HIPPOGRID — evidence pack for the preliminary results (2026) Raw result files and figures behind the preliminary results cited in the MSCA-PF proposal HIPPOGRID (SEP-211387371, call HORIZON-MSCA-2026-PF-01). Researcher: Álvaro González-Redondo (University of Granada). Each bundle below backs one claim of the proposal; each result file is the unmodified output of the experiment that produced it, and the commit hash anchors it in the (currently private) research repository, scheduled for open release (Apache-2.0) with the corresponding papers. Numbers were produced with 10 random seeds and paired comparisons against non-degenerate null models unless stated otherwise. License: CC-BY 4.0. Contact: alvarogr@ugr.es Bundle Claim it backs (as in the proposal) Key files Commit B1_real_sensor_binding Image and posture written to one shared address are recovered from each other on a real robot's sensor stream (8,346 frames, 10 seeds); writing to a shuffled address destroys the binding asymmetrically while the memory stays intact `n562_real.json`, figure 5498007e B2_innate_template_binding A one-shot Hebbian binding anchors an innate grid-module set at 1.0–1.4 cells median under biological-level velocity noise (10/10 seeds; bounded at 3× that noise; shuffled-binding and shuffled-velocity nulls fail); the anchored map reproduces the signature of classic deformation experiments (partial rescaling; anisotropic field stretching, cf. Barry et al. 2007; merged-map seam, cf. Wernle et al. 2018) `n569_ancla*.json`, `n569_deformada.json`, `n569_defensa.json`, figures 0f20cb40 B3_rate_grid_recipe A purely local Hebbian/anti-Hebbian rule yields clean 2-D grid maps with no explicit normalisation: best-unit grid score 0.81 (torus) / 0.71 (walled box), medians over 10 seeds `n565_toro.json`, `n565_caja.json`, `n565_repro.json`, figure 2c6455c7 B4_place_stage_chain The chain closes from raw sensed input through a competitive place stage (grid score ≥ 0.4 in 9/10 seeds; direct input 0/20); small modules of distinct grid units at small grid-layer sizes; a stored-experience place stage performs like a trained one `n567_u4096_rejilla.json`, `n568_10semillas.json`, `n568_nulos.json`, `n568_redundancia.json` 0243e5b0 B5_blackboard_capacity With learned addresses the blackboard's capacity grows ~N/2 vs ~N^0.45 without learning (`n562_escalado.json`, keys `ley*`); the worst alias between two distant places falls from 0.995 to 0.093 at 4,096 cells (`n562_aprendido_dos_tablas.json`; N-dependent: 0.904 at 1,024 cells) `n562_escalado.json`, `n562_aprendido_dos_tablas.json` 16d3322e / 3a22657e B6_local_rule_ceiling A single-layer delta rule with a self-generated teacher ties the exact optimum of its family (+0.71 vs +0.70) and the non-negative constraint improves it (+0.82, 16/16) `n541_techo_exacto.json`, `n542_delta.json`, `n542_rectificada.json` d764a6fd Figures are included where the proposal reproduces them. JSON field names are in Spanish (the project's working language); each file is self-describing, with seeds and conditions as keys. Version 2 adds the room-deformation battery at 10 seeds (bundle B2, files n571_*), cited by the preprint “A fixed grid template, bound in one visit, deforms with the room the way an animal's map does” (arXiv, September 2026).
Álvaro González-Redondo· Zenodo (CERN European Organi...· 0 citations
HIPPOGRID — evidence pack for the preliminary results (2026) Raw result files and figures behind the preliminary results cited in the MSCA-PF proposal HIPPOGRID (SEP-211387371, call HORIZON-MSCA-2026-PF-01). Researcher: Álvaro González-Redondo (University of Granada). Each bundle below backs one claim of the proposal; each result file is the unmodified output of the experiment that produced it, and the commit hash anchors it in the (currently private) research repository, scheduled for open release (Apache-2.0) with the corresponding papers. Numbers were produced with 10 random seeds and paired comparisons against non-degenerate null models unless stated otherwise. License: CC-BY 4.0. Contact: alvarogr@ugr.es Bundle Claim it backs (as in the proposal) Key files Commit B1_real_sensor_binding Image and posture written to one shared address are recovered from each other on a real robot's sensor stream (8,346 frames, 10 seeds); writing to a shuffled address destroys the binding asymmetrically while the memory stays intact `n562_real.json`, figure 5498007e B2_innate_template_binding A one-shot Hebbian binding anchors an innate grid-module set at 1.0–1.4 cells median under biological-level velocity noise (10/10 seeds; bounded at 3× that noise; shuffled-binding and shuffled-velocity nulls fail); the anchored map reproduces the signature of classic deformation experiments (partial rescaling; anisotropic field stretching, cf. Barry et al. 2007; merged-map seam, cf. Wernle et al. 2018) `n569_ancla*.json`, `n569_deformada.json`, `n569_defensa.json`, figures 0f20cb40 B3_rate_grid_recipe A purely local Hebbian/anti-Hebbian rule yields clean 2-D grid maps with no explicit normalisation: best-unit grid score 0.81 (torus) / 0.71 (walled box), medians over 10 seeds `n565_toro.json`, `n565_caja.json`, `n565_repro.json`, figure 2c6455c7 B4_place_stage_chain The chain closes from raw sensed input through a competitive place stage (grid score ≥ 0.4 in 9/10 seeds; direct input 0/20); small modules of distinct grid units at small grid-layer sizes; a stored-experience place stage performs like a trained one `n567_u4096_rejilla.json`, `n568_10semillas.json`, `n568_nulos.json`, `n568_redundancia.json` 0243e5b0 B5_blackboard_capacity With learned addresses the blackboard's capacity grows ~N/2 vs ~N^0.45 without learning (`n562_escalado.json`, keys `ley*`); the worst alias between two distant places falls from 0.995 to 0.093 at 4,096 cells (`n562_aprendido_dos_tablas.json`; N-dependent: 0.904 at 1,024 cells) `n562_escalado.json`, `n562_aprendido_dos_tablas.json` 16d3322e / 3a22657e B6_local_rule_ceiling A single-layer delta rule with a self-generated teacher ties the exact optimum of its family (+0.71 vs +0.70) and the non-negative constraint improves it (+0.82, 16/16) `n541_techo_exacto.json`, `n542_delta.json`, `n542_rectificada.json` d764a6fd Figures are included where the proposal reproduces them. JSON field names are in Spanish (the project's working language); each file is self-describing, with seeds and conditions as keys.
Álvaro González-Redondo· Zenodo (CERN European Organi...· 0 citations
HIPPOGRID — evidence pack for the preliminary results (2026) Raw result files and figures behind the preliminary results cited in the MSCA-PF proposal HIPPOGRID (SEP-211387371, call HORIZON-MSCA-2026-PF-01). Researcher: Álvaro González-Redondo (University of Granada). Each bundle below backs one claim of the proposal; each result file is the unmodified output of the experiment that produced it, and the commit hash anchors it in the (currently private) research repository, scheduled for open release (Apache-2.0) with the corresponding papers. Numbers were produced with 10 random seeds and paired comparisons against non-degenerate null models unless stated otherwise. License: CC-BY 4.0. Contact: alvarogr@ugr.es Bundle Claim it backs (as in the proposal) Key files Commit B1_real_sensor_binding Image and posture written to one shared address are recovered from each other on a real robot's sensor stream (8,346 frames, 10 seeds); writing to a shuffled address destroys the binding asymmetrically while the memory stays intact `n562_real.json`, figure 5498007e B2_innate_template_binding A one-shot Hebbian binding anchors an innate grid-module set at 1.0–1.4 cells median under biological-level velocity noise (10/10 seeds; bounded at 3× that noise; shuffled-binding and shuffled-velocity nulls fail); the anchored map reproduces the signature of classic deformation experiments (partial rescaling; anisotropic field stretching, cf. Barry et al. 2007; merged-map seam, cf. Wernle et al. 2018) `n569_ancla*.json`, `n569_deformada.json`, `n569_defensa.json`, figures 0f20cb40 B3_rate_grid_recipe A purely local Hebbian/anti-Hebbian rule yields clean 2-D grid maps with no explicit normalisation: best-unit grid score 0.81 (torus) / 0.71 (walled box), medians over 10 seeds `n565_toro.json`, `n565_caja.json`, `n565_repro.json`, figure 2c6455c7 B4_place_stage_chain The chain closes from raw sensed input through a competitive place stage (grid score ≥ 0.4 in 9/10 seeds; direct input 0/20); small modules of distinct grid units at small grid-layer sizes; a stored-experience place stage performs like a trained one `n567_u4096_rejilla.json`, `n568_10semillas.json`, `n568_nulos.json`, `n568_redundancia.json` 0243e5b0 B5_blackboard_capacity With learned addresses the blackboard's capacity grows ~N/2 vs ~N^0.45 without learning (`n562_escalado.json`, keys `ley*`); the worst alias between two distant places falls from 0.995 to 0.093 at 4,096 cells (`n562_aprendido_dos_tablas.json`; N-dependent: 0.904 at 1,024 cells) `n562_escalado.json`, `n562_aprendido_dos_tablas.json` 16d3322e / 3a22657e B6_local_rule_ceiling A single-layer delta rule with a self-generated teacher ties the exact optimum of its family (+0.71 vs +0.70) and the non-negative constraint improves it (+0.82, 16/16) `n541_techo_exacto.json`, `n542_delta.json`, `n542_rectificada.json` d764a6fd Figures are included where the proposal reproduces them. JSON field names are in Spanish (the project's working language); each file is self-describing, with seeds and conditions as keys.
Álvaro González-Redondo· Zenodo (CERN European Organi...· 0 citations
