When and how should SeekVault deliberately rewire itself?

Scope note: This capture draws on cognitive and learning science research about human schema restructuring. These are empirical claims about cognition. Their application to a vault system is treated as inferential and held to the commentary callout, not the claim body.

Claim 1 — Cognitive conflict is a prerequisite for schema restructuring; congruent information cannot trigger it

Claim type: technical mechanism
Source tier required: Tier 1–2 ✓
Source: Danek & Flanagin (2019), AIMS Neuroscience 6(2):60–84. PMC7179339. Direct access verified.

Schema restructuring — a change in the problem solver's mental representation — is not triggered by information that confirms existing structure. It requires cognitive conflict: the detection of incongruent information that does not fit the current schema. Specifically, "conflict detection is a prerequisite of restructuring." The directional asymmetry is sharp: "only the incongruent cues produce a cognitive conflict by forcing participants to question their initial problem representation," while congruent cues are absorbed without forcing structural change. The authors further specify the sequence: "cognitive conflict is needed in order to trigger a change in the problem representation," and "to resolve this conflict, the initial view on the problem must be modified which opens up new solution possibilities."

Empirically, the superiority of incongruent cues over congruent cues was confirmed: "incongruent cues led to higher solution rates than the unhelpful, congruent cues."

Exact quoted phrases (Tier 1 requirement):

• "conflict detection is a prerequisite of restructuring"
• "only the incongruent cues produce a cognitive conflict by forcing participants to question their initial problem representation"
• "cognitive conflict is needed in order to trigger a change in the problem representation"
• "to resolve this conflict, the initial view on the problem must be modified which opens up new solution possibilities"
• "incongruent cues led to higher solution rates than the unhelpful, congruent cues"

provenance: Danek, A.H. & Flanagin, V.L. (2019). "Cognitive conflict and restructuring: The neural basis of two core components of insight." AIMS Neuroscience, 6(2), 60–84. https://pmc.ncbi.nlm.nih.gov/articles/PMC7179339/

Claim 2 — Deep schema reorganization (accommodation) is global, not local, requires deliberate processing, and occurs infrequently

Claim type: technical mechanism
Source tier required: Tier 1–2 ✓ (source is Tier 1 preprint, but exact quotes are from abstract-as-reproduced-by-search; direct paper access returned 403)
Flag: [unverified-mechanism — needs primary] for exact quote confirmation
Source: Kurashige, Kaneko & Matsumoto (2025), bioRxiv. DOI 10.64898/2025.12.30.697002. Posted 2025-12-31.

"Schema accommodation is the reorganization of a preexisting memory schema to deeply accept new information incongruent with it. Although it is crucial for flexible intelligence, it occurs infrequently, making its neural basis difficult to study." The experimental results suggest "the schema changes that occurred during the task were global reorganizations rather than local adjustments." The mechanism is not passive: "the executive network responsible for deliberate processing played a central role, with the support of widespread amplified activity." A candidate neural mechanism for the deliberate schema update involves "reinforcement learning-based control implemented in these neural substrates, in cooperation with the caudate nucleus."

The contrast with accretion and tuning is implicit but sharp: most learning accommodates new information by local addition or parameter adjustment; accommodation that changes the schema's topology is a distinct, metabolically costly, and infrequent process.

Quoted phrases (from abstract as reproduced by search engine; verify against primary):

• "Schema accommodation is the reorganization of a preexisting memory schema to deeply accept new information incongruent with it."
• "it occurs infrequently, making its neural basis difficult to study"
• "the schema changes that occurred during the task were global reorganizations rather than local adjustments"
• "the executive network responsible for deliberate processing played a central role"

provenance: Kurashige, H., Kaneko, J., & Matsumoto, K. (2025, December 31). "Memory schema reorganization induced by the deliberate processing in the executive network supported by widespread amplified activity." bioRxiv. https://www.biorxiv.org/content/10.64898/2025.12.30.697002v1.full

Claim 3 — The SEEK model proposes a hierarchy of four learning mechanisms, each triggered by prediction error but varying in structural depth

Claim type: definitional (model description) — Tier 3–4 acceptable; source is Tier 1
Flag: [unverified-mechanism — needs primary] for exact definitions of each mechanism, since paper is behind paywall and abstract text is from search engine
Source: Xu, Sandhofer & Stigler (2026), Acta Psychologica. DOI 10.1016/j.actpsy.2026.106570.

The Schema Expansion and Error-driven Knowledge-building (SEEK) model "conceptualizes learning as a dynamic interplay among four mechanisms — accretion, tuning, restructuring, and schema formation — each triggered by prediction error and modulated by automatic or deliberate curiosity." The model accounts for how "curiosity evolves across development and supports increasingly complex forms of knowledge revision." The four mechanisms form a hierarchy from shallow to structural: accretion (facts added to existing schema), tuning (schema parameters adjusted), restructuring (schema topology changed), and schema formation (new schema created). Each is triggered by prediction error, but the type of curiosity that modulates them differs: automatic curiosity (perceptually driven) modulates early accretion and tuning; deliberate (metacognitive) curiosity modulates restructuring and schema formation.

The SEEK model's central argument: restructuring is not simply more learning — it is a qualitatively different process that requires a different type of cognitive engagement (deliberate curiosity, not automatic).

Quoted phrases (from abstract as reproduced by search engine; verify against primary):

• "conceptualizes learning as a dynamic interplay among four mechanisms — accretion, tuning, restructuring, and schema formation — each triggered by prediction error and modulated by automatic or deliberate curiosity"

provenance: Xu, A., Sandhofer, C.M., & Stigler, J.W. (2026). "Curiosity as a catalyst for conceptual change: A schema-based model of learning and development." Acta Psychologica, DOI 10.1016/j.actpsy.2026.106570. https://www.sciencedirect.com/science/article/pii/S0001691826003719

Further leads

• Resistance to restructuring (expediency effects): Griffiths et al., Princeton CoCo Lab, "Expediency and Resistance to Knowledge Restructuring" (cocosci.princeton.edu/tom/papers/restructuring.pdf — PDF returned corrupt on fetch). The abstract suggests expertise sometimes prevents restructuring; "little is known about the processes involved in knowledge restructuring." High priority lead for a follow-up run.
• Prediction error and P3 tracking schema updates: "Prediction errors indexed by the P3 track the updating of complex long-term memory schemas" (bioRxiv 2019, DOI 10.1101/805887) — could provide a quantitative signal for when schema updating crosses from tuning to restructuring territory. PDF returned 403.
• Desirable difficulties as restructuring accelerators: Bjork, R.A. (1994). "Memory and metamemory considerations in the training of human beings." In Metacognition: Knowing About Knowing (pp. 185–205). MIT Press. The spacing and interleaving literature argues these conditions force prediction errors at higher rate — which by the SEEK model would accelerate the arrival of restructuring triggers. No exact quotes obtained; PDFs returned corrupt. Tier 2 source.
• Neuroscience of insight (Danek & Flanagin deeper): The same 2019 paper identifies the angular gyrus and middle temporal gyrus as active in both conflict and restructuring, suggesting these are "important throughout the insight problem solving process." Possibly useful for a future note on the neural architecture of structural learning.
• Schema formation vs. restructuring: The SEEK model distinguishes restructuring (changing an existing schema) from schema formation (building a new one). For vault practice: schema formation = creating a new MOC from scratch; restructuring = splitting or merging existing ones. The distinction matters for the HOW, not just the WHEN.
• Ontology evolution literature (information architecture angle): The knowledge graph / ontology evolution research (academic.oup.com/database/article/doi/10.1093/database/baae133/7972659) describes change types analogous to the four SEEK mechanisms: adding elements (accretion), modifying existing (tuning), merging/splitting (restructuring). Potentially Tier 1 if the Oxford Academic paper is peer-reviewed — verify on a follow-up run.