feat(matlab): learning figure + methods write-up + organized CSV data export

Adds make_figure (2-panel learning curves + per-phase slopes, colorblind-safe
Box-B2/Box-A2 palette) -> results/figure_learning.png; analysis/writeup.md
(figure + methods + results summary); and tdcs_export_all/run_export exporting
every data variation into an organized export/ tree (curated_all, scenarios/9,
anchors/3 with tDCS factor, phases/9 + MANIFEST). Adds tExport tests. Suite 36/36.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

analysis/matlab/README.md

@@ -128,3 +128,17 @@ term, and MATLAB's native `fitglme` already *is* the random-intercept model.
   Result: at our n (3–5/group) honest power is ~0.3–0.7 even at the observed effect; ~8/group
   reaches ~80–90% if the effect is as large as observed, ~20/group if it is half that. The LME
   test is anticonservative only at small n and converges to the honest test by n≈12.
+
+## Figure and data export
+
+- **Figure** — two-panel learning figure (curves + per-phase slopes, Box-B2 vs Box-A2),
+  written to `results/figure_learning.png`:
+  ```
+  matlab -batch "make_figure"
+  ```
+- **Export all data variations to CSV** — organized under `export/`:
+  ```
+  matlab -batch "run_export"
+  ```
+  Produces `curated_all.csv`, `scenarios/<merge>_<window>.csv` (9), `anchors/<merge>_B2vsA2.csv`
+  (3, with the binary tDCS factor), and `phases/<merge>_phase_<lo>-<hi>.csv` (9), plus a MANIFEST.