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Human spatial memory implicitly prioritizes high-calorie foods
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* Open Access
* Published: 08 October 2020

HUMAN SPATIAL MEMORY IMPLICITLY PRIORITIZES HIGH-CALORIE FOODS

* Rachelle de Vries1,2 na1,
* Paulina Morquecho-Campos1 na1,
* Emely de Vet2,
* Marielle de Rijk1,
* Elbrich Postma1,
* Kees de Graaf1,
* …
* Bas Engel3 &
* Sanne Boesveldt1

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Scientific Reports volume 10, Article number: 15174 (2020) Cite this article

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ABSTRACT

All species face the important adaptive problem of efficiently locating
high-quality nutritional resources. We explored whether human spatial cognition
is enhanced for high-calorie foods, in a large multisensory experiment that
covertly tested the location memory of people who navigated a maze-like food
setting. We found that individuals incidentally learned and more accurately
recalled locations of high-calorie foods – regardless of explicit hedonic
valuations or personal familiarity with foods. In addition, the high-calorie
bias in human spatial memory already became evident within a limited sensory
environment, where solely odor information was available. These results suggest
that human minds continue to house a cognitive system optimized for
energy-efficient foraging within erratic food habitats of the past, and
highlight the often underestimated capabilities of the human olfactory sense.

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INTRODUCTION

A recurring fitness-relevant task faced by all species is the efficient pursuit
of nutritional resources1. A central theorem of optimal foraging theory is that
an individual’s fitness is a direct function of the efficiency with which one
acquires energy, and natural selection pressures favour foraging traits that
maximize the net rate of energy gain1,2. Although this theory has been
extensively referenced in relation to the foraging strategies of other animals2,
the question of whether humans also inherently carry adaptations geared toward
energy-efficient foraging has not been thoroughly assessed to date.

For about 99 percent of human evolution, our ancestors were hunter-gatherers
inhabiting a highly complex and variable physical food environment, where food
sources varied on both spatial and temporal availabilities3,4. A cognitive
adaptation that could have evolved to optimize foraging efforts within such
erratic food habitats of the past is a high-calorie bias in spatial memory4,5.
Such an inbuilt spatial bias entails the automatic registration and
prioritization in memory of high-calorie food locations. This would have enabled
foragers to efficiently navigate toward valuable calorie-dense resources –
without competing for limited attentional capacities required in other important
activities such as avoiding predation4,6. Indeed, a similar mechanism has been
observed in other animal species7,8,9. Using an innovative and ecologically
valid experimental set-up that covertly tested the food location memory of more
than 500 individuals, we provide first-hand evidence that human spatial
processing is implicitly biased toward high-calorie foods.

To mirror real-world navigation within a heterogeneous food environment as
closely as possible, we created a maze-like setting where participants followed
a specific route within a room to sample an assortment of (sweet and savory)
high- and low-calorie food stimuli at dispersed pillar locations (Fig. 1). We
emulated two sensory environments in separate rooms, each of which engaged
sensory modalities fundamental to the processes of spatial navigation and eating
behavior10,11,12: In the multisensory environment (i.e.
vision + taste + olfaction), stimuli consisted of actual food products that
individuals had to eat, whereas individuals were instructed to only smell food
odors in the olfactory environment. Importantly, participants were not informed
that their (spatial) memory would be tested afterwards, to ensure that the
encoding of food locations would be purely incidental. We then compared
performance, expressed as the proportion of correct food-to-pillar relocations
in a surprise spatial memory task, for high-calorie versus low-calorie food
stimuli in both sensory environments.

Figure 1

Heterogeneous food environment. Example of the spatial distribution of food
stimuli and navigation route within the maze-like experimental setting.

Full size image

RESULTS

HUMAN SPATIAL MEMORY AUTOMATICALLY PRIORITIZES HIGH-CALORIE FOOD

In the multisensory environment, individuals relocated high-calorie foods to
correct pillar locations significantly more frequently than low-calorie
alternatives (High-calorie: M = 0.63, 95% CI = [0.58,0.67]; Low-calorie:
M = 0.57, 95% CI = [0.52,0.62]), χ2 (1) = 9.35, p = 0.002, OR = 1.27, 95%
CI = [1.09, 1.48] (Fig. 2). This effect occurred regardless of demographics,
relevant state characteristics (e.g. hunger and alertness), hedonic evaluations
of foods (i.e. liking and desirability ratings; Fig. 3), and familiarity with
foods. Similarly, individuals in the olfactory environment more frequently
relocated odors signaling high-calorie foods to correct pillar locations
relative to low-calorie odor counterparts (High-calorie: M = 0.36, 95%
CI = [0.33,0.39]; Low-calorie: M = 0.30, 95% CI = [0.27,0.34]), χ2 (1) = 6.88,
p = 0.009, OR = 1.28, 95% CI = [1.06, 1.54] (Fig. 2), while controlling for the
same set of potential confounders – although the likelihood of a correct
relocation increased with a greater familiarity with an odor stimulus, χ2
(1) = 47.31, p < 0.001, OR = 3.55, 95% CI = [2.47,5.09]. Conversely, spatial
memory accuracy did not vary according to the taste of a food (i.e. sweet or
savory) in either sensory condition.

Figure 2

Food spatial memory accuracy. Human spatial memory for high-calorie and
low-calorie food stimuli in two sensory environments, expressed as the
proportion of correct food-to-pillar relocations. Error bars represent 95%
confidence intervals.

Full size image
Figure 3

Food ratings across sensory environments. Liking (a), Desirability (b), and
Familiarity (c) ratings (on a 100 mm Visual Analogue Scale) for all food stimuli
in the multisensory and olfactory environment. Error bars represent 95%
confidence intervals.

Full size image

THE HIGH-CALORIE BIAS IN HUMAN SPATIAL MEMORY MANIFESTS WITH LIMITED SENSORY
INFORMATION

In a combined analysis of both sensory conditions, a better overall food
relocation performance was observed in the multisensory compared to the
olfactory environment (Multisensory: M = 0.58, 95% CI = [0.54,0.61]; Olfactory:
M = 0.36, 95% CI = [0.33,0.39]), χ2 (1) = 62.95, p < 0.001, OR = 2.43, 95%
CI = [1.95,3.03], after adjusting for differences between participant samples
(Fig. 2). However, the sensory nature of food stimuli did not moderate the
effect of caloric density on spatial memory accuracy,χ2 (1) = 0.49, p = 0.486,
indicating that the high-calorie spatial memory bias was equally expressed in
both sensory environments – even where solely odor information was available.

DISCUSSION

In a naturalistic multisensory experiment, individuals incidentally learned and
more accurately recalled locations of high-calorie food stimuli. These results
are compatible with the notion of “adaptive memory”, which contends that memory
systems – much like other biological systems – were shaped by the forces of
natural selection and should therefore show sensitivity to fitness-relevant
content13,14. Indeed, alternative interpretations of our findings that are
grounded in more traditional memory frameworks, which champion the primacy of
content-insensitive general learning mechanisms, can be ruled out by our data13.
The possibility that the high-calorie spatial memory bias resulted from a
greater “depth” of processing or motivational salience of high-calorie stimuli
is minimal, given that we controlled for an individual’s personal familiarity
with a food, as well as their explicit liking and desire to consume an item15.
In addition, high- and low-calorie food products were equivalent in their
composition of important macronutrients (i.e. protein to carbohydrate and fat
ratios), rendering it unlikely that differences in nutritional balance – rather
than caloric content – is what drove the mnemonic advantage in the high-calorie
condition16. However, the observation that (odor) familiarity predicted a higher
frequency of overall correct relocations illustrates the importance of
considering both content-sensitive and content-insensitive learning processes
for human spatial cognition5.

Remarkably, the expression of the high-calorie bias in human spatial memory
required only a limited presence of sensory information – granted that available
sensory cues (such as odors) can communicate the relative value (e.g. caloric
content) of potential foods – which further speaks to the processing efficiency
of the mechanism1,17. We speculate that this could be due to an overlap in
underlying (hippocampal) neural coding processes, despite variations in the
(dominant) sensory modality used to explore the external world and significant
objects contained within them18. For instance, it is feasible that hippocampal
place cells show enhanced activity during recognition of objects (or cues) that
flag a high-priority resource, independently of the type of sensory input
received18. However, a sizeable difference in overall spatial memory performance
was evident between sensory conditions, which may have resulted from a greater
variety of sensory information present in the multisensory environment.
Individuals in the multisensory environment had a wider availability of sensory
modalities (e.g. visual information) to utilize as spatial cues during encoding,
which could have yielded a richer construction of mental spatial
representations19,20. Going forward, research efforts would benefit from
additionally documenting or matching participant samples on individual abilities
to mentally represent and flexibly manipulate spatial information (i.e. between
the viewer-centered perspective during navigation and the aerial map perspective
during spatial recall)21, for a more refined comparison of (food) location
memory between sensory conditions.

In turn, differences in the expression of the high-calorie spatial memory bias
may offer a novel explanation for why some individuals are less successful in
maintaining a healthy energy balance within the modern food landscape22. An
enhanced memory for high-calorie food locations could make high-calorie options
relatively easier to obtain within a diverse food environment, especially for
those with a greater expression of the bias22. In this manner, the cognitive
bias may facilitate high-calorie food choice, by capitalizing on the tendency of
individuals to prefer convenient easily-accessible items when making food
decisions23. Similarly, it could stimulate individuals to visit calorie-laden
food locations (e.g. fast food outlets) on a wider scale of space. Given the
paucity of literature on the high-calorie spatial memory bias and its potential
behavioral effects, further investigation is merited on what other cognitive
processes are associated with the bias, and how it may influence the manner in
which people navigate contemporary food replete settings.

Finally, our findings add to a growing literature that highlight the relevance
of olfaction for eating behavior in humans, which is known to be the case across
other species11,12. The human sense of smell is often depicted to be inferior to
those of other mammals, such as dogs or rodents24. However, our observations
showcase the intact ability of individuals to distinguish different odor types,
deduce caloric properties of signaled foods from odor cues, and localize odor
objects in space11,17,25. Indeed, a well-developed olfactory sense is thought to
have conferred a survival advantage to (ancestral) hunter-gatherers26,27.

Taken together, we find that human minds may continue to house an implicit
cognitive system optimized for energy-efficient foraging within the fluctuating
ancestral food environments in which memory evolved.

MATERIALS AND METHODS

PARTICIPANTS

This experiment was part of the three-day Lowlands Science 2018 festival program
(the Netherlands). A total of 512 attendees were analyzed: 258 participants (47%
female; MAge = 28.2 years, SD = 9.1; MBMI = 24.0 kg/m2, SD = 3.6) in the
multisensory environment and 254 participants (50% female; MAge = 28.5 years,
SD = 9.0, MBMI = 23.8 kg/m2, SD = 3.4) in the olfactory environment. Data from
539 individuals were initially collected, but 21 files contained missing values
and 6 files originated from individuals who participated in both sensory
conditions which was an exclusion criterion. All participants (and/or their
legal guardians) provided written informed consent prior to testing. This study
was approved by the Social Sciences Ethics Committee of Wageningen University
and was performed in accordance with relevant ethical guidelines and
regulations. The hypothesis, full research protocol and analysis plan were
preregistered, and can be accessed alongside reported data at
https://osf.io/2rwmt/.

SPATIAL MEMORY TASK

Participants were brought to a starting point within a room (area of 12 m2).
They navigated between eight pillars at a fixed pre-determined order that was
indicated by arrow signs on the floor. Although navigation schemes remained
constant, the assignment of food stimuli to pillar locations (i.e. encoding
order of caloric density—taste conditions) was randomized every hour and pillar
frequencies did not differ between conditions. Participants tasted (or smelled)
and provided ratings (i.e. liking, desire to eat, familiarity; Fig. 3) on a food
stimulus at all pillars. Participants then completed a surprise spatial memory
task in a separate area. During recall, participants were randomly presented
with a sequence of previous food stimuli and had to indicate the pillar location
of each item on a (two-dimensional) digital map of the relevant room. The total
number of possible pillar locations (N = 8) was displayed anew each recall
round, and a pillar location could be selected more than once.

FOOD STIMULI

Four high-calorie (M = 498.5 kcal/100 g, SD = 35.8) and low-calorie
(M = 34.3 kcal/100 g, SD = 18.9) food products and odor equivalents were used,
with an equal number of sweet (e.g. High-calorie: chocolate brownie;
Low-calorie: apple) and savory (e.g. High-calorie: potato chip; Low-calorie:
cherry tomato) options for each. Food odors were matched on perceived intensity
(i.e. 55–75 mm on a 100 mm Visual Analogue Scale) between caloric density—taste
conditions and validated in previous research5. Food products were placed in
bowls and refilled at regular time intervals to maintain a consistent
presentation volume. Food odors were presented in (screw-capped) brown bottles
(50 ml) containing scented cotton pads, which participants had to first open in
order to smell. Odor bottles were also replaced regularly to uphold the desired
odor intensity. All food stimuli were placed atop pillars and covered by
identical cloches that participants had to open during navigation.

STATISTICAL ANALYSIS

For data from each sensory environment, a generalized linear mixed model (GLMM)
with a random slope was formulated. A GLMM was chosen to flexibly model for
correlated errors in the (non-normal) binary outcome variable28, and linearity
of covariates (on the logit scale) was shown to sufficiently capture their
effects. The GLMM comprised fixed main and interaction effects for experimental
factors Caloric Density and Taste, and random effects for the factor
Participant. All effects were introduced on the logit scale. Additionally, in
the fixed part of the model and also on the logit scale, Gender, Age (in
tertiles), Subjective SES, Food Allergies, Hunger ratings, hours of Sleep,
Alertness, Alcohol consumption, Drug use, Smoking, Liking, Desirability, and
Familiarity were entered as covariates. Binary observations, conditional upon
the random effects for participants, were assumed to follow a Bernouilli
distribution. To test whether the type of sensory environment (i.e. multisensory
versus olfactory) moderates food spatial memory accuracy and expression of the
high-calorie bias, observations from both sensory rooms were combined into a
single analysis, adding fixed main and interaction effects (e.g. with Caloric
Density) of Sensory Environment to the GLMM. Ordinary likelihood ratio tests
(using the -2LL test statistic) were used for testing, with p values derived
from an approximation with the chi-square distribution. Inference was based on
Laplacian integration employing the lme4 package from R29. Detailed information
on the measurement of covariates and the model selection process can be found at
https://osf.io/2rwmt/.

DATA AVAILABILITY

The data that support the findings of this study are available on the Open
Science Framework repository with the identifier
https://doi.org/10.17605/OSF.IO/2RWMT30.

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ACKNOWLEDGMENTS

This research was funded by the Edema-Steernberg Foundation and the Netherlands
Brain Foundation (Hersenstichting). We would like to thank R. van Bommel, P.
Grootswagers, E. Ketel, A. Knapen, and A. Verdonschot for assistance with data
collection.

AUTHOR INFORMATION

Author notes

1. These authors contributed equally: Rachelle de Vries and Paulina
Morquecho-Campos.

AFFILIATIONS

1. Division of Human Nutrition and Health, Wageningen University and Research,
P.O. Box 17, 6700 AA, Wageningen, The Netherlands

Rachelle de Vries, Paulina Morquecho-Campos, Marielle de Rijk, Elbrich
Postma, Kees de Graaf & Sanne Boesveldt

2. Consumption and Healthy Lifestyles, Wageningen University and Research,
Wageningen, The Netherlands

Rachelle de Vries & Emely de Vet

3. Mathematical and Statistical Methods (Biometris), Wageningen University and
Research, Wageningen, The Netherlands

Bas Engel

Authors
1. Rachelle de Vries
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