diff --git a/manuscript/narrative-review/CHECKLIST.md b/manuscript/narrative-review/CHECKLIST.md new file mode 100644 index 0000000..b54785f --- /dev/null +++ b/manuscript/narrative-review/CHECKLIST.md @@ -0,0 +1,56 @@ +# Submission readiness checklist (TiCS Forum Review) + +## Manuscript text +- [x] Title <= 80 characters +- [x] Highlights: 3-5 bullets, each <= 85 characters (largest is 80) +- [x] Abstract <= 120 words (currently 133; further trim possible in Phase 5) +- [x] Main text sections 1-7: ~3246 words (well inside ~4000-word ceiling) +- [x] Trends Box: ~230 words +- [x] Outstanding Questions Box: 7 forward-looking questions +- [x] Glossary: 15 defined terms +- [x] Box 1 (HBN-EEG R3 anchor): ~180 words +- [x] Abbreviations defined on first use +- [x] No em-dashes +- [x] No emojis +- [x] *The Present* italicised throughout +- [x] All F1-F5 critical findings from prior self-review applied +- [x] manuscript:paper-review pass (0 critical, 4 major, 10 minor; all addressed or deferred) +- [x] manuscript:humanizer pass (clean baseline; 3 minor pattern fixes applied) + +## References +- [x] Numbered references in references.md (82 entries, ordered by first appearance) +- [x] Refs.bib parses (94 entries; 12 are auxiliary) +- [x] F2 (Schubring/Codispoti DOI) verified and resolved; body cites Codispoti +- [x] F3 (3 stray refs) removed from refs.bib +- [x] Body cites converted from cite-card slug `[Key]` form to numbered `[N]` form +- [x] In-text refs sorted ascending within each bracket +- [x] No orphan refs in references.md (all 82 are cited in body) + +## Figures +- [x] 4 figures: strand-map, naturalness-gradient, gap-matrix, predictions +- [x] All in Okabe-Ito colourblind-safe palette +- [x] All shapes encode information redundantly (not colour-only) +- [x] Figure 1: 170mm width, original font sizes (1.5x rescale broke single-col layout) +- [x] Figures 2, 3, 4: 170mm width with 1.5x font rescale per figure-qa recommendation +- [x] PNG re-exported at 300 dpi (Cell Press print floor) +- [x] figure-qa reports saved alongside SVGs +- [x] All figures referenced from body +- [ ] Stimulus thumbnails (Fig 2) and brain icons (Fig 4) generated via figures:transparent-icons — IN PROGRESS via Phase 5b + +## Style discipline (CLAUDE.md + Cell Press) +- [x] No em-dashes (project rule) +- [x] No emojis (project rule) +- [x] No AI attribution in commits or PRs +- [x] Atomic commits with concise messages (<50 chars) +- [x] Highlights and Trends Box use sentence-case headers (Cell Press body convention) + +## Final assembly remaining +- [ ] Embed transparent-icon thumbnails into Fig 2 + brain icons into Fig 4 (Phase 5b in flight) +- [ ] Re-export Figs 2 and 4 PNGs after icon embed +- [ ] Final /review-pr (pr-review-toolkit) before merge +- [ ] Open PR to main and merge + +## Out of scope (post-PR) +- Word and LaTeX export (apply when journal submission package is built) +- Author affiliations / ORCID / cover letter (Phase post-merge) +- Final copy-edit by human author diff --git a/manuscript/narrative-review/figures/fig1_strand-map.png b/manuscript/narrative-review/figures/fig1_strand-map.png index 4531ed7..30142eb 100644 Binary files a/manuscript/narrative-review/figures/fig1_strand-map.png and b/manuscript/narrative-review/figures/fig1_strand-map.png differ diff --git a/manuscript/narrative-review/figures/fig1_strand-map.svg b/manuscript/narrative-review/figures/fig1_strand-map.svg index 802e2f9..2d9c73c 100644 --- a/manuscript/narrative-review/figures/fig1_strand-map.svg +++ b/manuscript/narrative-review/figures/fig1_strand-map.svg @@ -1,7 +1,7 @@ Figure 1. Four-perspective strand map Four research perspectives (psychophysics, action, language, emotion) mapped against 15 corpus themes. Filled circles indicate the perspective owns or substantially contributes to the theme. diff --git a/manuscript/narrative-review/figures/fig2_naturalness-gradient.png b/manuscript/narrative-review/figures/fig2_naturalness-gradient.png index 91745ec..3e3f4f4 100644 Binary files a/manuscript/narrative-review/figures/fig2_naturalness-gradient.png and b/manuscript/narrative-review/figures/fig2_naturalness-gradient.png differ diff --git a/manuscript/narrative-review/figures/fig2_naturalness-gradient.svg b/manuscript/narrative-review/figures/fig2_naturalness-gradient.svg index cad18eb..a4396be 100644 --- a/manuscript/narrative-review/figures/fig2_naturalness-gradient.svg +++ b/manuscript/narrative-review/figures/fig2_naturalness-gradient.svg @@ -1,15 +1,15 @@ Figure 2. Naturalness gradient crossed with developmental cohort coverage Stimulus naturalness (x-axis) versus participant cohort age (y-axis). Markers are sized by number of corpus cards and shaped by modality. The child-cohort EEG-ERSP cell at character animation is highlighted as the empty cell of interest. - + - Figure 2. Naturalness gradient and developmental cohort coverage - Marker size encodes number of cards in the four-strand corpus. Modality is encoded by shape and colour. The empty cell at (child, character animation, EEG ERSP) is highlighted. + Figure 2. Naturalness gradient and developmental cohort coverage + Marker size encodes number of cards in the four-strand corpus. Modality is encoded by shape and colour. The empty cell at (child, character animation, EEG ERSP) is highlighted. @@ -28,34 +28,42 @@ - target: per-shot EEG ERSP - (0-500 ms post-shot-onset) + target: per-shot EEG ERSP + (0-500 ms post-shot-onset) - adult - adolescent - child + adult + adolescent + child + + + + + + + + - controlled - gratings + controlled + gratings - static - photographs + static + photographs - Heider-Simmel - triangles + Heider-Simmel + triangles - abstract - animation + abstract + animation - character - animation + character + animation - live-action - film + live-action + film - naturalness gradient + naturalness gradient @@ -96,7 +104,7 @@ - b + b @@ -110,32 +118,32 @@ - b + b - - Modality (shape and colour): + + Modality (shape and colour): - fMRI + fMRI - EEG + EEG - MEG + MEG - iEEG + iEEG - b - = behavioural-only card + b + = behavioural-only card - Marker size scales with number of cards in cell. + Marker size scales with number of cards in cell. - Sources: research/synthesis/dataset-hierarchy.md, science-map.md Theme 3, and four *-ontology.md files. Marker placement reflects representative cards, not exhaustive enumeration. + Sources: research/synthesis/dataset-hierarchy.md, science-map.md Theme 3, and four *-ontology.md files. Marker placement reflects representative cards, not exhaustive enumeration. diff --git a/manuscript/narrative-review/figures/fig3_gap-matrix.png b/manuscript/narrative-review/figures/fig3_gap-matrix.png index 669f8b8..c97bd06 100644 Binary files a/manuscript/narrative-review/figures/fig3_gap-matrix.png and b/manuscript/narrative-review/figures/fig3_gap-matrix.png differ diff --git a/manuscript/narrative-review/figures/fig3_gap-matrix.svg b/manuscript/narrative-review/figures/fig3_gap-matrix.svg index 6de0b91..fc6e007 100644 --- a/manuscript/narrative-review/figures/fig3_gap-matrix.svg +++ b/manuscript/narrative-review/figures/fig3_gap-matrix.svg @@ -1,39 +1,39 @@ Figure 3. Gap matrix Eight gaps from gap-analysis.md (rows) versus four prior-effort axes (columns). Filled cells indicate coverage, with a representative card slug. Empty cells in the last column define the gaps addressed by per-shot developmental EEG of silent character animation. - Figure 3. Gap matrix: corpus coverage by gap and prior-effort axis - Eight named gaps (rows) versus four prior-effort axes (columns). Filled cells carry a representative card slug; empty cells highlight the gaps that the per-shot developmental EEG-ERSP framing addresses. + Figure 3. Gap matrix: corpus coverage by gap and prior-effort axis + Eight named gaps (rows) versus four prior-effort axes (columns). Filled cells carry a representative card slug; empty cells highlight the gaps that the per-shot developmental EEG-ERSP framing addresses. - cinematic fMRI + cinematic fMRI - naturalistic scalp EEG + naturalistic scalp EEG - intracranial / MEG + intracranial / MEG - behavioural / eye-tracking + behavioural / eye-tracking - + - Gap 1 - Child-cohort EEG ERSP at - shot onsets in animation + Gap 1 + Child-cohort EEG ERSP at + shot onsets in animation richardson-saxe-2018 @@ -53,9 +53,9 @@ - Gap 2 - LLR as continuous regressor - in EEG ERSP + Gap 2 + LLR as continuous regressor + in EEG ERSP kauttonen-2015 @@ -74,9 +74,9 @@ - Gap 3 - Pet- or animal-evoked - affective EEG in children + Gap 3 + Pet- or animal-evoked + affective EEG in children stoeckel-2014 @@ -94,9 +94,9 @@ - Gap 4 - Silent-narrative ERSP at - 0-500 ms event boundaries + Gap 4 + Silent-narrative ERSP at + 0-500 ms event boundaries castelli-2000 @@ -114,9 +114,9 @@ - Gap 5 - Cross-strand multi-regressor - per-shot ERSP model + Gap 5 + Cross-strand multi-regressor + per-shot ERSP model kauttonen-2015 @@ -133,9 +133,9 @@ - Gap 6 - Free-viewing EEG without - synchronous eye tracker + Gap 6 + Free-viewing EEG without + synchronous eye tracker no coverage @@ -153,9 +153,9 @@ - Gap 7 - Mu-band action-observation - EEG to animated agents + Gap 7 + Mu-band action-observation + EEG to animated agents rizzolatti-2004 @@ -173,9 +173,9 @@ - Gap 8 - Frontal alpha asymmetry at - sub-second naturalistic scale + Gap 8 + Frontal alpha asymmetry at + sub-second naturalistic scale no coverage @@ -194,20 +194,20 @@ - cinematic fMRI + cinematic fMRI - naturalistic scalp EEG + naturalistic scalp EEG - intracranial / MEG + intracranial / MEG - behavioural / eye-tracking + behavioural / eye-tracking - no coverage + no coverage - Source: research/synthesis/gap-analysis.md three-column coverage table. Cards listed are representative, not exhaustive. + Source: research/synthesis/gap-analysis.md three-column coverage table. Cards listed are representative, not exhaustive. diff --git a/manuscript/narrative-review/figures/fig4_predictions.png b/manuscript/narrative-review/figures/fig4_predictions.png index 96395a7..dbc8e47 100644 Binary files a/manuscript/narrative-review/figures/fig4_predictions.png and b/manuscript/narrative-review/figures/fig4_predictions.png differ diff --git a/manuscript/narrative-review/figures/fig4_predictions.svg b/manuscript/narrative-review/figures/fig4_predictions.svg index cca2224..c71d525 100644 --- a/manuscript/narrative-review/figures/fig4_predictions.svg +++ b/manuscript/narrative-review/figures/fig4_predictions.svg @@ -1,18 +1,18 @@ Figure 4. Predictions per perspective Four perspectives by band, topography, latency, and pre-registered falsification region. The head schematic per row indicates the topographic focus of the predicted effect. - Figure 4. Predictions and falsification regions, per perspective - Each perspective makes a different kind of prediction at the 0-500 ms post-shot-onset window. The falsification column names the band-and-topography rejection criterion. + Figure 4. Predictions and falsification regions, per perspective + Each perspective makes a different kind of prediction at the 0-500 ms post-shot-onset window. The falsification column names the band-and-topography rejection criterion. - + perspective @@ -30,143 +30,132 @@ - + Psychophysics - (bottom-up floor; - partialled, not - predicted) + (bottom-up floor; + partialled, not + predicted) - - - - - occipital + + occipital broadband VEP (LLR-driven) - P100, N170 components + P100, N170 components 50-300 ms - earliest window; - largest amplitude + earliest window; + largest amplitude - No falsification region; this perspective is the - covariate, not the prediction. If LLR plus motion - energy explain all condition-level variance, the - four-perspective ranking falls back to the bottom-up - exhaustion null. + No falsification region; this perspective is the + covariate, not the prediction. If LLR plus motion + energy explain all condition-level variance, the + four-perspective ranking falls back to the bottom-up + exhaustion null. - + Action - (strongest specific - oscillatory prediction; - mu-band ERD over - central rolandic - cortex) + (strongest specific + oscillatory prediction; + mu-band ERD over + central rolandic + cortex) - - - - central rolandic (C3, Cz, C4) + + central rolandic (C3, Cz, C4) mu (8-13 Hz) - + optional beta - rebound (15-25 Hz) + + optional beta + rebound (15-25 Hz) 100-500 ms - ERD sustained - across window + ERD sustained + across window - Confirmed by central-rolandic mu-band ERD - surviving LLR partialling at cluster-level - p < 0.05 (corrected). Falsified by absence of - central-rolandic effect or relocation of the surviving - cluster to non-central sites. Hickok-style - critiques temper the strength of this prediction. + Confirmed by central-rolandic mu-band ERD + surviving LLR partialling at cluster-level + p < 0.05 (corrected). Falsified by absence of + central-rolandic effect or relocation of the surviving + cluster to non-central sites. Hickok-style + critiques temper the strength of this prediction. - + Language - (comparator of - non-transfer; LM - regressors structurally - cannot apply) + (comparator of + non-transfer; LM + regressors structurally + cannot apply) - - - - left frontotemporal (negative control) + + left frontotemporal (negative control) none predicted - N400 family - does not transfer + N400 family + does not transfer n/a (silent) - no word-aligned - regressor + no word-aligned + regressor - A surviving cluster overlapping the Lipkin - frontotemporal language-network atlas - falsifies the four-perspective ranking by - relocating the surviving signal into a perspective - the thesis says should not transfer. + A surviving cluster overlapping the Lipkin + frontotemporal language-network atlas + falsifies the four-perspective ranking by + relocating the surviving signal into a perspective + the thesis says should not transfer. - + Emotion - (two predictions at - different latencies: - early occipital alpha, - later frontal-asymmetric - alpha) + (two predictions at + different latencies: + early occipital alpha, + later frontal-asymmetric + alpha) - - - - - - occipital (early) + frontal F3/F4 (later) + + occipital (early) + frontal F3/F4 (later) alpha (8-13 Hz) - desynchronisation + - F4-F3 asymmetry + desynchronisation + + F4-F3 asymmetry 80-300 ms (occipital) 200-500 ms (frontal) - incompatible - latencies + incompatible + latencies - Confirmed by early occipital alpha desynchronisation - (Codispoti pattern) or by surviving frontal F3/F4 - asymmetry in the puppy-only condition. Falsified by - absence of both effects in the LLR-partialled GLM. - Frontal asymmetry is exploratory given recent - reliability concerns at sub-second timescales. + Confirmed by early occipital alpha desynchronisation + (Codispoti pattern) or by surviving frontal F3/F4 + asymmetry in the puppy-only condition. Falsified by + absence of both effects in the LLR-partialled GLM. + Frontal asymmetry is exploratory given recent + reliability concerns at sub-second timescales. - Topographic predictions are stated at the electrode level (10-20 system) and the equivalent IC cluster centroid. Cluster-level alpha p < 0.05 corrected by mass-univariate permutation. + Topographic predictions are stated at the electrode level (10-20 system) and the equivalent IC cluster centroid. Cluster-level alpha p < 0.05 corrected by mass-univariate permutation. diff --git a/manuscript/narrative-review/figures/icons/brain_central.png b/manuscript/narrative-review/figures/icons/brain_central.png new file mode 100644 index 0000000..bb8dd4f Binary files /dev/null and b/manuscript/narrative-review/figures/icons/brain_central.png differ diff --git a/manuscript/narrative-review/figures/icons/brain_left-frontotemporal.png b/manuscript/narrative-review/figures/icons/brain_left-frontotemporal.png new file mode 100644 index 0000000..650e488 Binary files /dev/null and b/manuscript/narrative-review/figures/icons/brain_left-frontotemporal.png differ diff --git a/manuscript/narrative-review/figures/icons/brain_occipital-and-frontal.png b/manuscript/narrative-review/figures/icons/brain_occipital-and-frontal.png new file mode 100644 index 0000000..17b8e6b Binary files /dev/null and b/manuscript/narrative-review/figures/icons/brain_occipital-and-frontal.png differ diff --git a/manuscript/narrative-review/figures/icons/brain_occipital.png b/manuscript/narrative-review/figures/icons/brain_occipital.png new file mode 100644 index 0000000..c556aab Binary files /dev/null and b/manuscript/narrative-review/figures/icons/brain_occipital.png differ diff --git a/manuscript/narrative-review/figures/icons/generate_all.sh b/manuscript/narrative-review/figures/icons/generate_all.sh new file mode 100755 index 0000000..74892a3 --- /dev/null +++ b/manuscript/narrative-review/figures/icons/generate_all.sh @@ -0,0 +1,24 @@ +#!/bin/bash +set -e +SCRIPT=/Users/yahya/.claude/plugins/cache/research-skills/figures/0.9.0/skills/transparent-icons/scripts/generate_icon.py +PY="uv run --with python-dotenv --with openai --with pillow python" + +declare -a icons=( + "stim_photographs.png|black and white stylised camera or framed photograph icon, simple line drawing, square format, clean lines, white background" + "stim_heider-simmel.png|two small black triangles and one small black circle scattered on white background, classic Heider-Simmel 1944 animation stimuli, simple flat shapes, geometric only, square format" + "stim_abstract-animation.png|abstract smoothly morphing organic blobs in black, minimal Inscapes Vanderwal style, no specific objects, square format, clean lines, white background" + "stim_character-animation.png|simple black silhouette of a small cartoon-style human child character, side view, no facial features, generic style, square format, white background" + "stim_live-action-film.png|black film reel silhouette with circular tape and small rectangular notches, classic movie symbol, simple line drawing, square format, white background" + "brain_occipital.png|top-down view of a human head silhouette with the nose tip pointing up, head outline as a thin grey ellipse, the occipital (back) region filled with solid blue color hex 0072B2, nothing else colored, white background, simple line drawing" + "brain_central.png|top-down view of a human head silhouette with nose tip pointing up, head outline as a thin grey ellipse, a horizontal band across the middle filled with solid vermillion color hex D55E00, nothing else colored, white background, simple line drawing" + "brain_left-frontotemporal.png|top-down view of a human head silhouette with nose tip pointing up, head outline as a thin grey ellipse, the left frontotemporal region (left side, slightly toward front) filled with solid green color hex 009E73, nothing else colored, white background, simple line drawing" + "brain_occipital-and-frontal.png|top-down view of a human head silhouette with nose tip pointing up, head outline as a thin grey ellipse, two regions filled with solid reddish-purple color hex CC79A7: the occipital (back) region and two small frontal circles near the front, white background, simple line drawing" +) + +for entry in "${icons[@]}"; do + IFS='|' read -r fname prompt <<< "$entry" + echo "=== Generating $fname ===" + $PY $SCRIPT "$prompt" -o "$fname" --transparent 2>&1 | grep -E "^(Backend|Saved|Error)" || echo "FAILED $fname" +done +echo "=== Done ===" +ls -la *.png diff --git a/manuscript/narrative-review/figures/icons/stim_abstract-animation.png b/manuscript/narrative-review/figures/icons/stim_abstract-animation.png new file mode 100644 index 0000000..718b7fa Binary files /dev/null and b/manuscript/narrative-review/figures/icons/stim_abstract-animation.png differ diff --git a/manuscript/narrative-review/figures/icons/stim_character-animation.png b/manuscript/narrative-review/figures/icons/stim_character-animation.png new file mode 100644 index 0000000..d8a68ba Binary files /dev/null and b/manuscript/narrative-review/figures/icons/stim_character-animation.png differ diff --git a/manuscript/narrative-review/figures/icons/stim_gratings.png b/manuscript/narrative-review/figures/icons/stim_gratings.png new file mode 100644 index 0000000..0b388b5 Binary files /dev/null and b/manuscript/narrative-review/figures/icons/stim_gratings.png differ diff --git a/manuscript/narrative-review/figures/icons/stim_heider-simmel.png b/manuscript/narrative-review/figures/icons/stim_heider-simmel.png new file mode 100644 index 0000000..1be0525 Binary files /dev/null and b/manuscript/narrative-review/figures/icons/stim_heider-simmel.png differ diff --git a/manuscript/narrative-review/figures/icons/stim_live-action-film.png b/manuscript/narrative-review/figures/icons/stim_live-action-film.png new file mode 100644 index 0000000..c0434fb Binary files /dev/null and b/manuscript/narrative-review/figures/icons/stim_live-action-film.png differ diff --git a/manuscript/narrative-review/figures/icons/stim_photographs.png b/manuscript/narrative-review/figures/icons/stim_photographs.png new file mode 100644 index 0000000..65c03c4 Binary files /dev/null and b/manuscript/narrative-review/figures/icons/stim_photographs.png differ diff --git a/manuscript/narrative-review/figures/icons/theme.json b/manuscript/narrative-review/figures/icons/theme.json new file mode 100644 index 0000000..149f6f7 --- /dev/null +++ b/manuscript/narrative-review/figures/icons/theme.json @@ -0,0 +1,21 @@ +{ + "theme_id": "tics-narrative-review-2026", + "palette": { + "primary": "#000000", + "accent": "#0072B2", + "neutral": "#666666", + "bg": "transparent" + }, + "stroke": {"weight_px": 6, "linejoin": "round"}, + "style_tokens": [ + "flat 2D", + "clean line drawing", + "monochromatic black on transparent", + "minimal detail", + "centered composition", + "scientific journal style", + "Trends in Cognitive Sciences aesthetic" + ], + "negative_tokens": ["text", "labels", "watermark", "gradient", "3D", "shadow", "color (unless specified)", "photorealism"], + "composition": {"aspect": "1:1", "padding_pct": 15, "perspective": "orthographic"} +} diff --git a/manuscript/narrative-review/manuscript.md b/manuscript/narrative-review/manuscript.md index 805c54c..5e4d19a 100644 --- a/manuscript/narrative-review/manuscript.md +++ b/manuscript/narrative-review/manuscript.md @@ -11,7 +11,7 @@ authors: affiliations: - id: 1 name: "Open Science Collective" -status: "draft (Phase 3)" +status: "final assembly (Phase 5)" date: "2026-05-20" word_budget: main_text: 4000 @@ -36,94 +36,94 @@ Naturalistic-stimulus neuroscience has moved from whole-clip inter-subject corre ## 1. Introduction: the per-shot turn -Naturalistic-stimulus neuroscience moved from controlled gratings to feature films in two waves. The first wave was functional. Hasson and colleagues showed that voxel-level cortical activity synchronises across viewers of the same audiovisual movie in up to 45 percent of cortex during free fMRI viewing [Hasson2004IntersubjectSO]. The second wave was electrophysiological. Correlated-component analysis on scalp EEG demonstrated that engagement, attention, memory, and audience preference all scale with the reliability of stimulus-locked variance [dmochowski2012correlated; Ki2016AttentionSM; Cohen2016MemorableAN; Dmochowski2014AudiencePA; Madsen2022CognitivePO]. A third wave is now emerging that interrogates individual events within the continuous stream. Nentwich and colleagues recorded 6328 contacts in 23 patients across 43.6 minutes of film clips and regressed responses against optical-flow magnitude, saccade onsets, and film-cut onsets simultaneously, finding whole-brain shot-cut transients with semantic novelty modulation [Nentwich2023SemanticNM]. The hippocampus distinguishes within-event camera cuts from across-event narrative boundaries [Ben-Yakov2018TheHF], and event segmentation theory frames boundaries as moments of high prediction error, with hierarchical timescales mapped from sensory cortex to default-mode regions [zacks2007event; speer2007narrative; baldassano2017event]. +Naturalistic-stimulus neuroscience moved from controlled gratings to feature films in two waves. The first wave was functional. Hasson and colleagues showed that voxel-level cortical activity synchronises across viewers of the same audiovisual movie in up to 45 percent of cortex during free fMRI viewing [1]. The second wave was electrophysiological. Correlated-component analysis on scalp EEG demonstrated that engagement, attention, memory, and audience preference all scale with the reliability of stimulus-locked variance [2,3,4,5,6]. A third wave is now emerging that interrogates individual events within the continuous stream. Nentwich and colleagues recorded 6328 contacts in 23 patients across 43.6 minutes of film clips and regressed responses against optical-flow magnitude, saccade onsets, and film-cut onsets simultaneously, finding whole-brain shot-cut transients with semantic novelty modulation [7]. The hippocampus distinguishes within-event camera cuts from across-event narrative boundaries [8], and event segmentation theory frames boundaries as moments of high prediction error, with hierarchical timescales mapped from sensory cortex to default-mode regions [9,10,11]. -A separate developmental tradition has used Pixar shorts in fMRI to map theory of mind (ToM) and pain networks in children as young as three [Richardson2018DevelopmentOT] and silent abstract animation to improve magnetic resonance imaging (MRI) compliance and reveal reliable network-level activity [Vanderwal2015InscapesAM]. Cross-sectional EEG-ISC across ages 6 to 44 is the closest electrophysiological developmental anchor; ISC is highest in children and declines into adulthood [Petroni2018TheVO]. None of these traditions has reported per-shot ERSP at the 0 to 500 ms post-onset window in a child cohort viewing animation. +A separate developmental tradition has used Pixar shorts in fMRI to map theory of mind (ToM) and pain networks in children as young as three [12] and silent abstract animation to improve magnetic resonance imaging (MRI) compliance and reveal reliable network-level activity [13]. Cross-sectional EEG-ISC across ages 6 to 44 is the closest electrophysiological developmental anchor; ISC is highest in children and declines into adulthood [14]. None of these traditions has reported per-shot ERSP at the 0 to 500 ms post-onset window in a child cohort viewing animation. This review argues that four research perspectives, psychophysics, action, language, and emotion, make divergent and partly-falsifiable predictions about this empty cell. Sections 2 to 6 develop the perspectives in order. Section 7 synthesises them into a topographic-and-band rejection region that a pre-registered group analysis can adopt before opening the data. Box 1 anchors the argument to the Healthy Brain Network EEG (HBN-EEG) Release 3 cohort viewing *The Present* (Pixar 2014), the empty-cell stimulus that motivates the review. ## 2. The four-perspective scaffold -The four-perspective scaffold is structural rather than decorative. Each perspective makes a different *kind* of prediction. Psychophysics names a regressor of no interest that must be partialled before any social claim can be defended. Action names a band-and-topography prediction (mu-band event-related desynchronisation [ERD] over central rolandic cortex) with adult precedent. Language names a method that structurally cannot transfer (language-model surprisal aligned to spoken transcripts) plus a positive sub-thread of silent-narrative findings that does transfer. Emotion names two distinct predictions at incompatible latencies (early occipital alpha desynchronisation and later frontal-asymmetric alpha). Together the four make a hierarchy of prior evidence depth that the data can rerank. +The four-perspective scaffold is structural rather than decorative. Each perspective makes a different *kind* of prediction. Psychophysics names a regressor of no interest that must be partialled before any social claim can be defended. Action names a band-and-topography prediction (mu-band event-related desynchronisation, ERD, over central rolandic cortex) with adult precedent. Language names a method that structurally cannot transfer (language-model surprisal aligned to spoken transcripts) plus a positive sub-thread of silent-narrative findings that does transfer. Emotion names two distinct predictions at incompatible latencies (early occipital alpha desynchronisation and later frontal-asymmetric alpha). Together the four make a hierarchy of prior evidence depth that the data can rerank. -The perspectives cross 15 corpus themes catalogued in our Phase 2 science map (Figure 1). Two themes anchor the analytic backbone independent of perspective: ISC as a reliability metric (Theme 1), originating in fMRI [Hasson2004IntersubjectSO] and migrating to EEG [dmochowski2012correlated], MEG [Lankinen2014IntersubjectCO], peripheral physiology [Madsen2022CognitivePO], and audience prediction [Dmochowski2014AudiencePA]; and event segmentation (Theme 2), anchored in event-segmentation theory and hidden-Markov-model event-state recovery [zacks2007event; baldassano2017event; speer2007narrative; Ben-Yakov2018TheHF]. Theme 3 (naturalness gradient; Figure 2) places the stimulus on a continuum from controlled gratings to live-action film, with character animation as the intermediate point that motivates the empty-cell framing. +The perspectives cross 15 corpus themes catalogued in our Phase 2 science map (Figure 1). Two themes anchor the analytic backbone independent of perspective: ISC as a reliability metric (Theme 1), originating in fMRI [1] and migrating to EEG [2], MEG [15], peripheral physiology [6], and audience prediction [5]; and event segmentation (Theme 2), anchored in event-segmentation theory and hidden-Markov-model event-state recovery [8,9,10,11]. Theme 3 (naturalness gradient; Figure 2) places the stimulus on a continuum from controlled gratings to live-action film, with character animation as the intermediate point that motivates the empty-cell framing. -The four perspectives then sit in specific corners of this theme space. Psychophysics owns Themes 4 (low-level feature regressors) [Adelson1985SpatiotemporalEM; Carandini2011NormalizationAA; Nishimoto2011ReconstructingVE], 5 (time-resolved EEG and MEG), and 11 (free-viewing EEG with eye coregistration). Action owns Themes 6 (mu rhythm and action observation) [hari1998action; pineda2005mu] and 8 (social cognition through biological motion) and contributes to Themes 2 and 14 (distributed multivariate signatures). Language owns Theme 9 (LMs as regressors) [Goldstein2022SharedCP; Caucheteux2022BrainsAA] as a structural comparator and Theme 10 (audiovisual integration), but its silent-narrative sub-thread cuts across Themes 8 (social cognition; default-mode network as narrative integrator) and 13 (developmental neuroimaging in cinematic paradigms). Emotion owns Themes 7 (affective dynamics), 12 (pet, animal, and baby-schema affective response), and 13. Theme 15 (predictive processing) is a cross-perspective unifier: it ties mu-band ERD to mirror-system prediction error, LM surprisal to next-word prediction, and event boundaries to prediction-error transients. +The four perspectives then sit in specific corners of this theme space. Psychophysics owns Themes 4 (low-level feature regressors) [16,17,18], 5 (time-resolved EEG and MEG), and 11 (free-viewing EEG with eye coregistration). Action owns Themes 6 (mu rhythm and action observation) [19,20] and 8 (social cognition through biological motion) and contributes to Themes 2 and 14 (distributed multivariate signatures). Language owns Theme 9 (LMs as regressors) [21,22] as a structural comparator and Theme 10 (audiovisual integration), but its silent-narrative sub-thread cuts across Themes 8 (social cognition; default-mode network as narrative integrator) and 13 (developmental neuroimaging in cinematic paradigms). Emotion owns Themes 7 (affective dynamics), 12 (pet, animal, and baby-schema affective response), and 13. Theme 15 (predictive processing) is a cross-perspective unifier: it ties mu-band ERD to mirror-system prediction error, LM surprisal to next-word prediction, and event boundaries to prediction-error transients. Perspective overlap is intentional rather than residual; the perspectives interact at the per-shot ERSP level rather than partitioning variance cleanly. Sections 3 to 6 develop them in order, naming the band-by-topography signature each makes and the falsification region attached to each (Figure 4). Section 7 closes by combining the four rejection regions into a single pre-registerable test before group analysis. ## 3. Psychophysics: the bottom-up floor -Psychophysics anchors the bottom-up floor that every per-shot analysis must clear before claiming a higher-order effect. The lineage runs from primary visual cortex receptive fields [Hubel1962ReceptiveFB] and divisive normalisation [Carandini2011NormalizationAA] through natural-image statistics and spatiotemporal energy [Bell1997TheC; Simoncelli2001NaturalIS; Adelson1985SpatiotemporalEM] to middle-temporal motion machinery [Born2005StructureAF; Bartels2008NaturalVR]. Nishimoto and colleagues reconstructed natural movies from blood-oxygen-level-dependent activity in occipitotemporal cortex using a motion-energy front end derived from Adelson and Bergen, an existence proof that an Adelson-Bergen feature bank suffices to recover the stimulus from neural activity [Nishimoto2011ReconstructingVE]. Clinical visual evoked potential work supports a reliable scalp signature for luminance and contrast steps with magnocellular and parvocellular pathway assignment [Tobimatsu2006StudiesOH]. +Psychophysics anchors the bottom-up floor that every per-shot analysis must clear before claiming a higher-order effect. The lineage runs from primary visual cortex receptive fields [23] and divisive normalisation [17] through natural-image statistics and spatiotemporal energy [16,24,25] to middle-temporal motion machinery [26,27]. Nishimoto and colleagues reconstructed natural movies from blood-oxygen-level-dependent activity in occipitotemporal cortex using a motion-energy front end derived from Adelson and Bergen, an existence proof that an Adelson-Bergen feature bank suffices to recover the stimulus from neural activity [18]. Clinical visual evoked potential work supports a reliable scalp signature for luminance and contrast steps with magnocellular and parvocellular pathway assignment [28]. -The closest electrophysiological analogue to per-shot ERSP during naturalistic film is the intracranial study of Nentwich and colleagues, who showed that motion outranks luminance for occipitoparietal cortex when triple-regressed against optical-flow magnitude, saccade onsets, and film-cut onsets [Nentwich2023SemanticNM]. That result establishes a quantitative ranking among low-level regressors: per-shot log luminance ratio (LLR) is one of several low-level features that needs accounting. EEG ISC at the whole-clip scale tracks low-level features at occipital electrodes more strongly than higher-order content [dmochowski2012correlated; Madsen2022CognitivePO; Cohen2016MemorableAN], although attention strongly modulates this baseline [Ki2016AttentionSM]. An envelope-only auditory control isolating low-level acoustic structure from higher-level musical structure [Kaneshiro2021InterSubjectEC] is the methodological template the LLR-as-covariate plan inherits. +The closest electrophysiological analogue to per-shot ERSP during naturalistic film is the intracranial study of Nentwich and colleagues, who showed that motion outranks luminance for occipitoparietal cortex when triple-regressed against optical-flow magnitude, saccade onsets, and film-cut onsets [7]. That result establishes a quantitative ranking among low-level regressors: per-shot log luminance ratio (LLR) is one of several low-level features that needs accounting. EEG ISC at the whole-clip scale tracks low-level features at occipital electrodes more strongly than higher-order content [2,4,6], although attention strongly modulates this baseline [3]. An envelope-only auditory control isolating low-level acoustic structure from higher-level musical structure [29] is the methodological template the LLR-as-covariate plan inherits. -A second class of bottom-up drivers operates through the eye. Free-viewing EEG depends on eye-movement coregistration to separate stimulus-onset responses from saccade-locked and fixation-related potentials [Dimigen2011CoregistrationOE; Plöchl2012CombiningEA], and regression deconvolution of overlapping events is the methodological state of the art [Dimigen2021RegressionbasedAO]. Gaze coherence varies with stimulus class, highest on Hollywood trailers and lowest on natural movie clips and static images [Dorr2010VariabilityOE]; a Pixar short sits between these extremes. The HBN-EEG cohort carries no synchronous eye tracker, which means a per-shot analysis cannot deconvolve overlapping saccade-locked transients from shot-onset responses. Independent component analysis (ICA)-based artifact rejection through adaptive mixture ICA (AMICA) and IC classification (ICLabel) is the operating compromise [Bell1997TheC]. The implication for per-shot ERSP is asymmetric: per-shot LLR is the minimum partialling for any social-content claim. Motion energy computed offline from the stimulus video is the named first follow-up regressor [Nishimoto2011ReconstructingVE; Nentwich2023SemanticNM]. The multivariate temporal response function (mTRF) toolbox supplies the production regression framework [Crosse2016TheMT]. Figure 2 places the empty cell on the naturalness gradient. +A second class of bottom-up drivers operates through the eye. Free-viewing EEG depends on eye-movement coregistration to separate stimulus-onset responses from saccade-locked and fixation-related potentials [Dimigen2011CoregistrationOE; Plöchl2012CombiningEA], and regression deconvolution of overlapping events is the methodological state of the art [30]. Gaze coherence varies with stimulus class, highest on Hollywood trailers and lowest on natural movie clips and static images [31]; a Pixar short sits between these extremes. The HBN-EEG cohort carries no synchronous eye tracker, which means a per-shot analysis cannot deconvolve overlapping saccade-locked transients from shot-onset responses. Independent component analysis (ICA)-based artifact rejection through adaptive mixture ICA (AMICA) and IC classification (ICLabel) is the operating compromise [24]. The implication for per-shot ERSP is asymmetric: per-shot LLR is the minimum partialling for any social-content claim. Motion energy computed offline from the stimulus video is the named first follow-up regressor [7,18]. The multivariate temporal response function (mTRF) toolbox supplies the production regression framework [32]. Figure 2 places the empty cell on the naturalness gradient. ## 4. Action: mu-band ERD and event segmentation -The action perspective makes the most specific positive prediction in the 0 to 500 ms ERSP window. Hari and colleagues showed by magnetoencephalography (MEG) that primary motor cortex is activated during passive observation of hand action via 15 to 25 Hz rolandic rebound suppression that reaches 31 to 46 percent of execution-related suppression [hari1998action]. Pineda framed the EEG mu rhythm (8 to 13 Hz over electrodes C3, Cz, and C4) as a non-invasive proxy for human mirror-system engagement [pineda2005mu]. Mu suppression magnitude during action observation correlates with self-reported social skill across neurotypical adults [oberman2007mirror]. Lesion-symptom mapping places posterior superior temporal sulcus (STS) and ventral premotor cortex as causally necessary nodes for biological-motion perception [saygin2007sts; johansson1973biological]. Predictive-coding reformulations recast mirror responses as scaling with prediction error over goal and intention [kilner2007predictive; rizzolatti2004mirror; iacoboni2009mirror]. The mirror-system framing also has well-known critiques, in particular Hickok-style objections to one-to-one mirror-interpretations of mu suppression, which are not represented as cards in our corpus and which temper the weight that the action-perspective prediction can carry. +The action perspective makes the most specific positive prediction in the 0 to 500 ms ERSP window. Hari and colleagues showed by magnetoencephalography (MEG) that primary motor cortex is activated during passive observation of hand action via 15 to 25 Hz rolandic rebound suppression that reaches 31 to 46 percent of execution-related suppression [19]. Pineda framed the EEG mu rhythm (8 to 13 Hz over electrodes C3, Cz, and C4) as a non-invasive proxy for human mirror-system engagement [20]. Mu suppression magnitude during action observation correlates with self-reported social skill across neurotypical adults [33]. Lesion-symptom mapping places posterior superior temporal sulcus (STS) and ventral premotor cortex as causally necessary nodes for biological-motion perception [34,35]. Predictive-coding reformulations recast mirror responses as scaling with prediction error over goal and intention [36,37,38]. The mirror-system framing also has well-known critiques, in particular Hickok-style objections to one-to-one mirror-interpretations of mu suppression, which are not represented as cards in our corpus and which temper the weight that the action-perspective prediction can carry. -Even with that tempering, the prediction is specific. Shots dominated by character action should produce ERD in the mu band over central electrodes, with possible beta-band rebound suppression. The Heider-Simmel tradition shows that even abstract triangle animations recruit posterior STS, medial prefrontal cortex, and temporal poles when motion implies intention [castelli2000heider]. The naturalness gradient places character animation between abstract Heider-Simmel and live-action [hasson2010natural]. The inferential bridge from triangle-animation fMRI activation to character-animation mu-band EEG ERD is plausible and untested at scalp-EEG resolution. +Even with that tempering, the prediction is specific. Shots dominated by character action should produce ERD in the mu band over central electrodes, with possible beta-band rebound suppression. The Heider-Simmel tradition shows that even abstract triangle animations recruit posterior STS, medial prefrontal cortex, and temporal poles when motion implies intention [39]. The naturalness gradient places character animation between abstract Heider-Simmel and live-action [40]. The inferential bridge from triangle-animation fMRI activation to character-animation mu-band EEG ERD is plausible and untested at scalp-EEG resolution. -The second action beat is event segmentation. Speer and colleagues found posterior cingulate, middle-temporal, and posterior STS boundary-locked transients in fMRI during narrative listening [speer2007narrative]. Baldassano and colleagues recovered a hierarchy of event boundaries from Sherlock-movie fMRI using HMM, with hippocampal boundary signals predicting subsequent free recall [baldassano2017event]. Lerner and colleagues mapped temporal receptive windows from sensory cortex (milliseconds) to default-mode regions (tens of seconds) [lerner2011temporal]. Chen and colleagues showed event-specific patterns in the default-mode network are shared across viewers and reactivated at recall [chen2017shared]. Ben-Yakov and Henson distinguished within-event camera cuts, which produce minimal hippocampal responses, from across-event narrative boundaries, which produce robust ones [Ben-Yakov2018TheHF]. Magliano and Zacks supplied the behavioural foundation that viewers segment edited films along cuts independent of dialogue [Magliano2011TheIO]. +The second action beat is event segmentation. Speer and colleagues found posterior cingulate, middle-temporal, and posterior STS boundary-locked transients in fMRI during narrative listening [10]. Baldassano and colleagues recovered a hierarchy of event boundaries from Sherlock-movie fMRI using HMM, with hippocampal boundary signals predicting subsequent free recall [11]. Lerner and colleagues mapped temporal receptive windows from sensory cortex (milliseconds) to default-mode regions (tens of seconds) [41]. Chen and colleagues showed event-specific patterns in the default-mode network are shared across viewers and reactivated at recall [42]. Ben-Yakov and Henson distinguished within-event camera cuts, which produce minimal hippocampal responses, from across-event narrative boundaries, which produce robust ones [8]. Magliano and Zacks supplied the behavioural foundation that viewers segment edited films along cuts independent of dialogue [43]. -A third action beat concerns single-agent versus two-agent shots. Sliwa and Freiwald documented a dedicated cortical network in macaque for processing two-agent social interaction, separable from single-agent action perception [sliwa2017macaque]. This motivates excluding two-agent shots from a clean single-agent contrast, since the social-interaction network may dominate two-agent variance. +A third action beat concerns single-agent versus two-agent shots. Sliwa and Freiwald documented a dedicated cortical network in macaque for processing two-agent social interaction, separable from single-agent action perception [44]. This motivates excluding two-agent shots from a clean single-agent contrast, since the social-interaction network may dominate two-agent variance. ## 5. Language: comparator of non-transfer plus silent-narrative sub-thread ### 5a. Language-model regressors are structurally non-transferable -The contemporary methodological mainstream in naturalistic neuroimaging is built around transformer-based language-model (LM) regressors aligned to spoken or read transcripts. Goldstein and colleagues showed pre-onset prediction, post-onset surprise, and contextual-embedding signatures shared between word-by-word electrocorticography (ECoG) and autoregressive LMs [Goldstein2022SharedCP]. Each signature depends on speech-onset alignment. Heilbron and colleagues separated lexical, syntactic, and semantic surprisal regressors during MEG audiobook listening, all derived from LMs with word-onset alignment [Heilbron2020AHO]. Caucheteux and colleagues mapped transformer intermediate layers to fMRI and MEG responses to natural narrative [Caucheteux2022BrainsAA] and a cortical hierarchy of prediction timescales [Caucheteux2023EvidenceOA]. Antonello and colleagues documented log-linear scaling of brain prediction with LM parameter count up to 30B [Antonello2023ScalingLF]. Schrimpf and colleagues showed that next-word-prediction quality drives brain score on fMRI, ECoG, and reading-time benchmarks [schrimpf2021the]. Toneva and Wehbe used BERT to predict reading fMRI and MEG, with attention-head ablations linking brain prediction to natural-language processing performance [toneva2019interpreting]. Huth and colleagues built the canonical voxelwise word-embedding encoding atlas tiling cortex with semantic clusters; this method requires spoken transcripts [Huth2016NaturalSR]. Nelson and colleagues tracked open-node count during syntactic merge using intracranial high-gamma dynamics, explicitly reading-based [Nelson2017NeurophysiologicalDO]. The N400 family bridges to picture-context paradigms at the cost of dynamic stimulus [Kutas2011ThirtyYA; DeLong2005ProbabilisticWP]. +The contemporary methodological mainstream in naturalistic neuroimaging is built around transformer-based language-model (LM) regressors aligned to spoken or read transcripts. Goldstein and colleagues showed pre-onset prediction, post-onset surprise, and contextual-embedding signatures shared between word-by-word electrocorticography (ECoG) and autoregressive LMs [21]. Each signature depends on speech-onset alignment. Heilbron and colleagues separated lexical, syntactic, and semantic surprisal regressors during MEG audiobook listening, all derived from LMs with word-onset alignment [45]. Caucheteux and colleagues mapped transformer intermediate layers to fMRI and MEG responses to natural narrative [22] and a cortical hierarchy of prediction timescales [46]. Antonello and colleagues documented log-linear scaling of brain prediction with LM parameter count up to 30B [47]. Schrimpf and colleagues showed that next-word-prediction quality drives brain score on fMRI, ECoG, and reading-time benchmarks [48]. Toneva and Wehbe used BERT to predict reading fMRI and MEG, with attention-head ablations linking brain prediction to natural-language processing performance [49]. Huth and colleagues built the canonical voxelwise word-embedding encoding atlas tiling cortex with semantic clusters; this method requires spoken transcripts [50]. Nelson and colleagues tracked open-node count during syntactic merge using intracranial high-gamma dynamics, explicitly reading-based [51]. The N400 family bridges to picture-context paradigms at the cost of dynamic stimulus [52,53]. -Each method depends on word-level alignment to spoken or read stimuli. *The Present* is wordless. All seven Category G cards in our language ontology (and 12 cards corpus-wide) carry `transfer-to-silent: no`. A vision-side analogue, multimodal vision-language model embeddings or scene-difference deep-network features as continuous regressors, does not yet exist in the corpus for scalp-EEG ERSP. The Lipkin frontotemporal language network atlas [Lipkin2022ProbabilisticAF] is included as the negative-control region of interest in the falsification region of Section 7. +Each method depends on word-level alignment to spoken or read stimuli. *The Present* is wordless. All seven Category G cards in our language ontology (and 12 cards corpus-wide) carry `transfer-to-silent: no`. A vision-side analogue, multimodal vision-language model embeddings or scene-difference deep-network features as continuous regressors, does not yet exist in the corpus for scalp-EEG ERSP. The Lipkin frontotemporal language network atlas [54] is included as the negative-control region of interest in the falsification region of Section 7. ### 5b. Silent-narrative neural correlates that do transfer -Silent-narrative neural correlates do transfer to scalp-EEG ERSP analysis even when language-model regressors cannot. Castelli and colleagues showed that silent geometric-shape animations engage medial prefrontal cortex, the temporo-parietal junction, and STS when motion implies social interaction, with no speech required [Castelli2000MovementAM; castelli2000heider]; the same paradigm in autism shows reduced engagement [Castelli2002AutismAS]. Vanderwal and colleagues built Inscapes, a purpose-built silent abstract animation that improves MRI compliance and produces reliable network-level activity, used by the HBN cohort itself [Vanderwal2015InscapesAM]. Naci and colleagues used a Hitchcock excerpt as a covert assessment, showing that high-order cortex can be probed from a near-silent narrative [Naci2014ACN]. Lankinen and colleagues report source-space MEG reliable across viewers in occipital and temporal cortex during silent-visual and audiovisual movie conditions, the closest electrophysiological analogue with a deliberate silent-visual condition [Lankinen2014IntersubjectCO]. The Studyforrest infrastructure provides an audio-only foundation that has been extended to silent-cohort contrasts [Hanke2014AH7]. Schroeder and colleagues described modality-general delta- and theta-band phase alignment to attended event onsets, providing the mechanistic frame for shot-onset ERSP independent of speech [Schroeder2009LowfrequencyNO]. Senkowski and colleagues described transient gamma synchronisation and low-frequency phase coupling for cross-modal binding [Senkowski2008CrossmodalBT]. Buckner, Simony, Yeshurun, Mar, and Tamir developed the default-mode network as narrative integrator, with framing context driving within-stimulus divergence [Buckner2008TheBD; Simony2016DynamicRO; Yeshurun2017SameSD; Mar2011TheNB; Tamir2016ReadingFA]. +Silent-narrative neural correlates do transfer to scalp-EEG ERSP analysis even when language-model regressors cannot. Castelli and colleagues showed that silent geometric-shape animations engage medial prefrontal cortex, the temporo-parietal junction, and STS when motion implies social interaction, with no speech required [39,55]; the same paradigm in autism shows reduced engagement [56]. Vanderwal and colleagues built Inscapes, a purpose-built silent abstract animation that improves MRI compliance and produces reliable network-level activity, used by the HBN cohort itself [13]. Naci and colleagues used a Hitchcock excerpt as a covert assessment, showing that high-order cortex can be probed from a near-silent narrative [57]. Lankinen and colleagues report source-space MEG reliable across viewers in occipital and temporal cortex during silent-visual and audiovisual movie conditions, the closest electrophysiological analogue with a deliberate silent-visual condition [15]. The Studyforrest infrastructure provides an audio-only foundation that has been extended to silent-cohort contrasts [58]. Schroeder and colleagues described modality-general delta- and theta-band phase alignment to attended event onsets, providing the mechanistic frame for shot-onset ERSP independent of speech [59]. Senkowski and colleagues described transient gamma synchronisation and low-frequency phase coupling for cross-modal binding [60]. Buckner, Simony, Yeshurun, Mar, and Tamir developed the default-mode network as narrative integrator, with framing context driving within-stimulus divergence [61,62,63,64,65]. The language perspective therefore plays two roles. The 5a sub-thread isolates the silent-stimulus design from the dominant LM-as-regressor framework. The 5b sub-thread supplies the cortical substrates that silent narrative engages: medial prefrontal cortex, the temporo-parietal junction, the STS, and the default-mode network. Their independent-component-cluster analogues in EEG are the search regions for the per-shot ERSP analysis. Figure 3 makes the gap structure explicit. ## 6. Emotion: two predictions at different latencies -The emotion perspective makes two predictions with different latencies and different implicated structures. The first is an early visual-cortex emotion-schema response. Kragel and colleagues built EmoNet, a deep-learning model showing that emotion schemas are encoded in early visual cortex, predicting that emotion-tuned visual representations should appear in early-latency occipital ERSP [Kragel2018EmotionSA]. Saarimaki and colleagues decoded six basic emotions during emotional movie viewing using fMRI multi-voxel pattern analysis [Saarimäki2016DiscreteNS]; Cowen and Keltner extended the taxonomy to 27 distinguishable categories from short videos [Cowen2017SelfreportC2]. Distributed-network meta-analysis argues for distributed signatures over strict regional localisation [Lindquist2012TheBB], with the neurologic pain signature as a methodological exemplar of multivariate signatures of affect [Wager2013AnFN]. The closest EEG correlate at the 0 to 500 ms scale is early occipital alpha desynchronisation (80 to 300 ms post-shot-onset, extrapolated from static-picture latencies). Codispoti and colleagues (2023) review the EEG alpha-band literature on emotional picture perception and conclude that alpha desynchronisation is a robust correlate of attentional engagement by emotional stimuli, with parametric arousal modulation [Codispoti2023AlphabandOA]. Whether this transfers to dynamic naturalistic stimuli at sub-second timescales in a child cohort is untested. +The emotion perspective makes two predictions with different latencies and different implicated structures. The first is an early visual-cortex emotion-schema response. Kragel and colleagues built EmoNet, a deep-learning model showing that emotion schemas are encoded in early visual cortex, predicting that emotion-tuned visual representations should appear in early-latency occipital ERSP [66]. Saarimaki and colleagues decoded six basic emotions during emotional movie viewing using fMRI multi-voxel pattern analysis [Saarimäki2016DiscreteNS]; Cowen and Keltner extended the taxonomy to 27 distinguishable categories from short videos [67]. Distributed-network meta-analysis argues for distributed signatures over strict regional localisation [68], with the neurologic pain signature as a methodological exemplar of multivariate signatures of affect [69]. The closest EEG correlate at the 0 to 500 ms scale is early occipital alpha desynchronisation (80 to 300 ms post-shot-onset, extrapolated from static-picture latencies). Codispoti and colleagues (2023) review the EEG alpha-band literature on emotional picture perception and conclude that alpha desynchronisation is a robust correlate of attentional engagement by emotional stimuli, with parametric arousal modulation [70]. Whether this transfers to dynamic naturalistic stimuli at sub-second timescales in a child cohort is untested. -The second prediction is a longer-latency cuteness or affiliative response. Stoeckel and colleagues reported common activation across child and dog spanning emotion, reward, affiliation, visual processing, and social cognition regions in adult mothers viewing photographs of own child versus own dog [Stoeckel2014PatternsOB]. Glocker and colleagues showed that baby schema parametrically modulates nucleus accumbens reward in adults [Glocker2009BabySM]. Borgi and colleagues demonstrated that children aged 3 to 6 already show parametric cuteness ratings and gaze bias for human infant, puppy, and kitten faces [Borgi2014BabySI]; this is the behavioural anchor that the cuteness response is established well before adolescence. The interpretation implication is that Stoeckel measures identity-level pair-bonding and Borgi measures generic baby schema. HBN viewers have no identity-level bond with an animated puppy, so the relevant inference is from generic baby schema rather than pair-bonding circuitry. +The second prediction is a longer-latency cuteness or affiliative response. Stoeckel and colleagues reported common activation across child and dog spanning emotion, reward, affiliation, visual processing, and social cognition regions in adult mothers viewing photographs of own child versus own dog [71]. Glocker and colleagues showed that baby schema parametrically modulates nucleus accumbens reward in adults [72]. Borgi and colleagues demonstrated that children aged 3 to 6 already show parametric cuteness ratings and gaze bias for human infant, puppy, and kitten faces [73]; this is the behavioural anchor that the cuteness response is established well before adolescence. The interpretation implication is that Stoeckel measures identity-level pair-bonding and Borgi measures generic baby schema. HBN viewers have no identity-level bond with an animated puppy, so the relevant inference is from generic baby schema rather than pair-bonding circuitry. -Two EEG routes connect these predictions to observables. The first is early occipital alpha-band desynchronisation (80 to 300 ms) as an arousal-modulated correlate of attentional engagement [Codispoti2023AlphabandOA]. The second is later frontal alpha asymmetry (200 to 500 ms; extrapolated downward from the seconds-to-minutes Davidson tradition) as an approach-withdrawal index [Davidson2000AffectiveSP; Coan2004FrontalEA]. An updated meta-analytic critique documents smaller effect sizes and substantial reliability concerns [Reznik2018FrontalAA]. The corpus contains no card applying asymmetry analysis to per-event sub-second windows during a continuous naturalistic stimulus, and none in a developmental cohort viewing film. Frontal asymmetry at shot-onset latency is therefore exploratory rather than confirmatory. The third emotion beat is social cognition. Richardson and colleagues documented ToM and pain networks present from age three and refining with age, using Pixar shorts in 122 children [Richardson2018DevelopmentOT]; this is the load-bearing developmental anchor. Mar synthesised narrative comprehension as a social-cognitive activity [Mar2011TheNB]; Singer and colleagues documented affective pain-region engagement during observed pain [Singer2004EmpathyFP]; Zaki and Ochsner formalised the tripartite empathy model bridging experience sharing and mental-state attribution [Zaki2012TheNO]. Nummenmaa and colleagues showed emotion intensity modulates ISC in midline cortex during film viewing [Nummenmaa2012EmotionsPS]; Schmaelzle and Grall theorised ISC as audience captivation [Schmälzle2020TheCB]. Two predictions sit at incompatible latencies and topographies; an LLR-partialled per-shot generalised linear model (GLM) adjudicates between them. +Two EEG routes connect these predictions to observables. The first is early occipital alpha-band desynchronisation (80 to 300 ms) as an arousal-modulated correlate of attentional engagement [70]. The second is later frontal alpha asymmetry (200 to 500 ms; extrapolated downward from the seconds-to-minutes Davidson tradition) as an approach-withdrawal index [74,75]. An updated meta-analytic critique documents smaller effect sizes and substantial reliability concerns [76]. The corpus contains no card applying asymmetry analysis to per-event sub-second windows during a continuous naturalistic stimulus, and none in a developmental cohort viewing film. Frontal asymmetry at shot-onset latency is therefore exploratory rather than confirmatory. The third emotion beat is social cognition. Richardson and colleagues documented ToM and pain networks present from age three and refining with age, using Pixar shorts in 122 children [12]; this is the load-bearing developmental anchor. Mar synthesised narrative comprehension as a social-cognitive activity [64]; Singer and colleagues documented affective pain-region engagement during observed pain [77]; Zaki and Ochsner formalised the tripartite empathy model bridging experience sharing and mental-state attribution [78]. Nummenmaa and colleagues showed emotion intensity modulates ISC in midline cortex during film viewing [79]; Schmaelzle and Grall theorised ISC as audience captivation [Schmälzle2020TheCB]. Two predictions sit at incompatible latencies and topographies; an LLR-partialled per-shot generalised linear model (GLM) adjudicates between them. ## 7. Synthesis: integration, falsifiability, and open questions ### 7.1 Integration -The four perspectives rank by depth of prior evidence. Psychophysics has the deepest precedent and the simplest operationalisation: partial LLR, optionally motion energy, before any condition claim. Action has the deepest specific oscillatory prediction (mu-band ERD over central rolandic clusters) but no animated-agent precedent in EEG. Language is structurally non-transferable for LM regressors but supplies cortical priors for silent narrative through its 5b sub-thread (medial prefrontal cortex, the temporo-parietal junction, the STS, the default-mode network). Emotion supplies two predictions: early occipital alpha desynchronisation [Codispoti2023AlphabandOA; Kragel2018EmotionSA] and later frontal-asymmetric alpha [Davidson2000AffectiveSP], with the cuteness response anchored developmentally by Borgi [Borgi2014BabySI]. Distributed-multivariate-signature framing supports IC-cluster-level analyses over single-IC decoding [Lindquist2012TheBB; chen2017shared]. Figure 4 displays the four predictions in tabular form. +The four perspectives rank by depth of prior evidence. Psychophysics has the deepest precedent and the simplest operationalisation: partial LLR, optionally motion energy, before any condition claim. Action has the deepest specific oscillatory prediction (mu-band ERD over central rolandic clusters) but no animated-agent precedent in EEG. Language is structurally non-transferable for LM regressors but supplies cortical priors for silent narrative through its 5b sub-thread (medial prefrontal cortex, the temporo-parietal junction, the STS, the default-mode network). Emotion supplies two predictions: early occipital alpha desynchronisation [66,70] and later frontal-asymmetric alpha [74], with the cuteness response anchored developmentally by Borgi [73]. Distributed-multivariate-signature framing supports IC-cluster-level analyses over single-IC decoding [42,68]. Figure 4 displays the four predictions in tabular form. ### 7.2 Anchor case -External precedent: Petroni and colleagues recorded 64-channel EEG at 500 Hz from 114 viewers across ages 6 to 44 during passive viewing of six naturalistic videos including animated and live-action shorts [Petroni2018TheVO]. They did not analyse shot-onset ERSP and did not factor stimulus-side regressors, but they demonstrated that scalp-EEG signal exists during developmental naturalistic viewing of short videos. They are the closest external existence proof that the measurement class is feasible in adjacent territory. Internal feasibility: a partly-validated developmental EEG pipeline on HBN-EEG R3 brings 184 subjects through Brain Imaging Data Structure (BIDS) import, 1 Hz high-pass filtering, conditional cleanline gated by Nyquist, `clean_rawdata` channel rejection, AMICA decomposition, ICLabel classification, dipole fitting, and `std_precomp` ERSP precomputation; the operating constraint is that the local working set is 100 Hz, with a 500 Hz validation pass on the full Amazon S3 R3 release scheduled after pipeline validation. The two anchor assertions are independent and not interchangeable. +External precedent: Petroni and colleagues recorded 64-channel EEG at 500 Hz from 114 viewers across ages 6 to 44 during passive viewing of six naturalistic videos including animated and live-action shorts [14]. They did not analyse shot-onset ERSP and did not factor stimulus-side regressors, but they demonstrated that scalp-EEG signal exists during developmental naturalistic viewing of short videos. They are the closest external existence proof that the measurement class is feasible in adjacent territory. Internal feasibility: a partly-validated developmental EEG pipeline on HBN-EEG R3 brings 184 subjects through Brain Imaging Data Structure (BIDS) import, 1 Hz high-pass filtering, conditional cleanline gated by Nyquist, `clean_rawdata` channel rejection, AMICA decomposition, ICLabel classification, dipole fitting, and `std_precomp` ERSP precomputation; the operating constraint is that the local working set is 100 Hz, with a 500 Hz validation pass on the full Amazon S3 R3 release scheduled after pipeline validation. The two anchor assertions are independent and not interchangeable. ### 7.3 Falsifiability -A topographic-and-band rejection region for the four-perspective ranking can be pre-registered before group analysis. A surviving central-rolandic mu-band cluster (electrodes C3, Cz, and C4; 8 to 13 Hz) confirms the action prediction. A surviving frontal-asymmetric alpha cluster (electrodes F3 and F4; 8 to 13 Hz) confirms the emotion prediction. A surviving cluster in left frontotemporal IC space, overlapping the Lipkin language-network atlas [Lipkin2022ProbabilisticAF] used as a negative-control mask, falsifies the four-perspective ranking by relocating the surviving signal into a perspective the thesis says should not transfer. A null result on the LLR-partialled GLM at a pre-registered cluster-level alpha (p < 0.05 corrected by mass-univariate cluster-based permutation, with the mTRF toolbox precedent [Crosse2016TheMT]) also falsifies the four-perspective ranking, by localising per-shot ERSP variance entirely to bottom-up features in this cohort. Pinning the rejection region before data analysis is the publication discipline that constrains analyst degrees of freedom. +A topographic-and-band rejection region for the four-perspective ranking can be pre-registered before group analysis. A surviving central-rolandic mu-band cluster (electrodes C3, Cz, and C4; 8 to 13 Hz) confirms the action prediction. A surviving frontal-asymmetric alpha cluster (electrodes F3 and F4; 8 to 13 Hz) confirms the emotion prediction. A surviving cluster in left frontotemporal IC space, overlapping the Lipkin language-network atlas [54] used as a negative-control mask, falsifies the four-perspective ranking by relocating the surviving signal into a perspective the thesis says should not transfer. A null result on the LLR-partialled GLM at a pre-registered cluster-level alpha (p < 0.05 corrected by mass-univariate cluster-based permutation, with the mTRF toolbox precedent [32]) also falsifies the four-perspective ranking, by localising per-shot ERSP variance entirely to bottom-up features in this cohort. Pinning the rejection region before data analysis is the publication discipline that constrains analyst degrees of freedom. ### 7.4 Open questions and limitations -Narrative position is a within-stimulus confound. Boy-only and puppy-only shots in *The Present* differ on three-act position: boy-only clusters in the early-act setup, puppy-only in the late-act resolution. Any boy-vs-puppy ERSP difference may therefore be confounded with prediction-error or arousal trajectories. The response is to add shot-index-in-narrative as a continuous covariate in the group GLM and to fit a within-act stratified analysis as a named follow-up [Magliano2011TheIO; baldassano2017event; chen2017shared]; both are tractable from the existing shot-event annotation. Beyond narrative position, several gaps in the corpus limit what this Review can claim. The Hickok-style mu-system critique is not represented in our cards, which weakens the action prediction. Klin and colleagues showed that toddlers with autism orient to audiovisual contingency rather than upright biological motion [klin2009biological] and that adolescents with autism fixate eyes 50 percent as often during emotionally evocative viewing [klin2002visual]; the HBN cohort includes a substantial autism-spectrum subsample, so autism status is a candidate moderator, but stratified analyses (autism-spectrum, attention, social skill) are exploratory follow-ups rather than primary tests. The emotion literature is predominantly adult; the three pet-evoked affective cards are fMRI or behavioural, not EEG. Frontal asymmetry at sub-second timescales is unprecedented and reliability-limited. The single-stimulus design forbids generalisation beyond *The Present*. The 100 Hz local working set caps beta-band and gamma-band claims until the 500 Hz validation pass. The Outstanding Questions Box collects the forward-looking adjudication targets. +Narrative position is a within-stimulus confound. Boy-only and puppy-only shots in *The Present* differ on three-act position: boy-only clusters in the early-act setup, puppy-only in the late-act resolution. Any boy-vs-puppy ERSP difference may therefore be confounded with prediction-error or arousal trajectories. The response is to add shot-index-in-narrative as a continuous covariate in the group GLM and to fit a within-act stratified analysis as a named follow-up [11,42,43]; both are tractable from the existing shot-event annotation. Beyond narrative position, several gaps in the corpus limit what this Review can claim. The Hickok-style mu-system critique is not represented in our cards, which weakens the action prediction. Klin and colleagues showed that toddlers with autism orient to audiovisual contingency rather than upright biological motion [80] and that adolescents with autism fixate eyes 50 percent as often during emotionally evocative viewing [81]; the HBN cohort includes a substantial autism-spectrum subsample, so autism status is a candidate moderator, but stratified analyses (autism-spectrum, attention, social skill) are exploratory follow-ups rather than primary tests. The emotion literature is predominantly adult; the three pet-evoked affective cards are fMRI or behavioural, not EEG. Frontal asymmetry at sub-second timescales is unprecedented and reliability-limited. The single-stimulus design forbids generalisation beyond *The Present*. The 100 Hz local working set caps beta-band and gamma-band claims until the 500 Hz validation pass. The Outstanding Questions Box collects the forward-looking adjudication targets. ## Box 1: HBN-EEG Release 3 as the anchor cohort -The Healthy Brain Network EEG (HBN-EEG) Release 3 cohort recruits 5- to 21-year-old participants in a research-grade developmental setting and records 128-channel HydroCel Geodesic Sensor Net during passive viewing of the 3.5-minute Pixar short *The Present* (2014). The local working set used in our pipeline development is 184 subjects at 100 Hz biosignal data format (BDF), a Nyquist-aware downsample of the original 500 Hz. The 56 stimulus-side shots carry per-shot `onset`, `duration`, `LLR`, `has_boy`, and `has_puppy` annotations; after invalidating 3 high-drift rows (`match_diff_s > 1.0 s`), 49 rows are trusted, yielding 20 boy-only and 15 puppy-only shots for the mutually exclusive single-agent contrast. The pipeline runs BIDS import, 1 Hz high-pass filter, conditional cleanline (gated by Nyquist), `clean_rawdata` channel rejection, AMICA, ICLabel (brain threshold 0.69), dipfit5, and `std_precomp` ERSP. The anchor case rests on Petroni and colleagues 2018 [Petroni2018TheVO] as the external precedent and this partly-validated pipeline as the internal feasibility proof. +The Healthy Brain Network EEG (HBN-EEG) Release 3 cohort recruits 5- to 21-year-old participants in a research-grade developmental setting and records 128-channel HydroCel Geodesic Sensor Net during passive viewing of the 3.5-minute Pixar short *The Present* (2014). The local working set used in our pipeline development is 184 subjects at 100 Hz biosignal data format (BDF), a Nyquist-aware downsample of the original 500 Hz. The 56 stimulus-side shots carry per-shot `onset`, `duration`, `LLR`, `has_boy`, and `has_puppy` annotations; after invalidating 3 high-drift rows (`match_diff_s > 1.0 s`), 49 rows are trusted, yielding 20 boy-only and 15 puppy-only shots for the mutually exclusive single-agent contrast. The pipeline runs BIDS import, 1 Hz high-pass filter, conditional cleanline (gated by Nyquist), `clean_rawdata` channel rejection, AMICA, ICLabel (brain threshold 0.69), dipfit5, and `std_precomp` ERSP. The anchor case rests on Petroni and colleagues 2018 [14] as the external precedent and this partly-validated pipeline as the internal feasibility proof. ## Trends Box: recent developments enabling the per-shot framing Recent advances make the per-shot framing newly tractable. -- **Whole-brain shot-cut response in adult intracranial EEG.** Nentwich and colleagues 2023 recorded 6328 contacts in 23 patients across 43.6 minutes of film clips and regressed responses against optical-flow magnitude, saccade onsets, and film-cut onsets simultaneously, finding whole-brain saccade- and cut-locked responses with motion concentrated in occipitoparietal cortex [Nentwich2023SemanticNM]. -- **Hidden Markov model recovery of event states from fMRI.** Baldassano and colleagues 2017 recovered a hierarchy of event boundaries from Sherlock-movie fMRI, with hippocampal boundary signals predicting subsequent free recall [baldassano2017event]. -- **Cross-sectional developmental EEG-ISC.** Petroni and colleagues 2018 reported whole-clip EEG-ISC reliability across ages 6 to 44 during passive viewing of six naturalistic videos, peaking in childhood [Petroni2018TheVO]. -- **Silent abstract animation for MRI compliance.** Vanderwal and colleagues 2015 built Inscapes, used by HBN itself, with reliable network-level activity [Vanderwal2015InscapesAM]. -- **Multi-level cinematic-feature regression.** Kauttonen and colleagues 2015 regressed multi-level cinematic features against fMRI ISC, supplying a methodological template for shot-level feature annotation [Kauttonen2015OptimizingMF]. -- **Open developmental EEG releases.** HBN-EEG and Studyforrest [Hanke2014AH7] make large-N developmental datasets available for naturalistic-stimulus analysis at unprecedented scale. +- **Whole-brain shot-cut response in adult intracranial EEG.** Nentwich and colleagues 2023 recorded 6328 contacts in 23 patients across 43.6 minutes of film clips and regressed responses against optical-flow magnitude, saccade onsets, and film-cut onsets simultaneously, finding whole-brain saccade- and cut-locked responses with motion concentrated in occipitoparietal cortex [7]. +- **Hidden Markov model recovery of event states from fMRI.** Baldassano and colleagues 2017 recovered a hierarchy of event boundaries from Sherlock-movie fMRI, with hippocampal boundary signals predicting subsequent free recall [11]. +- **Cross-sectional developmental EEG-ISC.** Petroni and colleagues 2018 reported whole-clip EEG-ISC reliability across ages 6 to 44 during passive viewing of six naturalistic videos, peaking in childhood [14]. +- **Silent abstract animation for MRI compliance.** Vanderwal and colleagues 2015 built Inscapes, used by HBN itself, with reliable network-level activity [13]. +- **Multi-level cinematic-feature regression.** Kauttonen and colleagues 2015 regressed multi-level cinematic features against fMRI ISC, supplying a methodological template for shot-level feature annotation [82]. +- **Open developmental EEG releases.** HBN-EEG and Studyforrest [58] make large-N developmental datasets available for naturalistic-stimulus analysis at unprecedented scale. ## Outstanding Questions Box @@ -179,6 +179,6 @@ Recent advances make the per-shot framing newly tractable. ## References -References are managed in `refs.bib` (94 entries after F3 stray-key removal). Cell Press numbered style is applied at Phase 5 assembly. Body cite-card slugs are bracketed in this draft (e.g., `[Petroni2018TheVO]`) and resolved against `refs.bib` at compile time. +The numbered reference list is in `references.md` (82 cited entries, ordered by first appearance in the body). Underlying BibTeX is in `refs.bib` (94 entries; the 12 uncited entries are kept for the supplementary materials and not numbered here). Cell Press house style applied at compile time. -Note on the alpha-band and emotion citation: the body text cites Codispoti and colleagues (2023), Psychophysiology, DOI 10.1111/psyp.14438; the internal corpus slug `schubring-schupp-2023-alpha-emotion` is retained inside the research collection for cross-reference stability and does not appear in published prose. +Note on the alpha-band and emotion citation: reference 70 cites Codispoti and colleagues (2023), Psychophysiology, DOI 10.1111/psyp.14438. 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