Memory Systems · Non-Declarative

Priming

Example

Perceptual: You glance at a shop sign without properly reading it. An hour later a word puzzle gives you E_E_H_NT and elephant arrives immediately, whether or not you remember the sign. Present the same word spoken rather than written and the advantage shrinks, because what persists is the form. Standard paradigms are perceptual identification and word-stem or fragment completion.

Conceptual: Same sign. Later someone asks you to name some animals and elephant is among the first. It makes no difference whether you saw the word or heard it, because what persists is the meaning. Standard paradigms are category exemplar generation and conceptual classification.

Structural: A colleague says "she sent the client a revised quote." Minutes later, describing something unrelated, you say "I gave my sister the address" rather than "I gave the address to my sister." You did not notice the pattern and would not have predicted repeating it.

Newly-Formed Associations: You read the pair window-reason once, in passing. Later, given "window REA___" you complete it as reason more often than if the cue had been "officer REA___", though you cannot report having seen the pair. The link did not exist before the study episode.

01

Priming in Humans

Definition

Prior exposure changes how later material is processed, without awareness of the exposure or any intention to recall it. Two forms are conventionally distinguished by what carries the effect: perceptual priming, driven by the physical form of the studied item, and conceptual priming, driven by its meaning (⁠Roediger & McDermott, 1993⁠). These dissociate both behaviourally and neurally (⁠Keane et al., 1995⁠). Structural priming is a third form, in which a syntactic frame persists independently of the words carrying it (⁠Bock, 1986⁠). Priming is a memory phenomenon rather than a fact about pre-existing lexical structure, because it extends to associations newly formed during a single study episode and survives in amnesia (⁠Graf & Schacter, 1985⁠).

Neural Substrate

Lesion evidence supports a division by type. Bilateral occipital lesions impair visuoperceptual priming while leaving recognition intact, and bilateral medial temporal lesions produce the reverse (⁠Keane et al., 1995⁠). The same patient with occipital damage showed intact conceptual priming, and a group study using structurally parallel tasks found perceptual priming poorer after occipital lesions and conceptual priming poorer after frontal lesions (⁠Gong et al., 2016⁠). Together these give occipital cortex for perceptual priming and dorsolateral prefrontal cortex for conceptual priming, both dissociable from the medial temporal system supporting recognition, though only the occipital half of the group dissociation is clean, since the frontal group was also impaired on explicit memory and general cognitive measures (⁠Gong et al., 2016⁠).

Neuroimaging complicates this. A coordinate-based meta-analysis of 65 fMRI studies with concurrent behavioural priming found repetition suppression mainly in left inferior frontal gyrus and fusiform gyrus for both task types, with no region showing suppression selective to one and no significant difference on direct contrast (⁠Lee, Henson, & Lin, 2020⁠). The authors take this as questioning the simple perceptual and conceptual distinction, and propose a hybrid in which inferior frontal suppression reflects retrieval of stimulus-response bindings while fusiform suppression reflects facilitated processing. The inferior frontal result is fragile: once picture-naming studies are removed, the conjunction survives only in fusiform gyrus.

Structural priming has its own substrate. Syntactic adaptation appears in left inferior frontal gyrus (BA45), left middle temporal gyrus (BA21), and bilateral supplementary motor area (BA6), and is equally strong within and between production and comprehension, which the authors read as one neurobiological system serving syntactic processing in both speaking and listening (⁠Segaert et al., 2012⁠). The direction of the effect depends on whether the structure is already represented: in left inferior frontal gyrus and posterior temporal cortex, repetition of a known structure produces suppression, repetition of an infrequent novel structure produces enhancement, and a frequent novel structure falls between the two (⁠Weber et al., 2016⁠). Both this and the Segaert result were obtained with the verb repeated between prime and target, so neither establishes the substrate for lexically independent priming.

Left inferior frontal gyrus therefore appears in the imaging meta-analysis for both perceptual and conceptual priming and in structural priming, while the lesion evidence for conceptual priming points to dorsolateral prefrontal cortex without lateralisation (⁠Gong et al., 2016⁠). Whatever separates the subtypes behaviourally, the imaging converges on shared regions, which is the basis for the meta-analysis authors' doubt that the division survives at the neural level.

One subtype has no imaging account. The same meta-analysis found no hippocampal repetition suppression, which its authors attribute to the predominance of single-item paradigms and flag as requiring work on implicit relational priming (⁠Lee, Henson, & Lin, 2020⁠). That is the newly-formed-associations case established behaviourally by Graf and Schacter (1985), where the primed link is created within the study episode rather than drawn from existing structure. The behavioural evidence is strong, including its survival in amnesia, but the substrate is unresolved, and this row does not claim one for it.

02

AI at a Glance

In humans a single earlier encounter changes how later material is processed, in forms separated by whether what persists is the physical form of the material, its meaning, or its syntactic frame. Language models reproduce several of the abstract regularities governing this, including the finding that rarer primes prime more strongly, but diverge on which cues drive the effect and on which structures are most primeable.

03

Priming in AI

How Far It Has Been Measured

Measurement in AI: Directly Measured

AI Memory Performance: Comparable to Humans approximate

Where It Lives in the System

What Has Been Measured

  • Run on a classic 1998 sentence-completion experiment (32 prime and target pairs, 1,000 runs each), ChatGPT and Vicuna reused the primed structure (ChatGPT 0.71 vs 0.58; Vicuna 0.81 vs 0.51), more so when prime and target shared a verb, as people do. Against the human means plotted in the paper (an effect of about 5 points with different verbs and 18 with the same verb), ChatGPT's effect (about 9 and 14) sits within the human values and Vicuna's (about 21 and 38) above them (⁠Cai et al., 2024⁠).
  • The comparison is approximate: materials and procedure differed, the human means come from the original study with no reported spread, and no test compared people with the models. The within-range reading still holds because the models could still see the prime in the conversation, so Vicuna's larger effect cannot count in its favour, and ChatGPT, the stronger system (it matched the human pattern in 10 of 12 experiments, Vicuna in 7), sits among the human values (⁠Cai et al., 2024⁠).
  • Seven multilingual models (XGLM, 564 million to 7.5 billion parameters, and PolyLM, 1.7 and 13 billion) were run on the materials of 12 human structural priming experiments across six languages, including priming from one language to another. All models showed priming on the single-language materials and most showed it on 8 of the 12 cross-language sets, with larger models usually showing larger effects; the authors compared only the direction of effects with people, not their size (⁠Michaelov et al., 2023⁠).
  • Across GPT-2 Large and 7-billion-parameter Llama-2, Falcon, Mistral and Zephyr models (base and tuned versions), priming was far more lopsided than in people: sentences that strongly primed one dative structure tended to prime the other weakly or negatively (correlation -0.72 to -0.77), with only 26 to 38% priming in both directions, whereas people generally show positive priming for both. Like people, the models were primed more by rarer structures (the inverse frequency effect) (⁠Jumelet et al., 2024⁠).
  • Using the same English dative sentences that people read during EEG recording, 13 transformer language models showed priming, but at both noun phrases after the verb, whereas people showed it only at the second. Across the full set of models, model priming scores were not good predictors of human priming effects (⁠Sinclair et al., 2026⁠).
  • Using the materials of a human study in which solving bracketed arithmetic shifted relative-clause attachment in 36 French speakers (in eye movements, among the math-skilled), five current models (Llama 3.3 70B, Qwen3 8B, Kimi K2, gpt-oss-120b and gpt-oss-20b) showed no robust cross-domain priming, even Qwen3, which solved every equation. This one condition falls below people, though the human and model measures differ (eye tracking versus an explicit choice) (⁠Lee et al., 2026⁠).
  • Beyond the conversation, a 2025 preprint found a training-level analogue it calls priming: after fine-tuning (further training that changes the model's stored weights) on one new fact, PaLM-2, Gemma and Llama models applied it in unrelated contexts, predictably from the fact's pre-training word probabilities, but with no human comparison. No study was found that tests priming from AI assistants' saved memory (⁠Sun et al., 2025⁠).

Purpose and Execution of Memory: Foundational Differences Between Human and AI Memory Architectures, and Implications

Elizabeth K. Bayardelle, PhD and Jennifer L. Thompson, PhD

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