The Biophysics Approach Make a model, with parameters Predict the model’s behavior Figure out a way to estimate the parameters from the observed data model behavior estimators

e.g. Coin Flips model behavior estimators check for consistency: Prob(heads) = p Prob(tails) = 1 - p probability # heads check for consistency: tosses 100 heads 55 tails 40 torsos 5

Why do EPCs decay? Transmitter diffuses away Enzymes alter transmitter Transmitter detaches from receptor

Channel Kinetics Model ‘closed’ ‘open’ time g Amplitude Frequency (Hz) Amplitude Frequency (Hz) V

# = 2 # is Poisson distributed # = 1 t # = 1 assume Poisson mean(#) = var(#) mean(g) =  mean(#) var(g) =  2 var(#) can be shown var(g) =  mean(g)

Five Predictions Spectrum is Lorentzian Exponential voltage dependence Estimates of alpha converge Estimates of Q10 converge Estimates of gamma converge