Verbal Paired Associates and the Hippocampus: - Am MIT spezialisierte KI-Forschung

Verbal Paired Associates and the Hippocampus:
The Role of Scenes

Ian A. Clark, Misun Kim, and Eleanor A. Maguire

Abstrakt

■ It is widely agreed that patients with bilateral hippocampal
damage are impaired at binding pairs of words together. Conse-
quently, the verbal paired associates ( VPA) task has become
emblematic of hippocampal function. This VPA deficit is not well
understood and is particularly difficult for hippocampal theories
with a visuospatial bias to explain (z.B., cognitive map and scene
construction theories). Resolving the tension among hippo-
campal theories concerning the VPA could be important for
leveraging a fuller understanding of hippocampal function.
Vor allem, VPA tasks typically use high imagery concrete words
and so conflate imagery and binding. To determine why VPA
engages the hippocampus, we devised an fMRI encoding task
involving closely matched pairs of scene words, pairs of object
Wörter, and pairs of very low imagery abstract words. We found

that the anterior hippocampus was engaged during process-
ing of both scene and object word pairs in comparison to ab-
stract word pairs, despite binding occurring in all conditions.
This was also the case when just subsequently remembered
stimuli were considered. Darüber hinaus, for object word pairs,
fMRI activity patterns in anterior hippocampus were more
similar to those for scene imagery than object imagery. Das
was especially evident in participants who were high imagery
users and not in mid and low imagery users. Gesamt, our results
show that hippocampal engagement during VPA, even when
object word pairs are involved, seems to be evoked by scene
imagery rather than binding. This may help to resolve the issue
that visuospatial hippocampal theories have in accounting for
verbal memory. ■

EINFÜHRUNG

The field of hippocampal neuroscience is characterized
by vigorous debates. But one point on which there is
general agreement is that people with bilateral hippo-
campal damage and concomitant amnesia (hippocampal
amnesia) are significantly impaired on verbal paired
associates ( VPA) tasks. The VPA task is a widely used
instrument for testing verbal memory and has been a
continuous subtest within the Wechsler Memory Scale
(WMS) from its initial inception ( Wechsler, 1945) to the
present day ( WMS-IV; Wechsler, 2009). Although the VPA
task has been revised many times (z.B., increasing the
number of word pairs to be remembered, changing the
ratio of difficult to easy word pairs), the basic premise has
remained the same. The requirement is to encode pairs
of words (z.B., bag–truck), memory for which is then
tested. Testing can be conducted in multiple ways, Aber
one primary outcome measure is performance on a
delayed cued recall test (d.h., the experimenter asks for
the word that goes with bag) 30 min after the completion
of the learning trials. Compared with matched healthy
control participants, patients with hippocampal amnesia
show a consistent and reliable deficit on delayed cued
recall tests (Giovanello, Verfaellie, & Keane, 2003; Spiers,

University College London

Maguire, & Bürger, 2001; Zola-Morgan, Squire, & Amaral,
1986; Graf & Schacter, 1985), and consequently, the VPA
has become emblematic of hippocampal function.

The VPA task is typically regarded as a verbal memory
Aufgabe. Jedoch, many theories focus on elucidating the
role of the hippocampus in visuospatial rather than
verbal processing. This includes accounts that consider
spatial navigation (Maguire et al., 2000; O’Keefe & Nadel,
1978), autobiographical memory (Hassabis & Maguire,
2007; Squire, 1992; Scoville & Milner, 1957), scene per-
ception (McCormick, Rosenthal, Müller, & Maguire, 2017;
Graham, Barense, & Lee, 2010), the mental construction of
visual scene imagery (Zeidman & Maguire, 2016; Maguire
& Mullally, 2013), and more specific aspects of visuospatial
Verarbeitung, including perceptual richness, a sense of re-
living, and imagery content (St-Laurent, Moscovitch, &
McAndrews, 2016; Andrews-Hanna, Reidler, Sepulcre,
Poulin, & Buckner, 2010; St. Jacques, Conway, Lowder, &
Cabeza, 2010).

The cognitive map theory, zum Beispiel, posits that the
hippocampus specifically supports flexible, allocentric
representations of spatial relationships (O’Keefe & Nadel,
1978). Im Gegensatz, the scene construction theory (sehen
also the emergent memory account; Graham et al.,
2010) proposes that the anterior hippocampus con-
structs models of the world in the form of spatially coher-
ent scenes (Dalton & Maguire, 2017; Zeidman & Maguire,

© 2018 by Massachusetts Institute of Technology. Veröffentlicht unter
eine Creative-Commons-Namensnennung 4.0 Unportiert (CC BY 4.0) Lizenz.

Zeitschrift für kognitive Neurowissenschaften 30:12, S. 1821–1845
doi:10.1162/jocn_a_01315

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2016; Maguire & Mullally, 2013; Hassabis & Maguire,
2007). A scene in this context is a specific type of visual
image that represents a naturalistic 3-D space typically
populated by objects and that is viewed from an ego-
centric perspective. The construction of scene imagery
involves associative processing and binding, aber die
scene construction theory asserts that the hippocampus
is specifically required to perform these functions in the
service of creating scene representations (Maguire &
Mullally, 2013). The difficulty with theories such as cog-
nitive map and scene construction is that they do not
appear to be able to explain why VPA learning is invari-
ably compromised following hippocampal damage.

On the face of it, another hippocampal theory does
seem to account for the VPA findings. The relational the-
ory suggests that the hippocampus makes associations
between any elements, regardless of whether or not
space or scenes are involved (Konkel & Cohen, 2009;
Cohen & Eichenbaum, 1993). This generic associative
process could account for the creation of an association
between two unrelated words in the VPA task, while also
explaining the involvement of the hippocampus in visuo-
spatial tasks and the combining of individual elements
into a coherent memory or the recombination of different
elements from past experiences to simulate the future
(Roberts, Schacter, & Addis, 2018; St. Jacques, Carpenter,
Szpunar & Schacter, 2018; Thakral, Benoit, & Schacter,
2017; Moscovitch, Cabeza, Winocur, & Nadel, 2016; Schacter
et al., 2012). Jedoch, a purely associative account of
hippocampal function is not completely satisfactory,
given that patients with hippocampal damage retain an
ability to form associations in some circumstances. Für
Beispiel, intact performance has been reported for
Yes/No and forced choice recognition of both intraitem
associations and associations between items of the same
kind (Mayes et al., 2004), when creating basic associa-
tions in probabilistic learning (Kumaran et al., 2007;
Knowlton, Mangels, & Squire, 1996), in the rapid learn-
ing of arbitrary stimulus–response contingencies (Henson
et al., 2017), and in other contexts (see Clark & Maguire,
2016; Mullally & Maguire, 2014).

Resolving the tension among hippocampal theories
concerning the VPA could be important for leveraging a
fuller understanding of hippocampal function. In taking
this issue forward, it is worthwhile first to step back.
Examination of the words used in typical VPA tests shows
the vast majority are high imagery concrete words. Es
could be that people use visual imagery when processing
the word pairs (Maguire & Mullally, 2013). This specula-
tion has recently received indirect support from the finding
that patients with hippocampal amnesia used significantly
fewer high imagery words in their narrative descriptions of
real and imagined events (Hilverman, Cook, & Duff, 2017),
suggesting a potential link between verbal processing
and visual imagery.

Currently, daher, standardized VPA tests may be
conflating associative processes and imageability. Patients

with hippocampal damage are reportedly unable to imag-
ine fictitious and future scenes in addition to their well-
reported memory deficits (Schacter et al., 2012; Race,
Keane, & Verfaellie, 2011; Hassabis, Kumaran, Vann, &
Maguire, 2007). It would, daher, follow that their im-
poverished scene imagery ability may place them at a
disadvantage for processing high imagery concrete words.
One way to deal with the conflation of visual imagery
and binding is to examine very low imagery (abstract)
word pairs, which would assess binding outside the
realm of imagery. Jedoch, abstract word pairs rarely fea-
ture in VPA tests used with patients or in neuroimaging
experiments.

Zusätzlich, different types of high imagery words are
not distinguished in VPA tests, with the majority of words
representing single objects. Jedoch, the scene con-
struction theory links the anterior hippocampus specifi-
cally with constructing visual imagery of scenes (Dalton
& Maguire, 2017; Zeidman & Maguire, 2016). Im Gegensatz,
the processing of single objects is usually associated with
perirhinal and lateral occipital cortices (Murray, Bussey,
& Saksida, 2007; Malach et al., 1995). It could therefore
be that a scene word (z.B., forest) in a pair engages the
hippocampus (via scene imagery) and not because of
binding or visual imagery in general. It has also been sug-
gested that even where each word in a pair denotes an
Objekt (z.B., cat–table), this might elicit imagery of both
objects together in a scene, and it is the generation of this
scene imagery that recruits the hippocampus (Clark &
Maguire, 2016; Maguire & Mullally, 2013). Folglich, Wenn
visual imagery does play a role in the hippocampal depen-
dence of the VPA task, then it will be important to establish
not only whether visual imagery or binding is more relevant
but also the type of visual imagery being used.

To determine why VPA engages the hippocampus, Wir
devised an fMRI task with three types of word pairs: Wo
both words in a pair denoted “Scenes,” where both words
represented single “Objects,” and where both words were
very low imagery “Abstract” words. This allowed us to sep-
arate imageability from binding and to examine different
types of imagery. Of particular interest were the Object
word pairs because we wanted to ascertain whether they
were processed using scene or object imagery. For all
word pairs, our main interest was during their initial pre-
sentation, when any imagery would likely be evoked.

Zusätzlich, we conducted recognition memory tests
after scanning to investigate whether the patterns of
(hippocampal) activity were affected by whether pairs were
successfully encoded or not. Although the VPA memory
test used with patients typically involves cued recall, Die
adaptation of the VPA task for fMRI necessitated the use
of recognition memory tests. This is because performing
a cued recall test for 135 word pairs that were each seen
only once is too difficult even for healthy participants.
We note that recognition memory for word pairs is not
often tested in patients, and in the few studies where it
has been examined, the results are mixed, with some

1822

Zeitschrift für kognitive Neurowissenschaften

Volumen 30, Nummer 12

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studies finding a deficit and others a preservation of per-
Form (Mayes et al., 2001; Haist, Shimamura, & Squire,
1992). Jedoch, we expected that the use of a recog-
nition memory test instead of cued recall would have
limited impact on the patterns of brain activity in this
study because we assessed brain activity during the initial
presentation of the word pairs and not during memory
retrieval. Endlich, given that people vary in their use of
mental imagery (McAvinue & Robertson, 2007; Kosslyn,
Brunn, Cave, & Wallach, 1984; Marks, 1973), we also tested
groups of high, mid, and low imagery users to assess
whether this influenced hippocampal engagement during
VPA encoding.

In line with the scene construction theory, we hypoth-
esized that anterior hippocampal activity would be ap-
parent for Scene words pairs, given the likely evocation
of scene imagery. We also predicted that anterior hippo-
campal activity would be increased for Object word
pairs and that this would be best explained by the use
of scene imagery. Zusätzlich, we expected that the effect
of scene imagery use on the hippocampus would be
most apparent in high imagery users. Im Gegensatz, Wir
predicted that Abstract words pairs would engage areas
outside the hippocampus, even when only subsequently
remembered pairs were considered.

METHODEN

Teilnehmer

Forty-five individuals took part in the fMRI study. All were
healthy, right-handed, and had normal or corrected-
to-normal vision. Given the verbal nature of the task,
all participants were highly proficient in English, hatte
English as their first language, and were educated in
English throughout their school years. Each partici-
pant gave written informed consent. The study was ap-
proved by the University College London Research Ethics

Tisch 1. Characteristics of the Participant Groups

Committee. Participants were recruited on the basis of
their scores on the Vividness of Visual Imagery Question-
naire ( VVIQ; Marks, 1973). The VVIQ is a widely used
self-report questionnaire, which asks participants to bring
images to mind and rate them on a 5-point scale as to their
vividness (anchored at 1 = Perfectly clear and as vivid as
normal vision and 5 = No image at all, you only “know”
that you are thinking of the object). daher, a high
score on the VVIQ corresponds to low use of visual imag-
ery. The validity of the VVIQ has been demonstrated in
numerous ways. Zum Beispiel, experimental studies have
found that high visualizers were able to match two pic-
tures more quickly than low visualizers when the first pic-
ture had to be retained as a mental image over a 20-sec
Zeitraum (Gur & Hilgard, 1975). Zusätzlich, significant cor-
relations between the VVIQ and the Betts’ Questionnaire
Upon Mental Imagery (another widely used imagery
questionnaire; Sheehan, 1967) have also been reported
(Campos & Pérez-Fabello, 2005; Burton & Fogarty, 2003).
Our fMRI participants comprised three subgroups (n =
15 in each), low imagery users, mid imagery users, Und
high imagery users. Anfänglich, 184 people completed the
VVIQ. Fifteen of the highest and 15 of the lowest scorers
made up the low and high imagery groups. A further 15
mid scorers served as the mid imagery group. We acknowl-
edge that these groups are relatively small for an fMRI
Studie, but we were nevertheless interested to see whether
any differences would be observed. The groups did not
differ significantly on age, Geschlecht, years of education,
and general intellect. Tisch 1 provides details of the three
groups.

Stimuli

To ensure that any fMRI differences were due to our
imagery manipulation and not other word properties,
the word conditions were highly matched. Six hundred

Imagery Group

Low

Mid

Hoch

Low vs. Mid

Low vs. High Mid vs. Hoch

Alter, Jahre

23.07 (2.31)

21.87 (2.20)

23.93 (5.26)

NEIN. of male participants

6 (40.0%)

7 (46.67%)

8 (53.33%)

Years of education

16.0 (1.89)

15.8 (1.61)

16.0 (2.33)

Matrix Reasoning

12.47 (2.26)

11.47 (2.17)

12.07 (3.61)

TOPF

FSIQ

VCI

54.93 (5.13)

57.47 (5.49)

53.0 (9.47)

110.13 (5.48)

111.97 (6.13)

110.22 (5.99)

108.93 (5.32)

110.81 (6.18)

108.75 (6.0)

.16

.71

.76

.23

.20

.39

.38

.57

.46

1.0

.72

.49

.97

.93

.18

.72

.79

.59

.13

.44

.36

VVIQ mean score

3.08 (0.45)

2.15 (0.17)

1.51 (0.25)

<.001 <.001 <.001 Means (SDs). Two-tailed p values for t tests (χ2 test for the number of male participants). General intellect was measured using the Matrix Reasoning subtest (scaled scores) of the Wechsler Adult Intelligence Scale-IV ( Wechsler, 2008) and the Test of Premorbid Function (TOPF; Wechsler, 2011), provided an estimate of Full Scale IQ (FSIQ) and a Verbal Comprehension Index ( VCI). Clark, Kim, and Maguire 1823 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 fifty-four words were required for the study—218 Scene words, 218 Object words, and 218 Abstract words. Words were initially sourced from databases created by Brysbaert and colleagues, which provided ratings for concreteness, word frequency, age of acquisition, valence, and arousal (Brysbaert, Warriner, & Kuperman, 2014; van Heuven, Mandera, Keuleers, & Brysbaert, 2014; Warriner, Kuperman, & Brysbaert, 2013; Kuperman, Stadthagen-Gonzalez, & Brysbaert, 2012). It was important to control for valence and arousal given reports of higher emotional ratings for abstract words, which could influence fMRI activity (Vigliocco et al., 2014; Kousta, Vigliocco, Vinson, Andrews, & Del Campo, 2011). We also used data from the English Lexicon Project (Balota et al., 2007) to provide lexical in- formation about each word—word length, number of phonemes, number of syllables, number of orthographic neighbors, and number of phonological and phonographic neighbors with and without homophones. To verify that each word induced the expected imagery (i.e., scene imagery, object imagery, or very little/no imagery for the abstract words), we collected two further ratings for each word. First, a rating of imageability to ensure that Scene and Object words were not only con- crete but also highly imageable (although concreteness and imageability are often interchanged, and although they are highly related constructs, they are not the same; Paivio, Yuille, & Madigan, 1968) and, additionally, that Abstract words were low on imageability. Second, a decision was elicited about the type of imagery the word brought to mind. This was in response to the following instruction: “If you had an image we would like you to classify it as either a ‘scene’ or an ‘object’. A scene is an image in your mind that has a sense of space; that you could step into or operate within. An object on the other hand is more of an isolated image, without additional background imagery. It is also likely that for a number of words you will experience very little or no imagery—please do select this option if this is the case.” These ratings were collected from 119 participants in total using Amazon Mechanical Turk’s crowdsourcing Web site, following the procedures used by Brysbaert and colleagues for the databases described above. Words were classified as a Scene or Object word when there was a minimum of 70% agreement on the type of imagery brought to mind, and the mean imageability rating was greater than 3.5 (out of 5). For Abstract words, the mean imageability had to be less than or equal to 2. An overview of the word properties is shown in Table 2. This also in- cludes summary comparison statistics. A list of the words in each category can be found in Appendices A–C and at www.fil.ion.ucl.ac.uk/Maguire/Clark_et_al_2018_Scene_ Words.pdf, www.fil.ion.ucl.ac.uk/Maguire/Clark_et_al_ 2018_Object_Words.pdf, www.fil.ion.ucl.ac.uk/Maguire/ Clark_et_al_2018_Abstract_Words.pdf. Scene, Object, and Abstract words were matched on 13 of the 16 measures. Scene and Object words were matched on all 16 measures, whereas Abstract words, as expected, were less concrete and less imageable than Scene and Object words and had a higher age of acqui- sition, as is normal for abstract words (Kuperman et al., 2012; Stadthagen-Gonzalez & Davis, 2006). As well as being matched at the overall word type level as shown on Table 2, within each word type, words were assigned to one of four lists (word pairs, single words, catch trials, or postscan memory test lures), and all lists were matched on all measures. Experimental Design and Task The fMRI task consisted of two elements, the main task and catch trials. The latter were included to provide an active response element and to encourage concentration during the experiment. To match the WMS-IV Verbal Paired Associate Test ( Wechsler, 2009), each stimulus was presented for 4 sec. This was followed by a jittered baseline (a central fixation cross) for between 2 and 5 sec, which aided concentration by reducing the predictability of stimulus presentation (Figure 1D). The scanning session was split into four runs, three runs containing 80 trials lasting 10 min each and a final run of 78 trials lasting 9 min 45 sec. Trials were presented randomly for each partici- pant with no restrictions on what could precede or follow each trial. Unknown to participants, there were six categories of stimuli—high imagery Scene words, high imagery Object words, and very low imagery Abstract words, shown either in pairs of the same word type (Figure 1A) or as single words (Figure 1B). To equalize visual presentation be- tween the word pairs and the single words, the latter were presented with a random letter string that did not follow the rules of the English language and did not re- semble real words (Figure 1B). The average, minimum, and maximum length of the letter strings was matched to the real words. Letter strings could either be presented at the top or the bottom of the screen. There were 45 tri- als of each condition, with each word shown only once to the participant. Our prime interest was in the word pair conditions and, in particular, the Object word pairs, as these related directly to our research question. The single- word conditions were included for the purposes of specific analyses, which are detailed in the Results section. Participants were asked to try to commit the real words to memory for later memory tests and were specifically instructed that they would be asked to recall the pairs of real words as pairs. They were explicitly told they would not need to remember the random letter strings. No further instructions about how to memorize the stimuli were given (i.e., we did not tell participants to use any particular strategy). Participants were told that, occasionally, there would be catch trials where they had to indicate, using a button 1824 Journal of Cognitive Neuroscience Volume 30, Number 12 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Table 2. Properties of Each Word Type Type of Word p Scene Object Abstract Scene vs. Object Scene vs. Abstract Object vs. Abstract Word Property Lexical Criteria No. of lettersa No. of phonemesa No. of syllablesa 6.73 (1.99) 6.64 (1.91) 6.75 (1.97) 5.61 (1.89) 5.41 (1.71) 5.66 (1.72) 2.09 (0.85) 2.06 (0.79) 2.16 (0.77) No. of orthographic neighborsa 2.57 (4.97) 3.09 (4.96) 2.35 (4.33) No. of phonological neighborsa 6.28 (11.71) 7.61 (11.80) 6.12 (11.31) No. of phonological neighbors (including homophones)a 6.88 (12.59) 8.13 (12.48) 6.66 (11.86) No. of phonographic neighborsa 1.53 (3.51) 1.78 (3.48) 1.46 (3.21) No. of phonographic neighbors (including homophones)a Word frequency: Zipf b Age of acquisitionc 1.61 (3.67) 1.96 (3.63) 1.49 (3.36) 3.90 (0.71) 3.80 (0.61) 3.88 (0.82) 7.69 (2.14) 7.40 (2.12) 9.78 (2.46) Emotional Constructs Valenced No. of positive wordsd,e Hedonic valenced,f Arousald Imagery Concretenessg Imageabilityh 5.68 (1.08) 5.63 (1.02) 5.58 (1.12) 171 (78.44%) 173 (79.6%) 167 (76.61%) 1.07 (0.69) 0.98 (0.68) 1.04 (0.70) 4.07 (0.96) 3.99 (0.87) 4.04 (0.71) 4.65 (0.22) 4.68 (0.22) 1.83 (0.29) 4.38 (0.29) 4.41 (0.32) 1.53 (0.20) .64 .25 .68 .28 .23 .30 .45 .32 .12 .15 .63 .81 .18 .34 .11 .31 .90 .77 .38 .62 .89 .85 .84 .72 .77 .55 .13 .18 .10 .18 .21 .32 .16 .27 <.001 <.001 .34 .65 .69 .73 .61 .49 .34 .46 <.001 <.001 <.001 <.001 Means (SDs). Two-tailed p values for t tests (χ2 test for the number of positive words). Note that each comparison was assessed separately to provide a greater opportunity for any differences between conditions to be identified. aFrom the English Lexion Project (Balota et al., 2007: exlexicon.wustl.edu). bFrom van Heuven et al. (2014). The Zipf scale is a standardized measure of word frequency using a logarithmic scale. Values go from 1 (low- frequency words) to 6 (high-frequency words). cFrom Kuperman et al. (2012). dFrom Warriner et al. (2013). ePositive words were those that had a valence score greater than or equal to 5. fHedonic valence is the distance from neutrality (i.e., from 5), regardless of being positive or negative, as per Vigliocco et al. (2014). gFrom Brysbaert et al. (2014). hCollected for the current study as detailed in the Methods. press, if they saw a real word presented with a “pseudo- word” (Figure 1C). The participants were informed that they were not required to remember the real word or the pseudoword presented in these catch trials. A pseudo- word is a combination of letters that resembles a real English word and follows the rules of the English language but is not an actual real word. Pseudowords were gener- ated using the English Lexicon Project (Balota et al., 2007) and were paired with Scene, Object, or Abstract words. They were presented at either the top or the bottom of the screen to ensure that participants attended to both. The number of letters and orthographic neighbors of the pseudowords were matched to all of the real word conditions and across the three pseudoword groups (all Clark, Kim, and Maguire 1825 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 had seen it in the scanner (old) or not (new). Following this, they rated their confidence in their answer on a 3-point scale—high confidence, low confidence, or guess- ing. Any trials where a participant correctly responded “old” and then indicated they were guessing were excluded from subsequent analyses. After the item memory test, memory for the pairs of words was examined. This associative memory test pre- sented all of the 135 word pairs shown to participants in the scanner and an additional 66 lure pairs (22 of each type), one pair at a time, for up to 5 sec. The word pairs were presented in a different random order for each participant. The lure pairs were constructed from the single words that were presented to the participants in the scanner. Therefore, the participants had seen all of the words presented to them in the associative recog- nition memory test, but not all were previously in pairs, specifically testing whether the participants could remem- ber the correct associations. Participants were asked to indicate whether they saw that exact word pair presented to them in the scanner (old) or not (new). They were explicitly told that some pairs would be constructed from the single words they had seen during scanning and not to make judgments solely on individual words, but to consider the pair itself. Confidence ratings were obtained in the same way as for the item memory test, and trials where a participant correctly responded “old” and then indicated they were guessing were excluded from sub- sequent analyses. Debriefing On completion of the memory tests, participants were asked about their strategies for processing the words while they were in the scanner. At this point, the partic- ipants were told about the three different types of words presented to them—Scenes, Objects, and Abstract. For each word type and separately for single words and word pairs, participants were presented with reminders of the words. They were then asked to choose from a list of options as to which strategy best reflected how they processed that word type. Options included the follow- ing: “I had a visual image of a scene related to this type of single word” (scene imagery for single words), “I had a visual image of the two entities that the words repre- sented within a single visual scene” (scene imagery for word pairs), “I had a visual image of a single entity (e.g., one specific object) for a word with no other background imagery” (object imagery), “I read each word without forming any visual imagery at all” (no imagery). Statistical Analyses of the Behavioral Data Stimuli Creation and Participant Group Comparisons Comparisons between word conditions and between the participant groups were performed using independent samples t tests for continuous variables and χ2 tests Figure 1. Example stimuli and trial timeline. (A) Examples of stimuli from each of the word types in the order of (from left to right) Scene word pair, Object word pair, and Abstract word pair. (B) Examples of single word trials in the order of (from left to right) Scene single word, Object single word, and Abstract single word. Single words were shown with random letter strings (which could be presented at either the top or the bottom) to be similar to the visual presentation of the word pairs. (C) Examples of catch trials, where a real word was presented with a pseudoword, which could be presented as either the top or bottom word. (D) Example timeline of several trials. ps > .3). Zusätzlich, across the pseudoword groups, Wir
matched the accuracy of pseudoword identification (alle
ps > .6) as reported in the English Lexicon Project (Balota
et al., 2007). Forty-eight catch trials were presented over
the course of the experiment, 16 trials with each of the
word types, ranging between 10 Und 15 in each of the four
runs. Catch trials were pseudorandomly presented to
ensure regular presentation, but not in a predictable man-
ner. Feedback was provided at the end of each scanning
run as to the number of correctly identified pseudowords
and incorrectly identified real words.

Postscan Recognition Memory Tests

Following scanning, participants had two recognition
memory tests. The first was an item recognition memory
test for all 405 words presented during scanning (45 Wörter
for each of three single word types and 90 words for each
of three paired word types) and a further 201 foils (67 von
each word type). Each word was presented on its own in
the center of the screen for up to 5 Sek. Words were pre-
sented randomly in a different order for each participant.
Participants had to indicate for each word whether they

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for categorical variables. An alpha level of p > .05 War
used to determine that the stimuli/groups were matched.
Note that each comparison was assessed separately
(using t tests or χ2 tests) to provide a greater oppor-
tunity for any differences between conditions to be
identified.

Main Study

Both within- and between-participant designs were used.
The majority of analyses followed a within-participant
Design, with all participants seeing all word conditions. In
addition, participants were split into three groups depen-
dent on their VVIQ score allowing for between-participant
analyses to be performed.

All data were assessed for outliers, defined as values
that were at least 2 standard deviations away from the
mean. If an outlier was identified, then the participant
was removed from the analysis in question (and this is
explicitly noted in the Results section). Memory per-
formance for each word condition was compared with
chance level (50%) using one-sample t tests. For all
within-participant analyses, when comparing across three
Bedingungen, repeated-measures ANOVAs with follow-up
paired t tests were used, and for comparison across two
Bedingungen, paired t tests were utilized. For between-
participant analyses, a one-way ANOVA was performed
with follow-up independent samples t tests.

All ANOVAs were subjected to Greenhouse–Geisser
adjustment to the degrees of freedom if Mauchly’s sphe-
ricity test identified that sphericity had been violated. Für
all statistical tests, alpha was set at .05. Effect sizes are
reported following significant results as Cohen’s d for
one sample and independent sample t tests, eta-squared
for repeated-measures ANOVA, and Cohen’s d for repeated
Maßnahmen (drm) for paired samples t tests (Lakens, 2013).
All analyses were performed in IBM SPSS statistics v22.

Scanning Parameters and Data Preprocessing

T2*-weighted echo-planar images (EPI) were acquired
using a 3T Siemens Trio scanner (Siemens Healthcare)
with a 32-channel head coil. fMRI data were acquired over
four scanning runs using scanning parameters optimized
for reducing susceptibility-induced signal loss in the
medial-temporal lobe: 48 transverse slices angled at −30°,
repetition time = 3.36 Sek, Echozeit (DER) = 30 ms, res-
olution = 3 × 3 × 3 mm, matrix size = 64 × 74, z-shim
gradient moment of −0.4 mT/m msec (Weiskopf, Hutton,
Josephs, & Deichmann, 2006). Fieldmaps were acquired
with a standard manufacturer’s double-echo gradient-
echo field map sequence (short TE = 10 ms, long
TE = 12.46 ms, 64 axial slices with 2-mm thickness
and 1-mm gap yielding whole-brain coverage; in-plane
Auflösung 3 × 3 mm). After the functional scans, a 3D
MDEFT structural scan was obtained with 1-mm isotropic
Auflösung (Deichmann, Schwarzbauer, & Turner, 2004).

Preprocessing of data was performed using SPM12
(www.fil.ion.ucl.ac.uk/spm). The output of the SPM image
realignment protocol showed that head motion was low
(mean [SD] in millimeters: x = 0.51 [0.32], y = 1.29
[0.33], z = 1.64 [0.80]; mean [SD] in degrees: pitch =
0.03 [0.03], roll = 0.01 [0.01], yaw = 0.01 [0.01]) und war
smaller than the voxel size. Functional images were co-
registered to the structural image and then realigned and
unwarped using field maps. The participant’s structural im-
age was segmented and spatially normalized to a standard
EPI template in MNI space with a voxel size of 2 × 2 × 2 mm
and the normalization parameters were then applied to
the functional data. For the univariate analyses, the func-
tional data were smoothed using an 8-mm FWHM Gaussian
kernel. In line with published representational similarity
Analyse (RSA) Literatur (z.B., Chadwick, Jolly, Amos,
Hassabis, & Spiers, 2015; Marchette, Vass, Ryan, & Epstein,
2014; Kriegeskorte, Mur, Ruff, et al., 2008), the multivariate
analyses used unsmoothed data. We used unsmoothed
data to capture neural information in the form of spatially
distributed activity across multiple voxels. Smoothing
potentially washes out the fine activity differences between
voxels.

Where bilateral ROI analyses were performed, Die
hippocampal ROIs were manually delineated on a pre-
viously collected (n = 36) group-averaged structural MRI
scan (1 × 1 × 1 mm) using ITK-SNAP (www.itksnap.org)
and then resampled to our functional scans (2 × 2 ×
2 mm). The anterior hippocampus was delineated using
an anatomical mask that was defined in the coronal plane
and went from the first slice where the hippocampus can
be observed in its most anterior extent until the final slice
of the uncus. In terms of structural space, this amounted
Zu 3616 voxels and in functional space to 481 voxels. Der
posterior hippocampus was defined as proceeding from
the first slice following the uncus until the final slice of
observation in its most posterior extent (see Dalton,
Zeidman, Barry, Williams, & Maguire, 2017, for more
Einzelheiten). In terms of structural space, this amounted to
4779 voxels and in functional space to 575. The whole hip-
pocampus mask combined the anterior and posterior
masks and therefore contained 8395 voxels in structural
space and 1056 voxels in functional space.

fMRI Analysis: Univariate

The six experimental word conditions were Scene, Object,
and Abstract words, presented as either word pairs or
single words. Wie oben beschrieben, our prime interest was in
the word pair conditions and, insbesondere, the Object word
pairs, as these related directly to our research question. Wir
therefore directly contrasted fMRI BOLD responses be-
tween the word pair conditions. The single-word condi-
tions were included for the purposes of specific analyses,
which are detailed in the Results section. We performed
two types of whole-brain analysis, one using all of the trials
(45 per condition) and the other using only trials where the

Clark, Kim, and Maguire

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items were subsequently remembered, not including
trials where the participant indicated they were guessing.
The average number of trials per condition were as
follows: Scene word pairs, 31.49 (SD = 6.25); Object
word pairs, 34.53 (SD = 5.84); Abstract word pairs,
27.42 (SD = 8.67). See Table 4 for comparisons of the
number of correct trials, not including guessing, across
the conditions.

For both analyses, the general linear model consisted of
the word condition regressors convolved with the hemo-
dynamic response function, in addition to participant-
specific movement regressors and physiological noise
regressors. The Artifact Detection Toolbox (www.nitrc.
org/projects/artifact_detect/ ) was used to identify spikes
in global brain activation, and these were entered as a
separate regressor. Participant-specific parameter esti-
mates for each regressor of interest were calculated for
each voxel. Second-level random effects analyses were then
performed using one-sample t tests on the parameter esti-
Kumpels. For comparison across VVIQ imagery groups, Wir
performed an ANOVA with follow-up independent sample
t tests. We report results at a peak-level threshold of p
less than .001 whole-brain uncorrected for our a priori
ROI—the hippocampus—and p less than .05 family-wise
Fehler (FWE)-corrected at the voxel level elsewhere.

Zusätzlich, several ROI analyses were performed on
a subset of the univariate analyses. Three ROIs were
considered—the whole hippocampus, the anterior hip-
pocampus, and the posterior hippocampus (all bilat-
eral). We used a peak-level threshold of p less than
.05 FWE-corrected at the voxel level for each mask
Und, where indicated in the Results section, also a more
lenient threshold of p less than .001 uncorrected for
each mask.

fMRI Analysis: Multivariate

Multivoxel pattern analysis was used to test whether the
neural representations of the Object word pairs were
more similar to the Scene single words than the Object
single words when separately examining bilateral anterior
and posterior hippocampal ROIs. For each participant,
t statistics for each voxel in the ROI were computed for
each condition (Object word pair, Object single word,
Scene single word) and in each scanning run. The Pearson
correlation between each condition was then calculated
as a similarity measure (Object word pair/Object word pair,
Object word pair/Scene single word, Object word pair/
Object single word). The similarity measure was cross-
validated across different scanning runs to guarantee
the independence of each data set. Repeated-measures
ANOVA and paired t tests were used to compare the sim-
ilarity between conditions at the group level. This multi-
variate analysis was first applied to the data from all
participants and then to the three subsets of participants
(niedrig, mid, and high imagery users). All data were as-
sessed for outliers, defined as values that were at least

2 standard deviations away from the group mean. Wenn ein
outlier was identified, then the participant was removed
from the analysis in question (and this is explicitly noted
in the Results section).

Note that the absolute correlation of the similarity
value is expected to be low because of inherent neural
variability and the fact that a unique set of words was pre-
sented for each scanning run. Als solche, the important
measure is the comparison of the similarity value between
the conditions, not the absolute similarity value of a single
condition. The range of similarity values that we found was
entirely consistent with those reported in other studies uti-
lizing a similar representational similarity approach in a
variety of learning, Erinnerung, and navigation tasks in a wide
range of brain regions (Kim, Jeffery, & Maguire, 2017;
Bellmund, Deuker, Navarro Schröder, & Doeller, 2016;
Deuker, Bellmund, Navarro Schröder, & Doeller, 2016;
Schapiro, Turk-Browne, Norman, & Botvinick, 2016; Schuck,
Cai, Wilson, & Niv, 2016; Chadwick et al., 2015; Hsieh &
Ranganath, 2015; Milivojevic, Vicente-Grabovetsky, &
Doeller, 2015; Hsieh, Gruber, Jenkins, & Ranganath,
2014; Staresina, Henson, Kriegeskorte, & Alink, 2012).

ERGEBNISSE

Behavioral

On average, participants identified 85.56% (SD = 11.52)
of the pseudowords during catch trials, showing that they
maintained concentration during the fMRI experiment.
On the postscan item memory test, Scene, Object, Und
Abstract words were remembered above chance, und da
were no differences between the conditions (Tisch 3,
which includes the statistics). Performance on the asso-
ciative memory test also showed that Scene, Object, Und
Abstract word pairs were remembered above chance
(Tisch 4, which includes the statistics). Considering the
average performance across the four word conditions
used in the main univariate analyses (d.h., Scene word
pairs, Object word pairs, Abstract word pairs, Abstrakt
single words) then one participant performed below
chance. The fMRI analyses do not change whether this
participant is included or not. Comparison of memory
performance across the word types found differences in
performance in line with the literature (Paivio, 1969). Beide
types of high imagery word pairs (Scene and Object) war
remembered better than Abstract word pairs (Figur 2;
Tisch 4), whereas Object word pairs were remembered
better than Scene word pairs. Given that the word pair
memory lures were highly confusable with the actual word
pairs (because the lure pairs were made up of the studied
values were also calculated for the word
single words), D
0
pairs. Scene, Object, and Abstract word pairs all showed d
values greater than 0, representing the ability to discrimi-
nate between old and new pairs (Tisch 4). Both Scene
0 values than Abstract
and Object word pairs had greater d
0 values were greater
word pairs, and Object word pairs d

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Tisch 3. Performance (% Correct) on the Postscan Item
Memory Test (Nonguessing Trials)

Scene
Single Words

Object
Single Words

Abstrakt
Single Words

Mean

67.41

14.93

66.37

17.71

67.61

16.06

than those for Scene word pairs (Tisch 4), showing the
same pattern as that calculated using the percentage
correct. Gesamt, these behavioral findings show that, von-
spite the challenging nature of the experiment with so
many stimuli, participants engaged with the task commit-
ted a good deal of information to memory and could suc-
cessfully distinguish between previously presented word
pairs and highly confusable lures.

Comparison to Chance (50%)

T(44)

7.82

6.20

7.36

<.001 <.001 <.001 d 2.36 1.87 2.22 Scene single words Object single words Abstract single words Comparison across the Word Types F(1.76, 77.51) Main effect 0.28 p .73 fMRI Univariate Analyses We performed two whole-brain analyses, one using all of the trials and another using only trials where the items were subsequently remembered in the postscan memory tests (the item memory test for the single word trials, the associative memory test for the word pairs, excluding trials where participants correctly responded “old” and then indicated that they were guessing). The two analyses yielded very similar results across the whole brain, even though the analysis using only subsequently remembered stimuli was less well powered because of the reduced number of stimuli. Given that our interest was in the point at which participants were initially processing the word pairs and potentially using mental imagery to do so, we focus on the results of the analysis using all of Table 4. Performance (% Correct and d 0 ) on the Postscan Associative Memory Test (Nonguessing Trials) Percent Correct 0 d Scene Word Pairs Object Word Pairs Abstract Word Pairs Scene Word Pairs Object Word Pairs Abstract Word Pairs Mean SD Scene word pairs Object word pairs Abstract word pairs 69.98 13.88 t(44) 9.65 13.83 3.81 76.74 12.97 Comparison to Chance (50%) p <.001 <.001 <.001 60.94 19.27 d 2.91 4.17 1.15 1.07 0.81 t(44) 8.83 10.84 8.94 1.33 0.83 Comparison to Chance (0) p <.001 <.001 <.001 0.74 0.56 d 2.66 3.27 2.70 Comparison across the Word Types Comparison across the Word Types Main effect Scene vs. Object Scene vs. Abstract Object vs. Abstract F(1.35, 59.48) 24.21 t(44) 5.25 3.58 5.75 p <.001 p <.001 .001 <.001 η2 .36 drm 0.50 0.52 0.94 F(2, 88) 23.75 t(44) 3.06 4.35 6.22 p <.001 p .004 <.001 <.001 η2 .35 drm 0.32 0.42 0.78 Clark, Kim, and Maguire 1829 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 2. Memory performance on the associative memory test shown by percentage correct (left) and d significant difference from chance (for percentage correct the dashed line indicates chance at 50%, for d differences across the word pair types: **p < .01, ***p < .001. 0 (right). Error bars are 1 SEM. ^ indicates a 0 it is 0) at p < .001. Stars show the significant the trials. Results are also reported for the analyses using only the remembered stimuli, which allowed us to con- trol for any memory-related effects. We first compared the high imagery (Scene, Object) and very low imagery (Abstract) word pairs. All of the condi- tions involved associative processing, and so we reasoned that any differences we observed, particularly in hippocam- pal engagement, would be due to the imageability of the Scene and Object word pairs. As predicted, Scene word pairs elicited greater bilateral anterior (but not posterior) hippocampal activity compared with Abstract word pairs (Figure 3A; see full details in Table 5A). Of note, increased activity was also observed in bilateral parahippocampal, fusiform, retrosplenial, and left ventromedial prefrontal cortices. The analysis using only the remembered stimuli showed very similar results, including for the anterior hip- pocampus (Table 6A). The reverse contrast identified no hippocampal engagement, but rather greater activity for l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 3. Comparison of high imagery Scene or Object word pairs with very low imagery Abstract word pairs. The sagittal slice is of the left hemisphere, which is from the ch2better template brain in MRicron (Rorden & Brett, 2000; Holmes et al., 1998). The left of the image is the left side of the brain. The colored bar indicates the t value associated with each voxel. (A) Scene word pairs > Abstract word pairs. (B) Object word pairs >
Abstract word pairs. Images are thresholded at p < .001 uncorrected for display purposes. 1830 Journal of Cognitive Neuroscience Volume 30, Number 12 Table 5. High Imagery Word Pairs Compared with Abstract Word Pairs Region Peak Voxel Coordinates A. Scene Word Pairs > Abstract Word Pairs

Left anterior hippocampus

Right anterior hippocampus

Left retrosplenial cortex

Left fusiform cortex

Right retrosplenial cortex

Left middle occipital cortex

Right parahippocampal cortex

Left inferior temporal cortex

Right fusiform cortex

Left ventrolateral prefrontal cortex

Right middle occipital cortex

Left middle frontal cortex

Left inferior frontal cortex

−20, −16, −20

20, −10, −20

−10, −52, 4

−22, −34, −20

10, −48, 6

−30, −74, 34

24, −34, −20

−56, −54, −10

32, −32, −14

−30, 32, −16

44, −70, 26

−26, 6, 50

−42, 32, 12

B. Object Word Pairs > Abstract Word Pairs

Left anterior hippocampus

Right anterior hippocampus

−20, −10, −18

20, −10, −18

Left ventral medial prefrontal cortex −32, 32, −14

Left fusiform cortex (extending to

−32, −34, −20

parahippocampal cortex)

Left middle occipital cortex

Right ventrolateral prefrontal cortex

Left inferior frontal cortex

−34, −80, 28

34, 32, −12

−40, 28, 14

Right fusiform gyrus (extending to

34, −32, −18

parahippocampal cortex)

8.79

7.58

9.15

9.03

8.73

8.49

8.40

8.03

7.72

6.51

6.48

6.19

5.74

4.45

3.98

9.45

8.88

6.17

6.05

5.72

hippocampal engagement, but rather greater activity for
Abstract word pairs in middle temporal cortex (−62, −32,
−2, T = 8) and temporal pole (−54, 10, −18, T = 7.12).
Increased anterior hippocampal activity was therefore
observed for both Scene and Object word pairs com-
pared with the very low imagery Abstract word pairs. Als
greater anterior hippocampal engagement was apparent
even when using just the remembered stimuli, it is un-
likely that this result can be explained by better associa-
tive memory or successful encoding for the high imagery
word pairs. Rather the results suggest that the anterior
hippocampal activity for word pair processing may be
related to the use of visual imagery.

All of the above contrasts involved word pairs, vorschlagen-
ing that associative binding per se cannot explain the

Tisch 6. Remembered High Imagery Word Pairs Compared
with Remembered Abstract Word Pairs

Region

A. Scene Word Pairs Remembered >
Abstract Word Pairs Remembered

Peak Voxel
Coordinates

Left hippocampus

Right hippocampus

−28, −22, −18

24, −20, −18

7.53

5.09

Left retrosplenial cortex

Left fusiform cortex (extending to

parahippocampal cortex)

−10, −50, 2

−30, −34, −14

10.20

8.21

Right retrosplenial cortex

Left middle occipital lobe

10, −48, 4

−30, −80, 40

Right fusiform cortex (extending to

26, −28, −20

parahippocampal cortex)

Left ventral medial prefrontal cortex −30, 34, −12

Right middle occipital lobe

Left inferior temporal cortex

44, −70, 28

−56, −54, −10

7.47

7.23

7.00

6.51

6.29

5.64

Left hippocampus

−32, −22, −12

5.05

Abstract word pairs in middle temporal cortex (−58, −36,
−2, T = 6.58) and temporal pole (−52, 10, −22, T = 6.16).
Object word pairs also showed greater bilateral anterior
(but not posterior) hippocampal activity compared with
the Abstract word pairs, along with engagement of bilat-
eral parahippocampal cortex, fusiform cortex, and ventro-
medial prefrontal cortex (Abbildung 3B; Table 5B), mit
increased anterior hippocampal activity also apparent
when just the subsequently-remembered stimuli were
berücksichtigt (Table 6B). The reverse contrast identified no

Left ventral medial prefrontal cortex −30, 34, −12

Left fusiform cortex (extending to

−30, −32, −18

parahippocampal cortex)

Left middle occipital lobe

Left inferior temporal cortex

−34, −82, 30

−54, −58, −6

9.26

7.94

6.43

6.13

Left middle temporal cortex

Left temporal pole

Left fusiform cortex

Left inferior frontal cortex

Left inferior occipital cortex

Right inferior occipital cortex

Right lingual cortex

Left precentral gyrus

−64, −36, 2

−52, 12, −16

−38, −46, −20

−54, 24, 12

−42, −68, −12

36, −74, −12

20, −82, −10

−50, 0, 48

8.39

6.72

6.64

6.54

6.52

6.11

5.87

5.84

Peak Voxel
Coordinates

Left inferior frontal gyrus

Left precentral gyrus

Left middle temporal gyrus

Left inferior occipital lobe

Right inferior occipital lobe

Left supplementary motor area

Right inferior frontal gyrus

Right superior temporal pole

Right caudate nucleus

Left pallidum

−54, 14, 12

−48, −2, 48

−52, −46, 4

−38, −78, −8

34, −80, −6

−2, 4, 56

50, 10, 28

46, −30, 4

12, 10, 6

−18, 6, 0

9.50

8.02

8.21

7.23

7.11

6.72

6.44

6.11

6.07

6.04

P < .001 uncorrected for the hippocampus (no activations found) and p < .05 FWE-corrected for the rest of the brain. Brain regions within the medial temporal lobe were identified via visual inspection. For regions outside the medial temporal lobe, the AAL atlas was used (Tzourio- Mazoyer et al., 2002). only: t(44) = 0.63, p = .53). Overall, therefore, even at lenient thresholds and using an ROI approach, no hippo- campal engagement was identified for Abstract word pairs compared with the Abstract single words. Although the absence of evidence is not evidence of absence, this is in direct contrast to our findings of increased hippo- campal activity for the high imagery word pairs compared with the very low imagery Abstract word pairs. This, there- fore, lends support to the idea that the use of visual im- agery might be important for inducing hippocampal responses to word pairs. We also predicted that anterior hippocampal activity would be specifically influenced by the use of scene imagery, as opposed to visual imagery per se. The inclu- sion of both Scene and Object word pairs offered the op- portunity to test this. Scene word pairs would be expected to consistently evoke scene imagery (as both words in a pair represented scenes), whereas Object word pairs could evoke both or either object and scene imagery (e.g., object imagery by imagining the two objects without a back- ground context or scene imagery by creating a scene and placing the two objects into it), thus potentially diluting the hippocampal scene effect. Scene word pairs might there- fore activate the anterior hippocampus to a greater extent than Object word pairs. This comparison also provided an additional opportunity to contrast the effects of scene im- agery and memory performance on hippocampal activity, because Object word pairs were better remembered than the Scene word pairs. As such, if hippocampal activity could be better explained by word pair memory performance 1832 Journal of Cognitive Neuroscience Volume 30, Number 12 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 4. Brain areas more activated by Scene word pairs than Object word pairs. The sagittal slice is of the left hemisphere, which is from the ch2better template brain in MRicron (Rorden & Brett, 2000; Holmes et al., 1998). The left of the image is the left side of the brain. The colored bar indicates the t value associated with each voxel. Images are thresholded at p < .001 uncorrected for display purposes. rather than scene imagery, we would expect that Object word pairs would show greater hippocampal activity than Scene word pairs. Contrasting Scene and Object word pairs revealed that, in line with our prediction, Scene word pairs evoked greater bilateral anterior (but not posterior) hippocampal activity than the Object word pairs (Figure 4; Table 9A). Analysis using just the remembered stimuli gave sim- ilar results (Table 10A). Other areas that showed in- creased activity for the Scene word pairs included the retrosplenial and parahippocampal cortices. The reverse contrast examining what was more activated for Object word pairs compared with Scene word pairs found no evidence of hippocampal activity despite better sub- sequent memory performance for the Object word pairs (Table 9B), even when just the remembered stimuli were examined (Table 10B). It seems, therefore, that the ante- rior hippocampus may be particularly responsive to scene imagery and that increases in hippocampal activity in this task were not driven by greater memory performance. To summarize, our univariate analyses found that Scene word pairs engaged the anterior hippocampus the most, followed by the Object word pairs, with the Abstract word pairs not eliciting any significant increase in activation (Figure 5). This is what we predicted and may be sugges- tive of particular responsivity of the anterior hippocampus to scenes. Multivariate Analyses We next sought further, more direct evidence that our main condition of interest, Object word pairs, elicited hippo- campal activity via scene imagery. Given our univariate find- ings of increased anterior hippocampal activity for Scene word pairs and Object word pairs compared with Abstract word pairs and the extant literature showing the importance of the anterior hippocampus for processing scenes (e.g., Zeidman & Maguire, 2016, but see also Sheldon & Levine, 2016), we looked separately at anatomically defined bilat- eral anterior and posterior hippocampal ROIs. We then used multivariate RSA (Kriegeskorte, Mur, & Bandettini, 2008) to compare the neural patterns of activity associated with encoding Object word pairs with Scene or Object single words. We predicted that the neural representa- tions of Object word pairs in the anterior hippocampus would be more similar to Scene single words than Object single words, but that this would not be apparent in the posterior hippocampus. As our aim was to specifically investigate the contribution of different types of imagery to hippocampal activity, the scene and object single words Table 9. Scene Word Pairs Compared with Object Word Pairs Region Peak Voxel Coordinates A. Scene Word Pairs > Object Word Pairs

Left anterior hippocampus

Right anterior hippocampus

−22, −18, −20

22, −20, −20

Right retrosplenial cortex

Left retrosplenial cortex

16, −54, 20

−10, −50, 4

Left fusiform cortex (extending to

−28, −38, −12

parahippocampal cortex)

5.55

6.07

7.35

7.34

7.25

Right fusiform cortex (extending to

28, −26, −20

6.87

parahippocampal cortex)

Left middle temporal cortex

−58, −6, −14

5.77

B. Object Word Pairs > Scene Word Pairs

Left inferior temporal cortex

−42, −48, −16

7.16

Peak Voxel
Coordinates

Right hippocampus

Left hippocampus

24, −20, −20

−22, −20, −18

Left retrosplenial cortex

−12, −50, 4

Right fusiform cortex (extending to

24, −28, −18

parahippocampal cortex)

Right retrosplenial cortex

10, −48, 6

Left fusiform cortex (extending to

−24, −38, −12

parahippocampal cortex)

5.18

4.26

6.74

6.49

6.46

6.37

B. Object Word Pairs Remembered >
Scene Word Pairs Remembered

Left inferior temporal gyrus

−42, −48, −16

6.12

P < .001 uncorrected for the hippocampus and p < .05 FWE-corrected for the rest of the brain. Brain regions within the medial temporal lobe were identified via visual inspection. For regions outside the medial temporal lobe, the AAL atlas was used (Tzourio-Mazoyer et al., 2002). were chosen as comparators because they consistently elicit either scene or object imagery respectively (see Methods). Abstract words do not elicit much visual imag- ery, so they were not included in the RSA analyses. Three similarity correlations were calculated. First, the similarity between Object word pairs and themselves, which provided a baseline measure of similarity (i.e., the correlation of Object word pairs over the four runs of the scanning experiment). The two similarities of inter- est were the similarity between Object word pairs and Scene single words and the similarity between Object word pairs and Object single words. For the anterior hip- pocampus ROI, two participants showed similarity scores greater than 2 standard deviations away from the mean and were removed from further analysis, leaving a sample of 43 participants. For the posterior hippocampus ROI, again two participants (one of whom was also excluded from the anterior hippocampus analysis) showed similar- ity scores greater than 2 standard deviations away from the mean and were removed from further analysis, leav- ing a sample of 43 participants. For the anterior hippocampus, a repeated-measures ANOVA found a significant difference between the three similarities, F(2, 84) = 3.40, p = .038, η2 = .075. As pre- dicted, the neural representations in the anterior hippo- campus of Object word pairs were more similar to Scene single words (Figure 6A, purple bar) than to Object single words (Figure 6A, light green bar; t(42) = 2.09, p = .042, drm = 0.21). In fact, representations of Object word pairs were as similar to Scene single words as to themselves (Figure 6A, orange bar; t(42) = 0.38, p = .71). Object word pairs were significantly less similar to Object single words than to themselves (t(42) = 2.54, p = .015, drm = 0.23). Of note, these results cannot be explained by sub- sequent memory performance because Scene single words and Object single words were remembered equally well (t(42) = 0.68, p = .50). For the posterior hippocampus, a repeated-measures ANOVA also found a significant difference between the three similarities, F(2, 84) = 4.83, p = .010, η2 = .10. However, in contrast to the anterior hippocampus, the neural representations in the posterior hippocampus of Object word pairs were more similar to themselves (Figure 6B, orange bar) than either Scene single words (Figure 6B, purple bar; t(42) = 2.60, p = .013, drm = 0.32) or Object single words (Figure 6B, light green bar; t(42) = 2.33, p = .025, drm = 0.26). Moreover, there was no difference between the representations of Scene and Object single words (t(42) = −0.71, p = .48). As before, these results cannot be explained by subsequent memory performance because Scene single words and Object single words were remembered equally well (t(42) = 0.74, p = .46). Overall, these multivariate results show that, within the anterior hippocampus, Object word pairs were repre- sented in a similar manner to Scene single words, but not Object single words. On the other hand, within the posterior hippocampus, Object word pairs were only similar to themselves. This provides further support for our hypothesis that Object word pairs evoke anterior Figure 5. Comparison of each word pair condition with a fixation cross baseline. Mean beta values extracted from a bilateral anatomical mask of the anterior hippocampus for each of the word pair conditions compared with the central fixation cross baseline. Error bars are 1 SEM. A repeated-measures ANOVA showed significant differences between the conditions, F(1.69, 74.51) = 16.06, p < .001, η2 = .27. Follow-up paired t tests revealed significant differences between Scene word pairs versus Abstract word pairs, t(44) = 6.46, p < .001, drm = 0.70; Scene word pairs versus Object word pairs, t(44) = 2.97, p = .005, drm = 0.30; Object word pairs versus Abstract word pairs, t(44) = 2.51, p = .016, drm = 0.34. *p < .05, **p < .01, ***p < .001. 1834 Journal of Cognitive Neuroscience Volume 30, Number 12 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 6. The neural similarity of Object word pairs, Scene single words, and Object single words separately for the anterior and posterior hippocampus. (A) Anterior hippocampus. (B) Posterior hippocampus. Object Pair Object Pair = the similarity between Object word pairs between runs; Object Pair Scene Single = the similarity between Object word pairs and Scene single words; Object Pair Object Single = the similarity between Object word pairs and Object single words. Error bars represent 1 SEM adjusted for repeated-measures (Morey, 2008). *p < .05. (but not posterior) hippocampal activity when scene imagery is involved. VVIQ and the Use of Imagery As well as examining participants in one large group, as above, we also divided them into three groups based on whether they reported high, mid, or low imagery ability on the VVIQ. We found no differences in memory perfor- mance among the groups on the word pair tasks (F < 0.4 for all contrasts). Similarly, fMRI univariate analyses involv- ing the word pair conditions revealed no differences in hippocampal activity. Voxel-based morphology (Ashburner, 2009; Mechelli, Price, Friston, & Ashburner, 2005; Ashburner & Friston, 2000) showed no structural differences be- tween the groups anywhere in the brain, including in the hippocampus. Interestingly, however, the imagery groups did differ in one specific way—their strategy for processing the Object word pairs. Although strategy use was similar across the imagery groups for the other word conditions, for the Object word pairs, twice as many participants indicated using a scene imagery strategy in the high imagery group (n = 12/15, 80%) than in the mid or low imagery groups (n = 5/15, 33% and 6/15, 40%, respec- tively). Comparison of scene strategy use compared with other strategy use across the imagery groups revealed this to be a significant difference, χ2(2) = 7.65, p = .022. Given this clear difference in scene imagery use specif- ically for the Object word pairs, we performed the ante- rior and posterior hippocampus RSA analyses again for the three imagery participant groups. We hypothesized that, in the anterior hippocampus, the high imagery group would represent Object word pairs in a similar manner to Scene single words (as with our whole-group analyses), whereas this would not be the case in the mid or low imagery groups. For the posterior hippocampus, on the other hand, we expected no differences between the imagery groups. Participants with similarity values greater than 2 standard deviations away from the mean were again excluded. For the anterior hippocampus ROI analyses, this resulted in one participant being re- moved from each group. For the posterior hippocampus two participants were excluded (both different partici- pants to those excluded from the anterior hippocampus analyses), one from the mid imagery group and one from the low imagery group. Importantly, the pattern of scene imagery strategy remained the same even after the re- moval of these few participants (anterior hippocampus: high imagery group, n = 11/14; mid imagery group, n = 5/14; low imagery group, n = 5/14; χ2(2) = 6.86, p = .032; posterior hippocampus: high imagery group, n = 12/15; mid imagery group, n = 4/14; low imagery group, n = 5/14; χ2(2) = 9.10, p = .011). As predicted, in the anterior hippocampus for the high imagery group, Object word pairs were more similar to Scene single words than Object single words (Figure 7A; t(13) = 4.63, p < .001, d = 0.78). This was not the case for the mid or low imagery groups (t(13) = 0.472, p = .65; t(13) = 0.20, p = .85, respectively). Of note, the inter- action between the imagery groups was significant F(2, 39) = 3.53, p = .039, η2 = 0.15). Inde- (Figure 7B; pendent samples t tests showed that the difference be- tween the similarities was greater in the high imagery group than in the mid and low imagery groups (t(26) = 2.09, p = .046, d = 0.79 and t(26) = 2.72, p = .011, d = 1.03, respectively). As before, these differences cannot be explained by subsequent memory performance be- cause all three groups showed no differences between the Scene single and Object single words (high imagery group: t(13) = 0.35, p = .74; mid imagery group: t(13) = 0.40, p = .69; low imagery group: t(13) = 1.18, p = .26). Clark, Kim, and Maguire 1835 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 7. RSA comparisons of the three imagery groups separately for the anterior and posterior hippocampus. (A) The neural similarity of Object word pairs, Scene single words, and Object single words in the anterior hippocampus when split by self-reported imagery use. Object Pair Scene Single = the similarity between Object word pairs and Scene single words; Object Pair Object Single = the similarity between Object word pairs and Object single words. (B) The difference in similarity between Object word pairs and Scene single words compared with Object words pairs and Object single words in the imagery groups in the anterior hippocampus. (C) The neural similarity of Object word pairs, Scene single words, and Object single words in the posterior hippocampus when split by self-reported imagery use. Object Pair Scene Single = the similarity between Object word pairs and Scene single words; Object Pair Object Single = the similarity between Object word pairs and Object single words. (D) The difference in similarity between Object word pairs and Scene single words compared with Object words pairs and Object single words in the imagery groups in the posterior hippocampus. Error bars represent 1 SEM. *p < .05, ***p < .001. For the posterior hippocampus, on the other hand, there were no differences in similarities in any of the imagery groups (Figure 7C; high imagery group: t(14) = −1.29, p = .22; mid imagery group: t(13) = 0.50, p = .63; low imagery group: t(13) = 0.084, p = .94). In line with these findings, the interaction between the imagery groups was also not significant (Figure 7D; F(2, 40) = 1.07, p = .35). As before, there were no differences in subsequent mem- ory performance between the Scene single and Object single words, suggesting this was not influencing the activ- ity patterns (high imagery group: t(14) = 0.40, p = .69; mid imagery group: t(13) = −0.06, p = .95; low imagery group: t(13) = 1.25, p = .24). In summary, the neural patterns in anterior hippocam- pus for Object word pairs showed greater similarity with the Scene single words in the high imagery group, whereas for the mid and low imagery groups, this was not the case. On the other hand, we saw no differences in any of the imagery groups in the posterior hippocampus. This provides further evidence linking the anterior hippo- campus with the processing of Object word pairs through scene imagery. DISCUSSION The aim of this study was to understand the role of the hippocampus in processing VPA. There were five findings. First, we observed greater anterior (but not posterior) hippocampal activity for high imagery (concrete) word pairs than very low imagery (abstract) word pairs, highlighting the influence of visual imagery. Second, very low imagery abstract word pairs compared with very low imagery abstract single words revealed no differences in hippocampal engagement, despite the former involving binding, adding further support for the significance of visual imagery. Third, increased anterior (but not poste- rior) hippocampal engagement was apparent for Scene word pairs more than Object word pairs, implicating spe- cifically scene imagery. Fourth, for Object word pairs, fMRI activity patterns in the anterior (but not posterior) hippo- campus were more similar to those for scene imagery than object imagery, further underlining the propensity of the anterior hippocampus to respond to scene imagery. Finally, our examination of high, mid, and low imagery users found that the only difference between them was the 1836 Journal of Cognitive Neuroscience Volume 30, Number 12 use of scene imagery for encoding Object word pairs by high imagers, which in turn was linked to scene-related activity patterns in the anterior (but not posterior) hippo- campus. Overall, our results provide evidence that ante- rior hippocampal engagement during VPA seems to be closely related to the use of scene imagery, even for Object word pairs. Previous findings have hinted that visual imagery might be relevant in the hippocampal processing of verbal mate- rial such as VPA. Work in patients with right temporal lobectomies, which included removal of some hippo- campal tissue, suggested that, although memory for high imagery word pairs was impaired, memory for low imagery word pairs was preserved (Jones-Gotman & Milner, 1978). Furthermore, instructing these patients to use visual imag- ery strategies impaired both high and low imagery word pair performance ( Jones-Gotman, 1979). More recently, detailed examination of the language use of patients with bilateral hippocampal damage showed that the patients used fewer high imagery words when producing verbal narratives compared with both healthy controls and pa- tients with damage elsewhere in the brain (Hilverman et al., 2017), supporting a link between the hippocampus and word imageability. In addition, higher than expected word pair performance has been found in amnesic patients for highly semantically related word pairs in comparison to unrelated word pairs of the kind that are usually em- ployed in VPA tasks (Shimamura & Squire, 1984; Winocur & Weiskrantz, 1976). This suggests that when alternate strategies can be used to remember word pairs (i.e., using their semantic relationship rather than constructing scene imagery), amnesic patients do not show the typical VPA impairment. We are, however, unaware of any study that has examined VPA in patients with selective bilateral hippocampal damage where high and low imagery word pairs were directly compared (Clark & Maguire, 2016). fMRI findings also support a possible distinction in hip- pocampal engagement between high and low imagery word pairs. Caplan and Madan (2016) investigated the role of the hippocampus in boosting memory performance for high imagery word pairs, concluding that imageability increased hippocampal activity. However, greater hippo- campal activity for high over low imagery word pairs was only observed at a lenient whole-brain threshold ( p < .01 uncorrected, cluster size ≥ 5), possibly because their low imagery words (e.g., muck, fright) retained quite a degree of imageability. Furthermore, they did not examine the influence of different types of visual imagery on hippo- campal engagement. We did not find hippocampal engagement for the low imagery Abstract word pairs compared with Abstract single words, even when using ROI analyses and just the remembered stimuli. We acknowledge that null re- sults can be difficult to interpret and that an absence of evidence is not evidence of absence. However, even our lenient uncorrected ROI analyses found no evidence of increased hippocampal activity. This is in clear contrast to the finding of increased hippocampal activity for the high imagery word pairs over the very low imagery Abstract word pairs at the whole-brain level. The most parsimonious interpretation is, therefore, that Abstract word pairs may be processed differently to the high imagery word pairs, in particular in terms of hippocampal engagement. By contrast, activity associated with the Abstract word pairs was evident outside the hippocampus, where re- gions that included the left middle temporal cortex, the left temporal pole, and the left inferior frontal gyrus were engaged. These findings are in line with other fMRI stud- ies that examined the representations of abstract words and concepts in the human brain (Wang et al., 2017; Wang, Conder, Blitzer, & Shinkareva, 2010; Binder, Westbury, McKiernan, Possing, & Medler, 2005). Our results, there- fore, align with the notion of different brain systems for processing concrete (high imagery) and abstract (low im- agery) concepts and stimuli. Our different word types were extremely well matched across a wide range of features, with the abstract words being verified as eliciting very little imagery and the scene and object words as reliably eliciting the relevant type of imagery. Using these stimuli, we showed that hippocam- pal involvement in VPA is not linked to visual imagery in general but seems to be specifically related to scene im- agery, even when each word in a pair denoted an object. This supports a prediction made by Maguire and Mullally (2013; see also Clark & Maguire, 2016), who noted that a scene allows us to collate a lot of information in a quick, coherent, and efficient manner. Consequently, they pro- posed that people may automatically use scene imagery during the processing of high imagery verbal material. For instance, we might visualize the scene within which a story is unfolding or place the objects described in word pairs in a simple scene together. If verbal tasks can provoke the use of imagery-based strategies and if these strategies involve scenes, then patients with hippocampal amnesia would be expected to perform poorly on VPA tasks involving high imagery concrete words because they are known to have difficulty with constructing scenes in their imagination (e.g., Kurczek et al., 2015; Mullally, Intraub, & Maguire, 2012; Race et al., 2011; Andelman, Hoofien, Goldberg, Aizenstein, & Neufeld, 2010; Hassabis, Kumaran, Vann, et al., 2007). This impair- ment, which was not apparent for single objects, prompted the proposal of the scene construction theory, which holds that scene imagery constructed by the hippocam- pus is a vital component of memory and other functions (Maguire & Mullally, 2013; Hassabis & Maguire, 2007). Findings over the last decade have since linked scenes to the hippocampus in relation to autobiographical mem- ory (Hassabis, Kumaran, & Maguire, 2007; Hassabis & Maguire, 2007) but also widely across cognition, including perception (McCormick et al., 2017; Mullally et al., 2012; Graham et al., 2010), future thinking (Irish, Hodges, & Piguet, 2013; Schacter et al., 2012; Hassabis, Kumaran, Vann, et al., 2007), spatial navigation (Clark & Maguire, Clark, Kim, and Maguire 1837 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 2016; Maguire, Nannery, & Spiers, 2006), and decision- making (McCormick, Rosenthal, Miller, & Maguire, 2016; Mullally & Maguire, 2014). However, as the current study was only designed to examine the role of the hippocampus in the VPA task, we do not speculate further here as to whether or not scene construction is the primary mecha- nism at play within the hippocampus. For more on this is- sue, we refer the reader to broader theoretical discussions of the scene construction theory (McCormick, Ciaramelli, De Luca, & Maguire, 2018; Dalton & Maguire, 2017; Clark & Maguire, 2016; Maguire, Intraub, & Mullally, 2016) and alternative accounts of hippocampal function (Moscovitch et al., 2016; Sheldon & Levine, 2016; Eichenbaum & Cohen, 2014; Schacter et al., 2012). Our hippocampal findings were located in the ante- rior portion of the hippocampus. Anterior and posterior functional differentiation is acknowledged as a feature of the hippocampus, although the exact roles played by each portion are not widely agreed (Ritchey, Montchal, Yonelinas, & Ranganath, 2015; Strange, Witter, Lein, & Moser, 2014; Poppenk, Evensmoen, Moscovitch, & Nadel, 2013; Fanselow & Dong, 2010; Moser & Moser, 1998). Of note, the medial portion of the anterior hippocampus contains the presubiculum and parasubiculum hippo- campal subfields. These areas have been highlighted as being consistently implicated in scene processing (re- viewed in Zeidman & Maguire, 2016) and were recently proposed to be neuroanatomically determined to process scenes (Dalton & Maguire, 2017). The current results seem to accord with these findings, although higher- resolution studies are required to determine the specific subfields involved. An important point to consider is whether our results can be explained by the effectiveness of encoding, as measured in a subsequent memory test. It is certainly true that people tend to recall fewer abstract than con- crete words in behavioral studies of memory (Paivio, Walsh, & Bons, 1994; Jones, 1974; Paivio, 1969). We tested memory for both single words and paired words. Memory performance for Scene, Object, and Abstract words was comparable when tested singly. Memory for the word pairs was significantly lower for the low imagery Abstract word pairs compared with the Scene word pairs and Object word pairs. Nevertheless, performance for all conditions was above chance, which was impressive given the large number of stimuli to be encoded with only one exposure. Increased hippocampal activity was apparent for both Scene word pairs and Object words pairs compared with the Abstract word pairs when all stimuli or only the sub- sequently remembered stimuli were analyzed. Further- more, although Object word pairs were remembered better than Scene word pairs, hippocampal activity was nevertheless greater for the Scene word pairs. This shows that our results cannot be explained by encoding success. It is also worth considering why such a gradient in mem- ory performance was observed within the word pairs, with Object word pairs being remembered better than Scene word pairs, which were remembered better than Abstract word pairs. One possibility may be that memory perfor- mance benefitted from the extent to which the two words could be combined into some kind of relationship. This is arguably easier for two objects than two scenes, both of which are easier than for two abstract concepts. Although differences between the performance of amnesic patients and healthy participants on VPA tasks are typically observed during cued recall, in the current study we used recognition memory tests postscanning to assess the success of encoding. This is because testing cued recall for 135 word pairs that were each seen only once is simply too difficult even for healthy participants. For example, learning just 14 (high imagery concrete) word pairs on the WMS-IV VPA task is performed over four learning trials. We did, however, ensure that the associative recognition memory test was challenging by constructing the lure word pairs from the single words that were presented to the participants during scanning. Thus, all words were previously seen by participants, but not all were previously seen in pairs. Moreover, we believe that the use of a recognition memory test instead of cued recall had little impact on the patterns of brain activity we observed because brain activity was assessed during the initial presentation of the word pairs and not during memory retrieval. As partici- pants were not told exactly how their memory would be tested after the learning phase, it might be expected that participants engaged in the most effortful encoding that they could. That the involvement of the hippocam- pus was identified when using all the trials in the fMRI analysis or just the subsequently remembered stimuli also points to the use of imagery at the time of stimuli presentation as being of most relevance rather than en- coding success. There is a wealth of research linking the hippocampus with associative binding (e.g., Palombo, Hayes, Peterson, Keane, & Verfaellie, 2018; Roberts et al., 2018; Rangel et al., 2016; Schwarb et al., 2015; Eichenbaum & Cohen, 2014; Addis, Cheng, Roberts, & Schacter, 2011; Konkel & Cohen, 2009; Davachi, 2006). We do not deny this is the case but suggest that our results provoke a reconsid- eration of the underlying reason for apparent associative effects. We found that the creation of associations be- tween nonimageable Abstract word pairs did not elicit an increase in hippocampal activity compared with Abstract single words, even when only subsequently remembered stimuli were considered. If binding per se was the reason for hippocampal involvement in our study, then this con- trast should have revealed it. We suggest instead that the anterior hippocampus engages in associative binding spe- cifically to create scene imagery and that this relationship with scenes has been underestimated or ignored in VPA and other associative tasks despite potentially having a significant influence on hippocampal engagement. Our participants were self-declared low, mid, or high imagery users as measured by the VVIQ. They differed 1838 Journal of Cognitive Neuroscience Volume 30, Number 12 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 only in the degree of scene imagery usage, in particular during the processing of Object word pairs, with high imagers showing the greatest amount. Given that scene imagery has been implicated in functions across cogni- tion, it might be predicted that those who are able to use scene imagery well might have more successful recall of autobiographical memories and better spatial naviga- tion. Individual differences studies are clearly required to investigate this important issue in depth, as currently there is a dearth of such work (a point also noted by Palombo, Sheldon, & Levine, 2018). In this study, increased use of scene imagery by the high imagery group did not convey a memory advantage for the Object word pairs. However, in the real world, with more complex memo- randa like autobiographical memories, we predict that scene imagery would promote better memory. In conclusion, we showed a strong link between the anterior hippocampus and processing words in a VPA task mediated through scene imagery. This offers a way to reconcile hippocampal theories that have a visuo- spatial bias with the processing and subsequent memory of verbal material. Moreover, we speculate that this could hint at a verbal system in humans piggy-backing on top of an evolutionarily older visual (scene) mechanism (see also Corballis, 2017). We believe it is likely that other common verbal tests, such as story recall and list learn- ing, which are typically highly imageable, may similarly engage scene imagery and the anterior hippocampus. Greater use of low imagery abstract verbal material would seem to be prudent in future verbal memory studies. Indeed, an obvious prediction arising from our results is that patients with selective bilateral hippocampal dam- age would be better at recalling abstract compared with imageable word pairs, provided care is taken to match the stimuli precisely. Our data do not speak to the issue of whether or not scene construction is the primary mechanism at play within the hippocampus, as our main interest was in examining VPA, a task closely aligned with the hippocampus. What our results show, and we believe in a compelling fashion, is that anterior hippocampal engagement during VPA seems to be best explained by the use of scene imagery. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Clark, Kim, and Maguire 1839 Appendix A. List of Scene Words Used in the Study Airfield Airport Aisle Alley Apartment Aquarium Arcade Arena Attic Auditorium Avalanche Avenue Backyard Bakery Ballroom Bank Banquet Barbecue Barnyard Basement Bathroom Battlefield Bay Beach Bedroom Blizzard Boardroom Bog Bookshop Boutique Brewery Brook Buffet Cabin Cafeteria Campsite Canyon Carnival Casino Castle Cathedral Catwalk Cave Cellar Cemetery Chapel Chateau Choir Church Cinema Circus City Classroom Cliff Clinic Coast Cockpit Coliseum College Constellation Corridor Cottage Countryside Courtroom Courtyard Cove Crater Creek Crowd Crypt Cubicle Dawn Depot Dock Dormitory Drawbridge Driveway Dungeon Eclipse Explosion Factory Farm Festival Fireworks Fjord Flood Forest Fortress Foyer Gallery Garage Garden Glacier Gorge Graveyard Gym Gymnasium Hairdresser Hall Harbor Heliport Herd Highway Hill Horizon Hospital Hotel Hurricane Infirmary Inn Island Jungle Kitchen Laboratory Lagoon Lake Landscape Lane Lawn Library Lightning Loft Manor Market Mausoleum Maze Meadow Monastery Morgue Motel Mountain Museum Newsroom Nightclub Nursery Oasis Observatory Ocean Office Orchard Orchestra Palace Parade Park Passageway Pasture Patio Peninsula Pharmacy Picnic Planetarium Plantation Plateau Playground Playroom Plaza Pond Port Prairie Pub Quarry Racetrack Railroad Railway Ranch Ravine Reservoir Restaurant River Road Rodeo Rooftop Salon Sandstorm Sauna School Sea Seaside Sewer Shipwreck Shipyard Shop Sky Snowstorm Stadium Stage Station Stockroom Storm Stream Street Studio Sunrise Sunset Supermarket Swamp Tavern Temple Terrace Terrain Theatre Tornado Tournament Tower Town Trail Tunnel Twilight University Valley Villa Village Vineyard Volcano Warehouse Waterfall Waterfront Zoo 1840 Journal of Cognitive Neuroscience Volume 30, Number 12 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Appendix B. List of Object Words Used in the Study Ambulance Amulet Apron Asterisk Badger Bandage Banjo Barrel Bayonet Beer Bench Biscuit Blazer Blindfold Blossom Book Boomerang Bouquet Bowl Brick Broccoli Brooch Bubble Buckle Bullet Buoy Butter Buttercup Button Cabinet Calf Camera Canoe Cap Card Cardinal Carp Carriage Catalogue Catapult Cent Certificate Chain Champagne Chariot Cheese Cheetah Cherry Chestnut Chisel Cigarette Cloak Clock Coaster Cocktail Cod Coffee Comet Compass Computer Conditioner Container Cooker Crepe Crocodile Crown Crucifix Cushion Cylinder Desk Diamond Dice Dictionary Dough Doughnut Dragon Drainpipe Driftwood Drill Dynamite Embroidery Emerald Envelope Espresso Fairy Fan Flask Frame Generator Guitar Hammer Hamper Handle Harness Harpoon Headphones Heart Helicopter Honey Honeycomb Hook Horseradish Jigsaw Kangaroo Kayak Ladle Leech Lemon Leopard Letter Lifeboat Limousine Lobster Locket Lotus Machine Magazine Marmalade Medal Medallion Menu Microphone Microwave Minibus Monkey Mosquito Motorbike Muffin Nest Newspaper Noose Nut Olive Ostrich Package Packet Page Painting Pallet Pamphlet Panda Parcel Parchment Pasta Pendulum Pepper Peppermint Photograph Picture Pint Potato Projector Prune Pterodactyl Pudding Pump Pussycat Rabbit Racehorse Radiator Raspberry Recorder Reptile Rifle Rocket Rose Ruby Sapphire Satellite Saucer Scale Scalpel Scone Screwdriver Seat Shampoo Shell Shrapnel Shutter Signature Skirt Skull Sleigh Smoothie Snorkel Socket Soup Spade Staple Stretcher Submarine Sunflower Swing Tabloid Tangerine Tapestry Telescope Thread Ticket Topaz Tortoise Treasure Tripod Trolley Tulip Turnip Typewriter Van Vase Vodka Wand Weasel Wedge Wheelbarrow Whip Whistle Window Witch Clark, Kim, and Maguire 1841 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Appendix C. List of Abstract Words Used in the Study Abstinence Absurd Accord Affront Ambition Amends Annual Aptitude Aspect Assurance Attempt Attitude Avail Awareness Basis Behavior Belief Bias Blame Bother Care Cause Certainty Chance Clarity Closure Commitment Concept Concern Conduct Confidence Conjecture Conscience Contention Context Courtesy Creed Cunning Debut Decision Decorum Default Desire Despair Destiny Difference Dignity Dilemma Discretion Distinction Distrust Doubt Dread Duty Effect Ego Empathy Envy Essence Esteem Eternity Ethic Euphemism Existence Expertise Extent Extreme Fairness Fate Fault Feel Feeling Finesse Folly Foresight Forgiveness Function Gain Gist Godsend Grandeur Grudge Guess Guilt Hint Honesty Honour Idea Ideal Idealist Importance Infinity Insight Intellect Intent Intention Interest Intuition Involvement Irony Issue Judgment Karma Kind Knack Lack Leeway Legacy Leniency Likelihood Logic Luck Manner Meaning Memory Mercy Merit Metaphor Method Midst Mistake Mode Moment Mood Moral Morale Motive Mystique Myth Need Neutral Nonsense Normal Notion Opinion Origin Outcome Oversight Paradigm Paradox Pardon Patience Pause Penance Piety Pity Plea Precaution Prestige Principles Prophecy Prudence Psyche Pun Purity Purpose Quality Rarity Readiness Realism Reason Reasoning Reckoning Reform Regard Relevance Remorse Renown Repression Reproach Resolve Respect Respite Retrospect Reverence Rhetoric Riddance Risk Role Rumour Sanctity Sanity Sarcasm Seriousness Skill Snub Splendour Standard Standpoint Stoic Strategy Subconscious Succession Taboo Tact Tendency Theory Think Thrift Tradition Transition Trust Truth Try Uncertainty Unknown Utmost Validity Value Version Virtue Way Whim Willpower Wisdom Wish Woe Zeal 1842 Journal of Cognitive Neuroscience Volume 30, Number 12 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / 3 0 1 2 1 8 2 1 1 7 8 7 9 0 1 / / j o c n _ a _ 0 1 3 1 5 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Acknowledgments E. 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