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1150 Current Neuropharmacology, 2018, 16, 1150-1163
REVIEW ARTICLE
1570-159X/18 $58.00+.00 ©2018 Bentham Science Publishers
Neural Network Alterations Across Eating Disorders: A Narrative Review
of fMRI Studies
Trevor Stewarda,b
, José M. Menchóna,d
, Susana Jiménez-Murciaa,b,c
, Carles Soriano-Masa,d,e,*
and
Fernando Fernández-Arandaa,b,c,*
a
Department of Psychiatry, University Hospital of Bellvitge -IDIBELL, Barcelona, Spain; b
Ciber Fisiopatologia Obesidad
y Nutrición, Instituto Salud Carlos III, Madrid, Spain; c
Department of Clinical Sciences, School of Medicine, University
of Barcelona, Barcelona, Spain; d
Ciber de Salud Mental (CIBERSAM), Instituto Salud Carlos III, Madrid, Spain;
e
Department of Psychobiology and Methodology in Health Sciences, Universitat Autònoma de Barcelona, Spain
Abstract: Background: Functional magnetic resonance imaging (fMRI) has provided insight on
how neural abnormalities are related to the symptomatology of the eating disorders (EDs): anorexia
nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED). More specifically, an increasingly
growing number of brain imaging studies has shed light on how functionally connected
brain networks contribute not only to disturbed eating behavior, but also to transdiagnostic alterations
in body/interoceptive perception, reward processing and executive functioning.
Methods: This narrative review aims to summarize recent advances in fMRI studies of patients with
EDs by highlighting studies investigating network alterations that are shared across EDs.
Results and Conclusion: Findings on reward processing in both AN and BN patients point to the
presence of altered sensitivity to salient food stimuli in striatal regions and to the possibility of hypothalamic
inputs being overridden by top-down emotional-cognitive control regions. Additionally,
innovative new lines of research suggest that increased activations in fronto-striatal circuits are
strongly associated with the maintenance of restrictive eating habits in AN patients. Although significantly
fewer studies have been carried out in patients with BN and BED, aberrant neural responses
to both food cues and anticipated food receipt appear to occur in these populations. These
altered responses, coupled with diminished recruitment of prefrontal cognitive control circuitry, are
believed to contribute to the binge eating of palatable foods. Results from functional network connectivity
studies are diverse, but findings tend to converge on indicating disrupted resting-state
connectivity in executive networks, the default-mode network and the salience network across EDs.
Keywords: Eating disorders, fMRI, neuroimaging, anorexia, bulimia, binge eating disorder.
1. INTRODUCTION
Brain imaging techniques have enabled researchers to
reframe our understanding of the pathophysiology of eating
disorders (ED) [1, 2]. The majority of neuroimaging studies
thus far have concentrated on anorexia nervosa (AN), a psychiatric
disorder characterized by the restriction of food intake,
an extreme fear of gaining weight, significantly low
body weight, and disturbances in the perception of one’s
body figure [3, 4]. To a considerably lesser degree, neuroimaging
studies have also been carried out on patients with
bulimia nervosa (BN) and binge eating disorder (BED).
*Address correspondence to these authors at the Department of Psychiatry,
Bellvitge University Hospital-IDIBELL, CIBEROBN and CIBERSAM, c/
Feixa Llarga s/n, 08907 L’Hospitalet de Llobregat Barcelona, Spain;
Tel: +34 93 260 79 88; Fax: +34 93 260 76 58;
E-mails: ffernandez@bellvitgehospital.cat & csoriano@idibell.cat
Binge eating is defined by the overconsumption of food in a
relatively short period of time and accompanying feelings of
loss of control. Apart from bingeing episodes, patients with
BN also present compensatory purging: any behaviors used
to offset weight gain, such as self-induced vomiting or the
use of laxatives or diuretics [5, 6].
Functional magnetic resonance imaging (fMRI) is an
inferential neuroimaging technique used to assess brain activity
associated with temporal changes in regional cerebral
blood flow. Thanks to its low level of invasiveness, the
widespread availability of MRI machines, and its high level
of spatial resolution, fMRI has become the gold-standard
approach for assessing neural function in both currently ill
and healthy individuals. fMRI can be performed in conjunction
with paradigms that are designed to pinpoint regions of
the brain that are associated with ED pathophysiology (e.g.
food-related decision-making or body-image perception) and
A R T I C L E H I S T O R Y	
  
Received: February 01, 2017
Revised: August 18, 2017
Accepted: October 10, 2017
DOI:
10.2174/1570159X15666171017111532	
  
Neural Network Alterations in Eating Disorders Current Neuropharmacology, 2018, Vol. 16, No. 8 1151
to elucidate their neural mechanisms [7]. The most common
fMRI paradigms to determine changes in neural response use
either block-related designs or event-related designs. In
block-related designs, different conditions are presented and
alternated in order to contrast differences in neural activations
between conditions. By contrast, event-related designs
are not presented in a set sequence and are randomized, with
varying times in-between stimuli. This technique allows for
the modeling of changes in fMRI signal in response to neural
events associated with behavioral trials [8].
fMRI can also be used to investigate synchronous brain
activity to determine functional connectivity between brain
regions [9]. Functional connectivity is measured either during
the execution a task, or via a stimulus-free fMRI approach,
defined as resting-state fMRI [10]. Functional connectivity
studies have led to the identification of distinct,
large-scale brain networks that are understood to drive behavior
[11].
In this narrative review, we will seek to provide an overview
of fMRI studies on patients with EDs published within
the past five years. As opposed to compiling recent findings
of neuroimaging studies on this population, here, we will
attempt to delineate shared alterations in neural networks
across disorders, with special emphasis being given to fMRI
studies examining reward processing, cognitive control, and
self-monitoring networks in currently ill ED patients. This
review will also cover a finite number of noteworthy studies
focusing on neural activity in recovered ED patients. Such
studies are useful in that they control for the obscuring effects
of malnutrition and help to disentangle the “state” and
“trait” characteristics of a given disorder [12]. It is our hope
that a dimensional approach may prove to be valuable in
pinpointing neurobiological targets that underlie ED symptomatology.
Due to space limitations, not all fMRI studies
involving patients with EDs can be included in this review;
instead our aim is to evaluate a limited selection of recent
studies that highlight common neural alterations in EDs. In
addition, the article will solely focus on patients with AN,
BN, or BED, since fMRI studies of patients with other specified
feeding or eating disorders (OSFED) are scarce. Likewise,
studies exclusively examining patients with obesity
and/or excess weight will be overlooked as they are beyond
the scope of this review. Lastly, this review will conclude by
highlighting potential future directions for neuroimaging ED
research.
2. REWARD PROCESSING NETWORKS
In order to decide whether individuals approach or avoid
rewarding food stimuli, the brain reward system must integrate
metabolic hunger and satiety signals with higher-order
processing of taste and cognitive motivational factors [13].
The role of dopamine in such “wanting” processes is well
established, and multiple studies have shown that the striatum,
cortical regions, including the orbital frontal cortex
(OFC), and the amygdala, are involved in driving the acquisition
of both primary (e.g. palatable foods) and secondary
(e.g. money) rewards [14, 15]. On the other hand, “liking”,
or the hedonic experience generated from rewarding stimuli,
is associated with increased opioid system activity. In the
case of food stimuli, these systems are modulated by the
primary taste cortex in the insula, which serves as a gatekeeper
between dopaminergic basal ganglia and top-down
prefrontal control regions [16]. Researchers have raised the
possibility that intrinsic disturbances of reward processing
could be a potential mechanistic explanation for the extremes
of food intake seen in EDs [17]. A table summarizing the
fMRI reward processing studies mentioned in this section
can be found in Supplementary Information Table 1.
2.1. Reward Processing in Anorexia Nervosa
2.1.1. Response to Reward
The food restriction typical of AN has been found to sensitize
reward circuits and several reward-centered models of
the pathophysiology of AN have been proposed [18-20].
These models overlap in supporting that AN is maintained
by a reward-based learned behavior in which central reward
systems are altered by abnormal eating- and weight-related
cognitions. Additionally, cues that are compatible with this
aberrant mode of thinking become rewarding for the individual
and thus promote anorectic behaviors.
As of late, more fMRI studies have focused on testing
neurotransmitter-based hypotheses, with midbrain dopaminergic
neurons being understood to mediate reward learning
[21]. fMRI prediction error paradigms that use a computational
model for reward receipt and omission have been
especially helpful in shedding light on alterations in neural
dopamine responsiveness in AN [22]. Numerous studies in
AN patients have found prediction error response to be
heightened in the dorsal striatum, using both taste [23] and
monetary stimuli [24]. DeGuzman et al., even found that
greater caudate prediction error response was associated with
lower weight recovery during treatment, suggesting that elevated
prediction error neural activity could potentially be a
neurobiological marker of AN [24]. It should be noted however
that the aforementioned paradigms did not require any
behavioral responses by the participants and that the clinical
relevance of prediction error in EDs remains speculative. In
this same vein, other researchers have found AN participants
exhibited an exaggerated response to losses compared to
wins during a monetary reward task in both executive, and
striatal regions [25]. These findings imply that altered responses
in the circuitry responsible for coding the affective
content of stimuli might be partly responsible for the exaggerated
negative bias observed in AN. Murao et al., also
observed heightened activations in the right posterior insula
and the cingulate during the anticipation of losses (i.e. punishment)
in AN patients with binge-eating/purging subtypes
compared to patients with restricting subtype and healthy
controls [26]. This hypersensitivity to punishment has been
further demonstrated in the context of social behavior, with
one study identifying ventral striatum activation during rejection
on a social-judgment task to be positively correlated
with AN severity scores [27]. Being that attentional bias
modification strategies have been utilized in treating AN and
other psychiatric disorders [28, 29], it might be particularly
beneficial to develop interventions aimed at rectifying dysfunctional
reward-related response biases to negative stimuli.
1152 Current Neuropharmacology, 2018, Vol. 16, No. 8 Steward et al.
2.1.2. Habit Formation
New evidence supports that the neural circuits engaged
by individuals with AN during food choice differ significantly
from healthy controls, and that these circuits are associated
with habit formation [30]. In an elegantly designed
study by Foerde et al., participants with AN were asked to
make a series of choices between self-rated “Neutral” food
items and other food items during fMRI scanning [31]. In the
AN group, less-caloric food choices were strongly associated
with dorsal striatum activity, a pattern that was not found in
the control group. Anatomical and interference studies uphold
that the dorsal lateral striatum is critical for control of
habitual action and learned automatic behaviors [32], thereby
suggesting that the persistent, maladaptive food intake behaviors
seen in AN are underpinned by fronto-striatal networks
crucial for forming habits [18]. Moreover, the authors
found that the AN patients actual food consumption in a
meal the day following fMRI scanning was also robustly
associated with dorsolateral prefrontal cortex (dlPFC) and
dorsal striatum connectivity. By observing that individuals
with AN engaged in neural circuits associated with habit
formation during food choice to a greater extent than healthy
controls, one can postulate that the deeply entrenched and
stereotyped dietary practices of AN are ultimately mediated
by these neural circuits.
2.1.3. Taste Processing
Taste is another known driver of food intake and therefore
could be implicated in the pathophysiology of restricted
eating in AN [33]. The insula has been shown to respond to
taste stimuli and it plays a central role in transmitting salience
information to both ventral striatal and OFC reward
pathways [34]. A recent study by Frank et al., using Multivariate
Bayesian pattern analysis found that AN was associated
with reduced taste pattern classification accuracy in the
insula when contrasting caloric sucrose against a control
solution during a neural taste discrimination paradigm [35].
As normal taste/smell discrimination is altered in patients
AN [36], it is feasible that disruptions in afferents from the
insula to basal ganglia reward centers and to higher-order
taste processing influence their drive to eat [33]. Moreover,
the hypothesis that the under-consumption of energy-dense
foods in AN is partly due to the over-activation of top-down
control regions when viewing energy-dense foods has been
corroborated by a recent study showing a differential pattern
of activation in the lateral frontal pole [37]. In this study, AN
patients displayed increased activations in supervisory attentional
control centers following the presentation of highcalorie
stimuli and decreased activations during the presentation
of low-calorie food pictures, the opposite of what occurred
in control participants. Likewise, Monteleone et al.,
identified a similar paradoxical brain response to basic sweet
taste stimuli over bitter taste stimuli in several taste-reward
pathway areas in AN subjects, with the opposite pattern of
activation appearing in healthy subjects [38]. This finding
suggests that pleasant taste stimuli is intrinsically more salient
for individuals with AN, being that sweet flavors are
attributed to foods with a higher calorie content, and hence,
perceived as more aversive than bitter taste stimuli. What is
more, a recent study examining sucrose taste processing
found that the hypothalamus drove ventral striatal activity in
healthy subjects, but, in both AN and BN, patients’ effective
connectivity was directed from the anterior cingulate via the
ventral striatum to the hypothalamus [39]. Such findings
give further support to the notion that cognitive-emotional
top-down control affects food reward processing, possibly by
overriding hypothalamic inputs to the ventral striatum.
2.2. Reward Processing in Bulimia Nervosa and Binge
Eating Disorder
2.2.1. Addictive-like Eating?
As opposed to AN, the overeating behavior observed in
BN and BED patients is hypothesized to be driven by an
unstable reward system which overrides homeostatic and
cognitive regulation systems [17, 40]. Animal research, for
example, has shown that sugar binging is associated with the
sensitization of dopamine-related reward systems [41]. One
study using the temporal difference model to examine dopamine-related
learning identified reduced brain responses in
BN patients when learning associations between arbitrary
visual stimuli and taste rewards compared to controls [42].
These attenuated responses were found in the insula, ventral
putamen, amygdala, and OFC, and were also linked to the
frequency of binge/purge episodes. The episodic excessive
food intake seen in BN and BED could lead to excessive
episodic dopamine release and bring about the subsequent
desensitization of dopamine circuits via the downregulation
of D2 receptors. These alterations in the dopamine taste reward
system coincide with the addictive-like model of craving
for excessive food stimulation [15]. Another longitudinal
study found that diminished recruitment of the ventral striatum
and the inferior frontal gyrus during the anticipatory
phase of reward processing, and reduced activity in the medial
prefrontal cortex (PFC) during the outcome phase of
reward processing was linked to poor response to treatment
in BED patients [43]. As similarly posited in the obesity literature,
hypo-responsivity in reward regions in BN and BED
patients is hypothesized to be a result of a history of repeatedly
overeating highly palatable foods, which thereby leads
to higher levels of food consumption in order to compensate
for this deficit [44].
However, some divergent findings have been observed
which put into question the addiction-like neurobiological
model of heightened anticipatory reward processing and
blunted response to reward receipt as a driver of overeating
[45]. Namely, Simon et al., observed the opposite pattern in
a large sample of BN and BED patients during the performance
of a food incentive delay task [46]. Compared to controls,
patients exhibited reduced brain activation in the posterior
cingulate cortex (PCC) during the expectation of food
and increased activity in the medial OFC cortex, anterior
medial PFC and posterior cingulate cortex during the receipt
of food reward. Likewise, another study using a chocolate
milkshake vs. tasteless solution task found that women with
BN displayed hypoactivation in the right anterior insula in
response to the anticipation of taste receipt compared to controls
[44]. BN patients also showed hypoactivations in the
left middle frontal gyrus, right posterior insula, right precentral
gyrus, and right dorsal insula in response to consumption.
Reduced activations during the expectation of reward
may be indicative of reduced involvement of self-control
Neural Network Alterations in Eating Disorders Current Neuropharmacology, 2018, Vol. 16, No. 8 1153
brain regions, whereas the sensitization of brain regions involved
in determining the hedonic valuation of food may be
the result of persistent attempts at dieting and recurring
binge eating episodes.
2.2.2. Drivers of Overeating
Numerous studies suggest that BN patients are less responsive
to both internal and external reward cues, which is
believed to contribute to their tendency to overeat during
binge episodes [45]. One study found, in concordance with
models of binge eating that highlight the role of negative
reinforcement in driving overeating [18, 47], a positive association
between negative affect and the responsivity of reward
regions (the putamen, caudate, and pallidum) to the
anticipated intake of palatable food in BN patients [48]. This
result implies that negative affect may positively modulate
the reward value of food and become a conditioned cue due
to a history of binge eating when in a negative mood. This
coincides with other evidence suggesting that unpleasant
acute stressors contribute to diminished hippocampal activation
responsiveness in relation to external food cues and increased
food consumption in BED-symptomatic women
[49]. Other researchers have postulated that impaired hippocampal
activity can lead to interference in the coding of conditional
cues evoked by food and potentially distort interoceptive
satiety [50]. Lastly, using a novel approach, Weygandt
et al., applied an ensemble classifier to predict the
clinical status of subjects (BED, BN, overweight controls,
and normal-weight controls) based on food-related brain
response patterns [51]. The authors found that patterns in the
right insular cortex provided a maximum diagnostic accuracy
for the separation of BED and BN patients from normal-weight
controls, thereby highlighting the importance of
the insula in processing food stimuli [51]. Taking these results
into account and the reduced sensitivity of the primary
gustatory cortex to aversive tastes found in Monteleone et al.,
[38], it is possible that dysfunctional insula cortex taste processing
may correspond to a neurobiological correlate of the
propensity of BED and BN patients to ingest both highly
palatable and non-pleasurable foods during binging episodes.	
  
2.3. Reward Processing in Recovered Eating Disorder
Patients
Increasingly, researchers have opted to recruit recovered
ED patients for fMRI studies in order to avoid the confounding
effects of altered nutritional states [52]. It has been argued
that this approach allows for the isolation of core temperament
and personality traits that persist after recovery and
that are similar to the symptoms described premorbidly in
ED patients [53]. Results from such studies have largely
been consistent with studies in ill ED patients [54] and it can
be argued that alterations in recovered patients may also
partly be the result of the “scarring” effect of a prolonged
semi-starvation state [55]. For example, Wegner et al., found
that both recovered AN and BN patients presented disturbed
sensitization patterns in response to sweet taste stimuli, with
subjects recovered from AN specifically displaying decreased
sensitization to sucrose, whereas subjects recovered
from BN displayed increased sensitization [56]. Interestingly,
the sensitization and habituation effects primarily occurred
in appraisal circuits in the medial frontal cortex, but
did not appear in the insula, as has been observed in currently
ill ED patients [38]. Wierenga et al., inventively used
a delay discounting monetary decision task during hunger
and satiated states to examine whether diminished response
to reward could underlie food restriction in women remitted
from AN [57]. These researchers found that, whereas in the
control group hunger significantly increased activation in
reward salience circuitry (ventral striatum, dorsal caudate,
anterior cingulate cortex) during processing of immediate
reward, brain response in reward and cognitive neurocircuitry
did not differ during hunger and satiety in the recovered
AN group. These findings uphold the notion that decreased
sensitivity to the motivational drive of hunger could
be a crucial maintenance factor for individuals with AN [57].
Another study examined food-cue processing in both chronically
ill and long-term recovered women with AN and indentified
increased activations in top-down control regions (i.e.
medial and lateral PFC, and anterior cingulate) in both patient
groups when compared to healthy controls [58]. This
suggests that a stronger aversion to food cues still remains
after recovery and that attentional biases may represent a
trait marker of the disorder. Likewise, it may be that recovered
AN patients require a greater allocation of top-down
cognitive neural resources to process subjectively aversive
stimuli, whereas control subjects process such stimuli
through more intuitive mechanisms. Other reward processing
alterations, such as heightened sensitivity to punishment
[54], also persist after recovery, whereas taste discrimination
deficits seem to normalize in AN [35].
3. COGNITIVE CONTROL NETWORKS
Cognitive control refers to the processes related to the
mindful deployment of attentional and cognitive resources
for the flexible response to shifting contingencies [59]. The
synergy of cognitive processes, spanning across domains
such as working memory, set shifting, and performance
monitoring, are integral to the deployment of adaptive decision
making [60] and emotion regulation [61, 62]. A frontoparietal
network containing the dlPFC (dlPFC) and posterior
parietal cortices, and a cingulo-opercular network containing
the dorsal anterior cingulate cortex (dACC), anterior
insula, and the anterior PFC have been identified as crucial
for the adaptive functioning of cognitive control [63, 64]. No
fMRI studies to date have been published using cognitive
reappraisal emotion regulation paradigms in ED patients,
though aberrant insula activity during the generation and
down-regulation of negative emotions has been linked to
excess weight [65]. Maladaptive cognitive functioning has
been proposed to be prevalent across eating disorders (i.e.,
transdiagnostically), with AN patients presenting increased
self-control, cognitive rigidity and impairments in setshifting
[66], and patients with BN and BED symptoms displaying
increased food-related impulsivity [67, 68]. A table
summarizing the cognitive control fMRI studies mentioned
in this section can be found in Supplementary Information
Table 2.
3.1. Cognitive Control in Anorexia Nervosa
Excessive cognitive control characteristics such as
perfectionism, dichotomous thinking, and obsessive–
1154 Current Neuropharmacology, 2018, Vol. 16, No. 8 Steward et al.
compulsive personality traits are predisposing factors for AN
that very often persist after clinical recovery [69]. More specifically,
patients with AN often display weak central coherence
[70] (i.e. a tendency to focus on local detail at the expense
of global processing), which is thought to hinder the
appropriate adjustment of cognitive strategies during treatment
[71]. Although the neural substrates of central coherence
impairments in AN are still relatively unknown, Fonville
et al. found that AN patients showed diminished activation
in the precuneus compared to controls when completing
an embedded figures test [72]. This region is known to be
implicated in visuospatial imagery processing and in shifting
attention between targets [73]. Furthermore, the AN group
showed greater activation in the right fusiform gyrus, a region
associated with object perception, suggesting that AN
patients use alternative cognitive mechanisms to controls to
carry out the task. This pattern of elevated cognitive rigidity
and performance monitoring is supported by the findings of
Geisler et al., who opted to use a probabilistic reversal learning
task to investigate the neural correlates of flexibility in
response to changing reward contingencies in acute AN patients
[66]. This study found that increased neural response
in the dACC on trials with negative feedback was followed
by behavioral adaptation in AN patients. Furthermore, the
authors found group differences in feedback-dependent
changes in functional connectivity between the dACC and
right amygdala, which is consistent with the notion of overresponsiveness
to conflict and negative feedback in AN. Abnormally
elevated performance monitoring and cognitive
control manifested as hyperfunctioning of the dACC could
be reflective of the additional allocation of cognitive resources.
These resources could reinforce the fixation on
goals commonly seen in AN (e.g. skinny body and food restriction).
However, it is worth noting that other studies have
found evidence of both reduced and increased PFC activations
in AN patients during error processing [74] and inhibitory
control [75], and that some cognitive domains, such as
verbal working memory, do not appear to be affected in restrictive-type
AN patients [76].
Another commonly reported risk factor of AN is impaired
set shifting [77] (i.e. the ability to alter a behavior in
response to changing contingencies), with the ventrolateral
PFC (vlPFC) being a key area for successful execution of set
shifting tasks [78]. One study found that AN patients showed
decreased activity in the right vlPFC and bilateral parahippocampal
cortex during an fMRI-adapted version of the Wisconsin
Card Sorting Test compared to controls [79]. Taken
further, Garrett et al., found that improvements in setshifting
performance following AN treatment were predicted
by lower vlPFC activation and higher anterior middle frontal
activation [80]. These findings imply that impairments in
cognitive flexibility found in AN patients are associated with
alterations in the recruitment of PFC resources and that the
vlPFC specifically is imperative for shifting between context-appropriate
responses. Relatedly, Sulston et al., identified
that reduced right dACC activation was correlated with
perseverative errors on a set-shifting task in a sample of currently
ill AN patients, suggesting that these patients require
greater neural resource allocation in order to properly perform
such tasks [81]. The hypothesis that the altered efficiency
of neural resource allocation might underlie the increased
levels of self-control in AN was also supported by
the findings of King et al., [82]. In their study, currently ill
adolescent AN patients presented decreased activations in
lateral prefrontal and posterior parietal regions during decision
making on a delay discounting task. Being that choices
were also consistently made faster by AN patients, the
authors suggest that their results might reflect a sustained
high-level of anticipatory cognitive control in AN patients. It
is possible that this ingrained and proactive mechanism
might compromise control mechanisms that are necessary to
adapt to shifting cognitive demands.
3.2. Cognitive Control Networks in Bulimia Nervosa and
Binge Eating Disorder
In contrast to AN, individuals with bulimic-type EDs
display diminished self-regulatory capacities in numerous
facets not limited to overeating, but also other impulsivecompulsive
behaviors (e.g. substance abuse, behavioral addictions),
which is suggestive of more extensive cognitive
dysregulation [83, 84]. Abnormalities in frontostriatal circuits
likely contribute to diminished self-regulatory capacity,
which subsequently become manifest as an inability to sufficiently
curb eating behavior in individuals with BN and BED
[68]. For example, Hege et al., found that increased rashspontaneous
behavior in BED subjects was related to decreased
response inhibition performance during a go/no-go
task, as well as reduced activity in the prefrontal control
network [85]. Correspondingly, Skunde et al., observed diminished
sensorimotor and the dorsal striatum activity during
a go/no-go task in patients with BN with high symptom
severity compared to controls [86]. Curiously, these differences
were specific to the general go/no-go paradigm but not
to the food-specific go/no-go paradigm, which is suggestive
of a more generalized impairment of behavioral inhibition
rather than a disorder-specific impairment. This coincides
with a recent study by Dreyfuss et al., which found that
patients with BN did not show enhanced activity in the prefrontal
cortex as observed in controls during a negativeemotional-arousal
cognitive-control task [87]. Furthermore,
in contrast to controls, patients with BN did not display an
age-dependent improvement in performance, indicating that
the emergence and maintenance of BN in late adolescence
could be linked to the altered recruitment of prefrontal control
circuitry. Another study using Stroop-Match-to-Sample
task found that both BED and BN subjects exhibited stronger
activation of striatal regions compared to controls, whereas
only BN subjects presented heightened premotor cortex activation
[88]. This result partially dovetails with the findings
of Balodis et al., who found that individuals with BED had
diminished activity in the vmPFC, the inferior frontal gyrus,
and the insula during Stroop performance, when compared to
obese and normal-weight controls [89]. These observed differences
in the neural correlates of inhibitory processing are
demonstrative of a diminished ability to recruit impulsecontrol-related
brain regions in individuals with BN [17] and
BED [47].
Patients suffering from BN and BED are also characterized
by a tendency to make disadvantageous food decisions
and by a failure to adapt their behavior in the face of the
negative consequences of overeating [90]. Burgeoning evi-
Neural Network Alterations in Eating Disorders Current Neuropharmacology, 2018, Vol. 16, No. 8 1155
dence on decision-making impairments in these disorders
has led to the emergence of a limited number of fMRI studies
examining the neural substrates of these alterations [91].
Reiter et al., for example, used computational modeling of
choice behavior to identify specific signatures of altered decision-making
in BED patients. The authors found BED patients
to be more likely to switch between choices, indicating
a bias towards exploratory decisions during behavioral adaptation
in a dynamic environment. Parallel to this behavioral
observation, BED patients showed reduced anterior insula
and vlPFC activation during exploratory decisions than
healthy controls [92]. This study stands out as it provides a
mechanistic account of the maintenance of maladaptive behaviors
despite negative consequences that is a hallmark of
binge-spectrum disorders. By identifying the specific impairments
in reward-guided decision-making in BED, these
results advance our understanding of the neurocognitive
phenotype of BED. Marsh et al., also identified abnormal
patterns of activation in frontostriatal circuits in adolescent
BN patients during a conflict resolution task [93]. More specifically,
during correct responses in conflict trials, the right
inferolateral and dorsolateral prefrontal cortices, and putamen
failed to activate to the same degree in adolescents
with BN as in healthy comparison subjects. Instead, deactivation
was seen in the left inferior frontal gyrus, as well as a
neural system encompassing the posterior cingulate cortex
and superior frontal gyrus [93]. These findings coincide with
another study which found that BN patients showed hypoactivation
during reorienting and executive attention in anterior
cingulate regions, the temporo-parietal junction and parahippocampus
compared with controls [94].
Novel approaches using ecological momentary assessment
(EMA) have also sought to clarify the association between
individual differences in neural response to food cues
under stress and natural environment binge eating episodes.
Using EMA, Fischer et al., found that changes in activation
in the ACC, precuneus, and dlPFC prefrontal cortex (dlPFC)
moderated the relationship of stress to binge eating, to the
extent that women with BN who exhibited decreased response
reported increasing stress prior to binges [95]. The
authors postulate that it is possible that increases in stress
may bring about reduced sensitivity to the negatively reinforcing
effects of food and thereby increase the vulnerability
to binge eating.
3.3. Cognitive Control Networks in Recovered Eating
Disorder Patients
The extent to which alterations in cognitive control and
perception persist after recovery from EDs remains unclear
and the vast majority of the literature has thus far focused on
examining recovered AN patients. Decker et al., used a delay
discounting task to explore choice behavior in a large sample
of controls and AN patients at pre- and post-treatment [96].
However, instead of showing increased neural activity in
regions associated with executive control, underweight AN
patients displayed relatively less activity in the dACC and
striatum. Interestingly, the authors found that the tendency to
prefer larger, delayed rewards in the acutely ill state normalized
as health improved. Being that neural activity in the
cingulostriatal and frontoparietal circuits was linked to behavioral
changes on the task after weight restoration, the
authors suggest that the tendency to prefer larger, delayed
rewards in the acutely ill state of AN may reflect a statespecific
shift in decision making. Whether this normalization
occurs in the context of the anticipation and receipt of reward
remains uncertain. Another study in a sample of recovered
AN patients and matched controls found no group differences
behaviorally or in neural responses in the mesocorticolimbic
system during the anticipation of- or in response
to monetary rewards [97]. However, during both anticipation
and response phases, recovered AN patients presented increased
recruitment of the dlPFC, a brain region broadly
implicated in top–down executive control. The study authors
assert that patients with elevated cognitive control may in
turn be able to adhere to dietary restriction more meticulously
than others, which could render them vulnerable for
an onset or relapse of AN. This suggests that an imbalance
between brain systems subserving bottom–up and top–down
processes may be a trait marker of AN.
4. SELF-MONITORING NETWORKS
4.1. Body-image Distortions
In AN, body image distortions are commonly focused on
areas of the body that are considered by the patient to be too
fat, and are often accompanied by the patient checking their
own body by pinching skin folds, or measuring specific areas
of the body (hips, thighs, upper arms, etc) [98, 99]. These
compulsive behaviors and alterations in self perception in
AN patients are understood to be driven by cognitive distortions
regarding the individual’s own weight and shape, and
their neurobiological underpinnings have received increased
interest by neuroimaging researchers in recent years [100].
Regions that have commonly been found to display either
hyper- or hypoactivations in response to images of body
shape include the fusiform gyrus, the precuneus, the insula,
and regions in the PFC [101]. The right precuneus in particular
appears to hold a central role in developing and maintaining
body representation [102]. In a skillfully designed paradigm,
Nico et al., had participants predict whether a stimulus
would hit or miss their body if it continued its linear motion
[103]. The researchers found that healthy volunteers and
stroke patients with focal left parietal damage estimated
body boundaries very accurately. Conversely, AN patients
and stroke patients with right parietal lesions underestimated
the boundaries of their body, supporting that this region is
implicated in the deviations of body schema found in AN.
The findings of Via et al., during a task in which AN patients
viewed video clips of their own body and another's body also
identified the precuneus as a key component of a network
supporting self-other-evaluative processes implicated in
body distortion [104].
However, some fMRI studies have not obtained differences
in right parietal lobe activations when comparing AN
patients to controls. For example, Suda et al., found that patients
with AN had less activation in the medial PFC and
right fusiform gyrus compared to controls in response to
body checking compared to neutral action images [105].
Likewise, another study identified increased activity in the
dlPFC in AN patients in response to the presentation of over-
1156 Current Neuropharmacology, 2018, Vol. 16, No. 8 Steward et al.
sized body pictures [106]. Hyperactivation in the dlPFC was
also significantly correlated with shape concern in these patients.
This direct association may represent an increased
need for top-down cognitive control in AN when confronting
emotionally salient cues, such as body images, which otherwise
would be experienced as overly aversive. In order to
test whether dysfunctional ventral–striatal signaling contributes
to the maintenance of AN, Fladung et al., used a body
weight estimation and self-referential task in a sample of
adolescent patients with AN [107]. Their results showing
that underweight stimuli were associated with greater activity
of the ventral striatum support that reduced food intake in
AN may serve as conditioned response that evolves over
time by associating underweight body stimuli and starvation
to motivational value. Body size processing biases have also
been found to be present in BN [108]. Given that there is
evidence in longitudinal studies that body size overestimation
is a predictor for the development of ED, the exploration
of the neurobiological underpinnings of body image distortion
and interception alterations in these patients is warranted
[108].
4.1.1. Interoception and Perception
An individual’s sensitivity to bodily signals, such as
heartbeats and hunger, is strongly linked to the perception
and regulation of emotions [109], with the insula playing a
key role in integrating interoceptive signals [16]. Furthermore,
it has recently been proposed that reduced levels of
interoceptive awareness may predispose individuals for
greater body-image dissatisfaction [100,110]. A recent review
of neuroimaging studies developed a speculative model
of body image distortion by dividing these alterations into
three neurobiologically based components: (1) a perceptive
component mainly related to alterations of the precuneus and
the inferior parietal lobe; (2) an affective component mainly
related to alterations of the PFC, the insula and the
amygdala; (3) a yet to be fully defined cognitive component
focusing on beliefs concerning body shape and appearance
[101].
As previously mentioned, aberrant visceral interoceptive
processing within the insula has been hypothesized to be an
important mechanism in the pathophysiology of EDs due to
its links to interoception, homeostatic signals that drive food
consumption, emotion regulation, and body-image dissatisfaction
[100, 111]. Using a well-validated interoceptive attention
task in which participants focus on the sensations in
specific parts of their bodies, Kerr et al., found that recovered
AN patients presented decreased activity in the dorsal
mid-insula during gastric interoception and that these patients
also presented heightened activity in this region during
anxious rumination [112]. In addition to abnormal insula
activity, individuals with AN exhibited decreased activity in
the precuneus during interoception. This finding reinforces
the role of the insula and precuneus in self-monitoring and is
in agreement with other research showing that individuals
with AN demonstrate alterations in the precuneus when responding
to statements relating to self-knowledge [113].
McAdams et al., 2016 opted to use a Faces task to compare
viewing oneself to a stranger [114]. AN participants
displayed elevated activity in the bilateral fusiform gyri for
self-images, unlike the weight-recovered and healthy
women, leading the authors to suggest cognitive distortions
about physical appearance are a state rather than trait feature
in AN [114]. However, one recent study identified persistent
hyperactivation in the medial PFC during attentional bias to
Fig. (1). Visual guide of brain regions implicated in eating disorder symptomatology. (The color version of the figure is available in the
electronic copy of the article).
Neural Network Alterations in Eating Disorders Current Neuropharmacology, 2018, Vol. 16, No. 8 1157
angry faces in recovered AN patients [115], possibly reflecting
the existence of compensatory mechanisms. Lastly, abnormal
spatiotemporal activation also appear to persists after
recovery in AN, with one study identifying alterations in
configural/holistic information for appearance- and nonappearance-related
stimuli processing in patients with body
dysmorphic disorder (BDD) and weight-restored AN patients
[116]. This study found that both AN and BDD groups demonstrated
similar hypoactivity in early secondary visual
processing regions and the dorsal visual stream when viewing
low spatial frequency faces, indicating a common phenotype
of abnormal early visual system functioning. The
above-mentioned differential patterns of response imply that
alterations emerging both during the processing of the self
and others, as well as while perceiving emotions [117], may
be partly due to a hypersensitive inward attentional system
response to self-image, and difficulties in processing and
interpreting information from others during self processes.
A table summarizing the self-monitoring fMRI studies
mentioned in this section can be found in Supplementary
Information Table 3.
5. RESTING-STATE FUNCTIONAL CONNECTIVITY
In contrast to having subjects perform a particular task,
resting-state fMRI studies allow for the examination of temporal
correlations between spontaneous fluctuations in
blood-oxygen-level dependent (BOLD) activations in distinct
brain regions [118, 119]. Resting-state fMRI analysis
generally either uses a seed-based or a network-based approach
[11]. A seed-based approach preselects a region-ofinterest
and creates a functional connectivity map to assess
the temporal correlations between this seed and other regions
of the brain.
Network-based approaches, on the other hand, investigate
putatively intrinsic neural networks from BOLD signal.
One commonly utilized network-based approach is independent
component analysis, which isolates sets of regions
showing the strongest levels of temporal synchronicity [120].
The default-mode network (DMN), for example, is the most
studied network in resting-state research and is recruited
during internally focused, non-goal oriented activity [121].
The DMN, which is deactivated when cognitive resources
are needed in order to carry out a task, includes areas such as
the precuneus-posterior cingulate, the inferior parietal cortex,
the medial PFC, and the hippocampus. Other networks implied
in ED pathology include the superior parietal/PFCcentered
executive control network, and the salience network
(a circuit linking the anterior cingulate, the frontal, and the
anterior insular cortices), which is understood to mediate
shifts between the DMN to goal-directed networks [10, 122].
Other analytical approaches less commonly found in the
ED literature include graph analysis, which consists of
dividing the brain into a network of nodes in order to assess
degree centrality (i.e. the number of links a given node has)
[10, 123].
A table summarizing the resting-state fMRI studies mentioned
in this section can be found in Supplementary Information
Table 4.
5.1. Resting-state Functional Connectivity in Eating
Disorder Patients
Although the methodological approaches employed to
examine resting-state functional connectivity vary greatly
across studies, results have fairly consistently overlapped in
identifying cortico-limbic network abnormalities in individuals
with EDs [119]. Of particular interest are findings
from seed-based studies examining regions involved in cognitive
control. For example, Lee et al., chose to explore the
functional connectivity of the dACC in a sample of AN and
BN patients and matched healthy controls [124]. The authors
found that the AN group exhibited stronger synchronous
activity between the dACC and retrosplenial cortex, whereas
the BN group presented heightened synchronous activity
between the dACC and the OFC. Furthermore, both groups
demonstrated greater synchronous activity between the
dACC and precuneus, which correlated with higher levels of
body shape concerns. These findings suggest that altered
dACC-precuneus connectivity could conceivably underlie
the disorder-specific weight and body shape concerns found
in ED patients. Biezonski et al., singled out the thalamus, a
key mediator of information flow through frontal-basal ganglia
circuit loops, as their region of interest of resting-state
functional connectivity in a sample of patients with AN and
matched controls [125]. Relative to controls, AN patients
displayed heightened functional connectivity between the
central-medial thalamus and the bilateral dlPFC, along with
lower connectivity between the anterior thalamus and the left
anterior PFC. Furthermore, alterations in thalamo-frontal
connectivity were associated with deficits in performance on
cognitive control and working memory tasks. These findings
coincide with those of Boehm et al., which revealed increased
functional connectivity between the angular gyrus
and the other regions of the fronto-parietal network in patients
with AN in comparison to controls [126]. Heightened
functional connectivity within the fronto-parietal network
might contribute to the high levels of anxiety and rumination
commonly found in AN by making it more difficult for patients
with AN to disengage from an internally oriented mental
states.
Instead of using a seed-based approach, Favaro et al.,
analyzed the spontaneous organization of visuospatial and
somatosensory networks in currently ill and recovered AN
patients through resting-state functional connectivity [127].
Their findings point to AN being associated with a double
disruption of brain connectivity, one associated with visuospatial
difficulties and the other with abnormalities in processing
somatosensory perceptual information. In their sample,
both AN groups showed decreased connectivity in the
occipitotemporal junction, a network involved in the “what?”
pathway of visual perception, whereas only the currently-ill
AN group displayed increased coactivation in the left parietal
cortex, a region within the somatosensory cortex and implicated
in integrating visual and interoceptive representations.
Within-network connectivity of the somatosensory
network has also been found to be reduced in BN, though the
authors did not observe any significant between-group differences
in the average within-network connectivity of the
DMN, the executive network, and the salience network
1158 Current Neuropharmacology, 2018, Vol. 16, No. 8 Steward et al.
[128]. Interestingly, functional connectivity of the right middle
occipital gyrus, a region implicated in body processing,
also correlated inversely with the bulimia severity and interoceptive
awareness levels. The study authors suggested
that this increased dependence on interoceptive awareness
may result from dysfunctional multisensory integration and a
reduced reliance on visual inputs.
Results on alterations in the DMN in patients with AN
have proven to be inconsistent, with some studies showing
altered DMN activity in both currently ill [104, 126] and
recovered AN patients [129], whereas other studies have not
identified significant differences in the DMN between AN
patients and controls [130, 131]. These discordant results are
in all likelihood due to differences in methodological approach
between studies (e.g. seed-based studies vs. networkbased
approaches) and sample heterogeneity (e.g. ED duration,
pharmacological treatment, prandial state). Contrastingly,
the few studies using graph analysis in AN patients
have been fairly consistent in identifying brain regions
with functional connectivity alterations. These data-driven
methods tend to show reduced functional connectivity in the
insula and the thalamus, which is suggestive of impaired
integration of visuospataial and homeostatic signaling [132-
134]. Kullmann et al., also found reduced functional connectivity
in the bilateral inferior frontal gyrus in AN patients
compared to controls, which the authors postulate might contribute
to the alterations in salience processing and hyperactivity
found in AN [135].
To the best of our knowledge, only one study to date has
examined resting-state functional connectivity in BED patients,
though it should be noted that BED patients were analyzed
alongside individuals with obesity not presenting
bingeing symptomatology [136]. Consistent with habit formation
theories, the authors found evidence of disruption in
global network properties and motor cortico-striatal networks
in their sample with obesity.
6. IMPLICATIONS AND FUTURE DIRECTIONS
Our global understanding of the neurobiology of the
brain and its role in psychiatric disorders is still not adequately
advanced for techniques such as fMRI to be reliably
used to diagnose or determine the severity of EDs. Even
though the identification of neural targets for effective brainbased
treatments is ultimately one of the goals of neuroimaging
research, at present, more research is needed to first develop
comprehensive models of the behaviors that underpin
EDs [137].
As highlighted in the present narrative review, the range
and diversity of methodological approaches applied in fMRI
studies for EDs, and the overall lack of reproducibility studies
in the literature greatly hinders researchers’ ability to
grasp the generalizability of any recent findings. Nonetheless,
this body of research indicates that commonalities in
specific neural network alterations are present across EDs
and endorse the potential advantages of using a dimensional
approach to elucidate the neurobiology of specific behavioral
constructs [38, 39]. Transdiagnostic studies are increasingly
more frequent in research of other psychiatric conditions,
such as mood disorders [62], and similar approaches could
prove to be beneficial to the field of EDs.
The fMRI studies presented in this review have repeatedly
demonstrated that altered activation in fronto-striato and
limbic regions play a significant role in the pathophysiology
of EDs. In the case of AN, the evidence presented suggests
that divergent responses in bottom-up regions such as the
striatum during food reward processing mediated by increased
activation in top-down information processing regions may
contribute to the formation of restrictive eating habits (see
Fig. 1). Though the number of studies in this population is
much more limited, abnormalities in top-down control regions
have also been identified in BN and BED, though differing
results regarding hypo- or hyper-activation in comparison
to controls during cognitive tasks could be due to the
choice of task or compensatory activations for these groups.
Likewise, resting-state functional connectivity studies indicate
that executive network, DMN, and salience network
alterations are implicated in the pathophysiology of EDs.
Although we strived to be parsimonious with our selection
of the publications featured in this review, the highly
blurred and distorted lens of neuroimaging techniques like
fMRI often requires researchers to reason backwards from
differential activation patterns to infer the existence of alterations
in specific mental processes. The use of reverse inference
to provide an interpretation of neuroimaging results has
rightly come under fire due to the multiple drawbacks this
line of reasoning entails [138]. Likewise, many studies fail to
detect behavioral differences between patient groups and
controls during fMRI scanning, despite significant differences
in neural activations being present. Interpreting results
based solely on differences in physiological response runs on
the risk of further reifying informal reverse inferences (e.g.
mining the literature to find past publications linking activations
in the anterior insula to interoceptive processes in order
to reason to the best explanation for a given finding). This is
one of the many motives for which researchers have increasingly
opted to formally test the ability to infer mental states
from neuroimaging data using tools from the field of machine
learning.
There are numerous approaches used in the research of
other psychiatric disorders that could be applicable to ED
research. Multimodal imaging techniques which utilize a
combination of resting state fMRI, task-based fMRI, magnetic
resonance spectroscopy (MRS), and diffusion tensor
imaging (DTI) have proven to be especially useful in highlighting
distinct levels of neuropathology in multiple interrelated
brain systems [139, 140]. Likewise, findings from
such studies could potentially be used to identify targets for
non-invasive neuromodulation strategies such as transcranial
direct-current stimulation (tDCS) and real-time fMRI [141].
Lastly, moving beyond the limitations of categorical, symptom-based
psychiatric diagnoses and adopting dimensional
frameworks such as those found in The Research Domain
Criteria (RDoC) when it comes to designing future studies
and testing hypotheses would be a symbol of advancement in
the field [142].
Neural Network Alterations in Eating Disorders Current Neuropharmacology, 2018, Vol. 16, No. 8 1159
CONSENT FOR PUBLICATION
Not applicable.
CONFLICT OF INTEREST
The authors declare no conflict of interest, financial or
otherwise.
ACKNOWLEDGEMENTS
The authors would like to thank Beatriz RamirezVaquero
for her help in preparing the figure and Maria PicóPérez
for her aid in reviewing the article content.
This work was supported by the Ministerio de Economía y
Competitividad (PSI2015-68701-R); AGAUR (2009SGR1554)
and Instituto de Salud Carlos III (FIS14/00290, PI13/01958
and PI16/00889). CIBER Fisiopatología de la Obesidad y
Nutrición (CIBERobn) and CIBER Salud Mental (CIBERsam)
are supported by ISCIII. C.S-M. is funded by a ‘Miguel
Servet’ contract from the Carlos III Health Institute
(CPII16/00048).
SUPPLEMENTARY MATERIAL
Supplementary material is available on the publisher’s
web site along with the published article.
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