Lowet (2015): Coupled Rhythms

A gamma phase-locking map and coupling-onset demonstration inspired by Lowet et al. (2015).

Abstract

We tested whether reciprocal excitation synchronizes two conductance-based gamma circuits across 143 combinations of input imbalance and coupling strength, with 1,024 input channels per circuit and mean input 25 Hz per channel. Thirteen settings met finite-time locking criteria; maximum valid phase-locking value (PLV) was 0.990. A selected coupling-onset diagnostic also reached PLV 0.990 over 800–1,500 ms. These results describe one network initialization and paired input realization, without testing repeatability across seeds or lasting locking.

Results

Reciprocal coupling and phase locking

Inspired by Lowet et al. (2015), we tested when two gamma rhythms hold a steady phase difference. Across 143 settings, 141 had valid rhythms and 13 met all finite-time locking criteria; maximum valid PLV was 0.99 (Fig. 1). PLV measures consistency of relative phase, from zero to one; a value near one need not mean zero phase difference. This sampled map describes one realization and does not establish a continuous locking boundary or robustness across seeds.

PLV across coupling strength, with measured frequency detuning below and input drive difference above.
Figure 1.

Each rectangle is one sampled setting. Bottom: uncoupled A-minus-B frequency difference (Hz); top: A-minus-B input-rate difference (Hz per channel). Vertical axis: equal nominal total coupling per pathway (μS). White–red–black indicates increasing PLV; gray marks invalid rhythms. Values use common phase-valid samples within 800–5,000 ms. Cell edges delimit sampled settings, not inferred boundaries.

Lowet et al.’s published map provides a qualitative comparison (Fig. 2). Their conductance-density coupling, Hodgkin–Huxley neurons and signal-based phase estimate differ from our conductance-LIF model and excitatory-volley phase, so the displays do not provide a quantitative replication.

Lowet et al. Figure 2G: a triangular region of high phase-locking value across excitatory-drive difference and coupling strength, with original color scale and conductance-density axes.
Figure 2.

Crop of Lowet et al. (2015), Fig. 2G. Brighter colors indicate stronger PLV. Axes show input-drive difference and coupling in mS/cm²; Fig. 1 uses measured frequency difference in Hz and coupling in μS. Original labels and colors retained. © 2015 Lowet et al., Creative Commons Attribution.

Switching on reciprocal coupling

We used the map’s −4 Hz input difference and 0.09 μS coupling, keeping its saved weights and connections in both directions. At 500 ms, we switched coupling on. S/R frequencies changed from 41.6/46 Hz to 45.7/45.7 Hz. Relative phase became nearly steady (Fig. 3); PLV was 0.99, fitted drift was 0.0077 cycles/s and phase span was 0.115 cycles over 800–1,500 ms.

This diagnostic reuses the selected map matrices and input realization; its spikes match that map trajectory over the displayed interval. It illustrates the onset of finite-time locking and is not an independent evaluation or evidence of lasting locking.

Full sender and receiver spike rasters over 1,500 ms with reciprocal coupling starting at 500 ms and relative phase beneath.
Figure 3.

(A) Sender S and (B) receiver R spikes: excitatory neurons in black, inhibitory neurons in red. Input rates are 23/27 Hz per channel for S/R. Dashed lines mark coupling onset at 500 ms. Corner values give frequency over 0–500 ms and 1,000–1,500 ms. (C) Unwrapped S-minus-R phase difference in cycles, shown between detected excitatory volleys. Phase metrics use shared valid times within 800–1,500 ms.

Methods

  1. Construct the paired circuits. Use the saved conductance-based leaky integrate-and-fire (conductance-LIF) networks in Fig. A1, with parameters in Table A1. Binary input spikes are drawn independently per channel and timestep, with probability equal to input rate times timestep in seconds. Split each original input afferent into eight channels with one-eighth weight, preserving summed input strength and recurrent matrices. No weights are trained.

  2. Sweep reciprocal coupling (Fig. 1). Cross 11 input differences (−10 to +10 Hz per channel, step 2 Hz) with 13 coupling strengths (0–0.12 μS, step 0.01 μS). Mean input stays 25 Hz per channel. Copy a shared 500 ms uncoupled prefix into each coupling condition, then simulate to 5,000 ms without resetting state. Reuse inputs across coupling strengths and underlying random draws across input differences. Exclude 300 ms after coupling onset. The zero-coupling condition supplies measured frequency detuning. Batched settings are conditions, not replicates.

  3. Measure relative phase (Figs. 1 and 3). Smooth excitatory population rate with a Gaussian of 1 ms standard deviation; detect peaks separated by at least 15 ms with prominence at least 10% of the maximum smoothed rate. Interpolate phase linearly between consecutive volleys, advancing by 2π2\pi radians per interval; omit samples outside observed volleys. Compute

    PLV=∣1N∑n=1Nei[ϕA(n)−ϕB(n)]∣.(1)\mathrm{PLV} = \left|\frac{1}{N}\sum_{n=1}^{N} e^{i[\phi_A(n)-\phi_B(n)]}\right|. \tag{1}

    Here ϕA(n)\phi_A(n) and ϕB(n)\phi_B(n) are circuit phases in radians at shared valid sample nn, NN is the number of those samples, ii is the imaginary unit, and bars denote complex magnitude. Use S/R in place of A/B for Fig. 3. Estimate frequency as the reciprocal mean inter-volley interval, drift as the least-squares slope of unwrapped relative phase in cycles against seconds, and span as its maximum minus minimum. For the map, each rhythm needs at least 20 volleys, frequency 30–80 Hz and interval coefficient of variation (standard deviation divided by mean) ≤0.2; its uncoupled calibration must also pass. Valid pairs meet the diagnostic locking criteria when absolute drift <0.25 cycles/s, PLV >0.95 and span <1 cycle. These thresholds describe finite windows.

  4. Inspect coupling onset (Fig. 3). Transfer the selected map’s input, local and both cross-network matrices with A→S and B→R, retaining the same inputs. Apply native step gain, zero before 500 ms and one thereafter, for a continuous 1,500 ms trajectory. Phase metrics use 100–500 ms before coupling and 800–1,500 ms after coupling. Raster frequencies use the first and last 500 ms; each window requires at least five volleys and the same frequency and interval-regularity checks. Retained-evidence checks compare transferred matrices, eight-afferent masks, scheduled gains and unchanged parameters; exact spike agreement with the map checks transfer consistency, not independent reproducibility.

Network diagrams

Figure A1.

Saved circuit diagrams for (A) the coupling map and (B) the sender–receiver run. E and I denote excitatory and inhibitory populations. Arrows show local and reciprocal pathways. Labels show base input strengths before the request gain in Table A1.

Parameters

ParameterCoupling mapOnset diagnostic
Network
Neurons per circuit, E / I80 / 2080 / 20
Input channels per circuit10241024
Neuron modelConductance-LIFConductance-LIF
Reciprocal pathwaysA E→B E/I and B E→A E/IS E→R E/I and R E→S E/I
Neurons
Capacitance, E / I1 / 0.5 nF1 / 0.5 nF
Leak conductance, E / I0.05 / 0.1 µS0.05 / 0.1 µS
Passive time constant, E / I (derived)20 / 5 ms20 / 5 ms
Resting voltage, E / I-65 / -65 mV-65 / -65 mV
Reset voltage, E / I-65 / -65 mV-65 / -65 mV
Initial voltage, E / I-65 / -65 mV-65 / -65 mV
Spike threshold, E / I-50 / -50 mV-50 / -50 mV
Refractory period, E / I3 / 1.5 ms3 / 1.5 ms
Synapses and weights
Input→E base initializer mean / SD0.2 / 0.03 µS0.2 / 0.03 µS
Input→E request gain9.29.2
Input→E nominal mean / SD after gain (derived)1.84 / 0.276 µS1.84 / 0.276 µS
E→I initializer mean / SD0.5 / 0.05 µS0.5 / 0.05 µS
I→E initializer mean / SD1 / 0.1 µS1 / 0.1 µS
Input→E synapse / decayAMPA / 2 msAMPA / 2 ms
E→I synapse / decayAMPA / 1 msAMPA / 1 ms
I→E synapse / decayGABA / 9 msGABA / 9 ms
Local E→I / I→E delay0.1 / 0.1 ms0.1 / 0.1 ms
Cross-network nominal total per pathway0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12 µS0.09 µS
Cross-network fan-in (derived) / zero fraction8 / 0.98 / 0.9
Cross-network zeroing / initializer SDExact fan-in / 0 µSExact fan-in / 0 µS
Cross-network synapse / decay / delayAMPA / 2 / 2 msAMPA / 2 / 2 ms
Cross-network gain before / after onset0 / 10 / 1
Input and simulation
Timestep / total duration0.1 / 5000 ms0.1 / 1500 ms
Coupling onset500 ms; continuous state500 ms; continuous state
Input rates per channelA: 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30; B: 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20 HzS / R: 23 / 27 Hz
Signed input difference-10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10 Hz-4 Hz
Network seed / input seeds85 / 8501, 850285 / 8501, 8502
Input pairingcommon underlying uniforms across detuning; exact reuse across couplingSame input realization as selected map point
Analysis
Rate smoothing SD / minimum volley spacing1 / 15 msUnavailable in recorded configuration
Peak prominence fraction0.1Unavailable in recorded configuration
Settling after onset300 msUnavailable in recorded configuration
Minimum volleys / gamma band / maximum interval CV20 / 30–80 Hz / 0.2Unavailable in recorded configuration
Strict finite-time locking thresholds|drift| < 0.25 cycles/s; PLV > 0.95; span < 1 cycleNot classified for this diagnostic
Table A1. Values follow the article's selected presentation to its separate map and onset compute runs: exp133-r028-compute; exp133-r037-compute. Native start snapshots describe the selected 0.09 µS map condition and the transferred diagnostic; sweep and input settings come from each compute configuration. E / I means excitatory / inhibitory; SD is standard deviation and CV is interval standard deviation divided by its mean. AMPA and GABA denote excitatory and inhibitory conductance kernels. Passive time constants are capacitance divided by leak conductance. Initializer statistics are nominal totals before fan-in normalization, not measured matrix statistics. Input weights were transferred by splitting each of 128 original afferents into eight channels of one-eighth weight, then applying the recorded gain once. Fan-in is the excitatory population size times one minus the exact zero fraction. Missing recorded fields are unavailable; analysis conventions verified in source are described in Methods.

Dataset

Upstream: —

Downstream: exp153 — Mean-field Frequency Coupling

RunDateDurationSizeEvidenceStorageRan onVerification
exp133-r039-present1s497.5 KBCurrentR2LocalLocal: absent; R2: catalog-verified
exp133-r038-analyse1s124.2 KBCurrentR2LocalLocal: absent; R2: catalog-verified
exp133-r037-compute6s2 MBCurrentR2LocalLocal: absent; R2: catalog-verified
exp133-r029-analyse3s107.6 KBCurrentR2LocalLocal: absent; R2: catalog-verified
exp133-r028-compute4m 53s31.7 MBCurrentR2LocalLocal: absent; R2: catalog-verified
exp133-r025-compute4m 18s11.5 MBCurrentR2LocalLocal: absent; R2: catalog-verified

References

  1. Lowet, E., Roberts, M., Hadjipapas, A., Peter, A., van der Eerden, J., and De Weerd, P. (2015). Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding. PLOS Computational Biology, 11(2), e1004072.