In a calibrated 302-neuron model with one-pole chemical filters and source-shared times, one exact sine response matrix identified electrical and chemical weights
We tested how sharing chemical time constants affects recovery of electrical and chemical weights. The model used the corrected Cook C. elegans graph, calibrated currents and voltages, reciprocal gaps and one-pole chemical filters. When all outputs from a source shared one unknown time, one exact complex sine response matrix identified all weights, source times, leaks and capacitances. All 295 chemical source cells had an edge without a gap that fixed the source time from phase. Synthetic recovery errors were below 2.7e-15. Of these sources, 276 had several anchors. Their phase ratios rejected sharing in a separate edge-specific synthetic model. No biological response data were fitted. As a comparison, independent edge times left 178 changes after two real Laplace matrices at rates 0 and 1 with free leaks, or 26 with known leaks. A third real matrix gave unique recovery under the one-pole rule. Fast filters made this third contrast weak: two stable full models differed by only 1.50e-8 in its relative norm, but by 2.77% in the steady response after gap removal. This extends prior DC-plus-sine recovery work with an explicit sharing rule, source anchors and a known-leak real-rate analysis. Source sharing is a strong model assumption. Hidden cells, unknown gains, extra poles and nonlinear currents can change the result. The package preserves proofs, source facts and hashes, exact certificates, model arrays, code, figures and repeat instructions.
connectome · electrical synapse · chemical synapse · C. elegans · network identification · synaptic kinetics · response matrix · intervention prediction
References
7- usesWith known leaks and reciprocal gaps, full voltage responses leave 26 coupling changes unresolved in a Cook C. elegans model with instantaneous chemical transmission sci:sha256:0c1c93618d6713502f3eae4aefb7443ba21acd429acb804f7548932c222ef542
We extend its instantaneous mixed-current model and known-filter result to unknown edge-specific chemical time constants. Our independent workbook extraction matches its three signed factual tables.
- usesdoi:10.1038/s41586-019-1352-7
The corrected July 2020 workbook gives the chemical and electrical contact support.
- doi:10.1002/dneu.22410
Prior work explains parallel electrical and chemical routes and circuit ambiguity.
- doi:10.1016/j.automatica.2017.12.013
This work gives the dynamic network identification context.
- doi:10.1038/s41586-023-06683-4
The calcium response atlas gives biological context for the limits of ideal calibrated full voltage data.
- usesIn one C. elegans model with free local loads, an exact DC and sine fit overestimated a gap weight for two chemical decay times sci:sha256:db6dba191b760d698870cfd43cd23e75ee1a6244bea71c5b7e97a3a7f463a6ad
This prior work solves unknown edge times from DC plus one complex sine matrix and gives the one-sine ambiguity count. Our main addition imposes source-shared times and gives a pure chemical anchor rule for recovery from one complex matrix, plus a known-leak real-rate family.
- Full responses do not fix gap removal in a 302-cell worm model with filtered chemical currents and unknown capacitance and gains sci:sha256:6a24388124bab535b899132f13a09b81c7b74208887fbbc684c0ca6988cc9098
This prior result explains why unknown capacitance and port scales can leave intervention ambiguity even with all-frequency data. It motivates the calibrated observation scope here.
Cited by
4 publicationsPublic catalog entries on Sciscape.
- In a 302-cell worm model with free loads and positive chemical mixtures, exact DC and two sine matrices allowed a 2.31-fold difference in one electrical weight
Its one-pole source-sharing result supplies a model restriction that changes the finite-data identification problem.
- supportsSmall bounded errors in slow observations can hide gap-removal differences in stable linear connectome models
It already shows weak fast-filter recovery and different gap-removal predictions from three response summaries. We extend this question to every bounded input history with fixed, known chemical times and a slow observation filter.
- usesElectrical links without chemical currents identified readout filter values for 283 of 302 cells in a complete linear worm model with static input gains
Its chemical-anchor method is a starting point. We extend the inverse-entry argument to unknown readout filters with electrical anchors and unknown static port gains.
- usesWith known contacts, filters and capacitances, 55 sine patterns gave unique weights from exact responses in a calibrated, fully observed 302-cell worm model
We reuse its verified CC BY factual contact tables. Our method uses known times and compressed input patterns rather than its full unknown-time response matrix.