Mean-Field Analysis of PING Bifurcations

An independent four-variable mean-field analysis identifies a Hopf bifurcation, sampled dynamics consistent with a supercritical transition, and decreasing onset frequency with slower inhibition.

Abstract

We analysed the four-state E→I→E specialisation of the mean-field model. Analytical-Jacobian continuation identified a Hopf bifurcation at 0.593905 nA with onset frequency 27.57 Hz. Ascending and descending near-onset integrations produced coincident sampled branches and continuous amplitude growth consistent with a supercritical transition. This numerical criterion does not exclude a narrower bistable interval or unstable cycle. Hopf frequency decreased as inhibitory decay lengthened.

Results

A reversible Hopf onset slows

At Iext,E=I_{\mathrm{ext},E} = 0.593905 nA, a complex-conjugate eigenvalue pair crossed the imaginary axis at fHopf=f_{\text{Hopf}} = 27.57 Hz (Fig. 1A). The sampled amplitude branches differed by at most 0.00687 Hz and had Rfit2=R_{\text{fit}}^{2} = 0.9994, consistent with a supercritical transition (Fig. 1B). Across the inhibitory-decay sweep, fHopff_{\text{Hopf}} decreased from 30.2 to 17.94 Hz (Fig. 1C). Finite spacing cannot exclude narrower bistability or an unstable periodic orbit.

Eigenvalue crossing, reversible oscillation-amplitude onset, and Hopf frequency across inhibitory decay constants.
Figure 1.

Mean-field Hopf bifurcation. (A) All four JflowJ_{\mathrm{flow}} eigenvalues, coloured by external drive; open markers identify the refined Hopf pair. (B) Peak-to-peak excitatory-rate amplitude over the final 500 ms of each ascending or descending drive condition, relative to the refined Hopf drive. (C) Refined Hopf frequency at τI→E=4.5,6,9,12,18\tau_{I\to E} = 4.5 , 6 , 9 , 12 , 18 and 2727 ms, with all other model parameters fixed. These deterministic calculations have no statistical uncertainty intervals.

Methods

The selected results precede the SNNLab 0.27 migration. They retain their original solver settings; the current recipe has not regenerated these displayed results.

  1. Model. The mean-field note supplies the shared derivation; Appendix A records this experiment’s specialisation.

  2. Hopf bifurcation and onset frequency. At the reference inhibitory-pathway decay τI→E=6\tau_{I\to E}=6 ms, we evaluated the equilibrium over 401 equally spaced external drives from 0 to 4 nA.

    2.1 — Solve for the equilibrium.

    Set the two recurrent conductance derivatives to zero in the note’s equations, apply the experimental specialisation, and substitute the inhibitory equilibrium rate into the excitatory equation. The scalar residual is the excitatory rate minus its predicted gain.

    Brent’s bracketed method searched 0≤rE≤1τref,E0 \le r_{E} \le \frac{1}{\tau_{\mathrm{ref},E}} with absolute tolerance 10−1310^{- 13} ms−1{\text{ms}}^{- 1} and relative tolerance 10−1210^{- 12}. We recovered rIr_{I}, geIg_{e}^{I} and giEg_{i}^{E} by substitution and required an absolute residual below 10−1110^{- 11} ms−1{\text{ms}}^{- 1}.

    2.2 — Calculate local stability. At every equilibrium, we evaluated the analytical reduced Jacobian and numerically calculated its four eigenvalues. Eigenvalues with positive imaginary part greater than 10−810^{- 8} ms−1{\text{ms}}^{- 1} were eligible for the leading complex pair. We plotted all four eigenvalues in the complex plane and coloured them by external drive; negative and positive real parts denoted local decay and growth, respectively (Fig. 1A).

    2.3 — Identify and verify the crossing.

    The first change of the leading complex pair from negative to nonnegative real part supplied a coarse drive bracket. Brent’s method refined the zero to absolute drive tolerance 10−1210^{- 12} nA and relative tolerance 10−1210^{- 12}, recomputing the equilibrium and analytical Jacobian at every trial drive. We confirmed nonzero imaginary part, negative real parts for the remaining modes, and positive transversality by a centred difference with 10−510^{- 5} nA half-step. The recorded crossing slope was 0.29 ms−1nA−1{\text{ms}}^{- 1} {\text{nA}}^{- 1} and the largest remaining real part was -0.458 ms−1{\text{ms}}^{- 1}.

    2.4 — Calculate the onset frequency. At the refined crossing, ωHopf\omega_{\text{Hopf}} was the magnitude of the critical pair’s imaginary part in radians per millisecond. We converted it to hertz using fHopf=1000ωHopf2πf_{\text{Hopf}} = 1000 \frac{\omega_{\text{Hopf}}}{2 \pi} (Fig. 1A).

  3. Numerical criticality test. We integrated 25 equally spaced drives from 0.1 nA below to 0.55 nA above the refined Hopf point, first in ascending and then in descending order. The initial state was the lowest-drive equilibrium with an added 10−310^{- 3} ms−1{\text{ms}}^{- 1} excitatory-rate perturbation; each subsequent condition began from the preceding endpoint. LSODA integrated each condition for 2,000 ms with relative tolerance 10−710^{- 7}, absolute tolerance 10−1010^{- 10} and maximum step 1 ms.

    For each drive, peak-to-peak excitatory-rate amplitude AppA_{\text{pp}} was measured over the final 500 ms. We classified the sampled dynamics as consistent with a supercritical transition when the maximum difference between ascending and descending amplitudes was below 10−410^{- 4} ms−1{\text{ms}}^{- 1}, and ordinary least-squares regression of App2A_{\text{pp}}^{2} on Iext,E−I∗I_{\mathrm{ext},E} - I^{\ast} above onset had positive slope and Rfit2>0.9R_{\text{fit}}^{2} > 0.9. This finite numerical criterion tests reversible, continuous onset; it does not detect an unstable cycle or prove the absence of narrower bistability.[1]

  4. Inhibitory-decay sweep. We repeated the equilibrium continuation and refined complex-pair crossing at τI→E=4.5,6,9,12,18\tau_{I\to E} = 4.5 , 6 , 9 , 12 , 18 and 2727 ms while holding all other model parameters fixed. At every decay constant, we applied the same nonzero-frequency, remaining-mode stability and transversality checks used at the 6-ms reference condition, then converted the critical angular frequency to fHopff_{\text{Hopf}} in hertz.

Appendix A — Model specialisation and stability

A1 — Experimental specialisation

The mean-field note defines the model and its derivation. This experiment disables E→E and I→I coupling and has no external conductance input. Instead, Iext,EI_{\mathrm{ext},E} is the swept tonic current and Iext,I=0I_{\mathrm{ext},I}=0. The four-state reduction therefore uses x=(rE,rI,geI,giE)x=(r_E,r_I,g_e^I,g_i^E).

Rates are spikes per neuron per ms. The decay times are τE→I=2\tau_{E\to I}=2 ms and swept τI→E\tau_{I\to E}; the resting-voltage driving forces are ΔVexc,Q=65\Delta V_{\mathrm{exc},Q}=65 mV and ΔVinh,Q=15\Delta V_{\mathrm{inh},Q}=15 mV for both populations Q∈{E,I}Q\in\{E,I\}. The fixed noise scale is σV,Q=4\sigma_{V,Q}=4 mV; rate-relaxation times are 20/5 ms for E/I. Recorded values and numerical settings are listed in the parameter table.

The note’s matrix sums denote this experiment’s imported reference couplings, not newly sampled matrices. The tonic current is a control parameter; no empirical input-rate mapping is inferred. The general gain, fixed-driving-force approximation and rate relaxation are not rederived here.

A2 — Stability calculation

The zero-self-coupling Jacobian applies directly with the experimental parameters above. The note gives the analytical gain slope and stability criteria. The numerical continuation, crossing checks and criticality test remain in Methods.

Setting the conductance and rate derivatives to zero defines the stationary problem in Method 2.1. Native SNNLab calculations solve all four equations together; the earlier calculation used scalar elimination.

Network diagrams

Mean-field cross-coupling; illustrative model schematic.
Figure A1. Mean-field cross-coupling. Illustrative schematic of the documented model; it is not a recovered historical execution bundle or a measurement. EE and II denote excitatory and inhibitory population rates. The arrows denote cross-population coupling in the analytical closure; WXYW_{XY} labels target XX first and source YY second. These symbols correspond to the imported summed couplings, not newly sampled synaptic matrices. Tonic applied currents, leak and rate relaxation are local dynamics and are omitted.

Parameters

This is an analytical population calculation, so simulation snapshots do not apply. Native runs export the SNNLab model document, including equations, parameters and closure assumptions. Imported constants and numerical choices below come from the selected computation’s recorded configuration. Missing historical fields are unavailable; current defaults are never substituted.

ParameterRecorded value
Network: imported reference sizes
E / I neurons1024 / 256
Neurons: imported reference physics
Capacitance, E / I (nF)1 / 0.5
Leak conductance, E / I (µS)0.05 / 0.1
Membrane time constant, E / I (ms; capacitance / leak)20 / 5
Rest / reset / threshold (mV)-65 / -65 / -50
Excitatory / inhibitory reversal (mV)0 / -80
Refractory period, E / I (ms)1.2 / 0.6
Synapses: imported reference coupling
AMPA / reference GABA decay (ms)2 / 6
E→I / I→E summed coupling (µS)1 / 2
Closure assumptions and experimental choices
Rate relaxation, E / I (ms)20 / 5
Effective voltage noise (mV)4
Driving-force referenceresting_voltage
External drive minimum / maximum (nA)0 / 4
GABA-decay sweep (ms)4.5 / 6 / 9 / 12 / 18 / 27
Numerical analysis
Drive-grid minimum / maximum (nA) / point count0 / 4 / 401
Equilibrium solverbrentq
Native scaled derivative toleranceUnavailable
Gain quadrature nodesUnavailable
Historical equilibrium absolute / relative tolerances1e-13 / 1e-12
Equilibrium residual tolerance (per ms)1e-11
Complex-pair imaginary threshold (per ms)1e-8
Hopf solver / absolute tolerance (nA)brentq / 1e-12
Hopf relative tolerance / transversality step (nA)1e-12 / 0.00001
Ramp relative-drive endpoints (nA)-0.1 / 0.55
Ramp points / duration (ms)25 / 2000
Ramp measurement start (ms) / samples1500 / 1001
Initial E-rate perturbation (per ms)0.001
Amplitude / branch-gap thresholds (per ms)0.0001 / 0.0001
Minimum amplitude-squared fit R²0.9
Ramp solverLSODA
Ramp relative / absolute tolerances1e-7 / 1e-10
Maximum integration step (ms)1

Dataset

Upstream: —

Downstream: exp110 — Manuscript

Current runset

RunDateDurationSizeEvidenceStorageRan onVerification
exp117-r025-present<1s323.4 KBCurrentR2LocalLocal: absent; R2: catalog-verified
exp117-r024-analyse<1s265 KBCurrentR2LocalLocal: absent; R2: catalog-verified
exp117-r023-compute30s1.6 MBCurrentR2LocalLocal: absent; R2: catalog-verified

References

  1. Y. A. Kuznetsov. Elements of Applied Bifurcation Theory, third edition. Springer (2004), Chapters 3 and 5. doi:10.1007/978-1-4757-3978-7