---
title: The Tug of War between Taxonomic and Thematic Relations in Young Toddlers
subtitle: Taxonomic and Thematic Semantics in Toddlers
#title-block-banner-color: default
#title-block-banner: false
author:
  - name: Kim Plunkett
    id: kp
    orcid: 0000-0003-0216-7480
    corresponding: true
    email: kim.plunkett@psy.ox.ac.uk
    roles:
      - Investigation
        Project administration
        Software
        Visualization
    affiliation:
      - name: University of Oxford
      - department: Department of Experimental Psychology
      - city: Oxford
      - url: www.psy.ox.ac.uk
  - name: Armando Angulo-Chavira
    # orcid: 0000-0002-7859-8394
    corresponding: false
    email: angulo_chavira@comunidad.unam.mx
    roles: []
    affiliations:
      - Universidad Nacional Autonoma de Mexico
keywords:
  - thematic memory
  - taxonomic memory
  - priming
  - semantic networks
  - eye-tracking
  - lexical semantics
  - language development
abstract: >
  Young toddlers will fixate unnamed objects that are either taxonomically or thematically related to named target. They respond faster to taxonomically related objects but show less sustained attention than to thematically related objects.
plain-language-summary: >
  Toddlers and adults looked at a computer display of 4 objects and listend to a word that could potentially be a name of one of the objects.
key-points:
  - adults and toddlers respond to thematic and taxonomic primes in a visual world task
  - thematic primes engender longer lasting fixations to thematically related objects
  - taxonomic primes engender faster fixations to taxonomically related objects
funding: "The authors received no specific funding for this work." 
date: last-modified
bibliography: bibliography.bib
bibliographystyle: apa
citation:
  container-title: A Journal of Cognitive Science
number-sections: true
---

## Introduction

### Taxonomic and Thematic Relations

Recent research suggests that adult semantic memory contains two
dissociable components: a *taxonomic* semantic system and a *thematic*
semantic system. The taxonomic semantic system captures information
about entities that are categorically related and often visually
related. Thus, CAT and HORSE are taxonomically related because they
belong to the same category ANIMAL and share common attributes or
features such as *four-legged*, *has-2-eyes*, etc. The thematic semantic
system captures information about entities that are related through
their co-occurence in events. Thus, DOG and BONE are thematically
related because dogs are frequently seen or depicted chewing at a bone.
There are many types of thematic relations, often only constrained by
the imagination. But the most commonly studied include *instrumental*
relations, as in COMB and HAIR, and *script* relations, as in WINE and
RESTAURANT [@moss94; @moss1995accessing].

Taxonomically and thematically related objects may also be *associated*
or *unassociated*. Unassociated pairs of objects are defined as being
rarely, if ever, produced in word association norms [such as
@Nelson2004assoc] <!--# include some refs here --> as associates of each
other, whereas associated pairs have attested associations in such
norming studies. For example, DOG and BONE are both thematically related
and associated, and DOG and CAT are both taxonomically related and
associated. PARTY and MUSIC are thematically related but unassociated,
and PIG and HORSE are taxonomically related but unassociated. It is also
possible for objects to be associated but taxonomically and thematically
unrelated, as in COUCH and POTATO, PILLAR and SOCIETY or COTTAGE and
CHEESE. @tbl-category provides a listing of some common taxonomic
categories and thematic relations.

::::: grid
:::: g-col-10

| Animal | Food   | Instrument |
|:-------|:-------|:-----------|
| Dog    | Bone   | Leash      |
| Horse  | Apple  | Saddle     |
| Mouse  | Cheese | Trap       |

: Cross-categorisatoin of objects: columns list objects belonging the same
taxonomic category; rows list objects that are thematically related
[after @mirman2017taxonomic]. {#tbl-category}

::::
:::::

### Evidence for Taxonomic and Thematic Memory Systems

It is well-established that taxonomically- and thematically-related
words prime each other (faster reaction times) in lexical decision and
naming tasks [e.g., @McNamara2005-MCNSPP; @neely1991semantic;
@meyer1971facilitation; @Lucas2000]. Priming is observed if the words
are only taxonomically-related or only thematically-related, though a
boost in the priming effect occurs for words that are both taxonomically
*and* thematically related [@moss1995accessing]. Thematic priming
effects are longer lasting than taxonomic priming effects, i.e., priming
survives longer inter-stimulus intervals (ISIs) between prime and target
for thematic pairs as compared to taxonomic pairs. However, priming is
rarely observed when an intervening unrelated word occurs between prime
and target. Such priming effects are typically interpreted as indicating
that taxonomic and thematic memory systems are structured, i.e., that
the lexical-semantic representations of words in the human brain are
organised according to taxonomic and thematic principles. The
contrasting dynamic characteristics of thematic vs. taxonomic priming
also suggest that different mechanisms may underlie these priming
effects.

Event related potential (ERP) studies have also demonstrated adult
sensitivity to the taxonomic and thematic relationships between words.
For example, @federmeier1999rose demonstrated a reduced N400 to a target
word following a taxonomically related prime word as compared to an
unrelated prime. Similarly, @mech2022last reported reduced N400
signatures to target words following either a taxonomically or
thematically related prime word, indicating both taxonomic and thematic
relationships between words. Interestingly, this latter study reported
reduced N400 effects for both left visual field (LVF) and right visual
field (RVF) presentations, suggesting that both the right and left
cerebral hemispheres can elicit taxonomic and thematic priming effects.
@mech2022last point out that thematic priming effects are stronger than
taxonomic priming effects, irrespective of the side of visual field
presentations.

What does it mean to suggest that there are different taxonomic and
thematic semantic systems? Evidence for the *separate* and *systematic*
organisation of taxonomic and thematic semantic systems requires an
account of how these meaning relations are organised in the brain, and
how this organisation gives rise to differences in the functioning of
taxonomically or thematically related items. Different types of evidence
have accumulated over the past 10–15 years suggesting that taxonomic and
thematic relations between items function differently. These include
neuro-psychological and neuro-imaging studies, as well as experimental
behavioural studies.

### Neuro-psychological and neuro-imaging studies

@schwartz2011neuroanatomical studied 779 naming errors across 86 aphasic
patients. The authors reported that category coordinate errors
(taxonomic errors), such as a picture of an *apple* named as *grape* or
*pear*, constituted the majority of errors in this group of aphasics.
However, a small minority of errors were thematic in character, such as
*bone* named as *dog* or *apple* named as *worm*. The authors argued
that taxonomic errors could be attributed to lesions in the left
anterior temporal lobe (ATL) whereas thematic errors could be attributed
to lesions to the temporoparietal junction (TPJ) (see @fig-brain).
Although not constituting a *behavioural* double dissociation between
taxonomic and thematic systems, their findings point to a
*neuroanatomical* [^1] dissociation between the 2 systems, enabling the
authors to argue for a complementary semantic systems account.

[^1]: @schwartz2011neuroanatomical do not claim that only TPJ lesions
    result in thematic errors, just that lesions in ATL and TPJ
    differentially impact taxonomic and thematic errors.

![Primary regions of the brain](images/brain.jpg){#fig-brain
.illustration .column-margin fig-alt="regions of the brain"
fig-align="center" width="95%"}

@kalenine2009sensory reported convergent findings in an fMRI study where
Ss had to match a target picture to a thematically or taxonomically
related picture. Contrastive analyses identified activation in visual
areas of the brain for taxonomic matches and in the inferior parietal
lobule (encompassing TPJ) for thematic matches. Other studies have also
highlighted the impact of lesions in the ATL on naming errors that are
primarily taxonomic in character and rarely ever thematic [e.g.,
@lambonralph2001no; @rogers2004structure].

::: column-margin
This is how you make a margin comment. $$ y = x^2 $$ Just so you know.
:::

::: {.callout-note collapse="true"}
And here is how you do callouts: note, warning, tip, important and
caution
:::

### Experimental behavioural studies

When adults are asked to name a target object, thematically related
distractors tend to facilitate naming whereas taxonomically-related
distractors tend to inhibit naming [@dezub2013differential]. The finding
suggests that taxonomically-related items compete in semantic memory
whereas thematically-related items are mutually supportive. This
state-of-affairs is readily understood in the context of a memory system
where taxonomically-related items compete with each other for
recognition and which have excitory connections to a separate system of
thematically-related items.

In an eye-tracking study using the visual world paradigm [e.g.,
@cooper1974control; @tanenhaus1995integration], Ss were directed to look
at an array of 4 pictures [@kalenine2012temporal]. The pictures
contained foils that were either thematically-related,
taxomically-related or unrelated to a spoken target item. Although the
adult Ss were equally likely to fixate the thematically and
taxonomically related pictures as compared to the the unrelated foils,
the time courses of these fixations were different: thematic foils
tended to be fixated earlier than taxonomic foils particularly when the
foils were artifacts or manipulable objects. In principle, this finding
could be explained within the confines of a unitary memory system where
taxonomically-related items are weakly connected with each other as
compared to thematically-related items. However, @kalenine2009sensory
and @kalenine2016thematic have also reported that the *speed* of
identification of taxonomically-related and thematically-related targets
is reversed for animals as compared artifacts. A connection-strength
type explanation would need to impose taxonomy-specific constraints
(animals vs. artifacts) to account for this reversal, undermining the
suggestion of a fully unitary organisation of thematic and taxonomic
semantic memory systems.

::: column-margin
Note similarity to current study.
:::

@landrigan2018cost argued that if thematic and taxonomic relations were
encoded in distinct semantic systems, then Ss should be faster to make
relatedness judgements when judgements on consecutive trials involved
the same type of relation (taxonomic or thematic), than if the type of
relation shifted between trials. For example, in a triads task, Ss were
asked to select which of 2 words was *most* related} to a prompt word.
In taxonomic trials the prompt word might be *dog* and the choice was
between *wolf* and *car*. On thematic trials the prompt might be *dog*
and the choice between *bone* and *car*. @landrigan2018cost reported
that Ss were slower to respond when their was a switch between trial
types, be it taxonomic to thematic or *vice versa*, than when
consecutive trials involved the same type of judgement. This result
points to a distinction between thematic and taxonomic processes or
representations.

::: {.callout-note collapse="true"}
Could say something here about organisation principles of the 2 systems
mentioning feature overlap vs. direct association a la Plaut.
:::

### Neuro-computational basis of the Thematic vs. Taxonomic distinction

An influential distributed network model that implements the
thematic/taxonomic processing distinction is due to @plaut1995semantic
and @plaut2000. The model can capture a broad range of experimental and
neuropsychological findings and offers converging evidence for the
theoretical foundations of this distinction [@moss94;
@plaut1995semantic]. For example, @plaut2000 suggest that taxonomic
priming is best explained by semantic feature overlap between prime and
target items in a distributed network model, whereas associative priming
occurs as a result of the frequent co-occurrence of words during
learning. According to @plaut2000, the short-lived character of
taxonomic priming is explained in terms of hysteresis effects in moving
from one stable state of the network to another: once the feature set of
the prime is fully activated, the transition to the feature set of the
target will benefit from the features it has in common with the prime
but will also be inhibited by the features that differ. At short
stimulus onset asynchronies (SOAs), nonoverlapping features are not
fully activated. Hence, overlapping features prime the transition to the
target. At long SOAs (around 800 ms), nonoverlapping features of the
prime are fully active and can inhibit the transition to the target
[@plaut1995semantic; @plaut2000]. No such inhibitory effects emerge with
associative priming because associative priming does not depend on
feature overlap. Facilitative associative priming occurs through direct
connections between lexical forms or derives from their referents
sharing a complementary relationship in time or space. Other distributed
network models of semantic priming implement synaptic depression
mechanisms to capture SOA effects [@lerner2012; @oreilly2003].

The aforementioned neuro-computational models make no strong claims as
to the anatomical location of the mechanisms underlying taxomomic and
thematic priming. However, the neuro-psychological and neuro-imaging
studies described above attempt to identify the anatomical locus of the
priming effects: The anterior temporal lobe (ATL) is at the apex of the
ventral visual *what* pathway that specialises in high-level object
recognition. It is proximal to those regions of the inferior temporal
lobe that specialise in the integration of shape and colour information.
The parietal temporal junction (PTJ) is part of the dorsal *where*
pathway which provides information about spatial location and action.
Thus, the ATL and the PTJ each have close connectivity to different
types of object representations.

As summarised above, it has been suggested that taxonomic relationships
and thematic relationships between items are encoded in the anterior
temporal lobe (ATL) and the parietal temporal junction (PTJ),
respectively. For example, damage to the ATL results in taxonomic These
anatomical regions are at opposite ends of the temporal lobe. The
auditory word form area (AWFA) is conveniently located in the posterior
temporal lobe, between the ATL and PTJ, and is well-positioned to
provide input to both these areas.

#### Hub-and-Spoke model

![Hub and Spoke model: single hub
version](images/Hub_Spoke_Tax_Them2.png){#fig-onesys .illustration
.column-margin fig-alt="one system model" fig-align="center"
width="95%"}

Insofar as taxonomic relations rely upon the integration of shape and
colour information, and thematic relations on spatial and action
information, neuro-anatomical and behavioural dissociations between
taxonomic and thematic responding, are consistent with a *hub-and-spoke*
computational model of the taxonomic and thematic semantic memory
systems [e.g., @rogers2004structure]. On this view, a taxonomic region
of the hub receives stronger connections from colour and shape features
encoded in the ventral visual pathway of the temporal lobe, whereas a
thematic region of the hub receives stronger connections from spatial
and action features in the dorsal visual pathway. Damage to connections
in the taxonomic can cause a deterioration in the ability to
discriminate between some colour and shape features, and results in
taxonomic errors such as incorrectly naming *apple* as *grape*. Damage
to connections in the thematic hub has the potential to impact
appropriate binding of spatial and action features, resulting in naming
errors such as *bone* as *dog*.

::: {.callout-tip title="Using Mermaid in Quarto" collapse="true"}
```{mermaid}
%%{init: {'theme': 'default'}}%%
flowchart LR
  subgraph parentNode["Parent Node"]
    child1["Child 1"]
    child2["Child 2"]
  end
    child1 <--> child2
```
:::

A simple representation of this neuro-computational architecture is
shown in @fig-onesys. A single hub receives input from multiple
features---the spokes of the model. The colour and shape features have
stronger connections to a taxonomic region of the hub and weaker
connections to a thematic region of the hub. The action and location
features have stronger connections to the thematic region of the hub and
weaker connections to the taxonomic region. Auditory input from the
auditory word form area (AWFA) is considered to have uniform
connectivity across the hub. Proponents of this type of architecture
[e.g., @jefferies2020neurocognitive; @ralph2017neural] argue that the
hub is located in the ATL. Damage to ATL can result in taxonomic errors.
Thematic errors can be caused by inaccurate processing in this area or
to *semantic control* errors resulting from inaccurate processing in the
PTJ or prefrontal lobes.

#### Two-systems model

An alternative approach---the \emph{dual-systems model}---suggests that
there are separate taxonomic and thematic hubs [see
@schwartz2011neuroanatomical; @Mirman2017; @zhang2023taxonomic]. They
are both functionally and anatomically separate, as depicted in
@fig-twosys. Colour and shape features feed into the taxonomic hub,
located in the ATL. Action and location features feed into the thematic
hub, located in the PTJ. Recurrent connections in the taxonomic hub are
auto-associative in nature permitting pattern completion from noisy or
incomplete inputs. Recurrent connections in the thematic hub are
associative enabling the encoding of co-occurring events and
predictions. Damage to the taxonomic and thematic hubs can lead to
taxonomic and thematic errors, respectively.

![Hub and Spoke model: dual hub
version.](images/Two_Sys_Tax_Them2.png){#fig-twosys .illustration
.column-margin fig-alt="Two systems model" fig-align="center"
width="95%"}

According to the two-systems model, hearing the word *dog* activates the
appropriate distributed phonological representation in the AWFA. This
propagates activity to the ATL and PTJ identifying the relevant features
of *dog* in these respective cortical areas. We presume that the
Anterior Temporal Lobe and the Parietal Temporal Junction are not
replicates of each other. In addition to efficiency considerations, this
assumption is justified on the grounds that damage to these 2 cortical
areas produce different patterns of naming errors [see
@schwartz2011neuroanatomical; @Mirman2017; @zhang2023taxonomic].
However, it raises the question as to the nature of the representations
that correspond to the concept DOG when they are activated in the ATL
and the PTJ. In other words, what is the meaning of the word *dog* in
these 2 cortical areas. The different patterns of naming errors
associated with damage to ATL and PTJ suggests that the meanings must be
different.

#### Explanatory Mechanisms

As a first approximation, accepting the two-systems model, we suppose
that the ATL receives perceptual input from cortical areas associated
with, say, colour and shape features. In contrast, the PTJ receives
functional input from cortical areas associated with motion and spatial
location information. Let us further assume that both these cortical
areas have a neuro-computational architecture akin to a self-organising
map (SOM). SOMs have a typological organisation such that neurons which
are close together on the map come to represent items that have similar
features [@kohonen2001]. This means that objects that possess similar
features, e.g., *cat* and *dog*, will be represented by neurons that are
close together. Damage to these cortical areas can lead to errors in
identification because inappropriate neurons are activated by incoming
perceptual information. However, depending on the site and extent of the
damage, the most likely candidates for inappropriate activation are
those neurons that are close by, because damage affects neurons and the
connections between them. Localised damage will result in neighbouring
areas becoming relatively more activated than in the undamaged case.

If the inputs to ATL are primarily perceptual in character, such as
colour and shape attributes, then the topological organisation of items
represented in ATL will reflect their similarity in terms of these
attributes. *Dogs* will be represented in a region of ATL close to that
of *cats* insofar as they possess similar perceptual attributes. Damage
to this area of ATL may lead to the inappropriate activation of *cat*
neurons in the presence of a dog or vice versa.

If the inputs to PTJ are primarily functional in character, such as
spatial location and motion attributes, then the topological
organisation of the same items in PTJ will likely be different to that
found in ATL because the overlap in their shared functional
characteristics may well be different from that of their perceptual
characteristics. For example, cats and dogs may be represented in more
distinct areas of PTJ because cats move in a different fashion to dogs,
as well as typically occupying in different locations. Localised damage
to PTJ need not lead to inappropriate activation of *cat* neurons in the
presence of a dog, but perhaps to the inappropriate activation of *bone*
neurons because they are represented close by in PTJ.

#### The Meaning of Meaning

A consequence of this separation in the representation of different
features of the same object is that the meaning of the label used to
name an object is distributed across distinct cortical areas. This
raises the question as to how representations of the same object are
linked. One way that they are linked, according to this model, is
through the auditory word form representation: the auditory
representation of *dog* points at both the taxonomic and thematic
meanings. But is there a concept DOG that represents both its perceptual
and functional characteristics independently of the word *dog*? In other
words, do you need to know the word *dog* in order to have a fully blown
concept of DOG. This is reminiscent of the problem of binding the
spatial and featural properties of objects that are represented
separately in the What and Where visual pathways [@mishkin1983object].
Received wisdom would suggest that it is possible to possess a concept
without knowing its name (see @murphy2004big pp.389 for some amusing
examples involving adults as well as @merriman1991names for experimental
evidence with children). However, if the concept is componential
(distinct regions for different types of meaning), it is conceivable
that the constituent components remain isolated in the absence of
language. This idea has some mileage. Let’s call it *partial meaning*.

According this theory of partial meanings, concepts only realise their
full meaning when activated by language. Language acts as a mediating
link between the partial meanings until direct links between those
partial meanings are established. This could occur as a result of the
frequent co-activation of the partial meanings, leading to the formation
of direct connections, independently of language. Thus,
barking[^2] might come to conjure up
perceptual representations associated with DOG, such as shape and
colour. Formation of direct connections between anatomically separate
cortical areas, such as the ATL and PTJ, might contribute to the
substantial growth of white matter observed in the brain after 2 years
of age [e.g., @mabbott2006white]. Indeed, the mediating role of language
in activating disparate areas of cortex may lead to the formation of
direct connections between the corresponding conceptual areas of ATL and
PTJ.

[^2]: Supposing for the moment that *barking* is a functional attribute
    encoded in PTL.

The alternative approach---the hub-and-spoke model---supposes that the
conceptual representations of objects are encoded entirely within the
ATL [@jefferies2020neurocognitive;@ralph2017neural]. The hub
receives a broad range of features, e.g., shape, colour, motion, and
location, contributing to the concept’s instantiation on the cortical
map. On this view, there is no need to connect partial meanings of words
because the sensorimotor features that define meaning converge on a
single location, i.e., the ATL.

An apparent difficulty with this approach is identifying the source of
thematic relationships in ATL. DOG shares no perceptual features with
BONE so what mechanism leads to one concept/word priming the other for
these thematically related items? Insofar as the thematic relationship
between these items originated in a frequently occurring event (e.g.,
dogs chewing bones), then shared functional features such as spatial
location and motion might serve to provide the feature overlap to encode
such thematic relationships. Indeed, exactly these shared functional
features are assumed to underly the encoding of thematic relationships
in the two-systems model. However, in the hub-and-spoke model little
additional machinery is needed to bind together representations that
share the same anatomical space or hub. In contrast, the two-systems
model needs additional machinery to bind together the partial meanings
encoded in ATL and PTL.

The Controlled Semantic Cognition (CSC) model
[@jefferies2020neurocognitive;@ralph2017neural] supposes that
thematic relationships derive from processes of semantic control
involved in retrieving or reconstructing an event. These processes are
effortful and are likely to impose greater cognitive load on the
individual. An advantage of the CSC account is that it can readily
explain why thematic priming effects are larger and longer-lasting than
taxonomic priming effects: the sustained effort needed to retrieve or
reconstruct the appropriate event in memory likely invokes robust
processing strategies that last at least as long as the time needed to
activate the event in working memory. In contrast, taxonomic priming
effects are considered the automatic outcome of feature overlap,
imposing no additional demands on the memory system. Of course, on both
the two-systems and CSC accounts, thematic priming effects might become
automatic as a result of repeated event re-activations in working
memory. Likewise, automatic priming of thematically related items might
occur as a result of the repeated co-occurrence of objects and/or words
in the auditory/visual environment, leading to a strengthening of
connections between the object representations in ATL.

::: {.callout-warning collapse="true"}
- Connectivity difficulties for CSC account: requires long distance spatial
location and motion connections to ATL.
- Double dissociation difficulties for CSC account. Should not predict
straightforward DDs.
- Why is thematic priming thought to be faster acting than taxonomic
priming?
:::

::: {.callout-note collapse="true"}
Both types of architecture are agnostic as to the relative prevalence of
taxonomic and thematic errors. The hub-and-spoke model predicts that
damage to the hub could result in either type of error, depending on the
location of the lesion in the hub. However, the integrated nature of the
hub suggest that both error types should be readily observed. The
two-systems model predicts that the nature of the error should depend on
the location of the damage, and that thematic and taxonomic errors
should be doubly-dissociable. In fact, it is commonly reported that
taxonomic errors are more frequent than thematic errors
[e.g., @schwartz2011neuroanatomical;@rogers2004structure;@patterson2007you].
This asymmetry in error prevalence is not predicted by either of the
architectures, as described here.
:::

 Given the current status of the neuropsychological and % experimental
evidence, it  is difficult to adjudicate between the two accounts of 
the neuroanatomical organisation of taxonomic and  thematic memory
systems.  However, we can be reasonably confident  that it makes sense
to talk about distinct memory systems be % they anatomically separate
(the two-systems account) or differentially distributed within a
common semantic hub (hub-and-spoke account).

::: {.callout-note collapse="true"}
Could say something here about organisation principles of the 2
systems mentioning feature overlap vs. direct association a la Plaut.
:::

## References {.unnumbered}

::: {#refs}
:::
