Oscillations Boost Stimulus Discrimination by Optimizing AP Precision

<div><p>(A1) Scheme showing the template-matching discrimination analysis: Spike trains of repetition A are correlated to trains from repetition B. Correlation coefficients are ranked and the rank of the correct match indicates level of discrimination: Examples shown are perfect (stimulus 1, highest correlation coefficient between 1A and 1B → rank 1) and near-perfect (stim. 3, second-highest correlation coefficient for 3A and 3B → rank 2).</p> <p>(A2) Stimulus discrimination plotted as the mean rank for the ten most separable stimulus sets from a single CA1 cell in vitro under control (no oscillation) and oscillation conditions ( <i>p</i> < 10⁻¹² for all <i>n</i> = 135 stimulus sets in <i>n</i> = 3 cells). </p> <p>(B1) Stimulus discrimination plotted as mean rank as a function of stimulus number in simulation in an InF neuron. Inset: Mean rank scores for low numbers of stimuli. For all panels, filled red circles indicate where the discrimination for the oscillation case is significantly better than the respective control discrimination ( <i>p</i> < 0.05, Mann-Whitney). Dotted lines indicate perfect and chance levels of stimulus discrimination. </p> <p>(B2) Discrimination in an InF neuron is plotted against injected noise levels (Gaussian noise, low pass filtered at 830 Hz, value given is SD of membrane potential) for ten (circles), 100 (triangles), and 1,000 (diamonds) stimuli with (red) and without oscillatory current injection (black open circles, black/gray-filled triangles and diamonds). Solid lines are sigmoidal least square fits. The inset trace (top right) is an example of the in vivo membrane potential (recorded in the presence of TTX) used to estimate realistic noise levels (arrow). This level of noise is used in all simulations unless otherwise stated. Scale bar is 200 ms and 200 μV. Dotted lines indicate optimal and chance levels of stimulus discrimination.</p> <p>(C) Increased discrimination in InF neurons is due to enhanced AP precision. (C1) AP precision was measured for control and oscillation cases. The difference in AP precision was subtracted (jitter was added to the output spikes as described in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040163#s4" target="_blank">Materials and Methods</a>) from the oscillation case so that overall AP precision was identical to control conditions and the simulation was re-run. The sigmoidal fit to both oscillation data (red) and control data (open circles) is plotted. Sigmoidal fits from B2 are provided for comparison. </p> <p>(C2) In this simulation, the oscillatory drive was replaced by brief, large amplitude current injections every 250 ms to evoke precise APs. Discrimination is plotted as a function of membrane noise and is indistinguishable from the oscillation case [F_(1,120) = 1.32, <i>p</i> > 0.25]. Lines indicate best fits of the discrimination data for oscillation and nonoscillation conditions shown in B2. </p>