Projection specificity in heterogeneous locus coeruleus cell populations: Implications for learning and memory

Abstract

Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory. This relatively small population of cells sends widespread projections throughout the brain including to a number of regions such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is important for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical, behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons respond during associative learning and when previously learned task contingencies change. Together, these studies suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection specificity.
© 2015 Uematsu et al.; Published by Cold Spring Harbor Laboratory Press.

Full text

Review
Projection specificity in heterogeneous locus coeruleus
cell populations: implications for learning and memory
Akira Uematsu,
1
Bao Zhen Tan,
1
and Joshua P. Johansen
1,2
1
RIKEN Brain Science Institute, Laboratory for Neural Circuitry of Memory, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan;
2
Department of Life Sciences, Graduate School of Arts and Sciences, University of Tokyo, Tokyo 153-8902, Japan
Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory.
This relatively small population of cells sends widespread projections throughout the brain including to a numberof regions
such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is impor-
tant for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but
it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical,
behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of
learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific
brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala
has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons
respond during associative learning and when previously learned task contingencies change. Together, these studies
suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning
functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general
framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection
specificity.
Learning and memory is critical to our survival as it facilitates
adaptive behavioral decision-making. Depending on the circum-
stances, different types of behavioral memories are formed and
sometimes these memories require alteration to match a con-
stantly changing environment. The process of forming and main-
taining associative behavioral memories or flexibly altering
behavioral strategies when task demands change recruits partially
separable neural circuits in the amygdala and medial prefrontal
cortex (mPFC), respectively (LeDoux 2000; Arnsten 2009). The
amygdala is important for emotional memory formation in which
sensory stimuli are associated with aversive (or rewarding) out-
comes to enable adaptive behavioral responses (Davis and
Whalen 2001; Johansen et al. 2011; Duvarci and Pare 2014;
Herry and Johansen 2014; Janak and Tye 2015; Tovote et al.
2015). In contrast, the mPFC is involved in cognitive flexibility
during learning, facilitating switches to new behavioral strategies
to optimize adaptive behavior (Arnsten 2009, 2011).
Noradrenaline neurons in the locus coeruleus (LC) have been
implicated in both emotional associative memory formation as
well as cognitive flexibility during learning (Berridge and
Waterhouse 2003; Aston-Jones and Cohen 2005; Arnsten 2009;
Sara and Bouret 2012). One hypothesis that has been proposed
is that noradrenaline action in amygdala engages more reflexive
adaptive behaviors while noradrenaline in mPFC facilitates cogni-
tive flexibility (Arnsten 2009). How LC noradrenaline neurons
regulate these different aspects of learning and memory is an
important open question. A commonly held view is that a homog-
enous population of LC neurons provides a common input to all
LC efferent targets including the amygdala and mPFC. According
to this view, the specificity of this homogeneous noradrenaline
signal would be controlled through its interaction with function-
ally distinct brain regions. Another possibility is that partially dis-
tinct populations of LC neurons project to the amygdala and
mPFC and that these heterogeneous LC cell populations directly
facilitate emotional learning or cognitive flexibility. This latter
scenario in which different populations of cells are defined, at
least partially, by their distinct efferent connectivity can be
termed projection or efferent specificity. Projection specificity is
apparent in Drosophila neuromodulatory networks where a num-
ber of studies have reported a high degree of connectional and
functional specificity in distinct populations of neuromodulatory
neurons (Liu et al. 2012; Waddell 2013). There is also evidence for
projection specificity in mammalian dopamine neurons in the
ventral tegmental area (Fallon 1981; Swanson 1982; Lammel
et al. 2014; Fields and Margolis 2015). To understand whether
LC-noradrenaline neurons exhibit projection specificity and
whether this has functional consequences for learning and mem-
ory we will first review anatomical, brain manipulation and neural
processing studies of LC. We will then integrate this information
into a hypothetical model of LC function during learning and
memory. We suggestthat distinct, heterogeneous pools of LC neu-
rons, based on their efferent connectivity, engage specific memo-
ry circuits depending on task requirements. This builds on
previous work (Chandler et al. 2014a,b), but examines this idea
in the context of functional neural circuits involved in specific
learned behaviors. The ultimate goal of this review is to assimilate
important information on LC function related to specific aspects
of learning and memory and to help generate hypotheses and
ideas for future study. We will focus on rodent and primate
work as studies in these species have provided a wealth of informa-
tion on noradrenaline circuits during learning and memory. For
Corresponding author: jjohans@brain.riken.jp
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ISSN 1549-5485/15; www.learnmem.org
444 Learning & Memory

excellent reviews on more general as-
pects of LC function see Berridge and
Waterhouse (2003), Aston-Jones and
Cohen (2005), and Sara and Bouret
(2012).
Anatomical connectivity and
efferent specificity in LC neurons
The LC consists of a small number of
NA containing neurons (1500 in the
rat, 15,000 in the human/hemisphere),
which project widely throughout the
brain and receive inputs from a diverse
array of brain regions. From the brain-
stem and midbrain, LC neurons receive
input from the reticular formation,
nucleus tractus solitarius, vestibular
nucleus, nuclei gigantocellularis and par-
agigantocellularis, and the periaqueduc-
tal gray conveying information about
visceral and sympathetic nervous system
function as well as pain and threat
(Cedarbaum and Aghajanian 1978; As-
ton-Jones et al. 1986; Van Bockstaele
et al. 1998a). Forebrain structures includ-
ing the dorsomedial, lateral, and para-
ventricular nuclei of the hypothalamus,
central nucleus of the amygdala, bed
nucleus of the stria terminalis, insular
cortex, and prefrontal cortex provide
complex emotional, homeostatic, and
cognitive information to LC neurons
(Cedarbaum and Aghajanian 1978; Arns-
ten and Goldman-Rakic 1984; Luppi
et al. 1995; Van Bockstaele et al. 1998b;
Reyes et al. 2005). The LC is also inter-
connected with various neuromodula-
tory brain regions including the ventral
tegmental area (dopamine) and dorsal
raphe (serotonin) (Palkovits et al. 1977;
Swanson 1982; Deutch et al. 1986; Orn-
stein et al. 1987). Together, these afferent
connections allow for modulation of LC
neural processing by basic sensory and
visceral experiences as well as regulation
by top-down influences from forebrain
structures conveying highly processed
cognitive/emotional information (Fig.
1A, see Berridge and Waterhouse 2003;
Aston-Jones and Cohen 2005; Sara and
Bouret 2012) for detailed anatomical ci-
tations of this work).
Despite the small number of neu-
rons in the LC, it projects broadly to most forebrain regions as
well as some midbrain and brainstem nuclei and the cerebellum
and spinal cord (for review, see Berridge and Waterhouse 2003;
Aston-Jones and Cohen 2005; Sara and Bouret 2012; Valentino
and Van Bockstaele 2015). Related to learning and memory, the
LC sends strong efferent projections to the amygdala (lateral,
basal, and central nuclei) and mPFC (Fallon et al. 1978; Arnsten
2009). Although the LC has traditionally been viewed as a homog-
enous population of cells (Fig. 1B), anatomical studies have dem-
onstrated some specificity in the projections of LC neurons. This
suggests a degree of anatomical (and possibly functional) hetero-
geneity. As an example of this, early studies using single retro-
grade tracer injections into different brain regions found some
limited topographical organization of LC efferents, with nonover-
lapping subregions of the LC projecting to distinct efferent targets
(Mason and Fibiger 1979; Waterhouse et al. 1983, 1993; Loughlin
et al. 1986). However, using this single retrograde tracer approach,
it is apparent that much of the LC contains cells, which project to
multiple brain regions. Thus, if there were cell heterogeneity
based on efferent targeting it would arise from intermixed popu-
lations of LC neurons. To adequately determine whether individ-
ual cells in an intermixed population project to specific brain
PAG
NTS
VN
PGi
Gi
LC
DMH/LH
CeA
BNST
IC
mPFC
VTA
DR
visceral and sympathetic information
emotional, homeostatic and cognitive information
neuromodulatory input
ACC
mPFC
OFC
Amy
LC
Thl
Hyp
MC
ACC
mPFC
OFC
Amy
LC
Thl
Hyp
MC
A
B
C
Figure 1. Afferent and efferent anatomical connectivity of the locus coeruleus (LC). (A) Afferent
inputs to the LC including those from the midbrain and brainstem (black), from neuromodulatory
areas (blue) and from forebrain regions (red). (B) Traditional view of LC efferent connectivity with a
single homogeneous population of LC neurons projecting widely throughout the brain. Note, the LC
projects to a wide array of brain regions and this figure does not include all efferent targets. (C)
Identified projection specificity in LC efferent connectivity (adapted from Chandler and Waterhouse
2012; Chandler et al. 2013, 2014a). Distinct subpopulations of LC neurons (individual populations
are colored) project to specific brain regions. (ACC) anterior cingulate cortex, (Amy) amygdala,
(CeA) central nucleus of the amygdala, (BNST) bed nucleus of the stria terminalis, (DMH/LH) dorsome-
dial and lateral hypothalamus, (DR) dorsal raphe, (Gi) nucleus gigantocellularis, (Hyp) hypothalamus,
(IC) insular cortex, (MC) motor cortex, (mPFC) medial prefrontal cortex, (NTS) nucleus tractus solitar-
ius, (OFC) orbitofrontal cortex, (PAG) periaqueductal gray, (PGi) nucleus paragigantocellularis, (VN)
vestibular nucleus, (VTA) ventral tegmental area.
Locus coeruleus in learning and memory
www.learnmem.org 445 Learning & Memory

regions, a combinatorial strategy using two or more retrograde
tracers is necessary. Using this type of approach, several studies
found a high degree of heterogeneity in LC neurons with respect
to their efferent connectivity. One study injected three different
fluorescent retrograde tracers into the orbitofrontal cortex
(OFC), mPFC, and anterior cingulate cortex (ACC) (Chandler
and Waterhouse 2012). Interestingly, largely nonoverlapping
cell populations projecting to these three regions were detected
in the LC. A related follow-up study found that these unique sub-
populations of LC neurons projecting to OFC, mPFC, and ACC
were also distinct from another population of LC neurons pro-
jecting to motor cortex (M1) (Fig. 1C; Chandler et al. 2014a).
Importantly, OFC and mPFC projecting LC neurons displayed a
different molecular profile from M1 neurons, expressing higher
transcript levels of proteins associated with glutamatergic trans-
mission and excitability. Moreover, in slice preparation studies
these cells were found to be more excitable and have higher base-
line firing rates compared with M1 neurons. This along with
prior studies demonstrating that subpopulations of LC noradren-
aline neurons coexpress different neurotransmitters (Berridge
and Waterhouse 2003) suggests that distinct classes of LC neu-
rons exhibit unique molecular identities along with projection
specificity.
Although the anatomical studies reveal that distinct LC neu-
rons project to specific brain regions, other studies using a variety
of anatomical approaches have found that LC neurons are homog-
enous and exhibit more collateralization in their efferent con-
nectivity (Nakamura and Iwama 1975; Nagai et al. 1981; Room
et al. 1981; Schwarz et al. 2015). It will be important in future
work to determine the degree of collateralization and specificity
individual populations of LC neurons exhibit in their efferent
connectivity. For example, the structures innervated by a given
subpopulation of LC cells may be governed by some functional
demand. Consistent with this, using a double retrograde tracer
approach one study found that subpopulations of LC neurons
send axon collaterals to the somatosensory thalamus and cortex,
but less to visual cortical/thalamic brain regions (Simpson et al.
1997). This suggests that functional demands may underlie the
connectivity and the degree of collateralization that individual
populations of LC neurons exhibit. Relating this to learning and
memory, it is possible that distinct classes of LC-noradrenaline
cells projecting to functionally distinct memory networks such
as the amygdala or mPFC (and functionally related regions) may
modulate specific forms of learning and memory.
LC noradrenaline neurons participate in emotional
associative learning and cognitive flexibility
While anatomical studies have revealed broad projections of LC
noradrenaline neurons and demonstrated some degree of projec-
tion specificity, the functional studies of LC have established the
causal importance of this system in various forms and aspects of
behavioral learning and memory. Many studies using neurotoxic
or electrolytic lesions of the LC or of the dorsal noradrenergic bun-
dle (a fiber bundle containing LC noradrenaline axons targeted to
specific forebrain targets) or LC specific pharmacological manipu-
lations have found effects on various aspects of learning and
memory including fear learning, extinction and reversal learning,
avoidance, and working memory (Mason and Iversen 1975;
Fibiger and Mason 1978; Plaznik and Kostowski 1980; Cole and
Robbins 1987; Tsaltas et al. 1989; Selden et al. 1990; Harris and
Fitzgerald 1991; Langlais et al. 1993; Neophytou et al. 2001;
Sears et al. 2013; Soya et al. 2013).
Although these studies suggest that LC neurons are impor-
tant in many different types of learning and memory one impor-
tant caveat is that some of the key findings have not been
replicated by other labs (Amaral and Foss 1975; Fibiger and
Mason 1978; Koob et al. 1978; Tsaltas et al. 1984, 1989; Selden
et al. 1990). It is possible that lesion technique, differences in
behavioral paradigms and/or compensation from spared nor-
adrenaline fibers, or receptor systems or even other neuromodula-
tory networks could have contributed to the variability in the
findings. Another possibility is that global manipulations of
many functionally distinct, possibly competing, LC neuronal sub-
populations could have produced variable or null effects on the
behavior. More precise anatomical, genetic and/or temporal ma-
nipulations may help to resolve these disparities in the literature
and offer important insights into LC function.
One way to more precisely study the involvement of LC-
noradrenaline in distinct aspects of learning and memory is to
manipulate adrenergic receptor signaling or LC fibers in specific
brain regions. Using this approach the role of noradrenaline in
the lateral and basal nuclei of the amygdala (LA/B) has been
examined. The LA/B is an important site of plasticity through
which sensory stimuli (auditory, visual, etc.) become associated
with aversive or rewarding outcomes to allow them access to
behavioral and visceral circuits involved in producing defensive
or reward-seeking behaviors (LeDoux 2000; Davis and Whalen
2001; Johansen et al. 2011; Duvarci and Pare 2014; Herry and
Johansen 2014; Janak and Tye 2015; Tovote et al. 2015). The aver-
sive form of this learning has been termed fear conditioning and
noradrenaline in the LA/B is particularly important for the acqui-
sition of fear memories. For example, injections of b-adrenergic
(b-AR) receptor antagonists into the LA/B reduce the acquisition
of fear learning (Fig. 2A; Bush et al. 2010). In contrast, intra-LA/
bantagonists given immediately following learning or before a
memory expression test have no effect on behavior. This suggests
that b-AR activation in this region is important during fear learn-
ing, but not necessary for consolidation or expression of fear
memories. Aversive footshock produces phasic activation of LC
neurons and increases in noradrenaline levels in the amygdala
(Galvez et al. 1996; Quirarte et al. 1998) which in turn modulates
the firing rate of LA/B neurons (Buffalari and Grace 2007; Chen
and Sara 2007). This suggests that phasic, footshock evoked acti-
vation of b-ARs on LA/B neurons could modulate fear learning.
These effects of noradrenaline in LA/B occur through noradrener-
gic modulation of Hebbian plasticity mechanisms (Johansen
et al. 2014) possibly by reducing feedforward inhibition and/or
through b-AR mediated modulation of calcium-dependent signal-
ing processes (Tully et al. 2007; Johansen et al. 2011). Once a fear
memory has been consolidated, recall of that memory places it
into a labile state (a process termed reconsolidation) where it
can be changed or disrupted through manipulation of specific sig-
naling pathways in LA neurons (Nader and Hardt 2009). In addi-
tion to amygdala noradrenaline involvement in fear memory
formation, intra-LA/Bb-AR blockade abolishes and stimulation
enhances fear memory reconsolidation (Debiec and Ledoux
2004; Debiec et al. 2011). In addition to its role in directly regulat-
ing plasticity mechanisms in the LA/B mediating fear learning,
adrenergic receptor activation in LA/B is important in modulating
hippocampal-dependent memories (McGaugh 2004; Berlau and
McGaugh 2006; Fiorenza et al. 2012). Overall, what is clear is
that noradrenaline in the LA/B is important for fear memory for-
mation and reconsolidation while also playing a role in modulat-
ing other forms of learning during the memory consolidation
period. It will be imperative in future work to determine whether
the LC is the functional source of noradrenaline to the amygdala
and how amygdala projecting LC neurons encode information
during fear learning and reconsolidation. It will also be important
to examine whether noradrenaline in the amygdala modulates
appetitive learning.
Locus coeruleus in learning and memory
www.learnmem.org 446 Learning & Memory

Although the amygdala and mPFC interact through recipro-
cal connectivity and some of their behavioral functions overlap
(Sotres-Bayon and Quirk 2010; Likhtik et al. 2014; Senn et al.
2014), the mPFC and noradrenaline in this region is thought to
be more important for behavioral flexibility, strategic planning,
and working memory (Arnsten 2009, 2011). For example, in con-
trast to its role in the acquisition of fear learning in the amygdala,
b-AR and a1-adrenergic receptor (a1-AR) activation in the infra-
limbic region of the mPFC is necessary for reversing fear and
reward-related behavioral memories when they are no longer ap-
propriate (see Fig. 2B for an example of these findings), a process
called extinction learning (Mueller et al. 2008; Do-Monte et al.
2010; LaLumiere et al. 2010). Supporting a role for mPFC nor-
adrenaline in regulating behavioral flexibility, noradrenaline
levels in the mPFC are increased during fear extinction training
(Feenstra et al. 2001; Hugues et al. 2007). In addition, a2-adrener-
gic receptors (a2-ARs) in the prelimbic region of the mPFC are in-
volved in working memory and reversal learning. Specifically,
a2-AR receptor activation in the prelimbic cortex is necessary
for optimal performance on a working memory version of the
T-maze task and readjustments of behavioral strategyfollowing er-
rors (Caetano et al. 2012). Furthermore, noradrenaline denerva-
tion of the mPFC results in reductions in reversal learning when
animals are faced with changes in task structure (McGaughy
et al. 2008; Newman et al. 2008). These types of cognitive deficits
are also evident in monkeys (for review, see Arnsten 2009). The ap-
parent deficits in reversal learning following manipulations of
noradrenaline in mPFC are consistent with theoretical ideas of
the role of noradrenaline in signaling “unexpected uncertainty”
(Yu and Dayan 2005) which occurs with contingency reversals.
Increases in tonic and reductions in phasic, task-related firing
rates in LC noradrenaline neurons has been suggested to favor ex-
ploratory, as opposed to task directed, behaviors to facilitate the
discovery of new optimal learning strategies (Aston-Jones and
Cohen 2005). This exploratory type of behavior could occur fol-
lowing contingency changes. Related to this, stimulation of LC
noradrenergic fibers in the mPFC during a complex decision-
making task produces stochastic/exploratory behaviorwhen goal-
directed decision-making is optimal (Tervo et al. 2014). In con-
trast, in animals that have been trained
to exhibit constant stochastic/explorato-
ry behavior, inhibiting LC terminals
in the mPFC produces a switch to an
optimal, goal-directed decision-making
strategy. Together, the available data sug-
gest that noradrenaline in the mPFC is
important in behavioral flexibility in-
cluding extinction and reversal learning.
Dynamic regulation of tonic and phasic
noradrenaline release in mPFC could fa-
cilitate behavioral flexibility and switch-
es to new, optimal behavioral strategies.
These studies on the role of LC
and noradrenaline in the amygdala and
mPFC demonstrate that noradrenaline
has distinct effects on specific aspects of
learning and memory depending on the
brain region it modulates. Based on this
and the fact that some LC-noradrenaline
cells have distinct connectivity with
their efferent targets it is possible that dif-
ferent subsets of LC neurons projecting
to amygdala or mPFC modulate either
the formation of emotional associative
memories or cognitive flexibility, respec-
tively. However, based on this data alone
it is also possible that the divergent effects of noradrenaline on
these different brain regions are governed by local processes with-
in the amygdala or mPFC and not by unique populations of LC
neurons. To properly address this question, modern anatomical
and cell type-specific manipulations including cell type-targeted
anatomical tracing approaches as well as opto- or chemogenetic
manipulations of anatomically defined neuronal populations
(Luo et al. 2008; Johansen et al. 2012; Tye and Deisseroth 2012)
are necessary. This would allow a determination of whether dis-
tinct LC cell populations project to amygdala and mPFC and
whether these cells are functionally dissociable.
Neural coding in LC neurons
The evidence for projection specificity and the differences in the
effects of noradrenaline manipulations in mPFC and amygdala
suggests that different populations of LC neurons may encode in-
formation in distinct ways depending on the brain regions they
innervate. This implies that LC neural codingshould be heteroge-
neous in some way and not uniform across the population of LC
noradrenaline neurons. While technical limitations have made
it difficult to measure neural activity from LC cells that project
to specific brain regions, many studies have examined the firing
properties of LC neurons in-vivo to elucidate their responsivity
to basic sensory events and understand how learning alters these
neural representations.
Noradrenaline neurons in LC have traditionally been charac-
terized as having low baseline firing rates (1 – 3 Hz) which is
modulated by wakefulness (see Berridge and Waterhouse 2003;
Aston-Jones and Cohen 2005; Sara and Bouret 2012 for reviews
of basic response properties of LC neurons). In addition, LC cells
are multimodal and respond to many different types of sensory
and visceral stimuli including aversive and rewarding outcomes.
The initial responses to sensory and visceral stimuli appear to
be somewhat uniform across all LC neurons suggesting homoge-
neity in processing these types of experiences. Interestingly, these
sensory and visceral-related responses are context dependent
and strongly regulated by learning and task performance. One
Figure 2. Examples of specific effects of noradrenaline manipulations in amygdala or medial prefron-
tal cortex (mPFC). (A)b-Adrenergic receptor (b-AR) blockade in amygdala reduces fear memory forma-
tion. When auditory cues are paired with aversive footshocks during training freezing responses develop
to the auditory cues providing a measure of fear. Intralateral amygdala (LA) injection of a b-AR antag-
onist (two different doses, 0.1 and 1.0 mg/side, x-axis) before fear conditioning reduces memory for-
mation (freezing, y-axis) measured at “Test” 48 h later (adapted from Bush et al. 2010). (B)b-AR
blockade in the infralimbic (IL) portion of the mPFC reduces extinction memory consolidation.
Following fear learning, repeated presentation of the auditory cue results in reduction of fear/freezing
responses (termed extinction learning). Intra IL injections of a b-AR antagonist before extinction learn-
ing reduces extinction memory consolidation as evidenced by higher freezing levels ( y-axis) upon cue
presentation 24 h after extinction training in the antagonist (propranolol) treated compared with the
vehicle (saline) treated group (adapted from Mueller et al. 2008).
Locus coeruleus in learning and memory
www.learnmem.org 447 Learning & Memory

example of this is that with repeated experience, LC neural re-
sponses to a variety of sensory stimuli are reduced, a process
termed habituation (Aston-Jones and Bloom 1981; Sara and
Segal 1991; Herve-Minvielle and Sara 1995). Importantly, habitu-
ation responses are not uniform across all LC cells (Sara and Segal
1991) suggesting that heterogeneity in neural coding can emerge
with experience during simple forms of learning. Later studies ex-
amined the firing properties of LC neurons during more complex
learning and memory tasks in which sensory cues or a combina-
tion of sensory stimuli and behavioral responses predicted aver-
sive or rewarding outcomes. Generally, these studies found that
LC neurons responded more to sensory cues predicting reward
or punishment (Rasmussen and Jacobs 1986; Sara and Segal
1991; Aston-Jones et al. 1994, 1997; Usher et al. 1999; Bouret
and Sara 2004; Rajkowski et al. 2004; Bouret and Richmond
2009). In some of these studies, a behavioral response was re-
quired following the sensory cue to achieve reward. Under these
circumstances, the sensory stimulus elicited modulation of LC
neural firing rate became better time-locked to the behavioral re-
sponse than to the sensory cue itself (Bouret and Sara 2004;
Rajkowski et al. 2004; Bouret and Richmond 2009). However,
this was not a purely behavior elicited change in firing rate as it
was not apparent when animals produced the same behavior in
the absence of the predictive cue (Bouret and Richmond 2009).
Importantly, while some studies reported homogeneity in the re-
sponse of LC neurons during these types of learning tasks, other
work suggested that distinct subsets of LC neurons encode reward
predictive sensory cues, task-related behavioral responses or both
(Bouret and Richmond 2009, 2015; Kalwani et al. 2014).
During contingency reversals or extinction, when task con-
tingencies change, the baseline or tonic firing rate of LC neurons
increases and the phasic, sensory cue elicited responses in LC neu-
rons eventually changes to reflect the new cue-outcome contin-
gencies (Sara and Segal 1991; Aston-Jones et al. 1997; Usher
et al. 1999). This increase in the tonic firing rate of LC neurons
is also evident when animals are performing poorly on a task.
Under these circumstances, this change in tonic firing rate is ac-
companied by a loss of phasic, task-related (sensory cue elicited
for example) responding (Usher et al. 1999) (but see Kalwani
et al. 2014). This suggests that during periods when animals are ei-
ther focused on other variables in the environment or when they
need to change their behavioral strategy, the firing mode of LC
neurons changes from sensory elicited, phasic firing mode to
heightened tonic activity. As discussed above, the change in tonic
and phasic firing modes of LC neurons has been proposed to facil-
itate exploratory or goal-directed behavior, respectively. Dynamic
changes in these firing modes could also facilitate switching
behavioral strategies during reversal or extinction learning.
In summary, LC neurons respond to a variety of sensory and
visceral stimuli and their response properties are modulated dur-
ing learning and memory tasks. Although it appears that LC cells
respond homogeneously to primary sensory and visceral experi-
ences, there is evidence for heterogeneity in LC neural responding
during learning that may reflect differential top-down control of
LC function. This could be implemented differentially in LC neu-
rons projecting to amygdala or mPFC. It will be critical in future
work to examine the neural coding properties of distinct subpop-
ulations of LC neurons during different learning and memory
tasks.
A hypothetical model of LC function during
learning and memory
Based on the evidence presented above including previous ana-
tomical/physiological studies showing projection specificity in
the LC system (Chandler and Waterhouse 2012; Chandler et al.
2013, 2014a) we propose a conceptual, hypothetical model of
LC function in which distinct subpopulations of LC noradrener-
gic neurons modulate specific aspects of learning and memory
based on their projection specificity. Specifically, we propose
that anatomically distinct populations of LC neurons project to
either the amygdala or mPFC (Fig. 3). Since noradrenaline in the
amygdala is involved in learning cue-aversive outcome associa-
tions and reconsolidating reactivated fear memories, we hypoth-
esize that amygdala projecting LC neurons are activated by
aversive outcomes and/or sensory predictive cues and that neural
activity during those time periods is important for the learning
and reconsolidation of emotional memories. In contrast, mPFC
projecting LC neurons may respond more during contingency
changes/reversals or extinction of cue/behavior-outcome contin-
gencies as noradrenaline in the mPFC appears to be important for
flexibility in learning under these conditions. In line with this we
propose that changes in sensory cue evoked or tonic neural activ-
ity in mPFC projecting LC neurons is important in regulating
changes in behavior during reversal learning and extinction. LC
neural subpopulations may function independently of one anoth-
er, with amygdala projecting cells being recruited solely during
emotional associative learning and mPFC projecting cells being
engaged when contingencies change or behavioral flexibility is re-
quired. However, emotional learning and changes or reversals in
learning are in many instances opposing processes. As a result,
an alternate possibility is that these distinct LC neural popula-
tions may function in parallel, but antagonistically during these
different forms of learning. Related to this, it is possible that differ-
ential coding across LC neuronal subpopulations does not occur
cue, context
LC
LA/B
mPFC
sensory cues/ behavioral context
LC
LA/B
mPFC
sensory cues aversive
outcome cue, outcome
Reversal/extinction learning
Emotional associative learning LC-NA neurons
excitatory inhibitor
y
unrecruited
A
B
Figure 3. Hypothetical projection specificity model of locus coeruleus
(LC) function during emotional associative learning (top) and reversal/ex-
tinction learning (bottom). On left, sagittal section of rat brain showing
medial prefrontal cortex (mPFC, pink) and amygdala (blue) projecting
LC neurons (adapted from Paxinos and Watson 1982). Insets on right
show coronal mockup of LC with mPFC (pink) and amygdala (blue) pro-
jecting cells corresponding to the blue and pink lines in the sagittal sec-
tions. Below this are the hypothesized extrinsic and intrinsic functional
connectivity (also depicted in the sagittal sections as inputs to LC),
which could modulate interactions between these cell populations.
Cells with dulled colors and dotted lines are those that are not engaged
or recruited during the specific behavioral paradigm. Note that “behavio-
ral context” and “context” refer to the learning context or state the
animal is in (examples include alterations in contingency, task focus,
etc.) which may or may not overlap with the physical environment.
Locus coeruleus in learning and memory
www.learnmem.org 448 Learning & Memory

through completely distinct coding strategies, but rather through
dynamic and more subtle shifts in the balance of task-related ac-
tivity across individual LC cell populations.
A potential advantage of projection specificity in the LC is
that it could allow for individual populations of LC neurons to
control broadly distributed efferent target circuits subserving a
distinct function (as suggested for LC innervation of somatosen-
sory versus visual system (Simpson et al. 1997)). For example, a
subpopulation of LC noradrenergic neurons may project to the
amygdala, but also send collaterals to other functionally related
brain regions to help coordinate activity across a distributed net-
work involved in forming or reforming emotional associative
memories. Another potential benefit to this type of anatomical ar-
rangement could be to facilitate local interactions between func-
tionally complementary or antagonistic neural subpopulations.
This could occur through local network interactions between
distinct cell populations in LC and/or through long range feed-
back connections from brain regions which receive input from
the LC (Fig. 3). These interactions could provide an on– off
switch for context dependent, dynamic regulation of functional-
ly/anatomically distinct cell modules. Supporting these ideas, lo-
cal connectivity as well as gap junction coupling between LC
neurons has been documented and many brain regions which re-
ceive LC noradrenaline innervation send direct or indirect projec-
tions back to LC (Aghajanian et al. 1977; Egan et al. 1983; Ennis
and Aston-Jones 1986; Christie et al. 1989; Christie and Jelinek
1993; Travagli et al. 1995; Ishimatsu and Williams 1996; Alvarez
et al. 2002). To examine this hypothesis, future studies should
determine how distinct LC neuronal populations are interconnec-
ted locally and through long range connectivity. This would then
allow a determination of the functional importance of theseinter-
connections for neural processing in distinct LC neuronal mod-
ules and behavior during learning and memory tasks.
Despite evidence for this model and for the importance of
projection specificity in the LC noradrenaline system, there are
still many open questions. For example, it hinges on the idea
that different subpopulations of LC neurons project to amygdala
and mPFC and that they serve distinct functions during different
types of learning. However, there are many studies which report
highly collateralized projection patterns of LC neurons (Naka-
mura and Iwama 1975; Nagai et al. 1981; Room et al. 1981;
Schwarz et al. 2015) and it is not clear whether specific subpopu-
lations of cells project to these regions or even, more generally,
whether distinct behaviorally functional subclasses of LC neurons
exist. Furthermore, this model may be too general. For example,
the mPFC is composed of functionally independent subregions
(infralimbic, prelimbic, and pregenual anterior cingulate cortices)
and it is possible that distinct populations of LC noradrenaline
neurons project to these different subregions. Even if there are dis-
tinct anatomically/genetically defined cell classes within LC, it is
possible that they do not perform unique neural processing func-
tions in the adult animal. For example, efferent-specific LC neuro-
nal populations may function to guide distinct developmental
processes occurring in different LC projection target regions, but
operate homogeneously after development. A final alternate pos-
sibility is that projection specific cell populations may receive the
same inputs and function identically with respect to their spiking
output, but might co-express and deliver distinct neurotransmit-
ters to their target structures.
To adequately test this model will require a multilevel ap-
proach utilizing cutting edge anatomical, neuronal recording,
optogenetic, and behavioral techniques. This type of experimen-
tal approach could be used to determine whether specific anatom-
ically and/or genetically defined populations of LC neurons
project to the amygdala and mPFC and participate differentially
in different aspects of learning and memory. Testing the function-
al role of the different cell populations for behavior will be the
most important goal as this can guide experimental interpretation
and design in anatomical and cell recording studies. If distinct
LC cell populations are differentially involved in behavior then
it will be important to examine whether LC cell subpopulations
receive distinct afferent inputs from different brain regions and/
or cell types within those regions. As discussed above, it will
also be important to catalog the broad efferent connectivity of in-
dividual LC cell populations. This is because unique connectivity
patterns in subpopulations of LC neurons may regulate distribu-
ted, but functionally related, brain circuits. It will also be essential
to determine how anatomically or genetically identified popula-
tions of LC neurons encode information during learning and
memory tasks. Studies such as these could reveal unique neuronal
coding strategies in individual LC cell populations.
This working model and technical approach offers a poten-
tially important framework for studying other aspects of LC func-
tion or even other neuromodulatory systems. LC noradrenaline
neurons innervate most of the brain and participate in many func-
tions outside of learning and memory. Understanding the ana-
tomical and functional heterogeneity of LC neurons and how
these cells interact during different experiences could help to
define a unitary function of this important neuromodulatory
system. It appears that other neuromodulatory circuits such as
tegmental dopamine neurons as well as other nonmodulatory
brain regions also exhibit projection specificity. Understanding
projection specificity in the LC could provide important insights
into what may be a general anatomical and functional organiza-
tional theme across neuromodulatory and other brain regions.
Acknowledgments
We thank Thomas McHugh and Tamas Madarasz for helpful com-
ments on the manuscript. This work was supported by grants
to J.P.J. from the Strategic Research Program for Brain Sciences
from the Ministry of Education, Culture, Sports, Science and
Technology (11041047) and Grants-in-Aid for Scientific Research
on Innovative areas and Kiban B (25710003, 25116531), a grant
to A.U. from Grants-in-Aid for Young Scientists B (26750380),
a RIKEN Special Postdoctoral Researcher Fellowship (SPDR)
A.U. and a RIKEN Foreign Postdoctoral Fellowship (FPR, 55800)
to B.Z.T.
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Received April 23, 2015; accepted in revised form June 22, 2015.
Locus coeruleus in learning and memory
www.learnmem.org 451 Learning & Memory