Rusty Morphospace and tissue-scale patterning
Bioelectric morphogenesis asks how voltage-like state, tissue coupling, perturbations, and memory can help shape living form. The current Mesmer Prism line stays deliberately modest: Rusty Morphospace keeps inspectable educational surface-field models, while Planarian Regeneration XR turns the same source-boundary discipline into a data-first WebXR atlas of body, graph, experiment record, reviewed source geometry, and outcome. Observed records, educational abstractions, source-derived GLBs, and model-inspired overlays remain separate layers.
Reviewed June 21, 2026.
Observed records, source-derived geometry, educational dynamics, and model-inspired replays stay separate.
Qualitative teaching models and source-backed atlas layers, not calibrated wet-lab prediction.
Rusty Matter/Optics fixtures, browser inspection, reviewed PlanformDB records, GLB overlays, and replay manifests.
A full physiology simulator, clinical tool, or proof that model-inspired overlays are observed dynamics.
Source boundary
A visual overlay may teach a patterning idea, but it is not a calibrated physiology trace unless a separate validation path supports that claim.
| Observed | Reviewed GLB derivatives and PlanformDB records. | Source-backed visualization and data layers. |
|---|---|---|
| Curated | Selected experiment records and outcome details. | Literature/database-derived teaching context. |
| Educational | Procedural body, fields, conductance, and readouts. | Qualitative model, not a full physiology simulator. |
| Replay | GIFs over reviewed point positions. | Model-inspired visualization, not observed dynamics. |
| Deferred | Object-level picking and observed-geometry dynamics. | Planned pending public-safe source-map sidecars. |
Computational medium
A planarian fragment does not only carry genes and geometry. It also carries physiological state across tissue: membrane potentials, gap-junction-like communication, wound signals, and downstream patterning responses. The experimental literature around planarian regeneration makes that a useful teaching case, because early bioelectric state can affect anterior/posterior polarity and regenerated head/tail outcomes (Durant et al., 2019; Beane et al., 2011).
The Rusty Morphospace model does not try to become a full physiology simulator. It treats bioelectricity as an inspectable layer over a stable surface graph: sample nodes on a body mesh, conductance edges between neighboring samples, normalized voltage state, perturbation bands, memory state, and readout fields. This is enough to teach the architecture of a tissue-scale model while leaving calibrated wet-lab prediction outside the current claim.
Current slice
Within Rusty Morphospace, the useful boundary is simple: Matter computes the state; Optics prepares views and browser inspection; Manifold is deferred until commands, sessions, packages, and audit surfaces need to become first-class.
Matter now carries compact source/target anchor IDs inside the planarian scenario metadata. Those anchors identify which publication target shaped a scenario; they do not turn the current fixtures into source-fitted physiological predictions.
Simulation truth
Matter owns mesh-surface samples, scalar and vector fields, bioelectric circuit state, deterministic stepping, edit results, schema fixtures, validation, and Wasm runtime exports.
Visual contracts
Optics owns renderer-neutral frames, color policy, pick/edit-intent contracts, readout panels, activity layers, conductance-edge picking, and browser presentation over Matter-owned payloads.
Deferred authority
Manifold is the later lane for commands, sessions, packages, reproducible edit traces, and audit. It should request Matter work; it should not own field arrays or circuit dynamics.
Planarian XR atlas
Planarian Regeneration XR is the data-first WebXR atlas surface for this
biological teaching case. Its central loop is body to graph to experiment
record to regeneration outcome. The app now carries a reviewed PlanformDB
subset with 20 selected source records and 54 outcome details, including
browser-facing frequency and sample-size values where reviewed, bundled
observed posterior and anterior muscle SpatialGraph GLB line overlays,
a neuron cell-cloud marker GLB, a nuclei centroid marker GLB, an
allometry FirstPoint marker GLB, and a Zenodo 12533272
mergeall.am high-intensity volume-marker GLB derived from
the ETLSM datasets. The app also registers three model-inspired replay
manifests: the original Sketchfab schematic replay, a Zenodo
neuron-cloud GIF replay, and a Zenodo 12533272 volume-marker
GIF replay. The observed Zenodo GLBs are not scientific simulation
outputs. The 12533272 derivative is a browser-safe marker
subset with projection PNGs, not a full-resolution volume or segmented
surface. A validation chain keeps
source files, raw downloads, decoder tooling, and conversion intermediates
outside the public bundle
(PlanformDB;
Lu, 2024 dataset1;
Lu, 2024 dataset2).
The atlas can enter WebXR and the non-XR browser flow remains complete: top-level Source Atlas, Records, Layers, Model Replay, and Teaching workflows; an inspector guide with a visible section index; anatomy selection, graph synchronization, cut controls, Records-mode PlanformDB filters, provenance panels, graph export, screenshots, and explicit educational/source-backed labels. Geometry source cards are filterable and their source-map, technical, and caveat details now start folded closed so the atlas is navigable before it becomes exhaustive. That does not make the atlas a live regeneration simulator.
The current app opens in Source Atlas mode with the reviewed Zenodo source
layers selected but only the posterior muscle SpatialGraph overlay visible by
default. Other reviewed GLB derivatives, including the allometry FirstPoint
markers and the Zenodo 12533272 high-intensity volume-marker GLB,
remain available as explicit source layers rather than default clutter; the
ETLSM2 volume marker lane is off until selected because it is a reviewed marker
subset, not an organized anatomy surface. Model Replay includes GIFs generated
from reviewed neuron-cloud and 12533272 volume-marker GLB positions,
with the dynamics labeled as model-inspired rather than observed. The Records
mode filters the reviewed PlanformDB subset by publication, outcome class,
manipulation type, timepoint, and measurement availability. Pending lanes for
further PlanformDB expansion, public source-map sidecars, object-level picking,
observed-geometry dynamics, and Quest Browser validation remain statused rather
than central.
The latest implementation plan also defines the missing bridge before real
observed GLBs become interactive scientific objects: public-safe source-map
sidecars for segment, point, label, FirstPoint, and volume-surface mappings.
These sidecars may carry reviewed element IDs, transforms, hashes, counts, and
caveats. They must not carry raw .togo, .am,
.am.dat, decoder output, local paths, logs, or review packets.
Data layers
The app separates observed geometry, curated literature/database records, model-inspired overlays, and educational abstractions at the dataset schema level.
Interaction
Anatomy nodes, graph nodes, cut states, perturbations, records, outcomes, field overlays, record filters, and lessons are all inspectable without hiding their evidence type or visualization status.
Validation
The local readiness chain validates data references, geometry notices, source labels, build output, public asset boundaries, and the documented implementation-plan gates before a build is treated as coherent.
Showcase export
The first two exports show the current Optics-owned preview/export path over Matter-owned synthetic educational state: a 720-node planarian graph, opaque body material, neon RGB activity/readout color, stable portrait framing, and a reset-activity showcase loop. The animation is a visual teaching mode for surface-field inspection, not a calibrated planarian physiology trace.
The new Zenodo replay uses the reviewed planarianneuronpool.Cloud
GLB as the display-node source: 3,467 source points are sampled into a
480-node nearest-neighbor graph and exported as a 96-frame, 720 x 860 GIF at
12 fps. It is a qualitative voltage/conductance visualization over observed
point positions, not a measured bioelectric trace or predictive regeneration
model.
A second Zenodo replay now uses the reviewed 12533272
volume-marker GLB: 5,089 selected high-intensity source points are sampled
into a 640-node nearest-neighbor graph with 2,430 conductance edges and
exported as a 96-frame GIF. The source geometry is a derived marker subset,
not a full volume, and the dynamics remain model-inspired display output.
Adjacent dynamics
Bioelectricity matters to Mesmer Prism because it gives another concrete vocabulary for multi-level patterning: voltage-like fields, conductance, gap-junction-like coupling, perturbation, memory, readout, repair, and target-state change. In Michael Levin's broader framing, cells, tissues, and organs are not passive materials. They are nested problem-solving systems whose physiological networks help navigate anatomical morphospace (Levin, 2023a; Levin, 2023b).
That does not make Plasmatic Multitudes, Mixed-Ability HSI, or Rusty Morphospace biological projects. The useful transfer is more constrained: bioelectric morphogenesis suggests synthetic dynamics for fields, coupling, memory, regeneration-like repair, and multi-scale agency. Those dynamics can inspire virtual swarm bodies or educational prosthetic/biotech questions later, while the current implementation remains a source-linked teaching model rather than a medical, prosthetic, or wet-lab system (Levin, 2021; Levin, 2022).
DiffeoMorph belongs on this adjacent side too: the paper DiffeoMorph: Learning to Morph 3D Shapes Using Differentiable Agent-Based Simulations and the hormoz-lab/diffeomorph implementation are useful for target-shape metrics and learned many-agent controllers, but they are not bioelectric or planarian physiology sources.
Current public work uses bioelectricity as a qualitative dynamics source and implementation test case for Rusty Matter and Rusty Optics. Any future prosthetic, regenerative, or biotech claim would need a separate evidence, ethics, and validation path.
Source status
The current implementation is source-linked at the target level. Two source
families already have qualitative Matter fixtures, and the derived
PlanformDB/metric/taxonomy layer now has a curated provenance fixture mirrored
into Matter. Planarian Regeneration XR carries a reviewed PlanformDB subset,
reviewed observed GLB overlays for posterior and anterior muscle SpatialGraph
objects, the planarianneuronpool.Cloud HxCluster marker
cloud, the Result nuclei centroid marker cloud, and the
Result(2).Label-Analysis(2) FirstPoint anchor marker cloud,
plus a reviewed 12533272 high-intensity volume-marker GLB.
The reviewed neuron-cloud and volume-marker GLBs now have public
model-inspired dynamics GIF replays. The current Source Atlas startup state
selects the reviewed source layers but shows the posterior muscle overlay
first; the 12533272 volume marker lane is intentionally available
rather than active by default. It also has a Quest Browser validation lane that
needs a refreshed headset pass whenever the production build changes.
Remaining targets are intentionally planned until source figures, tables,
categories, or datasets have been extracted into derived, rights-safe
artifacts.
| Target | Original sources | Current implementation | Status |
|---|---|---|---|
ap_transient_memory |
Durant et al., 2019 | Matter transient-depolarization memory scenario plus no-memory control; Optics can display the resulting sequence. | Qualitative fixture exists; numeric timing/value targets still need source extraction. |
gap_block_conductance |
Oviedo et al., 2010; Emmons-Bell et al., 2015 | Matter gap-block scenario reduces cross-band conductance and records outcome traces. | Qualitative fixture exists; figure/table targets still need extraction before thresholds. |
head_vs_tail_voltage |
Beane et al., 2011 | Represented only as normalized AP voltage and head/tail readout context. | Planned annotation layer; no named ion-channel or millivolt claim yet. |
head_size_scaling |
Beane et al., 2013 | Normalized region-extent metrics exist for annotation and validation fixtures. | No calibrated organ-size or physical morphometry claim yet. |
species_like_head_labels |
Emmons-Bell et al., 2015 | Synthetic species-like head-shape taxonomy fixture exists for educational labeling. | Non-calibrated; generated labels avoid paper figure reuse. |
planformdb_curated_subset |
PlanformDB; Lobo et al., 2013 | Rights-safe derived fixture records 14 selected Oviedo 2010 source IDs covering octanol crop-position, ventral nerve cord timing, and innexin RNAi crop-position labels, with transform notes, notice text, and use limits. | Expanded review fixture exists in Hub and Matter; metadata/annotation only, not runtime dynamics authority or a predictor. |
planarian_xr_data_first_navigation |
Planarian Regeneration XR | The atlas now opens with a top workflow selector, a Source Atlas guide, a visible inspector section index, filterable geometry source cards, and closed-by-default foldouts for source maps, technical details, and caveats. The default visible source layer is posterior.Smt.SptGraph; the ETLSM2 volume marker GLB is available but not active at startup. |
Public navigation and onboarding improvement; it changes how evidence lanes are presented, not the scientific claim boundary. |
planarian_xr_source_map_sidecars |
Planarian Regeneration XR; Zenodo dataset1/dataset2 object IDs | The implementation plan defines public-safe sidecar envelopes for segment-node, point-ID, label-ID, FirstPoint-ID, and volume-surface mappings. Sidecars may include public element IDs, transforms, hashes, counts, and caveats, but not raw source payloads, private decoder details, local paths, logs, or review packets. | Planned bridge before object-level picking, nearest-object annotation, or observed-geometry dynamics binding can be treated as reviewed behavior. |
zenodo_11724834_observed_glb_overlays |
Lu, 2024; CC BY 4.0 | Planarian Regeneration XR bundles reviewed GLB line overlays derived from posterior.Smt.SptGraph and anterior-filtered(2).CorrelationLines: 61,744 / 17,880 vertices, 30,872 / 8,940 line segments, SHA-256 daab05fbf234bb6db8b6618520982c1d159ca553a067825eba42929449478a2f and aa462e4141be28a5f7bb5d187a7b074a945815f19d3397110e90a8e102428ac7. It also bundles the planarianneuronpool.Cloud HxCluster marker GLB with 3,467 source points, 20,802 vertices, 10,401 marker line segments, and SHA-256 97a18266dfa0cfa0f1fac739cf01c64c5a02ea0413d5a0b7aa81e3eb24e45787; the Result nuclei centroid marker GLB with 4,304 centroids, 25,824 vertices, 12,912 marker line segments, and SHA-256 7a191333ff455427f63a0ff65d112d2073473e0d22966cfa5c506e2204ad1af2; and a Result(2).Label-Analysis(2) FirstPoint anchor marker GLB with 3,567 anchors, 21,402 vertices, 10,701 marker line segments, and SHA-256 7e26fc68b5f1297f33b9efc1375b0162646bd030f35e4a3c179e979679de1fcc. Source DOI/object IDs, attribution, and geometry notice are recorded. |
Observed source-derived atlas geometry only; raw Zenodo files, source exports, decoder tooling, and conversion intermediates remain outside the public bundle. Nuclei markers are centroids, FirstPoint anchors are not centroids, and the overlays are not a regeneration simulation. |
zenodo_neuron_cloud_bioelectric_replay |
Lu, 2024; Planarian XR public GLB replay generator | The reviewed planarianneuronpool.Cloud GLB supplies display positions for zenodo-neuron-cloud-bioelectric-replay.gif: 480 sampled nodes, 1,767 nearest-neighbor conductance edges, 96 frames at 720 x 860 pixels, GIF SHA-256 de307a94e2d67ae378816362c33cd43dbf49f6f288a5bbf796e057f09ab78ee2. |
Model-inspired display replay only. It is not a measured bioelectric trace, calibrated physiology, mechanistic model output, or predictive regeneration simulation. |
zenodo_12533272_volume_marker_glb |
Lu, 2024 dataset2; CC BY 4.0 | Public-safe sidecar and derivative facts are recorded: mergeall.am.lda verifies a 4469 x 7887 x 3520 16-bit tiled volume, 124,069,450,560 voxels, Gzip tile compression, intensity bounds from 0 to 44182, and a linked mergeall.am.dat volume of about 34.5 GB. The linked volume was downloaded under ignored raw storage and checksum-verified against MD5 a596aab89a5d793cfc71329e809b81ca. The public derivative mergeall-volume-lod3-high-intensity.glb contains 5,089 selected high-intensity marker points, 30,534 vertices, 15,267 marker line segments, and SHA-256 8fead939a8aabba7ee9c433fe0d6e158f490c924097b5c7fa35919072e39ff22; public UV/UW/VW maximum-intensity projection PNGs accompany the GLB. |
Observed source-derived atlas geometry only and not active in the default viewer state. It is not a full-resolution volume, not a segmented surface, not a measured bioelectric trace, and not a predictive regeneration simulation. Raw sidecar XML, raw histogram payload, TileMinMax payload, contributor-local source path, source volume, source export, intermediate, decoder output, and review packets remain outside the public bundle. |
zenodo_12533272_volume_bioelectric_replay |
Lu, 2024 dataset2; Planarian XR public GLB replay generator | The reviewed mergeall-volume-lod3-high-intensity.glb supplies display positions for zenodo-12533272-volume-bioelectric-replay.gif: 5,089 source points sampled into 640 nodes, 2,430 nearest-neighbor conductance edges, 96 frames at 720 x 860 pixels, GIF SHA-256 6571a79455c0d84bd9981ce3c3151de9a15f089719ae8b43fb5961251aeade53. |
Model-inspired display replay only. It is not a measured bioelectric trace, calibrated physiology, mechanistic model output, or predictive regeneration simulation. |
planarian_xr_schematic_replay_manifest |
Planarian XR schematic transition adapter; Sketchfab educational mesh substrate | The app registers sim_schematic_regeneration_replay_v0, a model-inspired adapter descriptor for src/worm/RegenerationAnimator with a SHA-256 replay-descriptor hash. |
Display replay only. It is not calibrated, mechanistic, predictive, or bound to the observed Zenodo GLB overlays. |
Why planarians
Planarians are useful here because regeneration is spatially legible. A transverse cut gives a wound band, an anterior/posterior axis, and a clear readout problem: head-like and tail-like identity must resolve in the right places. Experimental work gives qualitative constraints for an educational model, including gap-junction-mediated polarity effects and persistent altered morphology after transient perturbations (Oviedo et al., 2010; Emmons-Bell et al., 2015).
The first scenarios therefore stay simple: baseline anterior/posterior separation, transverse-cut wound response, conductance-block perturbation, transient depolarization with memory, and a no-memory control. Those scenarios are not meant to predict a real animal. They are checks that the model can express the right kind of tissue-scale relationship before any calibrated source data is introduced.
Head size and organ scaling studies add another useful lesson: voltage-like state can be read as an instructive patterning variable, not just a passive byproduct of cell state (Beane et al., 2013). In the current model, that idea appears as readout fields driven by normalized voltage and memory state.
Voltage is normalized in the current educational layer. Calibrated millivolt claims require a separate source, unit, and validation gate.
Reference lanes
The older planarian and xenobot work is useful, but it should not become an uncontrolled runtime authority for the Rusty Morphospace implementation. Planarian Regeneration XR is the current atlas surface for the planarian side of that boundary.
Planarian reference
The planarian atlas contributes educational region labels, body geometry lessons, outcome labels, source/provenance habits, reviewed and filterable PlanformDB records, and observed source-derived posterior/anterior muscle overlays plus neuron, nuclei, allometry, and dataset2 marker overlays. Its latest work adds data-first workflow navigation, closed-by-default source-card details, a posterior-muscle default source layer, and a public-safe source-map sidecar plan. Matter still builds its own computational surface graph and validation fixtures.
Xenobot reference
The xenobot planning material frames later body-surface and behavior questions. It is not the first implementation target. The current path builds a generic surface-field substrate first, then leaves locomotion, cilia, hydrodynamics, fabrication, and full xenobot simulation for later.
Computational morphogenesis reference
DiffeoMorph supplies public reference material for many-agent target-shape learning, shape-matching metrics, and robustness vocabulary. It can inform future Rusty Morphospace validation language without becoming a source for the planarian bioelectric model.
Curated metadata source
PlanformDB now enters through a reviewed, rights-safe metadata subset: selected experiment/result IDs, 54 outcome details, normalized labels, source notices, and transform notes across 12 source publication IDs. It remains annotation and validation context, not raw runtime authority or a shortcut to calibrated physiology.
Discovery map
Bioelectricity Nexus is useful for field navigation: papers, tools, researchers, and resource leads such as BETSE and PlanMine. It is a discovery source, not primary evidence for the biological claims on this page.
Claim boundary
The current implementation is not BETSE, a named-ion-channel simulator, a wet-lab planning system, a calibrated PlanformDB predictor, or a full xenobot/anthrobot world model. It uses normalized state and synthetic scenarios to make tissue-scale relationships visible before the project takes on heavier physiology or real-data claims.
That boundary is an engineering choice. It keeps the page readable, keeps code ownership clear, and avoids presenting educational dynamics as empirical prediction. The current PlanformDB slice is deliberately metadata-only. More detailed source-derived work can be added later when source IDs, license notices, transformations, source-map sidecars, and validation targets are explicit. The observed Zenodo overlays and marker GLBs are atlas geometry layers, not anatomical models of regeneration; source-paper figures, raw datasets, decoder tooling, source exports, local tile-review packets, and conversion intermediates should remain outside the public page unless rights and provenance have been reviewed.
References
