Mechanisms
Representational Structures · Schemas
Schema Application
Example
You wait ten minutes in an unfamiliar office and are asked afterwards what was in it. You will report a desk, a chair, papers, and quite possibly books and a filing cabinet, whether or not they were there, and you will miss the odd object that does not belong. Nothing in the reporting distinguishes the parts of the room you actually took in from the parts the office schema supplied.
Schema Application in Humans
Definition
Schema application is what happens when a stored knowledge structure is put to work on a particular situation. The activated schema acts as a template whose slots are filled by the specifics at hand, a process the neuroscience literature calls schema instantiation, and it begins early enough to shape how the situation is perceived rather than only how it is later remembered (Gilboa & Marlatte, 2017). Because the template also carries expectations about what usually accompanies what, it supplies parts of the picture that were never encoded. Those supplied parts come back in the same way as the parts that were, so people report expected items that were not present alongside items that were, with nothing to mark the difference (Brewer & Treyens, 1981).
Scope: The source literature separates two things this row treats together. Schema instantiation, the populating of the template, is characterised as an earlier and partly distinct process from the mnemonic effects that follow from it, and the review that supplies the term calls for more precise definitions of memory schema than current usage provides (Gilboa & Marlatte, 2017). This row covers both as the use of a schema, against Schema Formation, which covers how the structure is built.
Neural Substrate
The evidence here is largely human. A meta-analysis of activation foci from twelve imaging experiments of schema reinstatement and instantiation converges on the ventromedial prefrontal cortex, bilateral anterior temporal cortex, the temporoparietal junction including the angular gyrus, bilateral hippocampus, fusiform and parahippocampal gyrus, and posterior cingulate and retrosplenial cortex (Gilboa & Marlatte, 2017). Within that network the vmPFC appears to bias which posterior long-term representations are activated for the current context, with the hippocampus, angular gyrus and modality-specific cortices supplying the content that fills the template.
Lesion and stimulation work gives the vmPFC a causal role rather than a correlational one. Patients with vmPFC damage are impaired at judging whether a word belongs to an everyday schema even when nothing is being remembered, which points to a deficit in holding a schema active as a template for incoming information rather than a memory deficit as such. The same damage protects against schema-driven false recall on the Deese-Roediger-McDermott paradigm, and transcranial magnetic stimulation to medial prefrontal cortex reproduces that protective effect in healthy participants: removing the structure removes both the intrusions and the benefit. Electrophysiology places these influences early, with schema-related effects reported from around 170 ms and congruency effects between roughly 270 and 600 ms, and controls but not vmPFC patients show pre-stimulus theta coherence changes between vmPFC and temporal cortices, consistent with the template being held ready before the stimulus arrives (Gilboa & Marlatte, 2017).
Sources disagree on the vmPFC and hippocampus relationship. Competition accounts hold that strong congruence with an existing schema shifts processing to vmPFC and suppresses hippocampal binding of arbitrary detail, while interaction accounts hold that the two are jointly required, with coupling strongest at moderate rather than extreme levels of prior knowledge. The review reports evidence for both and does not resolve between them (Gilboa & Marlatte, 2017).
AI at a Glance
An activated schema is populated with the particulars of the current situation and supplies the rest of the expected structure, so that what is understood and later recalled combines what actually happened with what the structure implies (Gilboa & Marlatte, 2017; Brewer & Treyens, 1981). AI systems perform the same function, drawing on knowledge held in model weights, in the context window, or in a retrieval memory layer, but it is one of the two hardest categories in the benchmark that isolates it, and it is the only one there that a retrieval layer makes worse (Maharana et al., 2024).
Schema Application in AI
How Far It Has Been Measured
Measurement in AI: Directly Measured
AI Memory Performance: Not Yet Compared
Where It Lives in the System
What Has Been Measured
- Using the story from a human serial-reproduction study of gender stereotypes (Kashima, 2000), five preregistered experiments had ChatGPT (January 2023 version) repeatedly retell the story in chains; like people, it passed on stereotype-consistent content more than inconsistent content (beta = 0.058, p < .01), but unlike people it did so from the first retelling, where human participants had favoured inconsistent details (Acerbi & Stubbersfield, 2023).
- That comparison is uneven and off-scale: the model was told to summarize a text it could still see, whereas people retold the story from memory, and results were reported as regression slopes for one AI system with no matching human spread, so no rating can be drawn from it (Acerbi & Stubbersfield, 2023).
- A 2025 preprint ran the DRM false-memory task on three language models with the word lists kept in the context window, meaning the text the model can see in the current conversation; GPT-4 recognized all studied words, falsely recognized 5.3% of unrelated words and 11.4% of critical lures, while Mistral-7B and Llama-3-8B falsely recognized essentially no lures (Cao et al., 2025).
- GPT-4's 11.4% lure rate falls below the human range of roughly 27% to over 80% false recognition, but because the model could still see the lists, fewer false memories is exactly what its advantage predicts, so under the uneven-test rule this result does not count as a comparison (Stadler et al., 1999).
- For information held in the model's trained weights, researchers fine-tuned Mistral-7B on Bartlett's "War of the Ghosts" after giving it background training on one of five Wikipedia topics; its recalls drifted toward that background topic with topic-related intrusions, matching Bartlett's and Bergman and Roediger's findings only qualitatively, in a research model rather than a deployed assistant (Spens & Burgess, 2026).
- For retrieved (saved) memory, a 2024 preprint tested six AI systems on 1,200+ questions paired with documents containing altered answers; systems wrongly adopted the altered document 15.7% (Claude Opus) to 31.3% (GPT-3.5) of the time and did so less often the further the alteration departed from their prior knowledge, a knowledge-conflict measure with no human baseline (Wu et al., 2024).
- Not yet compared: the classic schema paradigms have been given to AI, but the only same-scale result (DRM) favours the side that could see the material, the story-retelling and Bartlett studies report only qualitative or regression-slope matches, and the retrieval study has no human data (Cao et al., 2025).
Where a Mechanism Can Live
04 Product
The whole configuration, and the only thing a benchmark observes directly.
01
Weights
Across deployments
02
Context Window
Within a session
03
Memory Layer
Across sessions
Which of the three a result belongs to is inferred from it, not seen in it.
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Angular gyrus
Cortex in the inferior parietal lobule
The inferior parietal gyrus arching around the upturned end of the superior temporal sulcus, behind the supramarginal gyrus.
The angular gyrus curves around the ascending terminal branch of the superior temporal sulcus, forming the back half of the inferior parietal lobule and corresponding roughly to Brodmann area 39. It sits at the meeting of visual, auditory and somatosensory association cortex and is connected to inferior frontal and lateral temporal regions. Left angular damage figures in Gerstmann's syndrome (agraphia, acalculia, finger agnosia, left–right confusion), though whether that cluster reflects one lesion site or the coincidental disconnection of separate pathways is disputed. Imaging also reports it in semantic processing and episodic retrieval.
Anterior temporal lobe
Lobe in the temporal lobe
The forward portion of the temporal lobe, converging on the temporal pole and heavily connected to orbitofrontal and limbic cortex.
The anterior temporal lobe covers the front of the superior, middle and inferior temporal gyri together with the temporal pole and the anterior fusiform gyrus. It sits at the end of the ventral visual and auditory streams and connects strongly to orbitofrontal cortex, amygdala and entorhinal cortex through the uncinate fasciculus. Its degeneration in semantic dementia produces progressive loss of word and object meaning across modalities, which motivated the "semantic hub" account. Whether the region is genuinely modality-general or an assembly of separable category-specific areas remains contested, partly because MRI signal here is badly distorted.
Fusiform gyrus
Cortex in the temporal lobe
A long spindle-shaped gyrus on the ventral surface, between the collateral sulcus medially and the occipitotemporal sulcus laterally.
The fusiform gyrus stretches along the underside of the temporal and occipital lobes, bounded by the collateral sulcus medially and the occipitotemporal sulcus laterally, and split lengthwise in most brains by a mid-fusiform sulcus. Its lateral mid-portion contains the fusiform face area, which responds more strongly to faces than to other objects, and nearby patches respond preferentially to words and to scenes. Whether these are domain-specific modules or the peaks of a graded map shaped by visual expertise has been argued since the late 1990s and is not settled.
Hippocampus
Cortex in the hippocampal formation
A curved allocortical structure in the medial temporal lobe whose bilateral damage reliably produces dense anterograde amnesia in humans.
A paired, seahorse-shaped fold of three-layered cortex running front to back inside the temporal lobe, connected to the rest of the brain mainly through entorhinal cortex and the fornix. What it does is genuinely contested and has been for fifty years: the human lesion literature reads it as necessary for forming new declarative memories, the rodent recording literature as a map of space, and a third position treats both as instances of binding arbitrary elements into relations. The accounts differ on which species and which task they explain best, and the question of which is right remains open.
Medial prefrontal cortex
Cortex in the prefrontal cortex
The inner wall of the prefrontal cortex, facing the midline between the two hemispheres and wrapping around the corpus callosum's front end.
The medial prefrontal cortex is the flat inner face of the frontal lobe, running from near the frontal pole back to the genu of the corpus callosum, where it meets the cingulate. It is usually divided into dorsal and ventral halves with different connections: the ventral part to amygdala, hypothalamus and brainstem, the dorsal part to lateral frontal and temporal cortex. It is a hub of the rodent memory-consolidation literature and of the human self-reference and default-mode literatures. The term is used loosely and often includes tissue another author would call cingulate.
Parahippocampal gyrus
Cortex in the medial temporal lobe
The medial temporal gyrus below the hippocampus, running from the uncus back to the isthmus of the cingulate gyrus.
The parahippocampal gyrus forms the medial edge of the temporal lobe's ventral surface, bounded laterally by the collateral sulcus and above by the hippocampal fissure. Its anterior part carries entorhinal cortex, which supplies the hippocampus with most of its cortical input through the perforant path; its posterior part is parahippocampal cortex proper, which continues into retrosplenial cortex at the isthmus. The uncus is its hooked front tip. Posterior parahippocampal cortex contains the parahippocampal place area, activated by scenes and spatial layouts; whether that response is about scenes, space, or contextual associations more generally is debated.
Posterior cingulate cortex
Cortex in the cingulate cortex
The rear section of the cingulate, above the splenium of the corpus callosum and above the retrosplenial cortex in the callosal sulcus.
The posterior cingulate cortex sits above and behind the splenium of the corpus callosum, bordering the precuneus above and the retrosplenial cortex below; its dorsal and ventral halves have different connections and different response profiles. It has one of the highest resting metabolic rates in the brain and is among the first regions to show reduced glucose metabolism in Alzheimer's disease. It is a core node of the default mode network and is engaged during autobiographical memory retrieval and imagining the future. Whether its activity reflects internally directed thought, the breadth of attention, or a more general scene-construction role is not settled.
Retrosplenial cortex
Cortex in the cingulate cortex
A small strip of cortex tucked behind and below the splenium of the corpus callosum, Brodmann areas 29 and 30.
The retrosplenial cortex lies immediately behind the splenium (the thickened rear end of the corpus callosum), buried in the callosal sulcus, and is substantially smaller in humans than its prominence in rodent work suggests. It connects the hippocampal formation and anterior thalamus with parietal and visual cortex, making it a waypoint between memory and spatial systems. Damage produces topographical disorientation in which landmarks are recognized but cannot be used for heading. Rodent and human literatures use the term for somewhat different tissue, since the human region is displaced by the expansion of surrounding cortex.
Temporal lobe
Lobe in the cerebral hemisphere
The lobe below the lateral fissure, running forward to the temporal pole and back into parietal and occipital cortex without a sharp boundary.
The temporal lobe sits beneath the lateral fissure, folded into superior, middle and inferior temporal gyri laterally, with the fusiform and parahippocampal gyri on its ventral surface and the hippocampal formation curled inside its medial wall. Heschl's gyrus, buried in the fissure's floor, carries primary auditory cortex. Its posterior boundary against parietal and occipital cortex is conventional rather than anatomical. The lobe is associated with auditory processing, object and face recognition along its ventral stream, semantic knowledge at its pole, and, through the medial structures, declarative memory.
Temporoparietal junction
Cortex
The territory where the posterior temporal lobe meets the inferior parietal lobule, named by convention rather than by any boundary.
The temporoparietal junction is the cortex around the meeting of the superior temporal sulcus, the angular gyrus and the supramarginal gyrus; it is a region of convenience with no agreed cytoarchitectonic borders, and coordinates published under the name do not converge on a single site. On the right it is central to the reorienting of attention and is damaged in most cases of hemispatial neglect; on both sides, and especially a more posterior part of it, it is among the most reliable activations in theory-of-mind tasks. Whether attention and mentalizing engage the same tissue or adjacent subregions is an active dispute.
Ventromedial prefrontal cortex
Cortex in the medial prefrontal cortex
The lower medial corner of the prefrontal cortex, where the medial wall meets the orbital surface above the eye sockets.
The ventromedial prefrontal cortex occupies the junction of the medial and orbital surfaces of the frontal lobe, covering parts of Brodmann areas 10, 11, 14, 25 and 32; its overlap with medial orbitofrontal cortex is substantial and inconsistently labeled. It is heavily connected with the amygdala, ventral striatum, and hypothalamus. Damage here (the Phineas Gage and Elliot cases, and later lesion series) produces poor real-world decisions with intact intelligence, and the region is central to the somatic marker hypothesis. Its popular description as a moral-decision region is a strong reading of weak evidence: the same tissue tracks subjective value, regulation of fear responses, and memory schemas.
Acerbi & Stubbersfield (2023)
Large language models show human-like content biases in transmission chain experiments
In
Proceedings of the National Academy of Sciences, 120(44)
Abstract
As the use of large language models (LLMs) grows, it is important to examine whether they exhibit biases in their output. Research in cultural evolution, using transmission chain experiments, demonstrates that humans have biases to attend to, remember, and transmit some types of content over others. Here, in five preregistered experiments using material from previous studies with human participants, we use the same, transmission chain-like methodology, and find that the LLM ChatGPT-3 shows biases analogous to humans for content that is gender-stereotype-consistent, social, negative, threat-related, and biologically counterintuitive, over other content. The presence of these biases in LLM...
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Brewer & Treyens (1981)
Role of schemata in memory for places
In
Cognitive Psychology, 13(2), 207-230
Abstract
A study of memory for places was carried out to examine five hypotheses about the use of schemata in memory performance: (a) that schemata determine what objects are encoded into memory; (b) that schemata act as frameworks for episodic information; (c) that schema-based information is integrated with episodic information; (d) that schemata facilitate retrieval; and (e) that schemata influence what is communicated at recall. Subjects were taken into what they thought was a graduate student's office and later were tested for memory of the room with either drawing recall, written recall, or verbal recognition. Memory scores for objects were correlated with schema expectancy and saliency...
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Cao et al. (2025)
Analyzing Memory Effects in Large Language Models through the lens of Cognitive Psychology
In
arXiv
Abstract
Memory, a fundamental component of human cognition, exhibits adaptive yet fallible characteristics as illustrated by Schacter's memory "sins".These cognitive phenomena have been studied extensively in psychology and neuroscience, but the extent to which artificial systems, specifically Large Language Models (LLMs), emulate these cognitive phenomena remains underexplored. This study uses human memory research as a lens for understanding LLMs and systematically investigates human memory effects in state-of-the-art LLMs using paradigms drawn from psychological research. We evaluate seven key memory phenomena, comparing human behavior to LLM performance. Both people and models remember less...
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Gilboa & Marlatte (2017)
Neurobiology of Schemas and Schema-Mediated Memory
In
Trends in Cognitive Sciences, 21(8), 618-631
Abstract
Schemas are superordinate knowledge structures that reflect abstracted commonalities across multiple experiences, exerting powerful influences over how events are perceived, interpreted, and remembered. Activated schema templates modulate early perceptual processing, as they get populated with specific informational instances (schema instantiation). Instantiated schemas, in turn, can enhance or distort mnemonic processing from the outset (at encoding), impact offline memory transformation and accelerate neocortical integration. Recent studies demonstrate distinctive neurobiological processes underlying schema-related learning. Interactions between the ventromedial prefrontal cortex...
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Maharana et al. (2024)
Evaluating Very Long-Term Conversational Memory of LLM Agents
In
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 13851-13870
Abstract
Paraphrase, not the publisher's wording. Prior work on long-term open-domain dialogue evaluates model responses over no more than five chat sessions, leaving the effectiveness of long-context models and retrieval augmentation in genuinely long-term conversation untested. The authors introduce a machine-human pipeline that generates high-quality very long-term dialogues by grounding LLM agent conversations in personas and temporal event graphs, with agents able to share and react to images. Human annotators verify and edit the output for long-range consistency and grounding. The resulting dataset, LoCoMo, supports an evaluation benchmark covering question answering, event summarisation,...
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Spens & Burgess (2026)
Hippocampo-neocortical interaction as compressive retrieval-augmented generation
In
Nature Communications, 17(1)
Abstract
Abstract Many aspects of learning, memory, and problem solving involve interplay between episodic (hippocampal) and semantic (neocortical) systems, but the neural mechanisms supporting this are unclear. We present a computational model in which sequential experiences are encoded in hippocampus in compressed form and replayed to train a neocortical generative network. This network captures the gist of specific episodes and extracts statistical patterns that generalise to new situations, enabling efficient reconstruction of the past and prediction of the future. The two systems interact during encoding, recall and problem solving, with the hippocampus retrieving relevant episodic...
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