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A world model supports intelligent behaviour by predicting the consequences of actions that need not be executed first. The prefrontal cortex can contribute task-state and goal control, while the hippocampus can supply relational and episodic content for constructing possible situations and trajectories. This is a division of computational requirements, not a rigid one-region-per-function scheme.

In a Markov decision process, a model can represent transitions $\hat{P}(s^{\prime }\mid s,a)$ and expected rewards $\hat{r}(s,a)$. Planning uses them to evaluate an action through a backup such asLonger searches apply the same principle across alternative trajectories. A world model can be symbolic, distributed, probabilistic or a combination; it need only preserve information relevant to the decision. In a partially observed situation, the intelligent agent must infer a state or maintain uncertainty over states rather than treating the latest image as a complete description of the world.

For a simple constructed example, suppose one action leads to food and another to water, with current outcome values $2$ and $1$. After the food is devalued to $0$, an intelligent agent that knows the action–outcome relations can immediately prefer water without experiencing the food-producing action again. A purely cached action value does not necessarily change at that moment. This demonstrates the usefulness of an internal model; it does not imply that every devaluation effect uniquely identifies one algorithm, because inferred state changes or offline value updates can also alter cached decisions.

Mental simulation can recombine remembered components into a possible future, evaluate an untried route and compare goals. It differs from simply replaying a previous trajectory verbatim. It also differs from episodic memory retrieval: simulated content may describe something that never happened. Both operations can use shared representations, so a new imagined situation need not be generated independently of memory.

The prefrontal cortex is well placed to contribute the control side of this process: maintaining the current task, selecting relevant information, representing goals and using prospective outcomes to guide action. It is heterogeneous, and activity in one subregion is not evidence that all of prefrontal cortex carries a complete internal simulator. A particularly relevant hypothesis concerns the orbitofrontal cortex: a useful decision state may depend on previous events and task rules even when current sensory input is unchanged.

A human fMRI study used superimposed face and house images with a rule determining which category to judge from the preceding task history. Different hidden task states could therefore accompany similar current inputs. Cross-validated multivariate decoding recovered task-state information from orbitofrontal cortex, and decoding fidelity related to behavioural accuracy. This supports a role in representing the situation in which values and actions are evaluated. It does not demonstrate that the decoded patterns themselves contain a complete future trajectory, and noninvasive imaging cannot identify the synaptic algorithm.^[ref]

The hippocampus provides a complementary source of spatial and relational content. A cognitive map describes relationships among locations or task states rather than only a sequence of rewarded responses. Such a representation can support a novel route when goals change, and event representations can contribute objects, locations and contextual relations to a simulated scene. Whether an internally generated sequence represents a possible future, a remembered past or a training signal must be tested rather than inferred from sequence-like firing alone.

In freely moving rats choosing journeys between food locations, hippocampal place-cell ensembles sometimes produced internally generated sequences before travel. Decoded sequences described trajectories related to remembered goals and predicted upcoming behaviour. The ordering and timing make the result relevant to prospective computation, but the recording is correlational: a sequence could reflect a prepared choice or goal-related retrieval rather than perform the decisive search itself.^[ref]

A separate intervention interrupted awake sharp-wave ripples during a spatial alternation task and impaired learning and performance. Place fields and post-experience reactivation were relatively preserved, helping distinguish the effect from wholesale destruction of spatial coding or later replay. This supports a causal contribution of awake ripple-associated processing to memory-guided decisions, without identifying every disrupted sequence as a planning calculation.^[ref]

Human lesion evidence extends the discussion beyond navigation. Patients with predominantly bilateral hippocampal damage were asked to construct new experiences from short scenario cues. Their descriptions were generally less spatially coherent than those of matched controls, despite preserved semantic retrieval; one patient performed well. The task therefore supports a hippocampal contribution to binding imagined scene elements, while the spared case, lesion selectivity and the difference between scene construction and action planning limit a universal necessity claim.^[ref]

A plausible integrated model lets prefrontal representations specify the task and current goal, hippocampal and cortical representations generate or retrieve candidate situations, and valuation and action-selection circuits compare their consequences. Communication can be iterative: candidate outcomes change what information is sought, and new observations update the inferred state. This is more specific than assigning “imagination” to the hippocampus and “intelligence” to prefrontal cortex, but remains a hypothesis about their interaction.

Planning also has costs. Long simulations can amplify model errors, and unlimited search is computationally expensive. An intelligent agent should select a useful abstraction, prioritize relevant branches and decide when a cached policy is adequate. Tests should distinguish sensitivity to reward changes from sensitivity to transition changes, and compare neural predictions before a decision rather than only after a successful action. World models enable flexible prospective control; the evidence implicates interacting state, memory and valuation processes, rather than a single anatomical seat of mental simulation.

Spatial and chemical multisensory processing share problems of binding, uncertainty, learning and common-cause attribution. They often differ in what their inputs represent: spatial cues can estimate the same location, whereas taste and odor frequently supply complementary attributes of a food. The comparison concerns particular computations and tasks, not a rigid separation between two kinds of brain.

In spatial localization, vision, audition and touch can each provide information about position, although they begin in different coordinates. Visual information is initially related to the retina, auditory location depends on binaural and spectral cues, and touch is related to a body surface. Combining them requires accounting for eye, head and body position. Spatial coincidence supports a common event, but is not sufficient: unrelated events can occur nearby, and one moving object can produce cues at different times.

A simple reliability-weighted cue integration model makes a precise prediction. Suppose $x_1,x_2$ are unbiased, independent estimates of one position, with variances ${\sigma }_1^2,{\sigma }_2^2$. An unbiased linear estimate is $\hat{x}=w{x}_1+(1-w)x_2$, withDifferentiating and setting the derivative to zero yieldsThe second derivative is positive. The minimum-variance two-cue estimate assigns greater weight to the more precise cue, and independent information reduces variance below either individual variance. With independent Gaussian noise and a flat prior, minimizing the negative log-likelihood gives the same weighted mean. Correlated errors, bias, a nonflat prior or separate causes change this benchmark.

Marc O. Ernst and Martin S. Banks measured visual and haptic estimates of object height and compared combined judgments with predictions based on unisensory variability. Manipulating visual uncertainty and cue conflict supported reliability-dependent weighting and improved combined precision in that task.^[ref] The conclusion is conditional optimality for measured inputs and task, not that every multisensory judgment or neuron always computes an optimum.

Development supplies a useful qualification. Monica Gori and colleagues measured visual, haptic and combined judgments of block size and orientation in children. Younger children did not always obtain the adult-like precision gain; the dominant modality differed between size and orientation, and adult-like combination emerged around eight to ten years in those tests.^[ref] The authors proposed a role for cross-sensory calibration. The result does not establish one universal maturation age for all multisensory tasks. It shows why adult cue-combination rules should not simply be assigned to every developing observer.

The chemical senses pose a different representational problem. Gustation responds to dissolved chemicals at taste receptors, while olfaction responds to volatile molecules; oral touch, temperature and irritation also contribute to a food percept. Retronasal odor can be attributed to the mouth through olfactory referral, even though its receptors remain in the nose. A sweet taste and a fruit odor are not necessarily two noisy measurements of one physical sweetness coordinate. They can jointly identify a food or predict nutritional and hedonic properties. Adding them with inverse-variance weights is therefore not automatically meaningful.

Nevertheless, the same inferential questions arise: do signals belong to the same food, how should prior experience affect interpretation, and which component is responsible for a judged quality? Richard J. Stevenson and colleagues' odor–taste conditioning results show that pairing an odor with sweet or sour tastes can alter later odor judgments.^[ref] Learned co-occurrence can thus influence flavor qualities. Verbal confusion or a rating change alone does not establish full sensory fusion; separate taste, odor and pleasantness scales help test response dumping.

Neural convergence is also shared without implying identical architectures. Ivan E. T. de Araujo and colleagues delivered tastes and retronasal odors separately and together during human functional magnetic resonance imaging. They identified overlapping responses in several regions and interactions in orbitofrontal cortex; some responses also covaried with consonance or pleasantness ratings.^[ref] A mixture interaction is stronger evidence than overlap alone, but an imaging voxel does not prove that every responding neuron receives both inputs. A neural correlation with pleasantness also differs from a causal explanation of food preference.

Temporal and spatial structure further distinguish typical tasks. Spatial audiovisual cues can be brief, externally localized events; food perception unfolds with sniffing, chewing, dissolution and swallowing. Taste and retronasal odor may be bound despite unlike onset profiles because their sequence is expected within eating. Chemical signals can adapt and interact at peripheral as well as central stages, while vision and audition face their own receptor and pathway nonlinearities. Neither class is exclusively early or late, automatic or attention-dependent. Attention, task instructions, hunger and learned expectations can change what is selected or reported; these influences must be measured rather than inferred from a unitary percept alone.

A decisive comparison therefore uses matched inferential questions: estimate a common property, identify a common object, or judge whether two signals share a cause. Measure unisensory performance, test cue conflict and temporal or semantic congruence, and distinguish changes in quality, uncertainty and response. Both domains integrate evidence about events; spatial averaging is a useful special case, while complementary chemical information often requires object, quality and value representations beyond a shared coordinate.