AutoSummary from ClassNotes:
Radical Embodied Relation at any Scale, from Remembering to Navigating (by Hiott, 2025) and Ecological Memory (2022)
Overview
This philosophical and neuroscientific paper challenges fundamental assumptions about neural representations in cognitive science. Hiott argues that recent hippocampal research forces us to reconcieve representations not as "findable" objects stored in brains, but as communicative assessments scientists create to understand dynamic, embodied processes. Ecological Memory is a wider understanding of memory as immediate and communicative from body to body and body to world and understands locomotion and mind as ways made towards continuance. The basic ideas presented in EM are: 1.that cognition is continuous with navigation (which means navigation itself can be understood as pre-reflective cognition); 2. that taking this seriously changes our understanding of landscape in ways that require non-binary vocabularies (i.e. using terms like 'mental' and 'physical' as dichotomies is no longer a productive strategy); and 3. the orientation and methods of cognitive neuroscience could be optimised by an ecological approach which looks at scales of complexity rather than stimulus-response and metricizes the experiment itself so it becomes part of the data and analysis.
Central Thesis of (2025) paper
The paper's core claim is provocatively simple yet counterintuitive: neural representations exist, but not in brains. Rather, they are communicative tools—like weather maps representing weather patterns—that help us understand ongoing brain-body-environment interactions that cannot be absolutely located or represented.
The Hippocampal Shift
Hiott builds her argument around recent discoveries in hippocampal research. The hippocampus, long associated with memory formation, was discovered in the 1970s to also function as the brain's "GPS," crucial for spatial navigation. For decades, scientists treated these as separate functions. However, contemporary research reveals they are the same underlying process assessed differently:
When we remember, we navigate "conceptual space"
When we navigate physically, we move through geographical space
Both involve the same hippocampal mechanisms of positioning and pattern-matching
This finding undermines traditional dichotomies between mental (cognitive) and physical (locomotive) processes. As Hiott puts it, we "think in the same way we navigate"—by habitually aligning with regularities encountered through sensory experience.
Way-Making: A Unifying Framework
To escape either/or binaries, Hiott introduces "way-making" as a term encompassing both traditionally "cognitive" activities (thinking, remembering, imagining) and "locomotive" activities (navigating, wayfinding). Way-making reframes cognition as the ways any designated body moves through its ongoing encounter—whether that encounter is a physical landscape, a conversation, a memory, or abstract thought.
This framework eliminates hierarchical assumptions (that "higher" cognition requires different mechanisms than "basic" navigation) and instead treats these as different scales of assessment of a continuous embodied process. The body develops its ability to "make way" through conceptual terrain using the same fundamental processes by which it learned to crawl toward a cookie jar.
Representations as Communication, Not Storage
Traditional neuroscience has long assumed neural representations are stored engrams—essentially hieroglyphs inscribed in brain tissue. Hiott argues this conflates our communicative tools (fMRI images, neural firing patterns, cognitive maps) with the dynamic processes they represent.
She draws an analogy to weather: We don't search for "70 degrees" inside the weather itself; rather, we create weather maps as representations to communicate about atmospheric dynamics. Similarly, neural representations are not in brains but are assessments scientists make of ongoing brain activity. These representations are real and useful—"adequate for purpose"—without requiring location within the brain.
This view aligns with recent critiques in neuroscience that warn against confusing observer perspectives with what is observed (as noted by researchers like Buzsáki and Brette). The representations we create to study memory or navigation are necessarily static and localized for communication purposes, but the living processes they represent are continuous, dynamic, and unlocatable.
Challenging the Scaling Problem
Radical embodied cognitive science (REC) has long questioned whether its anti-representationalist approach can "scale up" to explain complex cognition like imagination or abstract thought—the so-called "representation-hungry" problem. Hiott's solution is elegant: all scientific assessments are representation-hungry because representation is how we communicate understanding.
However, the representations remain communicative rather than engrammatic. There's no hierarchy where navigation is "basic" and episodic memory is "higher." Instead, these are different positions from which we assess the same embodied process of making way through encountered regularities. The body doesn't "have" levels or scales; we create those divisions through our assessments.
Implications for Cognitive Neuroscience
This reconception requires abandoning the search for locatable memory traces while still using neural representations as research tools. Scientists can continue mapping brain activity patterns without assuming those patterns are stored as discrete units. The patterns emerge from continuous agent-environment interaction—what Hiott describes as the body's ongoing "habituation of regularities."
When we study memory, we assess how bodies position current sensory input relative to all previously encountered regularities (their path-dependency). When we study navigation, we assess similar positioning in geographical space. Both are real phenomena studied through representations, but neither requires findable engrams.
Philosophical Foundations
Hiott draws on radical embodiment, ecological psychology (Gibson's affordances), process philosophy, and Daoist concepts of "way-making." Her approach avoids collapsing into either pure substance or pure process metaphysics. Instead, she holds the tension: representations are simultaneously real (as communications) and illusory (as supposedly located entities).
This parallels the observation that we can use representations to understand there are no representations in the traditional sense—stored, locatable mental objects. The goal is moving beyond either/or thinking (either we have internal representations or representation is meaningless) toward understanding representations as interactional and communicative throughout.
Conclusion
Hiott's paper offers a radical reorientation for cognitive neuroscience. By taking hippocampal research seriously, we must acknowledge that memory and navigation share mechanisms, that cognition and locomotion are continuous, and that neural representations are communicative assessments rather than findable brain contents. This preserves the usefulness of representation in science while avoiding misleading searches for "memory engrams" or cognitive maps literally inscribed in neural tissue.
The framework suggests new experimental paradigms focused on dynamic agent-environment interaction rather than isolated internal processing. It also extends radical embodiment beyond simple perception-action couplings to encompass the full range of human cognitive abilities, all understood as ways bodies make through their encounters—whether navigating cities, conversations, or memories.
Going Deeper:
https://link.springer.com/article/10.1007/s11245-025-10256-7
1. What the paper is about
At a high level, the paper argues that:
Traditional cognitive-science and neuroscience tend to treat memory and navigation as separate: memory = “thinking/mental” and navigation = “moving/physical”. Hiott argues these are not so separate. SpringerLink+1
New neuroscientific work on the hippocampal formation (brain region often associated with both memory and spatial navigation) shows that the processes underlying “remembering” and “navigating” share deep dynamics. SpringerLink
From this she deploys a notion of “way-making” (or the body making its way through environments, broadly conceived) to unify cognition (thinking, remembering) and locomotion (moving, navigating) under a single embodied and ecological process. SpringerLink
She criticizes the idea of representations (in brains, as discrete “things”) being located/stored within the brain. Instead, she suggests representations should be understood as communicative assessments of ongoing embodied agent-environment interactions. SpringerLink
The result: a “radical embodied relation” that works at any scale — be it bodily locomotion through a city, remembering one’s past, imagining one’s future, navigating conceptual/affective spaces.
So the paper’s aim is to shift how we conceive cognition (and mind) so that movement, embodied interaction, environment, and scale are integral—not as “add-ons” but as constitutive.
2. Key concepts & how they function
Here are some of the key terms and how Hiott uses them:
Way-makingShe defines “way-making” as the activity of a body making its way through an encounter (whether spatial, conceptual, social). It includes what we normally call remembering, imagining, navigating. (Source: SpringerLink and Author Writings ). It gives a unified term to link cognition and locomotion; helps avoid traditional dichotomies.
Representation Hiott argues that representations are not “things inside brains” that you find, locate and store. Instead: they are communicative, interactional, assessments of regularities in the agent-environment system. SpringerLink
This is a radical move in embodiment/ecological cognition debates: avoids the “mind as computer” metaphor.
Scale / ScalingThe issue of moving from “low” to “high” cognition (from simple sensorimotor to memory/imagining) is framed here as a matter of assessment scales rather than hierarchical levels. SpringerLink and EM DOI
Helps dissolve the “higher cognition = different mechanism” assumption.Embodied & ecological (radical embodiment)The paper situates itself in the tradition of radical embodied cognitive science (REC) — cognition embedded in bodily, environmental, relational processes. PhilPapers+1Establishes the theoretical background: cognition is not just neural, internal, abstract.
3. The argument flow (roughly)
Here’s how the paper proceeds:
Introduction — sets up the problem: the familiar separation between mental (memory, thinking) and physical (locomotion, navigation). Mentions how these familiar forms may mask deeper continuity. SpringerLink
“An Unusual Approach to the Familiar” — frames the key insight: newer hippocampal research shows navigation and memory share work (cells, maps, etc). So the mental/physical dichotomy is under pressure. SpringerLink
Way-making — introduces the term, describes how way-making can conceptually unify remembering and navigating as “making way” through some domain (spatial, conceptual) by the body in its movement/encounter. SpringerLink
Hippocampal formation re-viewed — uses that neuroscience example to illustrate how memory and navigation are integrated: e.g., place cells, grid cells, “cognitive map” concept. She argues the cognitive map should be reframed as communicative rather than a literal internal map. SpringerLink
The Way of Radicality — connects to the broader radical embodiment tradition: how this way-making approach helps to move beyond the mental/physical (and other dualisms) and also handles representations differently. SpringerLink
Conclusion — draws out the implications: we can have representations (they are real) but they aren’t “findable things” in the brain; cognition is continuous movement/interaction; we assess at different scales rather than assume levels. SpringerLink
4. Why this matters (and what it contributes)
It bridges neuroscience and philosophical/embodied cognition: many embodied cognition theories focus on perception/action; Hiott brings in memory/navigation neuroscience to enrich and challenge them.
It proposes a conceptual innovation (“way-making”) which might help researchers across disciplines talk coherently about cognition and locomotion, remembering and navigating, without assuming they’re fundamentally different.
It challenges representation assumptions: Instead of the search for an internal “map” in the brain, we rethink what a “map” does — as interactional/assessable rather than stored.
It offers a non-hierarchical view of cognition across scales: whether we’re remembering the past, imagining the future, hiking the trail, or navigating social space — they all involve making way in some domain.
It helps dissolve classic dichotomies (mind/body, mental/physical, high/low cognition) by shifting perspective to embodied relational dynamics.
5. How you might understand/apply it
Here are suggestions for reading and applying:
When you see “memory” think not just of a mental event (in brain) but of a bodily-environmental process of “making way” through past regularities.
When you see “navigation/wayfinding,” think not just of walking in space but as navigating conceptual, social, emotional spaces — similar processes.
Ask: What are the agent-environment regularities here? What body is making its way? What representations (if any) are communicative assessments rather than stored objects?
Use “scale” thinking: Instead of “lower body movement → higher thought”, think “different scales of the same embodied process”.
In empirical neuroscience or cognitive science: if a brain region is associated with both memory & navigation (e.g., hippocampus), don’t assume “this region supports thinking” vs “this region supports movement”; look for embodied way-making dynamics.
For philosophy of mind: This is a strong argument for redefining “cognition” beyond internal symbol-manipulation to embodied relational movement.
6. Possible questions / critiques & Hiott’s answers
If representations are not locatable in brains, how exactly do they function in agent-environment processes? Hiott answers: they are communicative assessments. But one might ask: how do we model this scientifically? Hiott answers: We already are. The point is to shift the prism through which we see our current ways of doing experiments and develop more nested models of how we understand what till now we have been trying to solve into one another (i.e. memory and navigation, mental and physical, or stimulus and brain representation).
Are the ‘scales’ (conceptual, spatial, emotional) truly the same process of way-making, or is there still meaningful difference? Hiott answers that waymaking is the term that is all of it. Push back: But if there are different assessments, doesn’t that mean there are still qualitative differences? Hiott answers: yes, but they are differences relative to what landscape of regularities is being assessed. It makes no sense to say way-making as differences to itself, but we also cannot study waymaking as a whole for many reasons such as that it has no findable beginning or end and such as that we are part of it. But we can assess our navigability in particular landscapes (conceptual, spatial, emotional, etc.) and this requires that we respect that there are qualitative differences. The new thing this view demands is that we stop trying to say either qualitative or quantitative and instead realize we much use metrics to discuss model the qualitative differences without thinking we have somehow captured the whole of anything. That is the idea of holding paradox so crucial to Hiott’s paper and argument, and also the hardest to fully grasp. I would recommend watching the interviews she does with philosophers and neuroscientists about this on YouTube or listening to them in some form of podcast. She skilfully demonstrates this and shows each guest how it applies to their own work, though she does this by championing the guest and their work rather than her own, so you have to look for this pattern, though it will be clearer once you have understood the ideas above.
How much of neuroscience (e.g., place/grid cells) can be reinterpreted in this way without losing explanatory power? Hiott says: all of it. And we must redesign experiments as nested and scaled in the sense expressed in the paper rather than assuming the pinpoint the physical and look for the cause inside the body hierarchical scale. Hiott is offering that rather than looking to solve binaries (which is at the heart of old representation debates) we explore the patterns they show us from irresolvable positions and see what those tells us about what is holding both of them. In terms of neuroscientific studies, this is already being validated by new papers such as the one by Peng et al., 2025 which shows that grid cells are not just global metrics but shifting frames of translation, which can best be understood through the sort of ideas presented in Hiott’s work, both here and elsewhere.
What are the empirical predictions of the “way-making” model versus traditional models of cognition/memory/navigation? Hiott predicts that rather than the current paradigm whereby different sorts of scientific approaches try to compete about which is correct, we will shift to a model of what she calls ‘kaleidoscopic cognition’ which does not try to solve sides into one another but looks at them through a constellatory form of modelling that allows them each to contribute something unique. Competitions still motivate in such a paradigm but not against one another but towards the most exciting contribution. Hiott also predicts that we will find ways to metricize the experiment itself so as to be able to do assessements of different landscapes.
How does this approach fit with other embodied/enactive theories that still allow for some internal representation or structure? (E.g., how does it compare with predictive processing, or extended mind theories?) Hiott has explored this in conversations with the leading philosophers and neuroscientists of those approaches, so you can hear or see this for yourself if you research those. The short answer is: Hiott is not part of any one tradition but sees way-making as a philosophical approach that has learned from all sides, though there is no doubt she aligns closely with 4e cognition, and her paper is coming from radical embodied cognitive science. She also cites Varela, Thompson, and Hegel quite often. In this particular paper, she aligns most with RECS. The central concept is that all cognitive processes, from basic navigation to complex memory and thinking, arise from a fundamental, direct, and dynamic relation between an organism's body and its environment, at every possible scale of interaction.
Key aspects of the argument:
Anti-Representationalism: Hiott argues against the need to invoke internal mental representations to explain "real cognition". Instead, behavior is an ongoing, dynamic interaction between the organism and its surroundings.
Embodiment and Embeddedness: The paper emphasizes that cognition is not an abstract, brain-bound process, but is fundamentally shaped by the physical body (morphology and physiology) and its direct interaction with the environment.
Scaling Up: The theory proposes that these principles of embodied interaction apply at various levels of complexity ("at any scale"), from individual sensorimotor loops to potentially social and global interactions.
Non-ideal Theory: The work is part of a broader movement within RECS to move from abstract "ideal theory" to "non-ideal theory," recognizing that cognitive processes are shaped by concrete factors like gender, race, and ability. This involves making theoretical assumptions explicit and acknowledging the diverse ways embodiment shapes experience.
In essence, Hiott is proposing a framework where the distinction between the cognitive agent and the world is less about a mind representing an external reality and more about an organism participating in a direct, continuous, and multi-scaled relationship with its environment.Here is what she writes elsewhere about how to fit these into other traditions:
Way-making is a general term for a new approach to philosophy.
As a term, it offers an alternative to binary linguistic assumptions and either/or choices in the philosophical and cognitive sciences. It does this by holding contrasting sides without trying to be rid of one or the other, allowing that from each position, there are distinctions that are irreconcilable. It also acknowledges that there is a space holding these conflicting positions—a dynamic process beyond those contrasts that also allows them.
When we stop trying to dissolve one side into the other, when we stop trying to force one side into the winning position, we may find that further contradictory nodes open beyond what first felt like binaries. The point is not to stop the discussion and debate, but to orient it out of the loop of competing philosophies and towards common challenges that philosophical thinking addresses in unique ways.
So, for example, we can use the term way-making to point to the process that is holding both ‘mental’ and ‘physical’ in traditional philosophical and neuroscientific discourse without losing the meaning of those terms. Instead, they become ways of assessing what is held in common process.
Similarly, and directly related to my work with the hippocampus, we can discuss ‘our locomotion’ and ‘our thinking and imagining’ as ways we make, ways which are irreconcilable assessments (as we measure), but which are also held as the same dynamic process (as they happen). See here for more.
In other words, we can discuss ‘mind’ and ‘body’ as different ways we make to understand this ongoing movement, a movement which is both ‘us’ and what we are assessing, even as it holds both. We can do this for any two terms that represent oppositional assessments.
This is way-making. It takes a bit of getting used to, which is partly the point—it is itself a practice gently moving us into another realm of movement and perception, without destroying our usual ones.
Section-by-section summary of (Hiott, 2025)
Introduction: Hiott begins by pointing out a longstanding divide in cognitive/neuroscientific philosophy between “mental” processes (e.g., memory, thinking) and “locomotive/spatial” processes (e.g., navigation, wayfinding). She points to recent neuroscientific work on the hippocampal formation as prompting reconsideration of this divide. SpringerLink+1The stage is set: familiar dichotomies (mind/body, memory/navigation) are under challenge.
Re-viewing Memory & Navigation (Hippocampal formation)In this section she reviews neuroscientific findings regarding the hippocampus (and related cells like place and grid cells) showing that what we often treat as separate (memory vs. navigation) may share mechanisms or dynamics. The idea of the “cognitive map” is discussed and reframed. SpringerLink+1Neuroscience provides empirical motivation for rethinking cognition as more broadly embodied, relational, moving through “space” (broadly construed).
Way-Making: A Conceptual ShiftHiott introduces the term way-making, derived from Daoist/complexity science inspirations. She argues that cognition, remembering, thinking and locomotion are all instances of a body (or agent) making its way through an encounter (whether spatial, conceptual, environmental). SpringerLink+1Way-making gives a unifying conceptual term: rather than separate categories (memory vs. navigation), we have one process assessed differently.
Representation & Scaling ReconsideredHere she tackles issues of representation (what are “maps,” “internal models,” etc?). She argues that representations should be thought of as communicative assessments of agent-environment regularities, rather than stored things inside the brain. She also addresses “scaling” (how cognition at small scale vs large scale differ) by saying the difference is in assessment and metrics, not necessarily in fundamental mechanism. SpringerLink+1This challenges standard cognitive science assumptions (internal representations, levels of cognition) and reframes them in embodied relational terms.
Radical Embodied Relation & ImplicationsHiott embeds the above within the tradition of radical embodiment / ecological cognitive science (REC). She argues that way-making helps us move beyond the “mental/physical” split, mind/body dualism, and offers an orientation that sees cognition as continuous with movement, environment, organism. She draws out implications for neuroscience, philosophy of mind, perhaps memory disorders or embodied technologies. SpringerLinkThe theoretical shift: cognition is not “in” the brain only, but in the relational dynamics of body, environment and encounter; this has wide implications.
ConclusionHiott summarizes the argument: memory and navigation can be understood as different assessments of the same embodied process; representations exist (and are real) but they are interactional/communicative, not stored objects; cognition is way-making at any scale. She invites further research in cognitive neuroscience (e.g., cerebellum) and other domains with this lens. SpringerLinkThe takeaway: we should reconceive how we study cognition, mind and movement; there’s a path forward for interdisciplinary work bridging neuroscience, philosophy, embodiment, ecology.
Important quotes / passages to note:
“Way-making reorients what we understand as cognition such that ‘introspecting’, ‘thinking’ or ‘remembering’ can be understood as agent-environment dynamics … in the same way … as locomotion …” SpringerLink
“Representations are the ways we communicate those assessments … they are real, and they are interactional.” PhilPapers+1
“… so neural representations are not in brains but of them.” SpringerLink
How to read it:
Pay attention to how she uses neuroscience (hippocampal research) as a heuristic model rather than a strict physical model.
Notice the shift from “levels” (lower motor, higher thought) to “scales/assessments” (different ways of measuring the same dynamics).
Consider how the concept of “way-making” works: when you remember a past event, take a walk, plan something, you’re “making way” in some space (temporal, conceptual, physical).
Think about representations: rather than “maps stored in brain”, we have patterns of interaction with environment that can be communicated.
Reflect on implications: for research (e.g., study of memory disorders might benefit from thinking of memory as embodied navigation), for design (technology/transportation) and for how we view self, mind, and body.
Other people / work doing similar stuff
Here are some other scholars and works you might like, who operate in a similar “embodied/ecological cognition” space:
Anthony Chemero — Radical Embodied Cognitive Science (2009) is a foundational work arguing for cognition as embodied, rejecting traditional internal representation models. PhilPapers+1
Evan Thompson — Mind in Life: Biology, Phenomenology, and the Sciences of Mind (2007) explores how life and mind connect in embodied/phenomenological terms. PhilPapers
Shaun Gallagher — In enactivist and embodied cognitive science, works on sense-making, body, environment.
Hanne De Jaegher & Ezequiel Di Paolo — They work on participatory sense-making in enactive cognition (social-environmental dynamics).
Work on minimal cognition / ecological neuroscience: For example, reviews like “The embodied brain: towards a radical embodied cognitive neuroscience” explore organism-environment systems. PubMed
You might also look into the “4E cognition” literature: embodied, embedded, enactive, extended cognition (these are frameworks that fit well with Hiott’s orientation).
C. How to connect these works
Use Hiott’s “way-making” as a concept that overlays and extends many of these embodied/4E frameworks. It gives a way to talk across domains (from navigation to memory to conceptual thought).
Compare how different scholars handle representation: Hiott emphasises communicative assessments; others (like Chemero) debate whether any internal representations are needed at all.
Use the ecological/embodied lens to examine different kinds of cognition: human memory, animal navigation, plant intelligence (this links back to earlier discussion with Paco Calvo).
Think about scale: Hiott emphasises “at any scale” (from movement in a city to thinking about a concept). Many embodied cognition works focus on one domain (e.g., motor action) — Hiott’s aim is broader.
"Kaleidoscopic cognition" is a key concept that provides a metaphor and framework for the theory outlined in Hiott's paper, Radical Embodied Relation at any Scale.
Here's how they relate:
The Metaphor: Hiott uses the kaleidoscope to illustrate a non-representational view of how the mind works. Just as a kaleidoscope creates infinite, complex patterns from simple elements (colored beads, mirrors, light) through continuous physical movement and rearrangement, cognition is the process of generating meaning through ongoing, dynamic interaction between the organism's body and its environment. The "patterns" are not stored internally as fixed images (representations), but emerge and shift in the flow of experience.
Holding Paradox/Beyond Dichotomy: A core aspect of kaleidoscopic cognition is the ability to "hold seemingly contradictory notions in mind at once" or perceive beyond simple binaries (e.g., mind/body, self/world). The Radical Embodied Relation paper addresses this by proposing a framework where the organism and environment are mutually constitutive and in continuous relation, rather than separate entities acting upon one another.
"Interactive Assessments" and "Prismatic Perception": The paper discusses "interactive assessments" as the alternative to "neural representations". This is a more formal term for the dynamic process described by the kaleidoscope metaphor. Elsewhere, Hiott refers to this as "prismatic perception," which involves sensing how patterns shift as one moves and interacts with the world, moving beyond "doubling" (seeing things in only two, opposing ways).
"Way-making" as the Process: "Way-making" or navigability is central to the paper's argument that cognition is continuous with locomotion. Kaleidoscopic cognition is the experience of this way-making — the emergent, rich, and ever-changing flow of perception and action as we navigate our physical and conceptual landscapes.
Emphasis on Dynamic Potential: In both concepts, the focus is on the dynamic potential for meaning creation through relationship and movement, rather than the storage and retrieval of static information. This shifts the focus from the brain as a computer to the whole organism as a dynamic, interactive system.
In short, Radical Embodied Relation at any Scale provides the formal philosophical and scientific argument for a process that Hiott describes metaphorically as "kaleidoscopic cognition."
how this reorients or solves old problems
This way of reframing it all via “representation as communication” solves several long-standing conceptual problems in hippocampal neuroscience and memory theory. These are problems that have troubled the field for decades, and Hiott’s view resolves them in an interesting and elegant way.
1. The “Where Is the Map Stored?” Problem
The problem:
Cognitive map theory implies that the hippocampus must ‘contain’ something like a map — a structure with stable coordinates or stored relationships.
But neuroscience has consistently shown:
* hippocampal “maps” change rapidly with context, goals, perspective
* place fields drift
* maps remap with subtle environmental changes
* the same neuron participates in multiple different “maps”
* map-like activity appears in non-spatial tasks (social space, conceptual grids)
→ This makes the ontology of a single stable “map stored in hippocampus” almost impossible.
Hiott’s solution:
If a representation is a ‘communication’ — a tool for describing interactions — then it ‘does not need to exist as a stored object’.
Nothing in the brain needs to ‘contain’ the map.
Instead, neural activity participates in patterns that ‘we describe using map-language’.
The “map” lives at the level of description, not as an object inside the skull.
This dissolves the storage-location puzzle entirely.
2. The “One-Neuron, Many-Maps” Problem
The problem:
The same hippocampal neuron can be:
* a place cell in one environment
* a sequence cell in another
* part of a social map in another
* represent a goal location in another
* encode time in a memory task
This is deeply inconsistent with the idea that neurons ‘store’ specific map-elements.
Hiott’s solution:
If a representation is a communicative description of interaction, then:
* the same neuron can participate in different communications
* the meaning of its firing depends on the *scale and context of assessment*
* the “representation” emerges from organism–environment coupling, not intrinsic stored content
No more need to fit neurons into fixed representational roles.
3. The “Non-Spatial Hippocampus” Problem
The problem:
The hippocampus clearly codes socioeconomic status, relationships, concepts, sound-source locations, abstract task variables, and logical relations — not just space.
This stretches the spatial map metaphor almost beyond usability.
Hiott’s solution:
Representation = communication about structure or relation
→ not limited to physical space
→ not limited to internal models
So whether hippocampal activity reflects:
* spatial layout
* social relationships
* conceptual axes
* temporal sequences
* reward structure
* body position relative to affordances
…it is all ‘the same kind of thing’:
patterns of embodied way-making described using different scales.
She unifies disparate hippocampal functions without forcing them into a single spatial mold.
4. The “Replay as Stored Memory” Problem
The problem:
Replay looks like memory recall — but:
* replay often generates ‘novel’ trajectories
* sometimes it predicts future actions
* sometimes it represents paths the animal didn’t actually take
* replay sequences shift with motivational state
* and preplay can occur before the experience happens
This contradicts a view of replay as “retrieving stored maps.”
Hiott’s solution:
If representations are ‘communications’ about ongoing or possible action patterns, replay becomes:
* not memory retrieval
* but ‘evaluative way-making’
* a communicative scaffold for exploring options, outcomes, contingencies
Replay becomes a ‘predictive, embodied assessment’ rather than an extraction of stored content.
This fits the data far better.
5. The “Encoding vs. Interaction” Problem
The problem:
Neuroscience keeps struggling with whether the hippocampus:
* encodes information
* stores information
* indexes information
* relates information
* retrieves information
* simulates possibilities
* or is part of a dynamic system coupling organism and environment
These can conflict.
Hiott’s solution:
All of these become ‘different communicative framings’ of:
> the embodied interaction between an organism and its environment across different scales.
Encoding is how neuroscientists talk about a pattern.
Simulation is how they talk about another pattern.
Storing is how they talk about a long-term pattern.
None of these imply that the brain contains literal stored objects.
It cuts the knot instead of tightening it.
---
# 6. The “Is the Cognitive Map Really a Map?” Problem
Neuroscientists have never agreed whether the hippocampal “map” has:
* metric structure
* topological structure
* coordinate structure
* no structure
* multiple structures
* flexible structures depending on task
Hiott solves this by saying:
> The “map” is not an object; it is a way of describing organism–environment relations at a certain scale.
So of course its form depends on scale, context, task, embodiment, affordances, etc.
No single structure is expected.
7. ‘Conscious vs. Unconscious Memory Divide’ Problem
Philosophers and neuroscientists struggle to explain whether hippocampal representations are:
* conceptual
* perceptual
* imagistic
* unconscious
* conscious
* spatial
* narrative
Hiott’s reframing says:
> These are different ‘communicative descriptions’, not different internal kinds of memory-stuff.
Thus the traditional taxonomy “in the head” dissolves.
Memory becomes a ‘scale of way-making’ rather than a thing with discrete types.
Why this Reframing Actually Solves Things
Because she declutters the ontology:
* stops reifying maps
* stops reifying representations
* stops treating hippocampal codes as stored objects
* stops forcing spatial, conceptual, or relational content into strict categories
and instead:
* treats all representational language as communication
* treats hippocampal or HEF activity as participation in ongoing embodied processes
* treats memory and navigation as two ‘manifestations’ of way-making at different scales, there can be others, thus the ‘constellatory’ nature of it all
This gives neuroscientists:
* all the freedom to model and talk as they currently do
* ‘without the conceptual contradictions’ inherent in representational realism precisely because of allowing seeming contradictions
It’s an elegant philosophical fix that aligns with cutting-edge empirical data.
models
The reframing (“representation = communication”) reshapes or clarifies the main computational models used in hippocampal neuroscience.
This is especially interesting because many of these models ‘lookÄ highly representational in the classical sense. But with Hiott’s reinterpretation, they gain coherence and lose several conceptual tensions.
We can look at the different models of this together. I put it into Python to make it as an outline below.
2. How Hiott’s View Impacts Computational Models of the Hippocampal–Entorhinal System
Model 1: Attractor Network Models (Grid Cells, Place Cells)
Classical view:
Grid cells implement a metric coordinate system via attractor dynamics.
Place cells read out a location in that system.
→ The model is treated as if it ‘literally’ implements an internal spatial map.
Problems (longstanding):
* Grid distortions break metricity
* Place cells shift with attention, goals, and body orientation
* Same circuits represent non-spatial domains
* Remapping destroys the idea of stable maps
Hiott’s reframing:
> The attractor dynamics are ‘not an internal coordinate map’
> They are ‘patterns of communication’ about regularities in the organism’s engagement with space, movement, and environment.
Under this view:
* A “stable attractor state” is a ‘communicative shorthand’ for a stable organization of organism–environment coupling.
* Drift and remapping are not failures of a metric map; they are ‘changes in communicative context’.
* Non-spatial attractors become perfectly natural — the same dynamics describe different patterns of embodied relation.
→ This turns attractor dynamics from “internal geometry simulators” into ‘interactional regularity compressors’.
---
Model 2: Successor Representation (SR)
(This is currently one of the most influential models of hippocampal function.)
Classical view:
The hippocampus stores predictive maps of future state occupancy (“if I am here, what states will I likely visit next?”).
This is used to explain:
* grid cell patterns
* place transitions
* replay sequences
* planning
Problems:
* SR implies a fixed state-space, but hippocampal maps change with task demands.
* SR representations are supposed to be stable, but hippocampal codes reorganize all the time.
* SR presumes that the “representation” is a stored data structure.
Hiott’s reframing:
> SR isn’t a stored internal map.
> It’s a **way we communicate** about how neural activity reflects behavioral regularities and possibilities.
This makes a huge difference:
* The “state space” is not a literal internal structure — it is whatever pattern of organism–environment interaction we choose to describe.
* SR’s predictive relationships reflect **embodied affordances** (possible paths, actions), not a fixed internal graph.
* When SR changes rapidly (e.g., new goals), that is not a glitch — it is a change in **the communicative frame**.
→ Under Hiott’s view, SR is a *useful mathematical compression of embodied way-making*, not a stored predictive map.
Model 3: Path Integration Models
Classical view:
The entorhinal cortex integrates self-motion signals to update an internal estimate of position.
Problems:
* Path integration drifts
* Animals rely on landmarks much more than expected
* Path integration circuitry is more flexible and context-dependent than models assumed
* Same circuitry participates in conceptual tasks
Hiott’s reframing:
> Path integration is not “integrating motion into a map.”
> It is a dynamic **communication about ongoing movement and embodied orientation**.
So drift is not a failure of internal modeling — it is a shift in bodily-environmental coupling.
Landmark dependence is not a patch — it is intrinsic to the relational nature of way-making.
Participation in nonspatial tasks is expected — because path integration is fundamentally a *relational process*, not a map-updating algorithm.
Model 4: Graph-based or Topological Models
These include models in which:
* place cells encode nodes
* transitions encode edges
* space is represented topologically (connectivity, not metric distance)
Problems:
* Hippocampal graphs reorganize depending on the animal’s goals
* Abstract tasks yield graph-like firing patterns as well
* Social networks also look like topological maps
These raise the question:
**What is the graph “of”? Space? Task? Relation? Anything?**
### **Hiott’s reframing:**
> A graph is simply the structure we impose on a pattern of embodied relations.
So:
* A spatial graph becomes a **communication about environmental affordances**
* A social graph is a **communication about relational affordances**
* A conceptual graph is a **communication about inferential affordances**
All graphs are communicative abstractions.
None are “internal maps of that domain.”
This dissolves the “multiple type problem” (spatial vs conceptual vs social maps) that plagues current theories.
Model 5: Reinforcement-Learning / Planning Models
(including Monte Carlo tree search models, or hippocampal forward planning models)
Classical view:
The hippocampus simulates future trajectories during replay to optimize decisions.
Problems:
* Replay often simulates irrelevant or never-taken paths
* Replay can encode entire task structures, not just navigational plans
* Replay depends on motivational state, not physical structure
* Sometimes replay happens in “reverse” or “offline” ways
Hiott’s reframing:
> Replay is not simulation of a stored model.
> It is communicative evaluation of possible ways of going on— at different scales.
This captures:
* forward replay (possible paths)
* reverse replay (recent paths as assessments)
* offline replay (evaluations with no spatial interpretation)
* abstract-replay in conceptual tasks (assessment of relational possibilities)
Planning becomes a ‘scale of way-making’, not an internal search algorithm.
What Hiott Does for Models
She does not eliminate computational models.
She keeps them but changes their ontological commitments:
Instead of:
> “The brain stores and manipulates representations like a computer.”
It becomes:
> “Neural dynamics express patterns of embodied relation;
> computational models describe these patterns;
> and ‘representation’ is our shorthand for those communications.”
These models become:
* phenomenological tools
* mathematical lenses
* structured ways of describing interactional dynamics
rather than literal descriptions of stored objects or internal maps.
Why this helps the field
Hiott’s reframing solves the biggest chronic issues in computational neuroscience:
How can a stored map also be flexible?
→ It isn’t stored. “Map” is a communicative model.
Why does the same circuit implement spatial and non-spatial tasks?
→ Because representations are patterns of communication, not domain-specific objects.
Why do models that assume stable structure work even though the brain is unstable?
→ Because stability is a property of our communicative model, not necessarily of the system.
Why do different models (grid attractors, SR, path integration, topological graphs) all work?
→ Because they describe *different scales or aspects* of way-making, not different “contents.”
Hiott gives computational neuroscientists a conceptual framework that ‘preserves their models and math’,
but removes the metaphysical burden that caused decades of confusion.
Hiott Still Embraces Computational Neuroscience so this opens a different discussion beyond either/or
— Hiott accepts computational modeling but rejects representational ontology.
She does rejects representational realism
* She rejects the idea that there are “representations in the head.”
* She rejects the idea that a cognitive map is an internal thing.
* She rejects “encoded content” as a metaphysical substance.
This is ‘a semantic re-interpretation of representational language’, not its abolition of it.
For Hiott:
Representation = ‘communication’
→ not symbol
→ not storage
→ not literal content
→ not intrinsic structure
→ not a thing one could point to in tissue
This lets her keep ‘computational models’ while discarding the problematic ontology.
Hiott explicitly embraces computational modeling.
Hiott insists that hippocampal mechanisms matter deeply and should be modeled.
Hiott endorses representational vocabulary — with a reinterpretation.
Hiott emphasizes multi-scale communication.
Her focus on scaling, assessment, and communicative patterning doesn’t map onto enactive autonomy frameworks.
Hiott aims to ‘clarify and support’ computational neuroscience by fixing its philosophical assumptions. |
Hiott is not enactive but deeply inspired by many in that tradition and often cites them.
She is ‘post-representational’, not anti-representational.
Her work is more like the following except via using hippocampus data and research, which is a new take:
* Ruth Millikan (but anti-realism about content)
* Andy Clark (but without the extended-representations thesis)
* Wilfrid Sellars (theory as communicative practice)
* Wittgenstein (meaning-as-use adapted to neuroscience)
She is offering a ‘conceptual clean up project’, not a revolution.
F. The Unique Middle Path Hiott Carves Out
We might summarize her stance as:
> Computational modeling is good.
> Neural mechanisms are real.
> Representational language is useful.
> Representations themselves are not stored internal things but communicative lenses for describing embodied interactions across scales
This lets her avoid:
* the metaphysical problems of classical representationalism
* the methodological anti-neuralism of enactivism
* the anti-computational stance of some radical embodied camps
* the reductionism of pure map-based theories
In effect, she gives neuroscientists permission to:
keep all their tools and all the ways they use langauge in their papers, but resense the data of those at the same time
but reinterpret what their tools ‘are about’
Hiott’s framework sits at the intersection of computational neuroscience, philosophy of mind, and AI:
It endorses computational modeling (good for AI).
It reinterprets memory as dynamic, perspectival, relational (good for hippocampal research).
It vindicates relational memory theories while avoiding naive representational realism.
How “Way-Making” Could Revise Theories of Episodic Memory via Spatial CogMap theories that influence her work (via Tolman tradition)
A. Classic View
Episodic memory: storage and retrieval of discrete events.
The hippocampus constructs maps or sequences internally.
Eichenbaum and colleagues: relational memory, spatial and temporal associations, context-dependent sequences.
B. Hiott’s “Way-Making” Concept
Way-making = organism actively generating relational patterns across scales.
Memory is not a static “record” but a dynamic pattern of activity that organizes experience.
Hippocampal representations (place fields, SR matrices, replay) are tools for coordinating action and interpretation, not literal storage.
C. Implications for Episodic Memory
Memory is action-oriented:
Events are remembered not just for recall but for organizing future behavior.
Memory is multi-scale:
Sequences of events, spatial context, and temporal order are all perspectival layers.
Memory is relational, not literal:
Episodic recollection is reconstructive pattern recognition, not retrieval of stored snapshots.
Bottom line:
Episodic memory is dynamic, perspectival, and constructive, fully compatible with Hiott’s multi-scale way-making.
This reframes hippocampal research: we can model it computationally while rejecting metaphysical “map storage” claims.
3. Relational Memory Theory (Eichenbaum) and Hiott
A. Eichenbaum’s Core Ideas
Hippocampus encodes relations among items, contexts, and sequences.
Emphasizes spatial-temporal associations and predictive planning.
Supports the idea of cognitive maps, successor representations, and replay.
B. How Hiott Partially Vindicates Eichenbaum
She accepts that hippocampal structures form relational patterns.
Computational models capturing these patterns are epistemically valid tools.
Multi-scale organization (cells → networks → behavior) aligns with Eichenbaum’s relational memory concept.
C. How Hiott Reinterprets It
She rejects literalist interpretations: the hippocampus does not store “maps” as objects.
Representations of relations are perspectival descriptions of way-making patterns.
Replay, SR, grid cells are tools for describing relational dynamics, not ontological facts.
Takeaway:
Hiott preserves Eichenbaum’s relational insights but reframes them in a perspectival, non-realist framework.
Neural phenomena are epistemic tools for understanding relational organization, not internal maps.
Research Proposal:
Way-Making-Inspired Transformer Memory Architecture
1. Motivation
Modern AI architectures (multimodal transformers, LLMs) excel at pattern recognition and generative tasks but struggle with:
Long-horizon episodic memory (maintaining coherent multi-step histories).
Relational, task-oriented reasoning (connecting events across modalities and time).
Interpretability of internal states (embeddings are opaque).
Hiott-inspired approach:
Treat internal representations as perspectival, communicative tools, not literal maps.
Build memory and predictive modules that actively generate relational patterns (way-making), mirroring hippocampal function.
Integrate computational neuroscience insights (e.g., Angela Langdon’s work on task-state representation and predictive coding) into transformer architectures.
2. Proposed Architecture
A. Multimodal Transformer Backbone
Processes sequences of inputs from multiple modalities (vision, language, audio).
Produces contextual embeddings for each token/event.
Functions as fine-scale “perceptual perspective” layer.
B. Episodic Memory Module (Hippocampal-Inspired)
Stores relational embeddings of events rather than raw data.
Dynamically encodes multi-scale patterns (event → sequence → context).
Supports replay: generates candidate future trajectories, informs both transformer predictions and RL module.
C. Predictive/Task-State Module (Langdon-Inspired)
Maintains expected outcome representations for each state.
Integrates replayed memory with current context to predict likely futures.
Uses reinforcement learning or Bayesian update rules to adjust predictions.
D. Perspective-Assessment Layer (Hiott-Inspired)
Chooses which module’s perspective is relevant for current decision-making.
Implements a meta-attention mechanism over multiple relational perspectives.
Ensures flexibility: the system can plan, recall, or imagine based on the task.
E. Optional Interface Layer
Converts internal relational states into outputs interpretable to humans.
Could visualize relational trajectories, event clusters, or replay simulations.
3. Training Regime
Phase 1: Pretraining
Train transformer backbone on multimodal tasks (e.g., captioning, question-answering).
Initialize episodic memory with simple relational embeddings of short sequences.
Phase 2: Episodic / Way-Making Training
Present sequences of multi-step tasks (like navigation or procedural tasks).
Encourage memory module to form relational embeddings and replay plausible future trajectories.
Use prediction error signals to refine task-state representations (Langdon-style).
Phase 3: Multi-Scale Integration
Train perspective-assessment layer to select relevant perspectives for each task (e.g., planning vs recall).
Jointly optimize transformer + memory + RL modules.
Loss Functions / Objectives:
Prediction accuracy: next event or outcome prediction.
Relational coherence: consistency of relational embeddings across episodes.
Replay utility: does simulated trajectory improve downstream task performance?
Perspective alignment: does selected perspective match task requirements?
4. Evaluation
A. Cognitive Benchmarks
Episodic memory tasks (sequence recall, event prediction).
Relational reasoning tasks (analogical reasoning, multi-step planning).
B. AI Performance Metrics
Task completion rate, generalization to unseen sequences, sample efficiency.
Ablation studies: test importance of replay, memory, perspective-selection.
C. Interpretability / Philosophical Checks
Visualize relational trajectories and memory embeddings.
Assess whether modules’ “perspectives” correspond to intuitive relational maps of events.
Compare to human episodic memory patterns or hippocampal replay sequences.
5. Philosophical & Neuroscientific Framing
Hiott’s Perspective: Internal representations are tools for communication and way-making, not literal stored maps.
Compatibility with AI: Justifies computational models of memory and planning, including transformer embeddings and RL updates.
Neuroscience Link: Memory module mirrors hippocampal relational and predictive functions (Eichenbaum, Langdon).
Implications: Bridges philosophy of mind, computational neuroscience, and AI — a working instantiation of perspectival, multi-scale memory.
6. Potential Extensions
Multimodal lifelong learning: Continually update relational embeddings as new events arrive.
Integration with large pretrained LLMs: Treat LLMs as high-level “perspective layers” that coordinate lower-level memory and planning modules.
Experimental Neuroscience Testing: Compare replay patterns in memory module to hippocampal activity patterns in rodents or humans.
Hiott-Inspired Way-Making Applied to Social Media
1. Conceptual Shift
Traditional social media metrics:
Likes, shares, and comments as proxies for engagement.
Trending topics measured statistically rather than relationally.
Algorithmic feeds that prioritize salience or predicted engagement.
Way-making perspective:
Social media is seen as a dynamic landscape of perspectives and relations.
Posts, threads, and interactions are relational “nodes”, not isolated pieces of content.
Users navigate, interpret, and construct meaning through personal and communal way-making.
2. Components of a Way-Making Social Media System
Relational Content Mapping (RCM) Module
Maps posts, threads, and interactions into relational embeddings.
Tracks not just content similarity but perspective alignment, conversational pathways, and thematic connections.
Could highlight “hidden bridges” between conversations across communities.
User Way-Making Profile (UWP)
Captures how individual users navigate social media content.
Includes attention patterns, interpretive choices, and relational navigation paths.
Evolves over time as the user explores different communities or topics.
Predictive Navigation Module (PNM)
Suggests next posts, threads, or interactions based on relational and perspectival context, not just engagement likelihood.
Learns which perspectives a user may find meaningful or challenging.
Could use replay-like mechanisms to simulate potential trajectories of content exploration.
Perspective-Assessment Layer (PAL)
Dynamically evaluates which relational perspectives should be surfaced.
Can flag diverse viewpoints, emergent trends, or underexplored connections.
Helps prevent echo chambers by revealing structural gaps in relational maps.
3. Applications
Personalized Learning / Intellectual Exploration:
Users can navigate topics based on relational understanding of ideas rather than trending popularity.
Example: Exploring climate science threads while maintaining exposure to multiple scientific perspectives.
Community Insight & Social Dynamics:
Analysts could visualize how groups “way-make” around a topic.
Could detect emerging consensus, conflict zones, or overlooked viewpoints.
Ethical Design:
Algorithms guided by way-making prioritize meaningful engagement over superficial metrics.
Could reduce disinformation spread by mapping relational coherence and perspective gaps.
4. Potential Implementation with AI
Transformer + Memory Architecture:
Transformer backbone embeds content (text, images, video).
Episodic memory module encodes relational paths between posts, threads, and communities.
Predictive module simulates user navigation, replaying relational trajectories.
Perspective-assessment layer selects diverse, coherent perspectives to surface.
Outcome:
Instead of a feed algorithmically determined by engagement, the system guides users through a web of meaning, allowing them to actively participate in constructing understanding — true digital way-making.
5. Philosophical Implications
Moves social media design from information delivery to experience shaping.
Treats memory, content, and interaction as tools for communal meaning-making rather than just data points.
Provides a computational analogy for Hiott’s idea that cognition is an ongoing, perspectival, embodied construction of understanding.
1. Representing Content as a Graph
In Mathematica, you can represent posts, threads, or pieces of content as nodes and their relationships (semantic similarity, conversation reply, shared perspective) as edges.
(* Example: Create a simple content graph *)
nodes = {"Post A", "Post B", "Post C", "Post D"};
edges = {{"Post A", "Post B"}, {"Post B", "Post C"}, {"Post A", "Post D"}};
contentGraph = Graph[nodes, edges,
VertexLabels -> "Name",
GraphLayout -> "LayeredDigraphEmbedding"
];
nodes= individual posts or threadsedges= relational connectionsGraphLayoutdetermines the visual flow
This graph is your Relational Path Module in the diagram.
2. Highlighting Alternative Paths (Way-Making)
You can compute and display all paths between nodes or particular “alternative routes”:
(* Find all paths from Post A to Post C *)
allPaths = FindPath[contentGraph, "Post A", "Post C", Infinity];
(* Highlight one path in the graph *)
highlightedPath = Graph[nodes, edges,
VertexLabels -> "Name",
VertexStyle -> {# -> Red & /@ Flatten[allPaths]},
EdgeStyle -> {# -> Red & /@ Flatten[allPaths /. {a_, b_} :> UndirectedEdge[a, b]]},
GraphLayout -> "LayeredDigraphEmbedding"
];
This lets users see alternative ways they could have explored content.
You could color-code paths by perspective, popularity, or diversity.
3. Perspective-Assessment Layer
You can tag nodes with perspectives:
perspectives = <|"Post A" -> "Expert", "Post B" -> "Diverse", "Post C" -> "Emergent", "Post D" -> "Expert"|>;
Graph[nodes, edges,
VertexLabels -> (Placed[#, Tooltip[#, perspectives[#]]] & /@ nodes),
GraphLayout -> "LayeredDigraphEmbedding"
]
Hovering over a node could show its perspective.
In Mathematica notebooks, tooltips, dynamic highlights, and interactive controls can simulate the user’s perspective-assessment interface.
4. Simulating “Replay” or Alternative Exploration
Mathematica can dynamically animate paths to simulate user exploration:
Manipulate[
HighlightGraph[contentGraph, PathGraph[path]],
{{path, {"Post A", "Post B", "Post C"}}, allPaths, ControlType -> PopupMenu}
]
Manipulatelets the user select which path to “replay.”Could be extended to animate or score alternative paths.
5. Building a Way-Making Dashboard
Combine all of the above:
Left panel: Interactive graph of content + perspectives
Right panel: List of alternative paths, with simulation options
Bottom panel: User history / Way-Making Profile
Mathematica supports dynamic modules, buttons, sliders, tooltips, and interactive graph highlighting, so you can prototype a fully interactive version without writing a full web app.
6. Philosophical / Conceptual Notes
Nodes = posts = relational “knowledge points”
Edges = relational connections = the structure of perspectives
Graph navigation = user’s way-making through content
Dynamic replay = simulation of alternative cognitive trajectories
The novelty here isn’t in the technical mechanics of nodes and edges, but in how they are interpreted through Hiott’s way-making lens:
Standard graph-based recommendation systems are utility-driven: maximize clicks, engagement, or predicted interest.
The Hiott-inspired approach is perspectival and relational: the system surfaces alternative ways of understanding the content landscape — not just the “best” or most popular next step.
The innovation is in transparency + epistemic scaffolding: the system doesn’t just present content, it makes the structure of meaning visible and shows potential cognitive trajectories.
So it could feel trite if implemented only as a fancy graph. But as a tool for navigational cognition and epistemic reflection, it’s conceptually new.
Is it really a perspective? Or better understood as a trajectory?
This is subtle:
Perspective (Hiott sense): a way of seeing or interpreting content. In the social media system, tagging a path as “Expert,” “Diverse,” or “Emergent” is perspective-like: it indicates a lens through which content is encountered.
Trajectory: the sequence of navigation choices a user takes through the relational space. Each trajectory is temporally extended, showing how understanding unfolds.
So both are relevant:
Perspective = qualitative lens
Trajectory = quantitative or dynamic path through content
Hiott’s notion of way-making emphasizes both: you are constantly negotiating perspectives as you move through relational space. The trajectory is how the perspective is enacted in practice. The map makes possible perspectives visible, the path shows how a user engages with them.
Why this matters
Many AI systems focus only on the trajectory (recommendation paths) or only on the perspective (static labeling).
The Hiott approach combines them: a user is always making meaning by traversing paths through perspectival spaces.
This gives a temporal, relational, and perspectival dimension to memory, understanding, and social cognition.
So the real novelty isn’t the graph, the pathfinding, or even the tags. It’s treating content navigation as an epistemic practice: a way for users to actively construct meaning, not just consume it.
ECOLOGICAL MEMORY
March 2022
DOI:10.13140/RG.2.2.12297.86885
Keywords: way-making, navigabilities, System 3
A note on the term 'ecological': Ecological as used here is inspired by many sources, from
Rachel Carson to Gregory Bateson. At its most general, it implies a stance that, in the words
of J.J. Gibson on affordance, “cuts across the dichotomy of subjective-objective and helps us
understand its inadequacy,” (Gibson, 1979, 129). The paper also does not fit to any either/or
choice as made in traditional notions of hippocampal research relative to association and
spatiality.