | In that case, using equation 23, the time constant of Kir4.1 channel-mediated return to equilibrium of astroglial membrane potential TA is defined as |
| The long-lasting astrocytic potassium uptake is due in part to the slow Kir4.1 conductance dynamics | This time constant is consistent with the fitted exponential decay time obtained in our simulations and experiments for a single stimulation where we obtained 1‘ z 0.75. |
| Detection of connectivity in fully-defined input setting | We used a presynaptic population consisting of the equal number of excitatory and inhibitory neurons, with log-normal distribution of synaptic amplitudes (same distribution, positive weights for excitatory, negative weights for inhibitory), and PSC kernels consisted of the same difference of two exponentials with time constants of 0.5ms and 5ms. |
| Experiment 2. Fully-defined input produced by a population of spiking neurons | Thus, the model parameters are N (the number of presynaptic neurons), k and 6 (the shape and scale parameters for the homogeneous Gamma renewal processes), [,4 and o (the shape and log-scale parameters of the log-normal amplitude distribution), and T1 and 72 (the time constants of the artificial PSCs). |
| Supporting Information | R denotes membrane resistance (1 / gL), 1‘ denotes the membrane time constant , DT determines the strength of the exponential nonlinearity near threshold, While a, b, and TW determine the dynamics of the adaptation variable. |