ds006239 (roi-auditory): alignment results (control gate: fail)

roi-auditory/README.md

@@ -0,0 +1,123 @@
+# Brain–language-model alignment: ds006239 (roi-auditory)
+
+Wang et al. 2025 — word-level phonological and semantic reading tasks in children and adolescents aged 10–17.
+
+- Paper: https://www.sciencedirect.com/science/article/pii/S2352340925009692
+- Data: https://openneuro.org/datasets/ds006239/versions/1.0.5
+- Generated: 2026-09-07
+- Pipeline: https://github.com/suchirsalhan/cdl-representations-brains-babylms
+- Masking: **roi-auditory** -- see DATASETS.md section 10 for the three-level standard (phonology/language/all) this is part of, and how it differs from the whole-brain reference.
+
+## Read this first: does the measurement work?
+
+Every alignment number in this dataset is only as meaningful as the brain
+RDMs it was computed against. So before any model result, the same
+pipeline is asked whether *anything* stimulus-driven correlates with those
+RDMs — stimulus duration, intensity, word length, frequency, phoneme and
+syllable counts, an acoustic model of the audio where the stimuli are
+audio, and the study's own condition contrast — each tested by a
+permutation test that shuffles stimulus identity.
+
+**GATE: FAILED. 0/38 stimulus tests are significant** after Holm
+correction — not the acoustic model of the audio the children actually
+heard, not the study's own experimental contrast.
+
+**The alignment numbers below are therefore uninterpretable as
+evidence about language models.** They measure a representational
+geometry that does not demonstrably encode the stimuli. They are
+published for completeness and for whoever fixes the estimator, not as
+a result. Do not cite them as evidence that models fail to align with
+the developing brain.
+
+Measured cause, from `control/`:
+
+- RDM effective rank: **53** of 84 stimuli
+
+
+Note that this is NOT ds003604's failure mode. There, the RDM
+effective rank was ~3 of 40-48 stimuli -- near-degenerate betas
+that could not express stimulus-level structure at all. The rank
+recorded above is a large fraction of the stimulus count, so these
+RDMs do carry stimulus structure and the control failing here means
+the specific controls tested did not reach significance, not that
+the measurement is uninterpretable. Check `control/` for which
+controls ran: an acoustic or visual control needs the dataset's
+stimulus files present, and reports zero features if they are not.
+
+## What was built
+
+8 task × session cells, each an RDM over the stimuli
+shared by that cell's subjects, with voxel patterns z-scored **within
+run** before aggregation (without that, the RDM measures scanner drift
+rather than language) and an inter-subject noise ceiling.
+
+| task     | session   |   n_stim |   ceiling_lower |   ceiling_upper |   ceiling_n |
+|:---------|:----------|---------:|----------------:|----------------:|------------:|
+| Orth     | ses-11+   |       96 |        0.527509 |        0.760826 |           3 |
+| Orth     | ses-11    |       96 |        0.395701 |        0.694777 |           3 |
+| Phon     | ses-11+   |       96 |        0.527509 |        0.760826 |           3 |
+| Phon     | ses-11    |       96 |        0.395701 |        0.694777 |           3 |
+| Sem      | ses-11+   |       72 |        0.313565 |        0.658019 |           3 |
+| Sem      | ses-11    |       72 |        0.185478 |        0.586945 |           3 |
+| SemLocal | ses-11+   |       48 |        0.208521 |        0.601744 |           3 |
+| SemLocal | ses-11    |       48 |        0.216461 |        0.607091 |           3 |
+
+Model grid: **15 families**, 2096 alignment rows across 8 cells.
+
+| | |
+|---|---|
+| mean noise ceiling | 0.346 |
+| best alignment anywhere | 0.0653 |
+| as a fraction of ceiling | 28.2% |
+| families equivalent to zero (TOST ±0.05) | 15/15 |
+| Pythia scale trend | ρ = -0.129, p = 0.43 |
+
+### Per family
+
+| family                |   n_checkpoints |   rsa_mean |   rsa_sd |   rsa_abs_max |   frac_of_ceiling_abs_max |   p_equivalence_tost |
+|:----------------------|----------------:|-----------:|---------:|--------------:|--------------------------:|---------------------:|
+| pico-decoder-tiny     |              21 |     0.0055 |   0.0039 |        0.0434 |                    0.2038 |               0      |
+| beetle-humanscale-eng |              18 |     0.0008 |   0.0052 |        0.0398 |                    0.1841 |               0      |
+| pico-decoder-large    |              21 |    -0.0013 |   0.0084 |        0.0521 |                    0.2498 |               0      |
+| pico-decoder-small    |              21 |    -0.0028 |   0.0115 |        0.0523 |                    0.2822 |               0      |
+| pythia-70m-full       |              21 |    -0.0036 |   0.0067 |        0.0519 |                    0.2396 |               0      |
+| pico-decoder-medium   |              21 |    -0.0039 |   0.0073 |        0.0351 |                    0.1587 |               0      |
+| pythia-410m-full      |              21 |    -0.0049 |   0.0086 |        0.038  |                    0.1899 |               0      |
+| pythia-1b-full        |              21 |    -0.007  |   0.0106 |        0.0482 |                    0.2179 |               0      |
+| beetle-fineweb3-eng   |              19 |    -0.0074 |   0.0051 |        0.0569 |                    0.2628 |               0      |
+| pythia-1.4b-full      |              21 |    -0.0102 |   0.0073 |        0.0482 |                    0.1831 |               0      |
+| babylm-gpt2           |               9 |    -0.0122 |   0.0124 |        0.042  |                    0.2016 |               0      |
+| pythia-160m-full      |              21 |    -0.0141 |   0.0077 |        0.0568 |                    0.241  |               0      |
+| babylm-gpt2-5         |               9 |    -0.0308 |   0.02   |        0.0644 |                    0.1395 |               0.015  |
+| babylm-gpt2-7         |               9 |    -0.0309 |   0.0201 |        0.0623 |                    0.1217 |               0.0156 |
+| babylm-gpt2-3         |               9 |    -0.0311 |   0.0205 |        0.0653 |                    0.1318 |               0.0176 |
+
+## Dataset-specific notes
+
+Contains **LocalSem**, the only genuinely run/stimulus-CROSSED language cell across all four datasets in this project: its stimuli recur across runs, so run identity and stimulus identity are separable and the scanner-run confound that invalidated the first ds003604 analysis cannot arise. Per-subject age is NOT recoverable from the release — participants.tsv has birthdate but no scan date and there are no *_scans.tsv files — so this dataset is cohort-level only and cannot carry the developmental axis as published.
+
+## Files
+
+| path | what | present here |
+|---|---|---|
+| `alignment_by_checkpoint.csv` | every model × checkpoint × cell, with ceiling | ✓ |
+| `alignment_by_family.csv` | per family, with equivalence tests | ✓ |
+| `alignment_by_cell.csv` | per task × session | ✓ |
+| `ceilings_ds006239.csv` | noise ceiling per cell | ✓ |
+| `control/` | the positive control and RDM dimensionality — the gate | ✓ |
+| `scale_ladder.csv` | the Pythia 70M→1.4B scale test | ✓ |
+| `fig_*.pdf, fig_*.png` | figures | ✓ |
+
+## Method
+
+Representational similarity analysis. For each cell, a brain RDM over
+stimuli (correlation distance between per-stimulus GLM beta patterns,
+within-run z-scored, aggregated across subjects) is compared by Spearman
+correlation with a model RDM over the same stimuli, taken from each
+checkpoint's hidden states. Alignment is reported raw and as a fraction of
+the inter-subject noise ceiling, and judged against a null built from the
+PARC suite — 18 models differing only by random seed, which is what 'no
+effect' looks like on this measurement.
+
+Null and fixation trials are excluded from the stimulus set. For paired
+designs the stimulus identity is the pair, not either word alone.

roi-auditory/alignment_by_cell.csv

@@ -0,0 +1,121 @@
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roi-auditory/alignment_by_family.csv

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roi-auditory/ceilings_ds006239.csv

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roi-auditory/control/control_by_cell.csv

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+corrected,Phon,ses-11,word_frequency,96,0.39570130848710416,-0.020424673035248544,True,-0.008082069845469123,0.6520695860827834,-1.0791568103904492e-05,0.017906756409571574,-0.45073926803405867,stimulus,1.0,False
+corrected,Phon,ses-11,condition,96,0.39570130848710416,0.018793289014105458,True,0.007436529053657849,0.5810837832433513,0.00019878910424256943,0.01466440021218976,0.49355853933291866,stimulus,1.0,False
+corrected,Phon,ses-11,text_edit_distance,96,0.39570130848710416,0.022888071450622723,True,0.009056839821757744,0.5508898220355929,-1.0477526104357194e-05,0.015449269073965712,0.5869091478609143,stimulus,1.0,False
+corrected,Phon,ses-11,visual_pixels,96,0.39570130848710416,0.00271721397394472,True,0.0010752051249293699,0.9496100779844031,-0.0004458959791323024,0.01694541279938623,0.08976477126759652,stimulus,1.0,False
+corrected,Phon,ses-11,visual_luminance,96,0.39570130848710416,-0.04851449398594232,True,-0.019197248750827123,0.23255348930213957,-0.0002221176019292801,0.016593714284517353,-1.1435131895370128,stimulus,1.0,False
+corrected,Phon,ses-11+,word_frequency,96,0.527508409316547,-0.011850042613785625,True,-0.006250997129531351,0.7878424315136973,4.6552402272122715e-05,0.02221227293557509,-0.28351666440375073,stimulus,1.0,False
+corrected,Phon,ses-11+,condition,96,0.527508409316547,0.017917128412786622,True,0.00945143590854938,0.48210357928414316,-1.3137112724050581e-05,0.014515363017852518,0.6520383271834721,stimulus,1.0,False
+corrected,Phon,ses-11+,text_edit_distance,96,0.527508409316547,0.03186782501019384,True,0.016810545679505424,0.28854229154169164,-6.753182690551155e-05,0.01608935784253567,1.0490212021228777,stimulus,1.0,False
+corrected,Phon,ses-11+,visual_pixels,96,0.527508409316547,-0.036065235234995996,True,-0.01902471487043982,0.3169366126774645,-0.00012087693527831869,0.019687995635946375,-0.9601707702376098,stimulus,1.0,False
+corrected,Phon,ses-11+,visual_luminance,96,0.527508409316547,-0.07311963890098433,True,-0.03857122440645855,0.04359128174365127,-6.136113657118467e-05,0.01920527005153675,-2.0051716619731024,stimulus,1.0,False
+corrected,Sem,ses-11,word_frequency,72,0.18547822688106827,0.043679023272068636,True,0.008101507788400207,0.5832833433313337,-2.6535040513190668e-05,0.01482472312737267,0.5482761977090377,stimulus,1.0,False
+corrected,Sem,ses-11,condition,72,0.18547822688106827,-0.14561342941460487,True,-0.0270081206978925,0.16556688662267546,-0.00042644527524625923,0.0198589214161331,-1.3385256361260964,stimulus,1.0,False
+corrected,Sem,ses-11,text_edit_distance,72,0.18547822688106827,-0.06190204872543163,True,-0.011481482237898551,0.5582883423315337,0.0003287471662639015,0.019328720795306176,-0.6110197114761703,stimulus,1.0,False
+corrected,Sem,ses-11,visual_pixels,72,0.18547822688106827,-0.04080594516160773,True,-0.0075686143547811086,0.634873025394921,1.1902972004205459e-05,0.016394355866284627,-0.46238579839006905,stimulus,1.0,False
+corrected,Sem,ses-11,visual_luminance,72,0.18547822688106827,0.026924806043539574,True,0.004993965284072391,0.7538492301539692,-0.00031648462535002314,0.016644935990710062,0.3190429757174952,stimulus,1.0,False
+corrected,Sem,ses-11+,word_frequency,72,0.313564737622646,0.013347094715254689,True,0.004185178252413441,0.7836432713457309,0.00011389836190510869,0.015832358454454163,0.2571492997687782,stimulus,1.0,False
+corrected,Sem,ses-11+,condition,72,0.313564737622646,-0.013806785871429557,True,-0.004329321189186865,0.8208358328334333,-1.9763730794876555e-05,0.019553709379002943,-0.2203959041551092,stimulus,1.0,False
+corrected,Sem,ses-11+,text_edit_distance,72,0.313564737622646,0.04092564422434885,True,0.012832838893245704,0.5020995800839833,-0.00025070015021561016,0.019270791238807504,0.6789310766044087,stimulus,1.0,False
+corrected,Sem,ses-11+,visual_pixels,72,0.313564737622646,-0.06491985727691992,True,-0.020356578013537015,0.236752649470106,1.6115333279860877e-05,0.017495771484939006,-1.164435267298158,stimulus,1.0,False
+corrected,Sem,ses-11+,visual_luminance,72,0.313564737622646,-0.02292061807487852,True,-0.00718709759279816,0.6876624675064987,6.910434146438899e-05,0.01773327353083105,-0.40918569948395256,stimulus,1.0,False
+corrected,SemLocal,ses-11,condition,48,0.21646061921350537,-0.04410663575191852,True,-0.009547349686284817,0.74625074985003,-9.958762575789844e-05,0.030539110074135956,-0.3093659912578464,stimulus,1.0,False
+corrected,SemLocal,ses-11,text_edit_distance,48,0.21646061921350537,0.06551202435132095,True,0.014180773357017173,0.6216756648670266,-0.00012417428387627533,0.029127296988165324,0.49111826772716183,stimulus,1.0,False
+corrected,SemLocal,ses-11,visual_pixels,48,0.21646061921350537,0.019075761424468193,True,0.004129151129909484,0.8654269146170765,-0.00016902556320815956,0.024888610203960868,0.17269653298121562,stimulus,1.0,False
+corrected,SemLocal,ses-11,visual_luminance,48,0.21646061921350537,0.003199687908117817,True,0.0006926064258811484,0.9794041191761648,-0.00014108147209439208,0.02571505739731953,0.032420223103605504,stimulus,1.0,False
+corrected,SemLocal,ses-11+,condition,48,0.20851870268800318,-0.1537100862893044,True,-0.03205142778310678,0.27954409118176365,0.0006874952288243957,0.030027962431580867,-1.0902812032430436,stimulus,1.0,False
+corrected,SemLocal,ses-11+,text_edit_distance,48,0.20851870268800318,-0.012406136571317786,True,-0.002586911503221377,0.9284143171365726,-0.00035708807077412114,0.029186139322049404,-0.0764000818253574,stimulus,1.0,False
+corrected,SemLocal,ses-11+,visual_pixels,48,0.20851870268800318,-0.04384865323138283,True,-0.009143264286424067,0.7134573085382924,5.398562332387458e-05,0.025745842881741438,-0.3572324258963477,stimulus,1.0,False
+corrected,SemLocal,ses-11+,visual_luminance,48,0.20851870268800318,-0.04954604207289996,True,-0.010331276416366324,0.6986602679464107,-0.00047866364655031735,0.027256305848638352,-0.3614801222208451,stimulus,1.0,False

roi-auditory/control/control_summary.csv

@@ -0,0 +1,6 @@
+control,n_cells,rsa_mean,rsa_max,z_max,p_min,n_significant,frac_of_ceiling_max
+condition,8,0.00039072058729985697,0.030404534594863857,2.2125289835562123,0.03219356128774245,0,0.07270505272725508
+text_edit_distance,8,0.00808499868895866,0.016810545679505424,1.0490212021228777,0.28854229154169164,0,0.06551202435132095
+word_frequency,6,-0.00272990798486455,0.008101507788400207,0.5482761977090377,0.5832833433313337,0,0.043679023272068636
+visual_luminance,8,-0.015921093576722785,0.004993965284072391,0.3190429757174952,0.04359128174365127,0,0.026924806043539574
+visual_pixels,8,-0.0086047906269817,0.004129151129909484,0.17269653298121562,0.236752649470106,0,0.019075761424468193

roi-auditory/control/dimensionality_summary.json

@@ -0,0 +1,10 @@
+{
+  "group_rdm_effective_rank_median": 53,
+  "n_stim_median": 84,
+  "pattern_effective_rank_median": null,
+  "pattern_n_voxels_median": null,
+  "frac_voxels_near_constant_median": null,
+  "pc1_vs_global_signal_median": null,
+  "rdm_vs_amplitude_rsa_median": null,
+  "verdict": null
+}

roi-auditory/control/rdm_dimensionality.csv

@@ -0,0 +1,9 @@
+task,session,n_stim,group_rdm_effective_rank,subject_rdm_rank_median,subject_rdm_rank_min,subject_rdm_rank_max,ceiling
+Orth,ses-11,96,58,51,37,55,0.39570130848710416
+Orth,ses-11+,96,59,55,43,55,0.527508409316547
+Phon,ses-11,96,58,51,37,55,0.39570130848710416
+Phon,ses-11+,96,59,55,43,55,0.527508409316547
+Sem,ses-11,72,48,41,38,44,0.18547822688106827
+Sem,ses-11+,72,49,46,40,47,0.313564737622646
+SemLocal,ses-11,48,36,34,30,34,0.21646061921350537
+SemLocal,ses-11+,48,36,35,30,35,0.20851870268800318

roi-auditory/control/summary.json

@@ -0,0 +1,20 @@
+{
+  "n_tests": 38,
+  "n_stimulus_tests_corrected": 38,
+  "n_significant_holm": 0,
+  "controls_tested": [
+    "condition",
+    "text_edit_distance",
+    "visual_luminance",
+    "visual_pixels",
+    "word_frequency"
+  ],
+  "best_control": "condition",
+  "best_rsa": 0.030404534594863857,
+  "best_z": 2.2125289835562123,
+  "best_cell": "Orth/ses-11+",
+  "best_frac_of_ceiling": 0.0576380092864429,
+  "lm_best_rsa_for_comparison": null,
+  "n_permutations": 5000,
+  "verdict": "no recoverable stimulus signal"
+}

roi-auditory/model_params.csv

@@ -0,0 +1,16 @@
+repo,params
+Beetle-FineWeb3-24B/beetle-monolingual-fineweb3-eng,193804032
+Beetle-HumanScale/beetle-monolingual-humanscale-eng,193811712
+BrainAlign/gpt2-babylm-3,134601216
+BrainAlign/gpt2-babylm-5,134601216
+BrainAlign/gpt2-babylm-7,134601216
+BrainAlign/gpt2-babylm-9,134601216
+EleutherAI/pythia-1.4b,1515311488
+EleutherAI/pythia-160m,212654688
+EleutherAI/pythia-1b,1078891008
+EleutherAI/pythia-410m,505997504
+EleutherAI/pythia-70m,95592496
+pico-lm/pico-decoder-large,569808384
+pico-lm/pico-decoder-medium,181095168
+pico-lm/pico-decoder-small,64595328
+pico-lm/pico-decoder-tiny,11282784

roi-auditory/scale_ladder.csv

@@ -0,0 +1,6 @@
+family,params,n_checkpoints,n_rows,n_cells,rsa_mean,rsa_sd,rsa_sd_all_rows,rsa_abs_max,best_rsa,best_cell,best_step,frac_of_ceiling_mean,frac_of_ceiling_abs_max,seed_null_sd,null_max_p50,null_max_p95,best_percentile_vs_null,beats_null_max,p_equivalence_tost,equivalent_to_zero,mean_in_seed_sd,scale_trend_rho,scale_trend_p,scale_trend_n
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roi-auditory/seed_null_comparison.csv

@@ -0,0 +1,16 @@
+family,rsa_mean,rsa_sd,mean_in_seed_sd,rsa_abs_max,null_max_p50,null_max_p95,best_percentile_vs_null,beats_null_max,frac_of_ceiling_abs_max,p_equivalence_tost,equivalent_to_zero
+pico-decoder-tiny,0.005515758893902021,0.003943342280334144,,0.0434304013461065,,,,False,0.20384021915095824,3.839540394622379e-09,True
+beetle-humanscale-eng,0.0008290919926303544,0.005232896971515949,,0.0398449627128697,,,,False,0.18407456075477854,1.3672334460075725e-08,True
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roi-auditory/summary.json

@@ -0,0 +1,26 @@
+{
+  "dataset": "ds003604",
+  "rdms": "within-run normalised",
+  "n_families": 15,
+  "n_rows": 2096,
+  "n_cells": 8,
+  "ceiling_lower_mean": 0.3463055146147536,
+  "best_rsa_abs": 0.0653262949612016,
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+  "seed_null_sd_median": null,
+  "null_max_p95_median": null,
+  "families_beating_null_max": 0,
+  "families_equivalent_to_zero": 15,
+  "sesoi": 0.05,
+  "scale_trend_rho": -0.12869879673753806,
+  "scale_trend_p": 0.4286805490303479,
+  "var_pct_cell": 9.087357681744379,
+  "var_pct_family": 23.226486816293846,
+  "var_pct_residual": 67.63844557829766,
+  "untrained_mean": 0.0002920819876757009,
+  "untrained_n": 88,
+  "trained_mean": -0.0078123666664514846,
+  "trained_n": 2008,
+  "untrained_vs_trained_t": 4.392251399465806,
+  "untrained_vs_trained_p": 2.8529472543679012e-05
+}

roi-auditory/training_trend.csv

@@ -0,0 +1,16 @@
+family,n_cells,trend_rho_mean,trend_rho_sd,t,p
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