Turning the PING Loop On

Abstract

We asked what the recurrent PING loop does before introducing training, classification or a learned readout. We compared the same Poisson-driven excitatory–inhibitory architecture with reciprocal feedback disabled and enabled.

Enabling the loop produced rhythmic population activity and strongly suppressed excitatory firing across the matched-drive sweep. This establishes the circuit’s basic operating behaviour, but the limited simulations do not show that gamma timing itself caused the suppression.

Results

Architecture, spectra and rates

Loop-off and loop-on schematics above population rasters, spectra and firing-rate curves.
Figure 1: (A–B) COBA and PING schematics; (C–D) E/I rasters; (E, G) E-population spectra; (F, H) firing-rate–input curves. COBA occupies A, C, E and F; PING occupies B, D, G and H. E spikes are black and I spikes red. Rasters and spectra show 400 ms at 5 and 45 Hz input, respectively. Rate curves show one-trial population means over the matched-drive sweep, without error bars; vertical scales differ. The dashed marker is the analysis-selected spectral peak, not a rhythmicity significance test. Schematics describe the model, not a measurement.

COBA excitatory membrane voltage

Figure 2: Membrane voltage of the highest-spike-count E neuron with the loop off, driven at 5 Hz for 400 ms. The dashed line marks the −50 mV threshold; spikes reset voltage to −65 mV. This is an illustrative neuron, not a population mean.

COBA excitatory-neuron conductances

Figure 3: Excitatory conductance (black) and fixed leak (dotted) for the same COBA neuron. Input spikes increase excitation, which decays between events; the disconnected inhibitory feedback contributes no conductance.

COBA excitatory-neuron currents

Figure 4: Signed excitatory and leak currents for the same COBA neuron. Positive current is depolarising; current was reconstructed from voltage and conductance using the driving-force relation in Methods.

PING excitatory membrane voltage

Figure 5: Membrane voltage of the highest-spike-count PING E neuron at 45 Hz input for 400 ms. This is a different input rate from COBA, not a matched-input trace comparison.

PING excitatory-neuron conductances

Figure 6: Excitatory (black), inhibitory (red when nonzero) and leak (dotted) conductances on the same PING E neuron. All conductances are non-negative; inhibition enters through its reversal potential, not a negative conductance.

PING excitatory-neuron currents

Figure 7: Signed currents on the same PING E neuron. Inhibitory current is hyperpolarising when voltage exceeds the −80 mV inhibitory reversal potential, even though inhibitory conductance is positive.

PING inhibitory membrane voltage

These cellular traces illustrate reciprocal E→I→E feedback; they do not measure population-wide phase locking or spikes per cycle.

Figure 8: Membrane voltage of the highest-spike-count PING I neuron, from the same trial as the PING E traces. The dashed line marks threshold.

PING inhibitory-neuron conductances

Figure 9: Excitatory conductance arriving from the E population (black) and fixed leak (dotted) on the selected I neuron. The model has no I→I synapse.

PING inhibitory-neuron currents

Figure 10: Signed excitatory and leak currents on the same I neuron. Positive current is depolarising.

Methods

We compared untrained loop-off and loop-on networks using the following simulation and measurement procedure.

  1. Construct the two loop conditions. Both networks contained 1024 excitatory (E) and 256 inhibitory (I) neurons. An input layer drove E neurons through feedforward weights; reciprocal E→I and I→E weights formed the PING loop, without E→E or I→I recurrence. Loop coupling was 0 or 1.5 the I→E parent mean was 2 times E→I, and both parent standard deviations were 10% of their means. Input parent weights had mean 1.5 and standard deviation 0.3 lower-clamped Gaussian draws were normalised by fan-in, with 95% initially zero and survivors rescaled.

  2. Generate the drive and simulate. Uniform Poisson input drove every channel at the condition’s rate, with seed 42 for input and network initialization. Membranes began at −65 mV and conductances at 0 µS. Exponential-Euler membrane integration used 0.1 ms steps; AMPA and GABA decay constants were 2 and 6 ms, with E/I refractory periods 1.2/0.6 ms. These describe the executed reset holds; the earlier 3/1.5-ms declaration was corrected without rerunning the simulations or changing their measured activity. Full trial recordings included spikes, voltages and conductances.

  1. Measure the drive response. Both loop conditions used 1 trial at each of 2, 5, 10, 20, 40, 70, 100 Hz through 784 input channels for 400 ms, without a discarded transient. Mean per-neuron firing rate was

    𝑟𝑃=𝑛spike,𝑃𝑁𝑃𝑇present,
    (1)

    where 𝑃 identifies E or I, 𝑛spike,𝑃 is the population’s total spike count, 𝑁𝑃 its neuron count, 𝑇present the full presentation duration in seconds and 𝑟𝑃 the rate in hertz. No averaging across independent seeds was performed.

  2. Estimate the population spectrum. The mean E spike trace was demeaned and passed to Welch’s density estimator with one full-trial window.[1] This is a single-window estimate, not an average over independent segments. The largest peak between 5 and 150 Hz was refined by three-bin parabolic interpolation, clamped to half a bin; it was reported only when I spikes were present. This reporting rule is not a test of significant rhythmicity.

  1. Reconstruct signed currents. Each displayed neuron was the first neuron attaining the highest total spike count in its population during that raster trial. A silent E population used neuron zero; a silent I population had no selected-neuron panels. Raster trials used 1024 input channels at 5 Hz for COBA and 45 Hz for PING, unlike the matched-drive sweep.

    For the selected neurons, recorded conductances and voltages gave

    𝐼𝑋in=−𝑔𝑋(𝑉𝑚−𝐸𝑋),
    (2)
    where 𝑋 identifies excitation, inhibition or leak; 𝑔𝑋 is conductance in µS, 𝑉𝑚 membrane voltage and 𝐸𝑋 reversal potential in mV, and 𝐼𝑋in inward current in nA. Reversals were 0, −80 and −65 mV, respectively; positive current is depolarising. The sign lives in the driving force, never in the conductance.

Dataset

References

  1. P. D. Welch. “The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging Over Short, Modified Periodograms.” IEEE Transactions on Audio and Electroacoustics 15(2), 70–73 (1967). doi:10.1109/TAU.1967.1161901