Contents lists available at ScienceDirect
Neurobiology of Stress
journal homepage: www.elsevier.com/locate/ynstr
Neurobiological links between stress and anxiety
, Michael R. Bruchas
, Bita Moghaddam
, Carmen Sandi
, Anna Beyeler
Hotchkiss Brain Institute. Department of Physiology & Pharmacology, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N
Department of Anesthesiology and Pain Medicine. Center for Neurobiology of Addiction, Pain, and Emotion. University of Washington. 1959 NE Paciﬁc Street, J-wing
Health Sciences. Seattle, WA 98195, USA
Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, 97239, USA
Laboratory of Behavioral Genetics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Station 19, CH, 1015, Lausanne, Switzerland
Neurocentre Magendie, INSERM 1215, Université de Bordeaux, 146 Rue Léo Saignat, 33000 Bordeaux, France
Corticotrophin releasing hormone
Stress and anxiety have intertwined behavioral and neural underpinnings. These commonalities are critical for
understanding each state, as well as their mutual interactions. Grasping the mechanisms underlying this bi-
directional relationship will have major clinical implications for managing a wide range of psychopathologies.
After brieﬂydeﬁning key concepts for the study of stress and anxiety in pre-clinical models, we present circuit, as
well as cellular and molecular mechanisms involved in either or both stress and anxiety. First, we review studies
on divergent circuits of the basolateral amygdala (BLA) underlying emotional valence processing and anxiety-
like behaviors, and how norepinephrine inputs from the locus coeruleus (LC) to the BLA are responsible for
acute-stress induced anxiety. We then describe recent studies revealing a new role for mitochondrial function
within the nucleus accumbens (NAc), deﬁning individual trait anxiety in rodents, and participating in the link
between stress and anxiety. Next, we report ﬁndings on the impact of anxiety on reward encoding through
alteration of circuit dynamic synchronicity. Finally, we present work unravelling a new role for hypothalamic
corticotropin-releasing hormone (CRH) neurons in controlling anxiety-like and stress-induce behaviors.
Altogether, the research reviewed here reveals circuits sharing subcortical nodes and underlying the processing
of both stress and anxiety. Understanding the neural overlap between these two psychobiological states, might
provide alternative strategies to manage disorders such as post-traumatic stress disorder (PTSD).
Although the relationship between psychological stress and anxiety
seems intuitive, the biological nuances that distinguish the two states
are extremely complex. Indeed, after decades of research in psychology,
ethology and neurophysiology, overlapping neural substrates of these
two psychobiological states have been identiﬁed. However, the
boundaries between stress and anxiety remain an open discussion.
A stress response, created by a real or perceived threat (stressor),
can be deﬁned as an emergency state of an organism in response to a
challenge to its homeostasis (Chrousos, 2009;Selye, 1936). During this
emergency state, the organism initiates an integrated reaction including
physiological and behavioral responses. Internal threats, or so-called
systemic stressors, include physical changes in the body, such as hy-
poglycemia or hypovolemia (decreased blood volume), happening, for
example, after a severe car accident. On the other hand, perceived
threats, or so-called psychological stressors, include situations that can
potentially lead to a danger and induce a homeostatic challenge, in-
troducing the critical factor of anticipation (de Kloet et al., 2005;
Koolhaas, 2011). The concept of anticipation in the stress response is
critical in understanding the relationship between stress and anxiety. In
that regard, stress as a physiological reaction to a stimulus is accom-
panied by a concomitant emotional response. That emotional response
is determined in part by the perception of the threat imminence
(Anderson and Adolphs, 2014;Davis et al., 2010). According to the
deﬁnition of The Diagnostic and Statistical Manual of Mental Disorders,
Fifth Edition (DSM-5) (American Psychiatric Association, 2013)“Fear is
the emotional response to a real or perceived imminent threat, whereas
anxiety is the anticipation of a future threat”. Thus, the emotional state
that our body experiences diﬀers between fear when we encounter an
aggressive dog, and anxiety when we know we will visit a friend which
has an aggressive dog.
Received 5 April 2019; Received in revised form 18 June 2019; Accepted 2 August 2019
E-mail addresses: email@example.com (N. Daviu), firstname.lastname@example.org (M.R. Bruchas), email@example.com (B. Moghaddam),
carmen.sandi@epﬂ.ch (C. Sandi), firstname.lastname@example.org (A. Beyeler).
Neurobiology of Stress 11 (2019) 100191
Available online 13 August 2019
2352-2895/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license
Anxiety is deﬁned as a temporally diﬀused emotional state caused
by a potentially harmful situation, with the probability or occurrence of
harm being low or uncertain (Goes et al., 2018;Spielberger et al., 1983;
Takagi et al., 2018). Historically, psychologists and psychiatrists have
diﬀerentiated state and trait anxiety (Belzung and Griebel, 2001;Goes
et al., 2018;Spielberger et al., 1983;Takagi et al., 2018). The diverging
element of these two types of anxiety is their duration: state anxiety is
an acute response to a potential threat, while trait anxiety is chronic, as
it is expressed constantly during the life of the individual, and is
therefore considered as a trait of an individual's personality (Endler and
Kocovski, 2001;Spielberger et al., 1983). State anxiety can be deﬁned
as hypervigilance in anticipation of a threat that can be triggered by
acute stress, and has the primary function of avoiding dangerous si-
tuations and also to facilitate memory consolidation (Roozendaal et al.,
2008). On the other hand, trait anxiety is a predisposition of an in-
dividual to express constant anxiety, and increases the probability of
state anxiety in potentially dangerous situations (Endler and Kocovski,
2001;Spielberger et al., 1983). State and trait anxiety are not mutually
exclusive, and state anxiety triggered by an event can be superimposed
on trait anxiety. Importantly, both state and trait anxiety responses
represent an evolutionary advantage to anticipate and avoid danger
(Goes et al., 2018;Spielberger et al., 1983;Takagi et al., 2018).
Therefore, anxiety per se is not a pathological state, as it can prevent
exposure to dangerous situations. However, when anxiety is sustained
and/or elicited by non-threating stimuli, it becomes maladaptive
(Belzung and Griebel, 2001;Sylvers et al., 2011). While state and trait
anxiety are essential psychological metrics to evaluate normal and pa-
thological levels of anxiety, these metrics do not consider the neural
substrate of anxiety, which partly explains the lack of new and eﬀective
therapies for anxiety disorders.
Over the past twenty years, human functional imaging has identi-
ﬁed multiple brain areas including the hypothalamus, amygdala, pre-
frontal cortex and nuclei of the brainstem which are active during both
stress and anxiety responses in healthy individuals (Mobbs et al., 2007;
Takagi et al., 2018). Interestingly, a subset of brain regions including
the basolateral amygdala (BLA), medial prefrontal cortex (mPFC), locus
coeruleus (LC), as well as reward processing areas such as the nucleus
accumbens (NAc), appear to be aﬀected in animal models of both stress
disorders and anxiety disorders (Calhoon and Tye, 2015;Etkin and
Wager, 2007;Sailer et al., 2008;Shin and Liberzon, 2010). The inter-
mingled neural circuits controlling both stress and anxiety suggests a
strong bidirectional relationship between stress experiences and anxiety
in both healthy and pathological conditions. Therefore, alterations of
the connectivity between the brain regions inﬂuencing both stress and
anxiety behaviors might contribute to the etiology of psychopathologies
such as generalized anxiety disorder (GAD), social anxiety disorders or
post-traumatic stress disorder (PTSD).
Herein, we summarize the views of the panel on Stress, Anxiety and
Corticolimbic Pathways, presented at the 2018 Stress Neurobiology
meeting, held in Banﬀ, Canada. This perspective reﬂects the diverse and
shared structures involved in both stress and anxiety responses. We aim
to reveal common subcortical processes that could support the interplay
between stress and anxiety-related behaviors.
2. Coding of emotional valence in the basolateral amygdala (BLA)
The attribution of emotional valence to sensory information is a key
process that allows individuals to navigate the world, and has been
shown to be altered in both anxiety and stress disorders (Etkin and
Wager, 2007;Sailer et al., 2008). Valence is the subjective value as-
signed to sensory stimuli, which determines subsequent behavior. Po-
sitive valence leads to approach and consummatory behaviors while
negative valence leads to defensive and avoidance behaviors (Pignatelli
and Beyeler, 2019;Russell, 1980). Attentional bias for stimuli of ne-
gative valence have been extensively demonstrated in patients with
anxiety disorders (MacLeod et al., 2019). For example, anxiety
increases negative interpretations of ambiguous sentences (Richards
and French, 1992) and scenarios (Hirsch and Mathews, 1997) sug-
gesting an anxiety-induced valence bias. Recent publications showed
that high trait anxiety individuals exhibit a bias towards negative in-
terpretations of surprised faces (Park et al., 2016a). The existence of a
correlation between negative valence bias and the level of anxiety in
health and disease observed in human studies supports the hypothesis
that the circuits encoding emotional valence could be dysfunctional in
anxiety disorders (Etkin and Wager, 2007;Lammel et al., 2014;
Mervaala et al., 2000;Pignatelli and Beyeler, 2019). A key structure
encoding emotional valence and therefore guiding animal behavior is
the basolateral nucleus of the amygdala (BLA). This region receives
sensory inputs of multiple modalities, and projects to output structures
controlling behavioral responses (Janak and Tye, 2015;McDonald,
1998). This central connectivity has made the BLA a focus for identi-
fying the neural substrate of valence processing. Moreover, a vast body
of literature has shown that BLA integrity is critical for processing po-
sitive (Bucy and Klüver, 1955;Tye et al., 2008;Weiskrantz, 1956) and
negative valence (Bucy and Klüver, 1955;LeDoux et al., 1990;
McDonald, 1998;Tye et al., 2008;Weiskrantz, 1956).
Interestingly, studies have shown that when deﬁned by their pro-
jection target, neurons of the BLA diﬀerentially control and encode
emotional valence (Fig. 1A). A set of studies revealed that photo-
stimulation of BLA neurons synapsing in the medial core/shell section
of the NAc (BLA-NAc) support reward seeking (Namburi et al., 2015).
Meanwhile, BLA neurons projecting to the medial section of the central
amygdala (BLA-CeA) mediate place avoidance (Namburi et al., 2015).
Importantly, these two diﬀerent BLA populations have divergent re-
sponses to valence predicting cues. Indeed, single-unit in vivo recordings
combined with optogenetic photoidentiﬁcation indicated that a higher
proportion of BLA-NAc neurons were excited by a cue predicting a re-
ward, while BLA-CeA neurons showed a higher proportion of neurons
excited by a stimulus predicting an aversive outcome (Beyeler et al.,
Furthermore, the authors identiﬁed a synaptic mechanism for
learning of valence associations. Speciﬁcally, synaptic inputs onto BLA-
NAc neurons and BLA-CeA neurons undergo opposing synaptic changes
following reward or fear conditioning (Fig. 1C, Namburi et al., 2015).
Notably, BLA neurons projecting to those distinct areas are inter-
mingled within the BLA, but are distributed following topographical
gradients (Fig. 1D, Beyeler et al., 2018), which are correlated with a
dorso-ventral bias of negative to positive valence coding (Beyeler et al.,
Another set of optogenetic experiments have shown that activation
of the BLA projection to the ventral hippocampus (vHPC) is suﬃcient to
induce real time anxiogenic eﬀects and conversely, inhibition of those
projections causes an anxiolytic eﬀect (Fig. 1B, Felix-Ortiz et al., 2013).
Single-unit recordings combined with optogenetic photoidentiﬁcation
have shown that BLA-vHPC neurons have no coding bias for learned
stimuli predicting outcomes of positive or negative valence compared to
the entire BLA (Beyeler et al., 2016). This observation supports the idea
that BLA-vHPC neurons may mediate anxiety-related behaviors which
can be deﬁned as an innate state of negative valence, rather than
Altogether, the BLA is a single structure which includes neural po-
pulations that underlie processing of learned emotional valence (BLA-
NAc and BLA-CeA) and a population that generates innate emotional
states (BLA-vHPC). This ﬁnding suggests that BLA is a key structure to
study how emotional states such as anxiety interfere with emotional
3. Locus coeruleus noradrenergic (LC-NE) projections to BLA:
acute stress-induced anxiety
Stressful experiences engage multiple structures to generate a co-
ordinated physical and psychological response to a challenge. The locus
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
coeruleus noradrenergic system (LC-NE) presents a brain-wide projec-
tion pattern (Schwarz et al., 2015) and is linked to both physical and
emotional responses to stress (Berridge and Waterhouse, 2003;
Valentino and Van Bockstaele, 2008), as well as aversive memory
consolidation (Roozendaal et al., 2008). Noradrenaline release during
an acute stress induces a state anxiety response that allow the organism
to maintain high attention, facilitate sensory processing and enhance
executive functions in order to increase memory consolidation during
stressful experiences (Berridge and Waterhouse, 2003;Sara and Bouret,
Electrophysiological and optogenetic studies indicate that LC-NE
neurons normally display three activation proﬁles: low tonic (1–2 Hz),
high tonic (3–8 Hz) and phasic activity (Carter et al., 2010). Acute stress
causes a robust increase in tonic ﬁring rate in LC-NE (Valentino and Van
Bockstaele, 2008) and this stress-induced tonic ﬁring is associated with
an increase in anxiety-like behavior. The role of tonic activation of LC-
NE neurons is further supported by the observations that optogenetic
stimulation of NE cell bodies in the LC, in the absence of a stressor,
mimics LC-NE tonic activity as well as acute-stress induced anxiety
(McCall et al., 2015). Furthermore, they suggest that this increase of
activity in LC-NE neurons is caused by synaptic inputs into the LC
containing corticotropin releasing hormone (CRH
stimulation of CRH
CeA-LC terminals increases activity in LC and
drives anxiety-like behaviors through type 1 CRH receptor (CRH1R)
activation (McCall et al., 2015).
Acute stress also promotes anxiety and other stress related behaviors
through BLA adrenergic receptor activation (Chang and Grace, 2013).
Even though the anatomical projections from LC and the role of NE in
stress and anxiety have been studied extensively, the mechanism by
which LC-NE inﬂuences BLA function to promote negative emotional
states has only recently been unravelled. McCall and collaborators
(2017) demonstrated that optogenetic activation of LC-NE ﬁbers in the
BLA in acute brain slices causes norepinephrine release into the BLA. In
vivo photostimulation of these terminals modulates BLA activity, and
LC-BLA stimulation is suﬃcient to cause conditioned place aversion as
well as anxiety-like behaviors. These stimulation-induced behavioral
changes require β-adrenergic receptor activity in the BLA, providing in
vivo evidence that endogenous NE release from LC terminals alters BLA
function and, as a consequence, modiﬁes behavior. Additional support
for β-adrenergic signaling promoting anxiety-like behaviors is provided
in Siuda et al. (2015), whereby selective optical activation of β-adre-
nergic signaling in CaMKII(+) neurons of the BLA produces robust
LC-NE neurons preferentially target neurons in the BLA that project
Fig. 1. Valence coding in the basolateral amygdala (BLA) projector populations. A. Projector valence coding (adapted from Beyeler et al. 2016). a. Schematic of
Pavlovian conditioning paradigm. Head-ﬁxed mice were trained to discriminate between one cue paired with sucrose (CS–S) and a diﬀerent cue paired with quinine
(CS-Q). b. Peri-stimulus time histogram (PSTH) of the ﬁring rates of representative units excited (top) or inhibited (bottom) during a CS-S presentation followed by a
sucrose delivery. c. Fraction of BLA neurons excited or inhibited by CS-S, CS-Q or both. d. PSTH of action potentials of a BLA single-unit photoidentiﬁed as a BLA-NAc
projector. e. Within-cell diﬀerence of response to CS-S and CS-Q depending on the neurons projection targets. f. Percentage of positive and negative valence units in
the BLA. B. Behavioral impact of optogenetic activation of diﬀerent BLA pathways (BLA-NAc and BLA-CeA projectors and BLA-vHPC terminals). C. Synaptic plasticity
mechanism observed in BLA-NAc and BLA-CeA projection neurons after learning of valence associations. D. Topographic maps of three projectors populations in the
BLA. CS: conditioned stimuli, S: sucorse, Q: quinine, NAc: nucleus accumbens, CeA: central amygdala, vHPC: ventral hippocampus.
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
to the ventral hippocampus (BLA-vHPC) and CeA (BLA-CeA), both
downstream structures involved in negative valence and anxiety-re-
lated behaviors (Beyeler et al., 2018;Felix-Ortiz et al., 2013;Namburi
et al., 2015). This suggests that LC-NE projections to BLA increase an-
xiety-like behaviors following stress exposure, through projections to
downstream structures such as CeA or vHPC (Fig. 2A). This recent work
reveals that part of the circuit underlying acute-stress, induces state
3.1. A new mitochondrial function linking stress and emotional traits
Even in our modern society, the necessity of positioning ourselves in
a social group through social competition has an enormous impact on
our daily lives. In spite of the importance that social competition has in
organizing and structuring our society, the psychological characteristics
that aﬀect social competitiveness of an individual have been largely
overlooked. Several brain regions such as the amygdala and the NAc
have been implicated in social status and competition in both humans
(Zink et al., 2008), and rodents (Goette et al., 2015). Recent studies
have speciﬁcally revealed the critical role of the NAc in social compe-
tition and the establishment of social status (Hollis et al., 2015;Larrieu
et al., 2017;Van der Kooij et al., 2018). During social competition, D1-
containing medium spiny neurons (MSNs) in the NAc are activated and
show a positive correlation with the level of oﬀensive behavior ob-
served in a social hierarchy test. In addition, when the NAc, but not the
BLA, is inactivated with a GABA
receptor agonist during a social
competition test, rats showed reduced social dominance (Hollis et al.,
The NAc is involved in motivation and has been implicated in the
regulation of anxiety and depressive-like symptoms (Lüthi and Lüscher,
2014). The neural mechanism through which anxiety might aﬀect so-
cial hierarchy has been poorly investigated. In humans, high-anxiety
individuals tend to display subordinate roles and to be less competitive
in social environments (Gilbert et al., 2009). Likewise, high-anxiety rats
show less social dominance after a social competition for a territory
(Hollis et al., 2015). These results are consistent with data obtained in
humans where high anxiety traits predispose subjects for social sub-
mission (Goette et al., 2015). These behavioral results, together with
the new data revealing a unique role of the NAc in the establishment of
social hierarchy open a new path to investigating how NAc function can
bridge anxiety and social competition. In search of potential mechan-
isms within the NAc, which could diﬀerentiate low and high anxiety
rats, Hollis et al. (2015) showed that high anxiety rats had lower mi-
tochondrial activity in NAc, compared to low anxiety rats. Speciﬁcally,
with similar mitochondrial numbers and density, highly anxious rats
have lower levels of respiratory complexes I and II of the electron
transport chain, resulting in a reduced mitochondrial function (Fig. 2B).
Furthermore, social status also predicts behavioral stress susceptibility
and metabolic proﬁle in the NAc after chronic social defeat (Larrieu
et al., 2017). These studies establish a key role of mitochondrial func-
tion in individual diﬀerences that impact social dominance in a non-
pathological condition. Altogether, the newly discovered role of mi-
tochondrial energy metabolism in the NAc in anxiety-induced social
deﬁcits opens a new path for therapeutic treatment that targets cell
In regards to the relationship between stress and anxiety, social
competition itself induces an endocrine stress response (Turan et al.,
2015). In humans, stress exposure diﬀerentially aﬀects low and high
anxiety subjects in a competitive task. Under stressful conditions, low-
anxiety individuals become overconﬁdent, while high-anxiety in-
dividuals show less social conﬁdence (Goette et al., 2015). Moreover,
several studies have reported increased risk of adult psychopathologies
after early life adversity (Haller et al., 2014;Maccari et al., 2014). In
preclinical models, early life stress paradigms have been proposed as a
tool to program or bias anxiety traits and, as a consequence, have ne-
gative impact in social competence (Tzanoulinou and Sandi, 2017).
Indeed, peri-pubertal stress leads to enhanced anxiety (Cordero et al.,
2016) and changes in social behavior in adulthood (Haller et al., 2014).
Interestingly, play-ﬁghting is a peri-pubertal social behavior which has
been linked to aggression in adulthood. Speciﬁcally, peri-puberal stress
increases play-ﬁghting and increases the chances to display abnormal
aggressive behaviors later in adulthood (Papilloud et al., 2018). Im-
portantly, this study also revealed a role of mitochondrial energy bal-
ance in regulating stress-induced behaviors, by showing that enhanced
play-ﬁghting behaviors following peri-pubertal stress was accompanied
by enhanced mitochondrial function in the amygdala.
4. Encoding reward-directed behavior under anxiety
In humans, patients suﬀering from anxiety disorders have impaired
decision making and behavioral ﬂexibility (Park and Moghaddam,
2017a). For example, high levels of anxiety are accompanied by
Fig. 2. Circuit and molecular mechanisms of stress and anxiety. A. LC-NE
projections to BLA increases anxiety-like behaviors acting on β-adrenergic re-
ceptors (βARs) and through projections to downstream structures such as the
CeA. B. NAc mitochondrial function and anxiety, and its inﬂuence on social
dominance. C. Circuit synchronicity between the PFC and VTA under diﬀerent
punishment probabilities. LC: locus coeruleus, BLA: basolateral amygdala, CeA:
central amygdala, NAc: nucleus accumbens, PFC: prefrontal cortex, VTA: ven-
tral tegmental area, NE: norepinephrine; ATP: adenosine triphosphate CRH:
corticotropin-releasing hormone TH: tyrosine hydroxylase DBH: dopamine
beta-hydroxylase Gal: galanin.
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
diﬃculty of shifting between strategies in the presence of changes in
task demand, and/or are easily distracted by irrelevant stimuli (Eysenck
et al., 2007). That inability to change strategies during a task can have
detrimental consequences in a person, by aﬀecting personal life and
professional performance. The prefrontal cortex (PFC) is a pivotal
structure in organizing behavior in a context dependent-manner
(Bechara et al., 2000;Miller and Cohen, 2001). Thus, during stress, the
PFC controls high order adaptive responses such as choosing optimal
behavioral output with an online evaluation of the situation
In rodents, anxiety levels are also related to decreased cognitive
ﬂexibility (Park and Moghaddam, 2017a). Recent studies have revealed
the functional consequence of anxiety upon PFC activity, by identifying
that a negative emotional state elicits sustained reduction of sponta-
neous ﬁring rate in the dorso-medial PFC (dmPFC) and orbitofrontal
cortex (OFC, Park et al., 2016b). This hypofrontality, and speciﬁcally
the reduced activity in the dmPFC, is linked to decreased behavioral
ﬂexibility in the set-shifting task (Park et al., 2016b). In this task the
subjects learn an instrumental behavioral response based on two dif-
ferent rules that sit on two diﬀerent dimensions (for example: shape and
color). The ability to switch between rules to maximize the proﬁt
(number of rewards) is PFC-dependent. The ventral tegmental area
(VTA) is also a critical component of reward-guided behavior, and to-
gether with the PFC, has been proposed as a circuit underlying deci-
sions during reward-seeking under punishment. VTA neurons are a key
component of the reward circuit (Morales and Margolis, 2017;Wood
et al., 2017) and their projections to the mPFC are involved in reg-
ulating mood and emotional states (Lammel et al., 2014).
Park and Moghaddam designed and developed a task to study the
dynamics of reward-based behavior while risking potential punishment
(Park and Moghaddam, 2017b). The task was designed to link instru-
mental action to reward, but at the same time, the same action will be
followed by a punishment with varying probabilities. This task aims to
recreate an environment where uncertainty of a negative outcome in-
duces anxiety. The probability of getting punished aﬀects behavioral
performance by increasing the variability of the time to react, sug-
gesting a transitory anxiety state caused by the possibility of being
punished. Single-unit recordings from both dopaminergic (DA) VTA
neurons, and mPFC neurons, during this task revealed that their ﬁring
rate around the motor response (time surrounding the action execution)
is correlated with the punishment risk, suggesting both neural popu-
lations encode the risk probability. Even though both VTA-DA and non-
DA neurons, as well as mPFC neurons, showed punishment risk en-
coding responses, VTA-DA neurons showed a higher temporal resolu-
tion around the action time than mPFC neurons, which showed a more
diﬀuse response around the action window. Interestingly, the single-
unit recordings did not correlate with the behavioral changes during
the task, and a more detailed analysis revealed that the variability in
the reaction time was related to a circuit dynamic. The correlation of
the ﬁring of VTA and mPFC neurons with the reaction time was evident
only in the riskiest part of the session, when the probability to be
punished was higher.
At the network level, the synchronicity of the theta oscillations is
important to coordinate groups of neurons to complete a behavioral
response (Akam and Kullman, 2010;Buschman et al., 2012). Interest-
ingly, during non-punished trials, the oscillations that emerged in the
VTA and mPFC are in the theta range (around 8 Hz, Park and
Moghaddam, 2017b). Moreover, increased probability of punishment
decreases the oscillations in both areas and weakens synchrony within
and between both structures.
These studies revealed that synchrony between the VTA and PFC
decreases with punishment probability, suggesting that VTA-PFC net-
work encodes punishment risk (Fig. 2C). Under normal conditions, VTA
drives oscillation synchronicity between both regions exerting a
bottom-up control of the network. When there is risk of punishment,
this bottom-up network control is diminished. Transient anxiety may,
therefore, aﬀect behavior in a reward-based task by disrupting the VTA-
PFC functional circuit.
5. Role of hypothalamic corticotropin (PVN-CRH) neurons in
Although the relationship between stress and anxiety is bidirec-
tional, the inﬂuence of stress as a risk factor for anxiety disorders has
been extensively studied (Armario et al., 2008;Tye and Deisseroth,
2012). Mapping of neural circuits involved in stress-induced anxiety
have mostly revolved around structures of the amygdala and extended
amygdala (Davis et al., 2010;Gross and Canteras, 2012). Surprisingly,
relatively less attention has been directed towards the paraventricular
nucleus of the hypothalamus (PVN), which is a crucial component of
the visceral stress response. The PVN receives and integrates informa-
tion about the stressor and controls the endocrine, behavioral and au-
tonomic response to stress (Denver, 2009;Herman et al., 2003;Ulrich-
Lai and Herman, 2009). Speciﬁcally, parvocellular neurosecretory cells
release corticotropin-releasing hormone (CRH) into the anterior pitui-
tary that stimulates the synthesis and release in the blood stream of
adrenocorticotropic hormone (ACTH). Once ACTH reaches the adrenal
glands it stimulates the release of glucocorticoid (Denver, 2009;
Herman et al., 2003;Ulrich-Lai and Herman, 2009). In the past ﬁve
years, the classical view of PVN-CRH neurons has been challenged by
demonstrations that these neurons also control multiple and complex
behaviors that are linked to stress (De Marco et al., 2016;Füzesi et al.,
2016;Sterley et al., 2018;Zhang et al., 2017). These observations open
an exciting line of research to investigate how this speciﬁc set of neu-
rons can drive stress-induced behavioral alterations.
The standard methods to study anxiety in rodents have relied on
established laboratory tests such as the elevated plus maze. However,
over the last decade, an increasing number of studies have focused on
developing new tools of behavioral analysis that are less invasive, re-
quire less subjective interpretations, and harken back to original etho-
logical approaches (Lezak et al., 2017). One of these approaches relies
on monitoring freely-behaving mice in their home-cage environment
without any intervention (Fig. 3A). Multiple behaviors such as
grooming, freezing, rearing or surveying can be detected. Importantly,
these behaviors show a speciﬁc but ﬂexible temporal distribution. Using
this approach, it was shown that a single stressful experience results in
the emergence of an organized and structured behavioral pattern where
self-directed behaviors such as grooming become predominant, taking
over exploratory behaviors such as locomotion or rearing (Fig. 3B,
Füzesi et al., 2016). The role of brainstem in generating stress-induced
behavioral responses such as freezing (Deng et al., 2016;Silva and
McNaughton, 2019), grooming (Kalueﬀet al., 2016), defensive beha-
viors or even anxiety-like behavior (McCall et al., 2015), has been ex-
tensively studied over the years (Myers et al., 2017). A recent study
from Füzesi et al. (2016) proposes the contribution of a diﬀerent
structure, by revealing a new role for PVN-CRH neurons in coordinating
the spontaneous behavioral patterns that emerge after acute stress.
Speciﬁcally, optogenetic silencing of PVN-CRH activity during the post-
stress period reduces grooming in a safe environment. On the contrary,
activating PVN-CRH neurons modiﬁes the intensity, but not necessarily
the temporal sequence of context appropriate behaviors (Fig. 3C). The
behavioral proﬁle that arises after an acute stress experience is context
dependent and related to PVN-CRH neuron activity.
Further work on PVN-CRH has revealed that these cells are neces-
sary and suﬃcient for stress-induced social investigation that is re-
quired for the transmission of stress from one individual to another
(Sterley et al., 2018). This social transmission of stress results in
changes in synaptic function and metaplasticity in the recipient mice,
which mirror the synaptic changes observed in stressed mice. This study
positions PVN-CRH neurons as a critical node for alarm signal proces-
sing and oﬀers a potential explanation for how individuals who have
not had a ﬁrst-hand traumatic experience can develop symptomology
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
consistent with post-traumatic stress disorders (Haugen et al., 2012;
Sial et al., 2016).
Recent studies have shown that PVN-CRH neurons are able to re-
spond diﬀerentially to stimuli with positive or negative valence (Kim
et al., 2019;Yuan et al., 2019). Using in vivo ﬁber photometry to
monitor population calcium dynamics, Kim et al. (2019) have shown
that the activity of PVN-CRH neurons rapidly increases in response to
stimuli with negative valence, and decreases when an appetitive sti-
mulus such as food or social interaction is presented. Moreover, a re-
ward presentation during stress can buﬀer PVN-CRH activation, and, as
a consequence, modify stress-related behaviors, such as grooming,
correlate with the activity of those neurons (Yuan et al., 2019). The
bidirectional response of PVN-CRH neurons based on stimulus valence
opens a new perspective to study stress coping and relieve.
Beyond CRH neurons, a distinct neuronal population in the PVN
containing CRH1R has been recently described. This population is 90%
GABAergic and has direct synaptic contact with PVN-CRH neurons, and
CRH, released from PVN-CRH neurons, modulates signaling between
both populations (Jiang et al., 2018;Ramot et al., 2017). This intra-
PVN network of CRH1R+ and CRF + neurons has been associated with
anxiety-like behavior, as knocking out CRH1R from PVN neurons has
anxiolytic eﬀects (Ramot et al., 2017;Zhang et al., 2017).
All these new data are contributing to update the role of
hypothalamic neural populations in stress-related behaviors.
Speciﬁcally, growing evidence implicates PVN-CRH neurons in mod-
ulating speciﬁc behaviors in a stress-related context. From controlling
how an individual responds to stress exposure (Füzesi et al., 2016;Kim
et al., 2019;Yuan et al., 2019) to regulating anxiety-like behaviors
(Ramot et al., 2017;Zhang et al., 2017), or driving social transmission
of stress (Sterley et al., 2018), the PVN-CRH neuron population appears
to be a central player linking stress and anxiety.
6. From research to clinics: new categorization of post-traumatic
stress disorder (PTSD)
The idea that stress and anxiety have segregated neurobiological
substrates despite their reciprocal inﬂuence has now moved beyond the
research ﬁeld to reach the clinical practice, resulting in changes in di-
agnostic tools. Speciﬁcally, according to the DSM-5 (American
Psychiatric Association, 2013) PTSD is not classiﬁed as an anxiety
disorder anymore, and the new manual categorizes it among the trauma
or stressor-related disorders. This new category requires explicitly an
exposure to a traumatic or stressful event as a diagnostic criterion, and
in particular, the PTSD requires a life threatening experience. Re-
classifying PTSD from anxiety disorders to this newly created trauma or
stressor-related disorders category has helped to move the focus away
Fig. 3. PVN-CRH neurons coordinate beha-
vioral patterns after stress (adapted from
Füzesi et al., 2016).A. Behavioral quantiﬁcation
of mice in their home-cage, before (naïve) and
immediately after a footshock (stress). Eight
distinct behaviors are prominent. Each row re-
presents one mouse. B. Histogram of grooming
behavior at each time-point for naïve and stress
mice. C. Schematic of in vivo photostimulation of
PVN-CRH to LH projections (20 Hz, 5 min) in-
creases grooming time and stimulated CORT
release. PVN: paraventricular nucleus of the
hypothalamus CRH: corticotropin-releasing
hormone LH: lateral hypothalamus ME: median
eminence CORT: corticosterone.
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
from anxiety, which is now rather considered as a comorbid pathology.
The new classiﬁcation in DSM-5 also emphasizes the abnormal re-
activity to a stimulus. Interestingly, an altered “ﬂight”response has
been observed in patients with PTSD (Park et al., 2017) and, in the last
ﬁve years, the interest in how microcircuits controlling threat proces-
sing are altered in PTSD has grown considerably. This emergent lit-
erature supports the idea that aberrant subconscious threat-related
processes are underlying part of the PTSD symptomatology (Lanius
et al., 2017). Current data indicates an increased connectivity between
areas involved in the innate alarm system, such as the LC, amygdala,
hypothalamus, and PFC in PTSD patients (Rabellino et al., 2016). In
humans, when a challenge is not life-threating, the subjects choose the
most suitable cost-eﬀective strategy to overcome that situation by en-
gaging the vmPFC, medial orbitofrontal cortex (mOFC) and other non-
cortical structures including the BLA which is causally involved in va-
lence processing. However, when the level of danger is life threatening
and the organism must prepare for a defensive response, subcortical
structures, such as the periaqueductal gray area (PAG) and CeA over-
rule the cognitive control, and guide the behavioral response (Mobbs
et al., 2007). The balance between cortical and subcortical systems
could also cast out key points to understand some anxiety disorders.
Negative emotional states such as anxiety may lead a person to over-
estimate the possibility of danger, leading to a shift in the balance of
these two systems. The dynamics between the cognitive and innate
circuitry in response to a challenge may reveal a path to a better
comprehension of how stressful experiences inﬂuence our emotional
state, and in turn, shape our future behaviors.
Although the dissection of multiple brain circuits controlling an-
xiety- and stress-related behaviors has made substantial advances, our
understanding of the neural substrates underlying the interplay be-
tween these two psychophysiological responses remains fragmented.
Here, we described speciﬁc roles of neural populations in the amygdala,
nucleus accumbens, prefrontal cortex, hypothalamus and locus coer-
uleus in emotional valence, stress and anxiety. The work described here
is providing foundational knowledge, however future investigation is
necessary to unravel the contribution of speciﬁc circuits to stress and/or
anxiety. Speciﬁcally, future work should use activity dependent map-
ping and recordings of genetically or anatomically deﬁned neural po-
pulations during stress exposure and at diﬀerent levels of anxiety within
the same animal. Beyond the technical advances catalyzing our un-
derstanding of the neural circuits underpinning stress and anxiety,
disentangling them will require the development of new behavioral
paradigms in pre-clinical models in order to ﬁnely capture the changes
of neural coding in these two conditions.
Conﬂicts of interest
The authors have no conﬂict of interest to declare.
We thank Matt Hill and Jaideep Bains for organizing the 2018 Stress
Neurobiology Workshop, and for their invitation to write this review to
summarize the major ﬁndings presented during the sessions including
the authors of this review. ND is supported by Fellowships from Alberta
Innovates-Health Solutions. We acknowledge the support of the Région
Nouvelle-Aquitaine and the INSERM-Avenir program of the French NIH
to the Beyeler Lab and of the Brain and Behavior Research Foundation
NARSAD young investigator grant to AB.
Akam, T., Kullman, D.M., 2010. Oscillations and ﬁltering networks support ﬂexible
routing of information. Neuron 67, 308–320.
American Psychiatric Association, 2013. In: Diagnostic and Statistical Manual of Mental
Disorders, ﬁfth ed. (Whashington).
Anderson, D.J., Adolphs, R., 2014. A framework for studying emotions across species. Cell
157, 187–200. https://doi.org/10.1016/j.cell.2014.03.003.
Armario, A., Escorihuela, R.M., Nadal, R., 2008. Long-term neuroendocrine and beha-
vioural eﬀects of a single exposure to stress in adult animals. Neurosci. Biobehav.
Rev. 6, 1121–1135.
Bechara, A., Tranel, D., Damasio, H., 2000. Characterization of the decision-making
deﬁcit of patients with ventromedial prefrontal cortex lesions. Brain J. Neurol. 123,
Belzung, C., Griebel, G., 2001. Measuring normal and pathological anxiety-like behaviour
in mice: a review. Behav. Brain Res. 125, 141–149.
Berridge, C.W., Waterhouse, B.D., 2003. The locus coeruleus–noradrenergic system:
modulation of behavioral state and state-dependent cognitive processes. Brain Res.
Rev. 42, 33–84. https://doi.org/10.1016/S0165-0173(03)00143-7.
Beyeler, A., Chang, C.-J., Silvestre, M., Lévêque, C., Namburi, P., Wildes, C.P., Tye, K.M.,
2018. Organization of valence-encoding and projection-deﬁned neurons in the ba-
solateral amygdala. Cell Rep. 22, 905–918. https://doi.org/10.1016/j.celrep.2017.
Beyeler, A., Namburi, P., Glober, G.F., Simonnet, C., Calhoon, G.G., Conyers, G.F., Luck,
R., Wildes, C.P., Tye, K.M., 2016. Divergent routing of positive and negative in-
formation from the amygdala during memory retrieval. Neuron 90, 348–361. https://
Bucy, P.C., Klüver, H., 1955. An anatomical investigation of the temporal lobe in the
monkey (Macaca mulatta). J. Comp. Neurol. 103, 151–251.
Buschman, T.J., Denovellis, E.L., Diogo, C., Bullock, D., Miller, E.K., 2012. Synchronous
oscillatory neural ensembles for rules in the prefrontal cortex. Neuron 76, 838–846.
Calhoon, G.G., Tye, K.M., 2015. Resolving the neural circuits of anxiety. Nat. Neurosci.
18, 1394–1404. https://doi.org/10.1038/nn.4101.
Carter, M.E., Yizhar, O., Chikahisa, S., Nguyen, H., Adamantidis, A., Nishino, S.,
Deisseroth, K., de Lecea, L., 2010. Tuning arousal with optogenetic modulation of
locus coeruleus neurons. Nat. Neurosci. 13, 1526–1533. https://doi.org/10.1038/nn.
Chang, C., Grace, A.A., 2013. Amygdala β-noradrenergic receptors modulate delayed
downregulation of dopamine activity following restraint. J. Neurosci. 33, 1441–1450.
Chrousos, G.P., 2009. Stress and disorders of the stress system. Nat. Rev. Endocrinol. 5,
Cordero, M.I., Just, N., Poirier, G.L., Sandi, C., 2016. Eﬀects of paternal and peripubertal
stress on aggression, anxiety, and metabolic alterations in the lateral septum. Eur.
Neuropsychopharmacol. 26, 357–367. https://doi.org/10.1016/j.euroneuro.2015.
Davis, M., Walker, D.L., Miles, L., Grillon, C., 2010. Phasic vs sustained fear in rats and
humans: role of the extended amygdala in fear vs anxiety.
Neuropsychopharmacology 35, 103–135.
de Kloet, E.R., Joëls, M., Holsboer, F., 2005. Stress and the brain: from adaptation to
disease. Nat. Rev. Neurosci. 6, 463–475. https://doi.org/10.1038/nrn1683.
De Marco, R.J., Thiemann, T., Groneberg, A.H., Herget, U., Ryu, S., 2016. Optogenetically
enhanced pituitary corticotroph cell activity post-stress onset causes rapid organizing
eﬀects on behaviour. Nat. Commun. 7. https://doi.org/10.1038/ncomms12620.
Deng, H., Xiao, X., Wang, Z., 2016. Periaqueductal gray neuronal activities underlie
diﬀerent aspects of defensive behaviors. J. Neurosci. 36, 7580–7588. https://doi.org/
Denver, R.J., 2009. Structural and functional evolution of vertebrate neuroendocrine
stress systems. Ann. N. Y. Acad. Sci. 1163, 1–16. https://doi.org/10.1111/j.1749-
Endler, N.S., Kocovski, N.L., 2001. State and trait anxiety revisited. J. Anxiety Disord. 15,
Etkin, A., Wager, T.D., 2007. Functional neuroimaging of anxiety: a meta-analysis of
emotional processing in PTSD, social anxiety disorder, and speciﬁc phobia. Am. J.
Psychiatry 164, 1476–1488. https://doi.org/10.1176/appi.ajp.2007.07030504.
Eysenck, M.W., Derakshan, N., Santos, R., Calvo, M.G., 2007. Anxiety and cognitive
performance: attentional control theory. Emotion 7, 336–353. https://doi.org/10.
Felix-Ortiz, A.C., Beyeler, A., Seo, C., Leppla, C.A., Wildes, C.P., Tye, K.M., 2013. BLA to
vHPC inputs modulate anxiety-related behaviors. Neuron 79, 658–664.
Füzesi, T., Daviu, N., Wamsteeker Cusulin, J.I., Bonin, R.P., Bains, J.S., 2016.
Hypothalamic CRH neurons orchestrate complex behaviours after stress. Nat.
Commun. 7, 11937. https://doi.org/10.1038/ncomms11937.
Gilbert, P., McEwan, K., Bellew, R., Mills, A., Gale, C., 2009. The dark side of competition:
how competitive behaviour and striving to avoid inferiority are linked to depression,
anxiety, stress and self-harm. Psychol. Psychother. Theory Res. Pract. 82, 123–136.
Goes, T.C., Almeida Souza, T.H., Marchioro, M., Teixeira-Silva, F., 2018. Excitotoxic le-
sion of the medial prefrontal cortex in Wistar rats: eﬀects on trait and state anxiety.
Brain Res. Bull. 142, 313–319. https://doi.org/10.1016/j.brainresbull.2018.08.009.
Goette, L., Bendahan, S., Thoresen, J., Hollis, F., Sandi, C., 2015. Stress pulls us apart:
anxiety leads to diﬀerences in competitive conﬁdence under stress.
Psychoneuroendocrinology 54, 115–123. https://doi.org/10.1016/j.psyneuen.2015.
Gross, C.T., Canteras, N.S., 2012. The many paths to fear. Nat. Rev. Neurosci. 13,
Haller, J., Harold, G., Sandi, C., Neumann, I.D., 2014. Eﬀects of adverse early-life events
on aggression and anti-social behaviours in animals and humans. J. Neuroendocrinol.
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
26, 724–738. https://doi.org/10.1111/jne.12182.
Haugen, P.T., Evces, M., Weiss, D.S., 2012. Treating posttraumatic stress disorder in ﬁrst
responders: a systematic review. Clin. Psychol. Rev. 32, 370–380. https://doi.org/10.
Herman, J.P., Figueiredo, H., Mueller, N.K., Ulrich-Lai, Y., Ostrander, M.M., Choi, D.C.,
Cullinan, W.E., 2003. Central mechanisms of stress integration: hierarchical circuitry
controlling hypothalamo–pituitary–adrenocortical responsiveness. Front.
Neuroendocrinol. 24, 151–180. https://doi.org/10.1016/j.yfrne.2003.07.001.
Hirsch, C., Mathews, A., 1997. Interpretative inferences when reading about emotional
events. Behav. Res. Ther. 35, 1123–1132.
Hollis, F., van der Kooij, M.A., Zanoletti, O., Lozano, L., Cantó, C., Sandi, C., 2015.
Mitochondrial function in the brain links anxiety with social subordination. Proc.
Natl. Acad. Sci. U.S.A. 112, 15486–15491. https://doi.org/10.1073/pnas.
Janak, P.H., Tye, K.M., 2015. From circuits to behaviour in the amygdala |. Nature 517,
Jiang, Z., Rajamanickam, S., Justice, N.J., 2018. Local corticotropin-releasing factor
signaling in the hypothalamic paraventricular nucleus. J. Neurosci. 38, 1874–1890.
Kalueﬀ, A.V., Stewart, A.M., Song, C., Berridge, K.C., Graybiel, A.M., Fentress, J.C., 2016.
Neurobiology of rodent self-grooming and its value for translational neuroscience.
Nat. Rev. Neurosci. 17, 45–59. https://doi.org/10.1038/nrn.2015.8.
Kim, J., Lee, S., Fang, Y.-Y., Shin, A., Park, S., Hashikawa, K., Bhat, S., Kim, D., Sohn, J.-
W., Lin, D., Suh, G.S.B., 2019. Rapid, biphasic CRF neuronal responses encode po-
sitive and negative valence. Nat. Neurosci. 22, 576. https://doi.org/10.1038/s41593-
Koolhaas, J.M., 2011. Stress revisited: a critical evaluation of the stress concept. Neurosci.
Biobehav. Rev. 35, 1291–1301.
Lammel, S., Tye, K.M., Warden, M.R., 2014. Progress in understanding mood disorders:
optogenetic dissection of neural circuits. Genes Brain Behav. 13, 38–51. https://doi.
Lanius, R.A., Rabellino, D., Boyd, J.E., Harricharan, S., Frewen, P.A., McKinnon, M.C.,
2017. The innate alarm system in PTSD: conscious and subconscious processing of
threat. Curr. Opin. Psychol., Traumatic stress 14, 109–115. https://doi.org/10.1016/
Larrieu, T., Cherix, A., Duque, A., Rodrigues, J., Lei, H., Gruetter, R., Sandi, C., 2017.
Hierarchical status predicts behavioral vulnerability and nucleus accumbens meta-
bolic proﬁle following chronic social defeat stress. Curr. Biol. CB 27, 2202–2210. e4.
LeDoux, J.E., Cicchetti, P., Xagoraris, A., Romanski, L.M., 1990. The lateral amygdaloid
nucleus: sensory interface of the amygdala in fear conditioning. J. Neurosci. 10,
Lezak, K., Missig, G., Carlezon, M., 2017. Behavioral methods to study anxiety in rodents.
Dialogue Crinical. Neurosci. 19, 181–191.
Lüthi, A., Lüscher, C., 2014. Pathological circuit function underlying addiction and an-
xiety disorders. Nat. Neurosci. 17, 1635–1643. https://doi.org/10.1038/nn.3849.
Maccari, S., Krugers, H.J., Morley-Fletcher, S., Szyf, M., Brunton, P.J., 2014. The con-
sequences of early-life adversity: neurobiological, behavioural and epigenetic adap-
tations. J. Neuroendocrinol. 26, 707–723. https://doi.org/10.1111/jne.12175.
MacLeod, C., Grafton, B., Notebaert, L., 2019. Anxiety-linked attentional bias: is it reli-
able? Annu. Rev. Clin. Psychol. 15 null. https://doi.org/10.1146/annurev-clinpsy-
McCall, J.G., Al-Hasani, R., Siuda, E.R., Hong, D.Y., Norris, A.J., Ford, C.P., Bruchas,
M.R., 2015. CRH engagement of the locus coeruleus noradrenergic system mediates
stress-induced anxiety. Neuron 87, 605–620. https://doi.org/10.1016/j.neuron.
McDonald, A.J., 1998. Cortical pathways to the mammalian amygdala. Prog. Neurobiol.
55, 257–332. https://doi.org/10.1016/S0301-0082(98)00003-3.
Mervaala, E., Föhr, J., Könönen, M., Valkonen-Korhonen, M., Vainio, P., Partanen, K.,
Partanen, J., Tiihonen, J., Viinamäki, H., Karjalainen, A.K., Lehtonen, J., 2000.
Quantitative MRI of the hippocampus and amygdala in severe depression. Psychol.
Med. 30, 117–125.
Miller, E.K., Cohen, J.D., 2001. An integrative theory of prefrontal cortex function. Annu.
Rev. Neurosci. 24, 167–202. https://doi.org/10.1146/annurev.neuro.24.1.167.
Mobbs, D., Petrovic, P., Marchant, J.L., Hassabis, D., Weiskopf, N., Seymour, B., Dolan,
R.J., Frith, C.D., 2007. When fear is near: threat imminence elicits prefrontal-peria-
queductal gray shifts in humans. Science 317, 1079–1083. https://doi.org/10.1126/
Moghaddam, B., 2016. The complicated relationship of stress and prefrontal cortex. Biol.
Psychiatry, Stress, Fear, and Anxiety 80, 728–729. https://doi.org/10.1016/j.
Morales, M., Margolis, E.B., 2017. Ventral tegmental area: cellular heterogeneity, con-
nectivity and behaviour. Nat. Rev. Neurosci. 18, 73–85. https://doi.org/10.1038/
Myers, B., Scheimann, J.R., Franco-Villanueva, A., Herman, J.P., 2017. Ascending me-
chanisms of stress integration: implications for brainstem regulation of neuroendo-
crine and behavioral stress responses. Neurosci. Biobehav. Rev., Stress, Behavior and
the Heart 74, 366–375. https://doi.org/10.1016/j.neubiorev.2016.05.011.
Namburi, P., Beyeler, A., Yorozu, S., Calhoon, G.G., Halbert, S.A., Wichmann, R., Holden,
S.S., Mertens, K.L., Anahtar, M., Felix-Ortiz, A.C., Wickersham, I.R., Gray, J.M., Tye,
K.M., 2015. A circuit mechanism for diﬀerentiating positive and negative associa-
tions. Nature 520, 675–678. https://doi.org/10.1038/nature14366.
Papilloud, A., Suduiraut, I.G. de, Zanoletti, O., Grosse, J., Sandi, C., 2018. Peripubertal
stress increases play ﬁghting at adolescence and modulates nucleus accumbens CB1
receptor expression and mitochondrial function in the amygdala. Transl. Psychiatry
8, 156. https://doi.org/10.1038/s41398-018-0215-6.
Park, G., Vasey, M.W., Kim, G., Hu, D.D., Thayer, J.F., 2016a. Trait anxiety is associated
with negative interpretations when resolving valence ambiguity of surprised faces.
Front. Psychol. 7. https://doi.org/10.3389/fpsyg.2016.01164.
Park, J., Marvar, P.J., Liao, P., Kankam, M.L., Norrholm, S.D., Downey, R.M.,
McCullough, S.A., Le, N., Rothbaum, B.O., 2017. Baroreﬂex dysfunction and aug-
mented sympathetic nerve responses during mental stress in veterans with post‐-
traumatic stress disorder. J. Physiol. 595.
Park, J., Moghaddam, B., 2017a. Impact of anxiety on prefrontal cortex encoding of
cognitive ﬂexibility. Neurosci., Cognit. Flexibil.: Dev., Dis. Treat. 345, 193–202.
Park, J., Moghaddam, B., 2017b. Risk of punishment inﬂuences discrete and coordinated
encoding of reward-guided actions by prefrontal cortex and VTA neurons. eLife 6,
Park, J., Wood, J., Bondi, C., Del Arco, A., Moghaddam, B., 2016b. Anxiety evokes hy-
pofrontality and disrupts rule-relevant encoding by dorsomedial prefrontal cortex
neurons. J. Neurosci. Oﬀ. J. Soc. Neurosci. 36, 3322–3335. https://doi.org/10.1523/
Pignatelli, M., Beyeler, A., 2019. Valence coding in amygdala circuits. Curr. Opin. Behav.
Sci., Pain and Aversive Motivation 26, 97–106. https://doi.org/10.1016/j.cobeha.
Rabellino, D., Densmore, M., Frewen, P.A., Théberge, J., Lanius, R.A., 2016. The innate
alarm circuit in post-traumatic stress disorder: conscious and subconscious processing
of fear- and trauma-related cues. Psychiatry Res. Neuroimaging 248, 142–150.
Ramot, A., Jiang, Z., Tian, J.-B., Nahum, T., Kuperman, Y., Justice, N., Chen, A., 2017.
Hypothalamic CRFR1 is essential for HPA axis regulation following chronic stress.
Nat. Neurosci. 20, 385–388. https://doi.org/10.1038/nn.4491.
Richards, A., French, C.C., 1992. An anxiety-related bias in semantic activation when
processing threat/neutral homographs. Q. J. Exp. Psychol. 45, 503–525.
Roozendaal, B., Castello, N.A., Vedana, G., Barsegyan, A., McGaugh, J.L., 2008.
Noradrenergic activation of the basolateral amygdala modulates consolidation of
object recognition memory. Neurobiol. Learn. Mem. 90, 576–579. https://doi.org/
Russell, J.A., 1980. A circumplex model of aﬀect. J. Personal. Soc. Psychol. 39,
Sailer, U., Robinson, S., Fischmeister, F.PhS., König, D., Oppenauer, C., Lueger-Schuster,
B., Moser, E., Kryspin-Exner, I., Bauer, H., 2008. Altered reward processing in the
nucleus accumbens and mesial prefrontal cortex of patients with posttraumatic stress
disorder. Neuropsychologia 46, 2836–2844. https://doi.org/10.1016/j.
Sara, S.J., Bouret, S., 2012. Orienting and reorienting: the locus coeruleus mediates
cognition through arousal. Neuron 76, 130–141. https://doi.org/10.1016/j.neuron.
Schwarz, L.A., Miyamichi, K., Gao, X.J., Beier, K.T., Weissbourd, B., DeLoach, K.E., Ren,
J., Ibanes, S., Malenka, R.C., Kremer, E.J., Luo, L., 2015. Viral-genetic tracing of the
input–output organization of a central noradrenaline circuit. Nature 524, 88–92.
Selye, H., 1936. A syndrome produced by diverse nocuous agents. J. Neuropsychiatry
Clin. Neurosci. 10, 230a–2231. https://doi.org/10.1176/jnp.10.2.230a.
Shin, L.M., Liberzon, I., 2010. The neurocircuitry of fear, stress, and anxiety disorders.
Neuropsychopharmacology 35, 169–191. https://doi.org/10.1038/npp.2009.83.
Sial, O.K., Warren, B.L., Alcantara, L.F., Parise, E.M., Bolaños-Guzmán, C.A., 2016.
Vicarious social defeat stress: bridging the gap between physical and emotional
stress. J. Neurosci. Methods 258, 94–103. https://doi.org/10.1016/j.jneumeth.2015.
Silva, C., McNaughton, N., 2019. Are periaqueductal gray and dorsal raphe the founda-
tion of appetitive and aversive control? A comprehensive review. Prog. Neurobiol.
177, 33–72. https://doi.org/10.1016/j.pneurobio.2019.02.001.
Siuda, E.R., McCall, J.G., Al-Hasani, R., Shin, G., Il Park, S., Schmidt, M.J., Anderson, S.L.,
Planer, W.J., Rogers, J.A., Bruchas, M.R., 2015. Optodynamic simulation of β-adre-
nergic receptor signalling. Nat. Commun. 6, 8480. https://doi.org/10.1038/
Spielberger, C.D., Gorsuch, R.L., Lushene, R.D., 1983. Manual for the State-Trait Anxiety
Inventory (STAI). Palo Alto Consulating Psychol. Press.
Sterley, T.-L., Baimoukhametova, D., Füzesi, T., Zurek, A.A., Daviu, N., Rasiah, N.P.,
Rosenegger, D., Bains, J.S., 2018. Social transmission and buﬀering of synaptic
changes after stress. Nat. Neurosci. 21, 393–403.
Sylvers, P., Lilienfeld, S.O., LaPrairie, J.L., 2011. Diﬀerences between trait fear and trait
anxiety: implications for psychopathology. Clin. Psychol. Rev. 31, 122–137. https://
Takagi, Y., Sakai, Y., Abe, Y., Nishida, S., Harrison, B.J., Martínez-Zalacaín, I., Soriano-
Mas, C., Narumoto, J., Tanaka, S.C., 2018. A common brain network among state,
trait, and pathological anxiety from whole-brain functional connectivity. Neuroimage
172, 506–516. https://doi.org/10.1016/j.neuroimage.2018.01.080.
Turan, B., Tackett, J.L., Lechtreck, M.T., Browning, W.R., 2015. Coordination of the
cortisol and testosterone responses: a dual axis approach to understanding the re-
sponse to social status threats. Psychoneuroendocrinology 62, 59–68. https://doi.
Tye, K.M., Deisseroth, K., 2012. Optogenetic investigation of neural circuits underlying
brain disease in animal models. Nat. Rev. Neurosci. 13, 251–266. https://doi.org/10.
Tye, K.M., Stuber, G.D., de Ridder, B., Bonci, A., Janak, P.H., 2008. Rapid strengthening
of thalamo-amygdala synapses mediates cue–reward learning. Nature 453,
Tzanoulinou, S., Sandi, C., 2017. The programming of the social brain by stress during
childhood and adolescence: from rodents to humans. In: Wöhr, M., Krach, S. (Eds.),
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191
Social Behavior from Rodents to Humans: Neural Foundations and Clinical
Implications, Current Topics in Behavioral Neurosciences. Springer International
Publishing, Cham, pp. 411–429. https://doi.org/10.1007/7854_2015_430.
Ulrich-Lai, Y.M., Herman, J.P., 2009. Neural regulation of endocrine and autonomic stress
responses. Nat. Rev. Neurosci. 10, 397–409. https://doi.org/10.1038/nrn2647.
Valentino, R.J., Van Bockstaele, E., 2008. Convergent regulation of locus coeruleus ac-
tivity as an adaptive response to stress. Eur. J. Pharmacol. 583, 194–203. https://doi.
Van der Kooij, M.A., Hollis, F., Lozano, L., Zalachoras, I., Abad, S., Zanoletti, O., Grosse,
J., Guillot de Suduiraut, I., Canto, C., Sandi, C., 2018. Diazepam actions in the VTA
enhance social dominance and mitochondrial function in the nucleus accumbens by
activation of dopamine D1 receptors | Molecular Psychiatry. Mol. Psychiatry 23,
Weiskrantz, L., 1956. Behavioral changes associated with ablation of the amygdaloid
complex in monkeys. J. Comp. Physiol. Psychol. 49, 381–391.
Wood, J., Simon, N.W., Koerner, F.S., Kass, R.E., Moghaddam, B., 2017. Networks of VTA
neurons encode real-time information about uncertain numbers of actions executed
to earn a reward. Front. Behav. Neurosci. 11. https://doi.org/10.3389/fnbeh.2017.
Yuan, Y., Wu, W., Chen, M., Cai, F., Fan, C., Shen, W., Sun, W., Hu, J., 2019. Reward
inhibits paraventricular CRH neurons to relieve stress. Curr. Biol. 29, 1243–1251. e4.
Zhang, R., Asai, M., Mahoney, C.E., Joachim, M., Shen, Y., Gunner, G., Majzoub, J.A.,
2017. Loss of hypothalamic corticotropin-releasing hormone markedly reduces an-
xiety behaviors in mice. Mol. Psychiatry 22, 733–744. https://doi.org/10.1038/mp.
Zink, C.F., Tong, Y., Chen, Q., Bassett, D.S., Stein, J.L., Meyer-Lindenberg, A., 2008. Know
your place: neural processing of social hierarchy in humans. Neuron 58, 273–283.
N. Daviu, et al. Neurobiology of Stress 11 (2019) 100191