REVIEWS
Finding the engram
Sheena A. Josselyn1–4, Stefan Köhler5,6 and Paul W. Frankland1–4

Abstract | Many attempts have been made to localize the physical trace of a memory, or
engram, in the brain. However, until recently, engrams have remained largely elusive. In thisReview, we develop four defining criteria that enable us to critically assess the recent
progress that has been made towards finding the engram. Recent ‘capture’ studies use novel
approaches to tag populations of neurons that are active during memory encoding, thereby
allowing these engram-associated neurons to be manipulated at later times. We proposethat findings from these capture studies represent considerable progress in allowing us toobserve, erase and express the engram.
Neuronal ensembles
Collections of neurons thatshow coordinated firing
activity, equivalent to the cell
assembly defined by Hebb.

Program in Neurosciences &Mental Health, The Hospitalfor Sick Children (SickKids),
555 University Avenue,
Toronto, Ontario M5G 1X8,
Canada.
2
Department of Psychology,
University of Toronto, 100 St.
George Street, Toronto,
Ontario M5S 3GM, Canada.
3
Department of Physiology,
University of Toronto, 1 King’s
College Circle, Toronto,
Ontario M5S 1A8, Canada.
4
Institute of Medical Science,
University of Toronto, 1 King’s
College Circle, Toronto,
Ontario M5S 1A8, Canada.
5
Brain and Mind Institute,
University of Western
Ontario, Natural Sciences
Centre, London, Ontario N6A
5B7, Canada.
6
Department of Psychology,
University of Western
Ontario, London, Ontario
N6A 5C2, Canada.
e‑mails: sheena.josselyn@
sickkids.ca; stefank@uwo.ca;
paul.frankland@sickkids.ca
doi:10.1038/nrn4000
1

Memories are thought to be encoded as enduring physi­
cal changes in the brain, or engrams1,2. Most neuro­scientists agree that the formation of an engram involves
strengthening of synaptic connections between popula­tions of neurons (neuronal ensembles). However, charac­terizing the precise nature and location of engrams has
been challenging. Lashley was among the first to attempt
to localize engrams using an empirical approach3,4.
Famously, his search proved unsuccessful, and his con­clusion — that the engram is elusive — became widely
influential5–8. Today, we appreciate that this elusivity wasdue, at least in part, to the sparse, widely distributed anddynamic nature of memory representations in the brain,
making engrams challenging to identify using traditional
scientific methods.
However, new tools have recently been developed thatprovide unprecedented opportunities to visualize andmanipulate specific brain regions and cell populations. In
particular, molecular and transgenic methods in rodents
now allow neurons that were active at the time of learning(engram encoding) to be captured and tagged for later
manipulation. In this Review, we develop four criteria fordefining the engram and use them to evaluate whether
recent studies have indeed uncovered the engram. We
group the evidence on the basis of the type of experimen­
tal approach used, and discuss the advantages and limita­
tions of each approach. We propose that findings fromrecent experiments have gone a considerable way towards
satisfying these engram-defining criteria and, therefore,
towards finding the engram.

Defining the engram
Memory is the capacity of an organism to acquire, store
and recover information based on experience. The term
engram was introduced by Semon more than 100 years
ago1,2 (BOX 1) and refers to the physical substrate ofmemory in the brain. Semon suggested that an engram
has four defining characteristics9 (FIG. 1). First, an engram isa persistent change in the brain that results from a specificexperience or event. Second, an engram has the potential
for ecphory; that is, an engram may be expressed behav­
iourally through interactions with retrieval cues, which
could be sensory input, ongoing behaviour or voluntary
goals. Third, the content of an engram reflects what tran­spired at encoding and predicts what can be recovered
during subsequent retrieval. Fourth, an engram may exist
in a dormant state between the two active processes of
encoding and retrieval. That is, an engram exists beyond
the operations and processes required to form andrecover it. Therefore, an engram is not yet a memory but
provides the necessary physical conditions for a mem­ory to emerge10. Here, we use these four defining criteria— persistence, ecphory, content and dormancy — toevaluate whether recent studies have found the engram.
The prevailing view is that the formation of anengram involves strengthening of synaptic connections
between populations of neurons that are active during
encoding, leading to the formation of a neuronal ensem­
ble11–14. This increase in synaptic strength between
neurons increases the likelihood that the same spati­
otemporal pattern of neural activity that occurred dur­ing encoding will be recreated at a later time (retrieval).
Engrams need not be confined to a single brain region,
but rather may be composed of widely distributed net­
works of neuronal ensembles. Nonetheless, the building
blocks of the engram may be studied at smaller scales.
For example, experience-induced epigenetic changes atthe level of the nucleus, increases in synaptic strengthand changes in neuronal excitability have been probed
to investigate the cellular and subcellular componentsthat may contribute to the formation and maintenanceof an engram. Recent progress in finding the engram

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REVIEWS
Box 1 | Origin of the term engram
The term engram was introduced by Semon (1859–1918), a German scientist who
wrote two books on human memory9. Semon made several important, albeit often
overlooked, contributions to the understanding of how memories are formed, stored
and retrieved. To avoid confusion with the vernacular, Semon called for precise
scientific nomenclature in describing memory representations and processes.
Specifically, he introduced two terms, engram and ecphory, that remain influential
today. He defined an engram as “…the enduring though primarily latent modificationsin the irritable substance produced by a stimulus…” (REF. 1). Ecphory was defined by
Semon as the process which “…awakens the mnemic trace or engram out of its latentstate into one of manifested activity…” (REF. 1). As such, the engram can be consideredsimilar to a memory trace (and engraphy is the process used to form the engram),
whereas ecphory is similar to memory retrieval. Although originally introduced anddefined by Semon, it is Lashley (1890–1959) who popularized the term engram. In aseries of related experiments that spanned over three decades, Lashley attempted to“find the locus of specific memory traces” (REF. 4). Lashley cited Semon on two
occasions143,144 but failed to credit Semon for introducing the term engram in his
famous treatise The Search for the Engram.

has been fuelled in particular by advances in experi­mental techniques that allow investigation at the levelof neuronal ensembles.
It is also important to note that the engram is notstatic. Following encoding, consolidation processes mayalter the physical and chemical organization of engrams,
which may alter an engram in terms of strength andquality 7. Although consolidation implies a process offixation or stabilization, engrams can be dynamic15. For
instance, memory retrieval may transiently destabilizea previously consolidated engram and initiate a newconsolidation cycle (that is, reconsolidation; see BOX 2)that can lead to further changes in the engram16,17 (FIG. 1).
Although the engram is a moving target over time, thischaracteristic does not preclude tractability and successin capturing the engram at any given moment in time.
Finally, different types of memory may be supported
by engrams in distinct collections of brain regions. Here,we consider studies examining a range of memory types,
in multiple species, but emphasize studies in rodents
with a primary focus on memory functions that are
mediated by the hippocampus and amygdala (that is, themedial temporal lobe). This is not to suggest that these
are the only studies that have sought the engram. For an
overview of other engram literature, see BOX 3.

Consolidation
The transformation of engramsfrom an initially labile state (inwhich they are vulnerable todisruption) to a morepermanent state (in which they
are resistant to disruption).

Observing the engram
Observational studies have been designed to exam­
ine experience-induced changes in neural substrates(at the level of molecules, synapses, neurons, neuronalensembles, and/or brain circuits and networks) that may
reveal the location of the engram. Ramón y Cajal wasamong the first to articulate specific ideas about how andwhere experience-induced changes might be observed at
the level of the neuron. Although he believed that the
number of neurons was fixed after development, hemaintained that the connections between neurons weremodifiable by experience, a process he termed ‘cerebral
gymnastics’ (REF. 18). Furthermore, Ramón y Cajal cor­
rectly hypothesized that the protrusions he observedin neurons (dendritic spines) represented the con­nection points with axon terminals and proposed thatexperience-induced modifications would occur atthese points, which were later identified as synapses19.
Evidence for the idea that experience changes neuronalmorphology followed swiftly, as studies reported changes
in dendritic spine number and shape following several
interventions, including electrical brain stimulation20,21.
Ramón y Cajal’s influential ideas that experience sculpts
the brain by modifying connections between neurons
were subsequently championed by the Canadian psychol­ogist Hebb12,22. Hebb proposed that learning strengthened
the synaptic connections between neurons and thereby
facilitated the formation of neuronal ensembles (or, as
Hebb called them, ‘cell assemblies’). These neuronalensembles are thought to comprise collections of neurons
that fire together at the time of learning and again at thetime of memory retrieval. As such, they were proposed
as a neural substrate for the engram.
Decades later, empirical studies established thatenvironmental enrichment 23, learning 24 and inductionof long-term potentiation25,26 alter brain structure at
the level of spine morphology. Beyond changes in den­dritic spines, other persistent learning-induced changes
in neurons have been characterized. These include
changes in DNA structure (histone modifications andDNA methylation27), post-translational modificationof kinases (for example, protein kinase Mζ (PKMζ)28
and α‑calcium/calmodulin-dependent kinase II(αCaMKII)29), activation of transcription machinery 30,31,
induction of immediate-early genes (IEGs) such as Fosand activity-regulated cytoskeleton-associated protein(Arc)32–34, phosphorylation and trafficking of recep­
tors35,36, alterations in synaptic strength35,37,38 and changes
in neuronal excitability 39 (FIG. 2).
Two themes emerge from these findings. First, learn­
ing-induced brain changes vary in their persistence.
Although some changes are fleeting (for example, phos­
phorylation of αCaMKII), others persist for longer peri­ods (for example, learning-induced alterations in synaptic
strength). At the extreme, experience-induced changes
in DNA structure may even be transmitted to future
generations40,41. Second, many of the learning-inducedchanges described above are inter-related. For example,
phosphorylation of αCaMKII enhances the function of
AMPA and NMDA receptors, which in turn leads to apersistent increase in synaptic strength42,43. This increasein synaptic strength between cells underlies the forma­tion of neuronal ensembles44. Therefore, although none ofthese changes alone constitutes the engram, they may benecessary for engram formation and, as such, can be used
to point to the location of an engram at any given time.
However, in the absence of experimental interven­tion, it is unclear whether any observed brain changes
following learning constitute an essential component of
the engram. Some post-learning changes in the brain
may reflect incidental aspects of the training experi­ence or ongoing cellular housekeeping processes thatare unrelated to memory formation or consolidation45.
Moreover, although observed experience-inducedchanges in the brain may be linked to encoding, they
do not necessarily predict subsequent retrieval success.
For instance, the induction of IEGs is tied to encoding

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REVIEWS
Neuron activity state
Low

Retrieval

Retrieval

Dormant

Engram state

ActiveEncoding

High

Neuronal
ensemble

Consolidation

Reconsolidation
Time

Figure 1 | The lifetime of an engram. The formation of an engram (encoding) involves strengthening of connections
between collections of neurons (neuronal ensemble) that are active (red) during an event. Consolidation further
strengthens the connections between these neurons, which increases the likelihood that thesameReviews
activity pattern
can beNature| Neuroscience
recreated at a later time, allowing for successful memory retrieval. During consolidation, the engram enters a mainly
dormant state. Memory retrieval returns the engram back to an active state and transiently destabilizes this pattern ofconnections. The engram may be restabilized through a process of reconsolidation and re-enter a more dormant state.
Therefore, an engram may exist in a dormant state between the active processes of encoding and retrieval required toform and recover the memory. In this way, an engram is not yet a memory, but provides the necessary conditions for amemory to emerge.

but has not been related directly to subsequent retrieval
success. Nevertheless, a subset of observational studies
convincingly show that some learning-induced brainchanges reflect what transpired during encoding andalso predict what will transpire during retrieval. Suchobservational studies can provide particularly compel­ling evidence with respect to the content criterion forengram identification.

ReplayRecapitulation ofexperience-induced patterns ofneuronal activity that occur
during sleep or awake rest
periods following anexperience.

Sharp wave–ripple
High-frequency neuraloscillations that occur in the
hippocampus during periods ofslow-wave sleep andbehavioural immobility.

Functional connectivity
Task-specific coordination ofactivity between different
elements (for example,
neuronal ensembles) withinneural systems.

Rodent multi-unit recordings and human fMRI studies. Observational approaches that address the content
criterion are perhaps best exemplified by activity replay
studies, which show that neuronal activity patterns that
occur during a particular experience reoccur at latertimes46. Rodent studies suggest that spontaneous reac­tivation of event-specific neural activity occurs during
brief high-frequency bursts in the hippocampus known
as sharp wave–ripple events47–49. Activity replay may beobserved while rats are actively engaged in a task, dur­ing rest periods after an experience50 or even when the
animal is sleeping and deprived of sensory input 51,52.
The strength of reactivation correlates with subsequent
memory expression53,54, and preventing replay by elec­
trically disrupting sharp wave–ripples following learn­
ing impairs subsequent expression of that memory 55–57.
These findings indicate that replay is essential for con­solidation of the engram. Further evidence suggests that
replayed sequences contain information about specificprior experiences58–62 and, moreover, that this firing
sequence also predicts future behaviour 53. For instance,
in a spatial alternation task in which rodents were trained
to remember past locations to guide future behaviour(that is, selection of a correct rewarded choice), sharpwave–ripple activity at the choice point was shown topredict future choices62. Finally, sensory cues related tothe training experience that are present in the environ­ment at later time points may act as a retrieval cue andinduce replay 63–66.
Functional MRI (fMRI) studies in humans also showthat neural activity patterns produced by an experience
may reoccur during either subsequent sleep67,68 or wake­
ful69 periods. Regions of the hippocampus that are active
during route learning have been found to be reactivatedduring subsequent slow-wave sleep, and the amount of
replay activity has been shown to be positively corre­
lated to successful retrieval of these routes the following
day 67. Importantly, event-specific activity patterns can beobserved at times that do not overlap with encoding or
retrieval and are therefore independent of external cues,
active memorization or retrieval attempts. Moreover,activity patterns can be specific for discrete events. For
example, in a paired-associate learning task, in which
specific pairings produced unique, identifiable activ­
ity patterns, accuracy of recall for each paired-associate
was predicted by its spontaneous reactivation frequency
in the post-learning resting state70 (see also REF. 71).
Furthermore, patterns of replay alter functional connectivity
between the medial temporal lobes and cortical structuresthat are involved in pertinent perceptual analyses during
encoding and retrieval72, and this connectivity is begin­ning to be understood at the level of neural oscillations.
Neural oscillations occur simultaneously at multiple fre­quencies, and emerging evidence from intracranial andelectroencephalogram scalp recordings suggests that

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REVIEWS
Cued fear conditioning
A form of Pavlovian
conditioning in which an
initially neutral conditioned
stimulus is paired with anaversive unconditioned
stimulus. Subsequent
presentation of theconditioned stimulus alone
induces a conditioned fear
response.

Contextual fear conditioning
A one-trial learning paradigm
that is hippocampus andamygdala dependent, in whichanimals are placed in a specificcontext and administered one
or a series of footshocks.

neural oscillations use a frequency- and phase-dependent
coding scheme that may represent information at a highlevel of specificity 73.
To a large degree, multi-unit recording studies inrodents and resting-state fMRI studies in humans suc­ceed in linking what transpired at encoding to what willtranspire at retrieval; as such, they provide evidence thatspecifically addresses the content criterion. Moreover,as activity pattern replay occurs at times remote fromthe initial experience (and after other experiences haveintervened), they also address the persistence criterion.
However, many, if not all, of the learning-induced changes
identified in these observational studies reflect different
stages of ongoing consolidation of the engram. Therefore,
in most observational studies (ranging from molecular tofunctional imaging studies), the engram is being observedin what could still be considered an active, rather thandormant, state (epigenetic changes may be an exception
to this, in that they may be observed while the engram islikely to be in a dormant state40,41).
Observing a dormant engram presents a particularchallenge. Processing of the engram — for example,
during consolidation — allows for its detection by theobservational methods described above. However,as the frequency of consolidation-related processes
declines with time, so too does the possibility of engram
detection. Indeed, replay events in rodents may be
detected up to 24 hours following an experience using
neurophysiological recordings47,63,74 but, at least withcurrent techniques, fall below detectable levels in thedays after that experience. This limits opportunities forobserving the engram at time points long after encoding.
Engram capture strategies. One solution to bridge this
temporal divide is to permanently mark those neu­rons that are active during encoding, thus allowing
the visualization of these neurons at time points after
initial consolidation, when the engram is more likely
to be in a dormant state. This temporal bridging has
been achieved using neuronal capture strategies, whichtake advantage of the observation that IEGs (such as
Fos, transcription factor zinc finger 268 (Zif268; also

Box 2 | Reconsolidation and the engram
Retrieving a memory transiently destabilizes the engram supporting that memory.
Although originally described in the 1960s145, interest in this process of reconsolidation
was revived in 2000 (REF. 138). In the latter study, rats underwent auditory
fear-conditioning training in which a footshock was paired with a tone. Twenty-fourhours later, rats were presented with the tone in the absence of a footshock in analternative context to retrieve the fear memory. Immediately after retrieval, rats
received intra-amygdala microinjections of the protein synthesis inhibitor anisomycin.
Upon subsequent presentation of the tone, the animals showed impaired auditory fear
memory, suggesting that memory retrieval destabilized the engram and that protein
synthesis is necessary for engram restabilization (or reconsolidation). Only thememories that are directly reactivated by this cue are sensitive to the amnestic effects
of protein synthesis inhibition146,147, and therefore memory impairments induced byblocking reconsolidation show high content specificity. However, the interventions
used to disrupt reconsolidation involve systemic or brain-region-wide interventions(typically drug injections) that do not specifically target putative engram neurons.
Therefore, at present, this approach lacks neural specificity and does not pinpoint thelocation of an engram beyond broad brain structures.

known as Egr1) and Arc) are induced by neural activ­
ity 75–79. Indeed, analysis of IEG expression has been
widely used to identify populations of active neurons
during memory encoding 33,80. However, IEG mRNAand protein levels return to baseline within minutes andhours, respectively, following induction.
To address this temporal limitation, transgenic mice
have been engineered that, rather than using expression
levels of the endogenous IEG itself to label neurons, use
the IEG promoter to drive transcription of a geneticallyencoded label such as green fluorescent protein (GFP)
or LacZ. This enables neuronal ensembles that wereonce active to be captured and permanently tagged81–83(FIG. 3). Various strategies have been used to restrict activ­
ity tagging to a particular time window. In the ‘TetTag’
method, tetracycline controls the capture of activatedneurons (using a self-activating tTA–TetO system), andthe window of activity tagging is opened by withdrawing
mice from a diet containing the tetracycline derivative,
doxycycline81. Another strategy (targeted recombinationin active populations (TRAP)) uses a tamoxifen-inducible
Cre recombinase (CreERT2) system, and the window ofactivity tagging is opened by systemically injecting micewith tamoxifen82,83. These capture studies have shown thatthe populations of neurons that are active during training
in memory tasks are also active during a recall test, sug­gesting that these neurons are part of the engram support­
ing this memory. For instance, TetTag mice were removed
from a doxycycline diet (to open the window of activity
tagging) before auditory cued fear conditioning such that
active neurons were tagged with LacZ. Several days later,mice were tested for memory recall. Neurons active dur­ing this recall test were assessed using immunohistochem­
istry for endogenously expressed ZIF268. The degree ofoverlap observed between basolateral amygdala neuronal
populations that were active during training (tagged with
LacZ) and recall testing (immunostained with ZIF268)
was above chance levels81. Similarly, subsets of neurons
in the hippocampus82,84,85 and cortex 84 that were activitytagged during contextual fear conditioning were reactivatedat above chance levels when that contextual fear memory
was later recalled.
As with many fMRI studies in humans86,87, theseengram tagging studies in rodents find correspondence
between neural activity during encoding and during
retrieval. Whereas in fMRI studies this correspondence
is observed at the level of brain regions or networks, inrodent tagging studies correspondence can be detected at
the level of the neuronal ensemble. Furthermore, because
tagged neurons may be observed throughout the brain
in the weeks following training, these studies may also
help to reveal the distributed and dynamic nature of theengram88. Indeed, patterns of neuronal reactivation thatare induced by retrieval change over time, with reduced
reactivation of tagged neurons at more remote time
points in some hippocampal subfields (for examples, see
REFS 82,84).
Two caveats are worth noting with respect to therodent capture-and-tag studies. First, although the pro­portion of neurons that were tagged at encoding and reac­tivated by retrieval exceeded chance, it was nonetheless524 | SEPTEMBER 2015 | VOLUME 16

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REVIEWS
Box 3 | Previous attempts to find the engram
From a historical perspective, there have been many other examples of attempts tolocalize to engrams in addition to those described in this Review. These attempts haveused several different approaches, searched in many parts of the brain and focused on
many different types of behaviour. Notable, though definitely not exhaustive, examples
include O’Keefe and Dostrovsky96 who used electrophysiological recordings to identify
hippocampal cells that stably respond to specific environmental locations andtherefore provide the basis not only for navigating, but also for recognizing andremembering, previously encountered environments148. Using similar techniques, otherresearchers studied how neuronal activity changes during Pavlovian conditioning, inwhich initially neutral discrete stimuli (for example, a tone; the conditioned stimuli)
acquire motivational salience by virtue of being paired with appetitive or aversive
stimuli (the unconditioned stimuli) (for example, see REFS 13,149–151). For example,
Thompson and colleagues152 identified conditioned stimulus‑related neuronal activity
in a cerebellar circuit mediating the classical conditioning of an eyeblink response.
Lesioning this same locus disrupted memory expression6. In fact, lesioning has been aparticularly influential technique used to localize brain structures that contain theengram for many different types of memory, across many species (for example, see
REFS 97,153–155). Neurophysiological approaches have also included probing reduced
or increased responsiveness to a learned stimulus (including repetition suppression156),
persistent firing during a memory delay157 and cued activation of cells158,159. In humans,
attempts to find the engram historically took advantage of neurophysiologicalrecordings73,160 and lesion studies94,161,162, but perhaps the most prevalent techniqueused today to localize the engram in humans is functional neuroimaging163.

surprisingly low (<10% of tagged neurons were reacti­
vated)81,82,84,85. Previous studies using alternative labelling
strategies (for example, cellular compartment analysis of
temporal activity by fluorescence in situ hybridization(catFISH)) reported reactivation rates as high as ~40%in the CA1 region of the hippocampus80. The low reac­tivation rate observed in tagging studies might reflectengram contraction (that is, a reduction in the size ofneuronal population in the engram following encod­ing)89,90. However, because the duration of the tagging
window (hours to days) greatly exceeds the duration oftraining experience (typically minutes), it is more likelythat these protocols overestimate the size of the encod­
ing population for the experience of interest (‘over-tag­ging’) because neurons active in the hours or days before
and/or after training might be unintentionally tagged.
Second, as is true for all of these observational studies,
the evidence is correlational. Thus, tagging alone does notindicate whether identified neurons are necessary and/or sufficient for memory expression and therefore does
not address the criterion of ecphory. However, ecphory
may be assessed by selectively manipulating these tagged
neuronal populations.

Cyclic AMP-responsive
element-binding protein(CREB). A transcription factor
that, when activated, results inthe expression of downstream
proteins thought to beimportant for long-term
memory.

Erasing the engram
Nonspecific lesion studies. Erasure studies are designed
to chronically remove or to acutely inhibit a necessarycomponent of the engram to prevent its reactivation andsubsequent memory expression. Early erasure experi­ments attempted to find the engram by nonspecificallylesioning various brain regions in rodents. In a seminal
study, Lashley and Franz3 used this strategy but failed tofind the engram. Rats were trained to navigate a maze toobtain food, and different parts of the cortex were sub­sequently ablated using heat (thermocautery) or knife
cuts. Animals showed memory impairment only afterlarge cortical lesions irrespective of location. This led
to the conclusion that the engram is not localized in a
discrete cortical region but instead is widely distributed.
This concept continues to resonate today, particularly
in studies focused on understanding the organization ofmemory in the brain at the network level (for example,
see REF. 91).
However, these pioneering studies had limitations.
In most of these experiments, memory for a spatial
task was assessed in rats that were trained extensively,
and recent findings indicate that memories producedby over-training are less prone to disruption by brain
lesioning than memories produced by moderate train­
ing 92,93. Furthermore, although it was not known at thetime, it is now appreciated that there are multiple mem­ory systems94,95 and that the hippocampus, in particular,
has an essential role in the formation and maintenanceof spatial memory 96,97. In the rat brain, the cortex lies
just dorsal to the hippocampus, and a re‑examination of
Lashley’s data has led to the suggestion that the degree ofmemory impairment observed in his classic experiments
may correspond to (unintended) hippocampal damage
produced only by large cortical lesions98.
Although modern techniques produce more local­
ized, neuron-specific lesions, such approaches do nottarget specific neuronal ensembles (that is, the collec­
tion of neurons that might correspond to the engram).
Instead, an optimal strategy would be to lesion only thoseneurons involved in a given engram, leaving other neu­rons unaffected (BOX 4). By identifying neurons that wereactive during encoding of a given experience, current
capture strategies allow this to be achieved. Two primarycapture strategies that allow for specific manipulation(ablation, silencing or activation) of engram neurons
at later time points (‘allocate-and-manipulate’ and ‘tagand-manipulate’) have been developed. Crucially, bothare based on the premise that neurons that are active
during memory encoding are likely to become part ofthe engram supporting that memory.
Allocate-and-erase strategies. Previous findings haveshown that, during a training experience in mice, indi­vidual neurons with relatively high expression levels of
the transcription factor cyclic AMP-responsive elementbinding protein (CREB) are selectively recruited, or allo­cated, into a resulting engram99,100 (FIG. 4). In these initialstudies, CREB was virally overexpressed before training
in a small, random subset (~15%) of pyramidal neurons
in the lateral amygdala (LA), a structure known to beimportant in auditory fear conditioning 13,101–103. Using
Arc mRNA expression as a marker of a recently active
neuron80, it was found that neurons with higher CREB
activity at the time of training were more likely, thantheir neighbours with lower CREB activity, to be active
during memory retrieval, suggesting that higher levelsof CREB activity mediate allocation to the engram8,104.
Although this effect was initially described in the LA
for auditory fear memory, it has also been observedin the LA during encoding of conditioned taste aver­sion 105 and encoding of cocaine-conditioned place
preference106 memories, in the insular cortex during

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REVIEWSb Populationa Network

c CellBrainregion
PrL

ACC

Spine

NeuronLAd Synapse

e Nucleus

Synaptic
vesicleCa2+

Intracellularsignalling molecule

Receptor

NeurotransmitterDNA
Histonemodiﬁcation

Transcriptional
machinery
HistoneNatureengrams
Reviewsare| Neuroscience
Figure 2 | Multiple levels of analysis of an engram. Althoughthought toinvolve strengthening of connections between neurons (neuronal ensembles) widelydistributed throughout the brain, the engram can be probed at different scales and levelsof analysis. This schematic depicts the components of a hypothetical fear engram (shownin red) at different levels of analysis, from a brain network to a neuronal nucleus. a | At thebrain network level, a subset of brain regions may be involved in this engram. Red lines
depict functional connections between these engram brain regions. Cyan lines depict
underlying anatomical connections between brain regions. b | At the neuronal
population level, subsets of neurons within a brain region may be involved in this engram.
c | With the formation of each engram, changes occur at the level of individual neurons(for example, changes in the pattern of connectivity). d | Changes can also occur at
subsets of synapses (for example, synaptic strengthening). e | At the nuclear level, theengram can be reflected in transcriptional and epigenetic changes. ACC, anterior
cingulate cortex; LA, lateral amygdala; PrL, prelimbic cortex.

Designer receptors
exclusively activated bydesigner drugs(DREADDs). Engineered
G protein-coupled receptors
that are no longer activated by
the endogenous ligand but are
instead activated by otherwise
inert drug-like small molecules,
used to control G protein
signalling in vivo.

encoding of a conditioned taste aversion memory 107
and in the dentate gyrus (DG) during encoding of acontextual fear memory 108. Subsequent experiments
showed that neurons with higher CREB activity werepreferentially allocated to the engram because they
were more excitable than their neighbours105,108,109.
Indeed, increasing the excitability in populations of
LA neurons in the minutes before fear conditioning
using genetically encoded modulators of neuronal

activity — for example, by pharmacological activationof excitatory designer receptors exclusively activated bydesigner drugs (DREADDs)110 or light-induced activa­tion of opsins111 — also resulted in preferential alloca­
tion of these more active neurons to the engram109.
Experimentally increasing excitability in a subset ofneurons at the time of training may mimic and amplify
endogenous processes that occur during normal mem­ory encoding. Thus, during natural engram formation,neurons that happen to be more excitable at the timeof training are preferentially allocated to the resulting
engram109,112, an effect predicted by in silico modelling
data113.
Using these techniques to allocate and capture engram
neurons, the effects of post-training ablation of captured
neurons on subsequent memory retrieval have been
examined. In one study, mice in which a subpopulationof LA neurons overexpressed CREB underwent auditory
fear conditioning. When initially tested, mice showed
high levels of freezing to the auditory tone (indicating
intact tone-fear memory). However, selectively ablatingthese engram neurons (via a diphtheria toxin system)
after training decreased subsequent expression of thatfear memory114. After these engram neurons were ablated,mice were able to re‑learn this task normally, indicatingthat the decrease in freezing did not reflect a simple per­formance deficit. In addition, ablating a similar numberof non-allocated (that is, non-engram) neurons had noeffect on subsequent memory expression114. Moreover,
reversibly silencing (rather than permanently ablating)engram neurons in the minutes before a memory test
using an allatostatin receptor–ligand system also impaired
memory expression and, crucially, mice showed normal
tone-fear memory when these neurons were no longer
silenced105. This allocate-and-erase strategy has also beenused to disrupt the expression of conditioned taste aver­sion105,107 and cocaine-induced conditioned place prefer­ence106 memories. Therefore, using different methods tosilence allocated neurons, in various tasks, these allocateand-erase experiments show that it is possible to disrupt
the expression of a specific engram.
Tag-and-erase strategies. The tag-and-erase approachtakes advantage of activity-dependent neuronal tagging
strategies described above81–83,85 not only to tag active
neurons but also to express genetically encoded inhibi­
tors of neural activity (such as inhibitory DREADDs or
opsins). As with the allocate-and-erase techniques, thisallows captured engram neurons to be inhibited at latertime points. This strategy has been used to tag populationsof neurons in the DG82, CA3 (REF. 82) and CA1 (REF. 115)
regions of the hippocampus that were active during con­textual fear training in mice. Subsequent silencing of thesetagged engram neurons decreased the expression of thecorresponding contextual fear memory. Memory deficits
were observed days115 or weeks82 after training, indicatingthat these tagged neurons remained essential for memory
expression at these time points (FIG. 3). In addition to stud­ies of conditioned fear, a similar strategy has been used todisrupt the expression of memories of contexts associatedwith access to rewarding drugs116,117.

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REVIEWSa Encoding and tagging

b Storage

Layer I
Layer II
Layer III
Layer IV
Layer V
Layer VI

c Retrieval

CortexCeL
CeM
LA

ITC cells

Context 1

Home caged Opsin-induced inhibition

Freezing

AmygdalaFreezing

Dentate gyrus

Context 1

e Opsin-induced excitationLightstimulation

Untagged,inactive neuron

Context 1

Freezing

Freezing

Tagged, active
engram neuron
Tagged, inactive
engram neuron
Tagged, inhibitedengram neuron

Context 2

Figure 3 | The tag-and-manipulate approach to finding theengram. In this approach, transgenic mice are generated in which
neurons that are active during a memory-encoding event are captured
and tagged. Through the use of immediate-early gene promoters,
these tagged neurons express genetically encoded modulators ofneuronal activity (for example, inhibitory or excitatory opsins),
allowing them to be silenced or activated at later times.
a | During training for contextual fear conditioning, a mouse is placedin context 1 and given a footshock. This activates widely distributed
neuronal ensembles in the dentate gyrus, cortex and lateral amygdala(LA) and these engram neurons are tagged. b | Following training, miceare returned to their home cage (where they do not freeze). The
engram is consolidated, and tagged engram neurons become inactive.
c | When returned to context 1, the mouse shows conditioned fear

Reviews| Neuroscience(freezing behaviour), showing successfulNature
retrieval.
This successful
retrieval is associated with above chance reactivation of engram
neurons. d | If tagged neurons in the dentate gyrus are optogeneticallysilenced when the mouse is returned to context 1, then successful
memory retrieval is blocked, and mice show reduced conditioned fear.
Inhibiting engram neurons in the dentate gyrus is sufficient todecrease reactivation of tagged neurons in the cortex and amygdala.
e | Conversely, artificially activating tagged engram neurons in thedentate gyrus alone is sufficient to act as a memory retrieval cue suchthat mice now freeze in a third, unique context (context 2). Activating
dentate engram neurons is sufficient to induce reactivation of tagged
neurons in the cortex and amygdala. CeL, central nucleus of theamygdala lateral division; CeM central nucleus of the amygdala,medial division; ITC cells, intercalated cells.

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REVIEWS
Whereas other conceptually related approaches havebeen used to disrupt memory expression (BOX 2), thesecapture-and-erase experiments have made notable pro­
gress in finding the engram. Because the erasure experi­ments reveal that preventing reactivation of populationsof engram neurons interferes with subsequent memory
expression, they begin to address the ecphory criterion.
Moreover, as memory deficits were observed at time
points remote from initial encoding, these studies address
the persistence and dormancy criteria. Indeed, activationof the same population of neurons is necessary for suc­cessful memory retrieval weeks after encoding 82, at a time
when, presumably, the engram is in a dormant state.
Limitations of capture-and-erase experiments. Althoughthese capture-and-erase strategies offer improvements
over nonspecific lesion methods to localize and erase
the engram, they remain imperfect. For instance, manystudies capture and erase engram neurons in only one
brain region (such as the LA or a specific subfield of the
hippocampus), even though an engram may span mul­
tiple brain regions115, in line with Lashley’s idea that theengram is widely distributed4. Nonetheless, silencing
only a subpopulation of these putative engram cells in theLA105–107,114 or hippocampal subfields (in CA1 (REF. 115),
DG or CA3 (REF. 82)) was sufficient to impair subsequent
memory expression. These findings indicate that, within
what is probably a broad engram network, particular
neuronal populations within certain brain regions havemore critical roles in memory expression. Indeed, the LA
has been shown to be essential in motivationally relevant
memories, and the hippocampus has long been hypoth­esized to have a crucial role in retrieving contextual andspatial memory by reinstating training-like patterns ofneural activity across the cortex. Consistent with the ideathat neuronal ensembles in the hippocampus coordinate
retrieval of memories stored in the cortex 118–120, silenc­
ing tagged neurons in the CA1 both impaired memory
retrieval and reduced the reactivation of tagged corticalneurons during retrieval attempts115. Therefore, althoughengrams may involve interactions between neuronal pop­
ulations across multiple brain regions, these results indi­cate that there is a degree of specialization within theselarger networks. Graph theory analyses suggest that par­ticular regions in the brain that interact extensively withother regions within the overall engram network (thatis, hub-like regions) may have more prominent roles inmemory expression121,122.
In addition, the duration of capturing time windows
in both the allocate-and-erase and tag-and-erase stud­ies greatly exceeds the duration of training, leaving open
the possibility that both strategies ‘over-tag’ by captur­
ing neurons that are not part of that engram. Might theobserved memory deficits arise from ablating or silencing
these non-engram neurons? Thoughtful control studies
suggest not. In one example, researchers115 tagged CA1
neurons when mice were exposed to one environment
and then subsequently silenced these tagged neurons

Box 4 | The evolution of lesion techniques in the search for the engram

OpsinsLight-sensitive proteins thatchange their conformationfrom a resting state to asignalling state upon lightabsorption, used to excite or
inhibit neuronal populations
using light (that is,
optogenetics).

Graph theory
Graph theory is a branch ofmathematics used to compare
both global (for example, ‘small
worldness’) and local (‘hubs’)
properties of networks.

Progress in finding the engram is directly linked to tool evolution. Lashley and Franz3,4 first began their engram searchusing non-targeted lesions (thermocautery) that affected several brain regions and destroyed astrocytes,
oligodendrocytes and non-engram neurons as well as the intended target, engram neurons (see the figure). Because theselesions did not offer regional or cell-type specificity, there was substantial collateral damage. Ablation techniques thattargeted more discrete brain regions became available in the 1970s and 1980s, and were widely used in the search for theengram. These included
Region 1
Region 2
Region nelectrolytic lesions thattargeted one brain region
Non-targetedrather than many6,97.
ablation
However, these types oflesions damaged all cell
types (including glia) andfibres of passage.
Neuron-specific lesion
approaches (for example,
Targetedablation
ibotenic acid-induced
E.g. electrolytic
lesions) emerged next
lesionsbut, again, both engram
and non-engram neurons
were targeted. The
engram capture approach
Neuron-speciﬁcallowed engram-specificablation
neurons to be ablated andE.g. ibotenic acidwas first successfully
Engram neuronapplied in the search for
speciﬁc ablation
the engram in 2009
E.g. tag-and(REF. 114). In this way, themanipulate andability to find the engram
allocate-andmanipulate
was guided by the
specificity of the tools
Glial cell
Non-engram neuron
Engram neuron
available.
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REVIEWS
a Allocation

CeL
CeM

b Encodingc Retrieval

LA

ITC cells

Freezing

Freezing

AmygdalaContext 1

Home caged DREADD-induced inhibition

Context 1

e DREADD-induced excitation

Non-allocated,inactive neuron

Context 1

Freezing

Freezing

Allocated, active
engram neuron
Allocated, inactive
engram neuron
Allocated, inhibitedengram neuron

Context 2

Nature the
Reviews| Neuroscience
Figure 4 | The allocate-and-manipulate approach to finding the engram. In this approach,activityof a small
subset of neurons is increased at the time of memory encoding (through the use of viral expression of thetranscription factor CREB (cyclic AMP-responsive element-binding protein), excitatory DREADDs (designer
receptors exclusively activated by designer drugs) or optogenetic constructs), facilitating the allocation of theseneurons to the resulting engram. At any time after training, the activity of these allocated engram neurons can be
manipulated via the DREADD or optogenetic construct. a | During allocation, the activity of a subset of lateral
amygdala (LA) neurons is increased just before training in an auditory fear-conditioning paradigm. The mouse is thenplaced in context 1 and presented with a tone that co‑terminates with a footshock. Neurons made more excitable
are shown in pink. b | Neurons that are active during training (tone–footshock pairing) are allocated to a fear memory
engram in the LA (engram neurons, shown in red). c | Successful retrieval is associated with above chance reactivation ofengram neurons, and the mouse shows conditioned fear (freezing behaviour when the tone is replayed). d | Memory
retrieval is blocked by silencing tagged engram LA neurons, via inhibitory DREADD activation, and mice show reduced
conditioned fear (freezing) when the tone is replayed. e | Conversely, memory retrieval can be artificially induced by
activating tagged engram LA neurons. This activation is sufficient to act as a memory retrieval cue such that mice now
freeze in a unique context (context 2) in the absence of the tone. CeL, central nucleus of the amygdala lateral division;
CeM central nucleus of the amygdala, medial division; ITC cells, intercalated cells.

while the mice underwent fear conditioning in a second
environment, thereby preventing the previously tagged
neurons from becoming part of the contextual fear mem­ory engram for the second context. Silencing the neurons
tagged in the first environment had no effect on the sub­sequent expression of the contextual fear memory fromthe second environment. This indicates that silencing
components of one hippocampal engram does not affectexpression of another engram or, more generally, thatsilencing a subpopulation of neurons in the hippocampus
does not broadly disrupt processes required for memory
retrieval. Similarly, silencing neurons allocated to one
LA engram does not disrupt expression of another 105.
Therefore, the use of capturing strategies allows the

specific manipulation of one engram (which supports one
memory) rather than all engrams (and all memories), andthereby begins to address the content criterion.

Artificially expressing the engram
Typically, a memory emerges when the latent engram
is awakened by an external retrieval cue, the processof ecphory 1,2,10. Studies in both humans and animals
have revealed that engrams can also be awakened arti­
ficially by stimulating the neuronal components of theengram. During the surgical treatment of patients withepilepsy, Penfield found that focal electrical stimulationof the human brain could awaken latent engrams andartificially induce memory retrieval123. Although most

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REVIEWS
stimulation-induced experiential responses were vague,
some were specific (for contemporary examples, see
REFS 124,125). In this way, Penfield showed that it is possi­
ble to bring to mind past experiences by directly activating
the engram in the absence of an external sensory retrievalcue or internal retrieval attempt.
At first glance, these early findings satisfy several of
the criteria for engram identification. Stimulation led tomemory expression, which addressed the ecphory crite­
rion. Furthermore, in some instances, evoked memories
corresponded to events from the distant past, thereby
addressing the persistence and dormancy criteria.
However, there was no a priori way of predicting whichmemory would be evoked at any given stimulation site, alimitation that remains relevant to contemporary humanstimulation studies126. By using neuron capture strategies
to restrict activation to those neurons that were active
during encoding, present-day rodent studies build on
this tradition and begin to address the content criterion.

Pattern completion
The ability of a network to
retrieve stored information on
the basis of partial or degraded
input patterns.

Activating captured neurons. By combining allocation
or tagging methods with techniques that allow selec­
tive activation of neurons, modern-day rodent studies
can predict the content of a particular memory that will
be retrieved when a particular engram is stimulated. In
this way, a latent engram can be awakened by artificial
stimulation of captured engram neurons using excitatory
DREADDs or opsins in the absence of a retrieval cue.
For example, using a tag-and-manipulate strategy, DG
neurons that were activated by auditory fear conditioning
were tagged with channelrhodopsin 2 (ChR2) in mice85.
Over the next 5 days, the mice were placed in a familiar
context that had not been paired with a footshock, andfreezing behaviour was measured. Remarkably, when the
DG neurons that were active during initial fear condi­
tioning were transiently stimulated using light, mice froze
in this familiar context that had never been paired with afootshock. Interestingly, this artificially awakened memory
did not seem to undergo extinction over repeated test days.
This approach has also been used to reawaken an engram
for a rewarding event, in which male mice encountered afemale mouse127,128. Therefore, these and other 129 tag-andmanipulate studies show that experimentally reactivatingneurons that have been incorporated into an engram issufficient to act as a retrieval cue, similar to the nonspecificneural stimulation used in Penfield’s experiments.
Similar findings have been obtained from allocateand-manipulate studies in which a memory emerged
following artificial stimulation of allocated neurons109.
To allocate LA neurons to a fear engram, researchers
expressed an excitatory DREADD in a small random
population of neurons and administered the DREADD
ligand clozapine-N‑oxide (CNO) to activate these neurons
immediately before auditory fear conditioning. Artificially
activating these allocated engram neurons by administer­ing CNO in the days after training induced freezing ina novel context, whereas artificially activating a similarly
sized population of non-engram neurons did not.
Context-associated fear memories are thought todepend on a distributed hippocampal–cortical memory
trace88. Just as artificial stimulation of tagged DG neurons

was sufficient to induce freezing 85, stimulation of tagged
neurons in the retrosplenial cortex also resulted in fear­
ful behaviour 130. Presumably, this focal reactivation ofengram neurons in either the DG or the retrosplenialcortex triggered a broader pattern of reactivation acrossthe entire engram. Indeed, reactivating tagged retrosple­
nial cortex neurons activated other tagged neurons in the
amygdala and entorhinal cortex, in a manner similar to
the reactivation pattern produced by the natural external
retrieval cue (the conditioning context)130. These find­ings are consistent with Penfield’s assertion that focal
stimulation of a particular brain site produced a broader
reactivation of the engram in a process similar to patterncompletion131.
Criteria satisfied by artificial expression studies. Havethese artificial expression studies successfully trans­
formed latent engrams into expressed memories? We
think that the evidence is compelling. Stimulationof engram neurons in the examples described above
led to involuntary memory expression, addressing
the ecphory criterion. Moreover, memories could be
evoked at time points remote from encoding when thelikelihood that these engrams are being actively pro­
cessed is low, addressing the persistence and dormancy
criteria. However, is the expressed memory ‘real’? To
what extent do these studies satisfy the content crite­
rion? At first glance, artificial reactivation of captured
engram neurons and physical presentation of an exter­
nal retrieval cue seemed to be functionally equivalent,but in fact there were some differences. In particular, inmost experiments, the neurally reinstated behavioural
response was smaller in magnitude than the naturally
reinstated response, which was evoked by presentationof the external sensory cue85,109,127. At the psychologicallevel, memory retrieval is thought to be most success­ful when environmental and internal cues available atencoding are also present at the time of retrieval (thatis, the principle of encoding specificity 132). Similarly, atthe neural level, artificial reactivation of an engram islikely to be most successful for behavioural memory
expression when it faithfully recapitulates the patternof neural activity present at encoding 133. Of course,
artificial reactivation is not likely to recapitulate theprecise spatiotemporal activity pattern that accompa­
nied encoding. The loss of this fidelity may occur inthe spatial domain, temporal domain or both, leading
to less effective reinstatement and subsequently weaker
behavioural expression of the memory.
Another way to address this question is to ask whether‘artificial memories’ behave similarly to ‘real memories’.
Classical psychological studies emphasize that memory
is a constructive process134, with engrams being recon­
structed into memories in a use-dependent manner thatis influenced by the amount of pertinent detail available
and the individual’s current goals, among other factors.
Many types of memory errors described in the cognitive
literature support this notion135. Reconstruction may, inturn, lead to changes in the corresponding engram (thatis, the engram may be updated), including the formationof new associations with salient stimuli or events.

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REVIEWS
A recent study examined whether artificial activationof an engram could be associated with a new event andthereby create a false memory 136. In this study, active
neurons were captured while mice were exploring anovel context. These captured neurons were optogeneti­
cally reactivated while the mice underwent fear condi­
tioning in a second context. Remarkably, mice did notlearn to fear this second context but now froze whenplaced back in the original context that had never been
paired with shock, indicating that the experimentallyreinstated memory had been conditioned and a ‘false’
memory had been created. Taking this strategy one stepfurther, another group of researchers successfully cre­ated a false association between two distinct engrams inmice137. Hippocampal CA1 neuronal ensembles that wereactive while the animal was in a neutral context (that is, acontext not paired with shock) were labelled. Basolateral
amygdala neuronal ensembles that were active dur­ing footshock in a different context were also labelled.
Subsequent co‑activation of both engrams produced an
association between the two memories, such that freez­
ing now occurred in the neutral context that had notpreviously been paired with footshock.
The process of memory retrieval and reconstructionis thought to involve destabilization of the engram, fol­
lowed by a protein synthesis-dependent restabiliza­tion process (collectively termed reconsolidation)(BOX 2). For instance, in an auditory fear-conditioning
experiment, presenting the external retrieval cue (tone)
immediately before intra‑LA administration of the pro­tein synthesis inhibitor anisomycin disrupted recon­solidation, and the tone fear memory was no longer
expressed138. Might a neurally reinstated memory also
undergo reconsolidation? Intra‑LA administration ofanisomycin before artificial activation of engram neu­rons, in the absence of a retrieval cue, also disrupted
subsequent memory expression139. This suggests that
disrupting protein synthesis prevented the restabiliza­tion of a neurally reinstated engram, a finding similar
to that observed following reconsolidation blockadein traditional studies of memory. This susceptibility
to reconsolidation blockade provides evidence thatthe artificially expressed memory behaves like areal memory.
One cautionary note is that these artificial expression
studies so far have been limited to fear- and rewardconditioning paradigms. In these tasks, the behav­
ioural expression of memory is relatively impoverished(that is, limited to freezing or approach or avoidance
behaviour), and so it is not obvious whether the arti­
ficially expressed memory captures the full details of
the encoding experience (for example, beyond thefootshock or the presence of a female mouse). As such,
behavioural paradigms used in current research pose
limits for addressing the content criterion. One prom­ising avenue for future studies is to use more complex
tasks in which the details of the encoding experiencecan be probed more extensively. A potentially suitabletask, for example, is sequence learning in which correct
recognition of particular temporal sequences of events(for example, ordered presentations of odours A, B, C

and D) is reinforced140. As the temporal organization of
events is a defining feature of episodic memory 141,142,
such tasks might more closely probe ‘remembering
what transpired’ than conditioning paradigms, and morethoroughly address the content criterion than the studies
performed to date.

Conclusions
More than 60 years ago, Lashley conceded defeat in his
search for the engram. Here, we applied four engramdefining criteria to evaluate recent experimental evidence
from three types of studies that have attempted to findthe engram. Observational studies have been the mostsuccessful in addressing the content criterion. In rodent
multi-unit electrophysiological recording studies, pat­terns of neuronal activity that occurred during encoding
are detected at later time points, and these replayed pat­terns predict future behaviour. Perhaps with even greater
specificity at the content level, human fMRI studies haveidentified event-specific neural activity that occurs in the
period between encoding and retrieval and, furthermore,reflects what transpired at encoding and predicts successin subsequent retrieval.
Contemporary techniques in rodents that capture
neurons that are active at the time of encoding haveprovided a powerful new way of hunting for the engramand have been especially successful in addressing theother three criteria through the manipulation of spe­cific ‘engram neurons’. Erasure studies have shown thatsilencing engram neurons prevents memory expression,and thus establish that activation of these neurons isnecessary for successful retrieval. Conversely stimula­tion of these engram neurons has been used effectively
to induce artificial memory recovery, and thus establishthat their activation is sufficient for retrieval. Therefore,
these types of experiments may be the first line of evi­
dence that convincingly satisfies the ecphory criterion.
These studies show that it is possible to induce memory
expression, even without interactions with any external
retrieval cue or dedicated retrieval attempts, by directly
activating engram neurons. That these manipulations
are effective at time points remote from encoding, whenthe engram is likely to be dormant, additionally satisfies
the persistence and dormancy criteria.
To date, these capture strategies have only been
applied in fear- and reward-conditioning experiments.
In these paradigms, the behavioural readout is limited incomplexity, which makes it challenging to fully address
the content criterion. Nonetheless, these studies reveal
some content specificity by showing that capture strat­egies allow the erasure of a targeted engram, and notjust any engram. Similarly, activating captured neurons
leads to the artificial expression of the corresponding
memory, and not just random memories. Moreover,these artificially expressed memories share properties
with real memories in that they reconsolidate and canform de novo associations. In addressing each of the four
engram-defining criteria that were derived from the defi­
nitions originally offered by Semon1,2, not only can con­temporary rodent studies claim to have found the engram,but also have identified means to control it.

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REVIEWS
1.
2.
3.
4.

5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.

20.

21.
22.
23.
24.

25.
26.
27.
28.
29.
30.
31.

32.

Semon, R. The Mneme (G. Allen & Unwin, 1921).
Semon, R. Mnemic Psychology (G. Allen & Unwin,
1923).
Franz, S. I. & Lashley, K. S. The retention of habits by
the rat after destruction of the frontal portion of thecerebrum. Psychobiology 1, 3–18 (1917).
Lashley, K. S. in Society of Experimental Biology
Symposium, No. 4: Psychological Mechanisms in
Animal Behavior (eds Danielli, J. F. & Brown, R.)
454–482 (Academic Press, 1950).
Bruce, D. Fifty years since Lashley’s In search of theEngram: refutations and conjectures. J. Hist. Neurosci.
10, 308–318 (2001).
Thompson, R. F. The search for the engram. Am.
Psychol. 31, 209–227 (1976).
Dudai, Y. & Eisenberg, M. Rites of passage of theengram: reconsolidation and the lingering
consolidation hypothesis. Neuron 44, 93–100 (2004).
Josselyn, S. A. Continuing the search for the engram:examining the mechanism of fear memories.
J. Psychiatry Neurosci. 35, 221–228 (2010).
Schacter, D. L. Forgotten Ideas, Neglected Pioneers:
Richard Semon and the Story of Memory (Psychology
Press, 2001).
Moscovitch, M. in Science of Memory: Concepts (eds
Roediger, H. L. III, Dudai, Y. & Fitzpatrick, S. M.)
17–29 (Oxford Univ. Press, 2007).
Kandel, E. R. The Cellular Basis of Behavior (W. H.
Freeman, 1976).
Milner, P. M. The Autonomous Brain: A Neural Theoryof Attention and Learning (Psychology Press, 1999).
LeDoux, J. E. Emotion circuits in the brain. Annu. Rev.
Neurosci. 23, 155–184 (2000).
Bliss, T. V. & Collingridge, G. L. A synaptic model ofmemory: long-term potentiation in the hippocampus.
Nature 361, 31–39 (1993).
Nadel, L. in Science of Memory: Concepts (eds
Roediger, H. L., Dudai, Y. & Fitzpatrick, S. M.) 177–182(Oxford Univ. Press, 2007).
Dudai, Y. Neurobiology. The shaky trace. Nature 406,
686–687 (2000).
Nader, K. Memory traces unbound. Trends Neurosci.
26, 65–72 (2003).
Ramon y Cajal, S. The Croonian lecture: la finestructure des centre nerveux. Proc. R. Soc. Lond. 55,
444–468 (in French) (1894).
Ramon y Cajal, S. A quelle epoque apparaissent les
expansions des cellules nerveuses de la moëlle
épinière du poulet? Anat. Anz. 5, 609–613, 631–639(in French) (1890).
Stefanowska, M. Les appendices terminaux desdendrites cerebraux et leur differents etats
physiologiques. Ann. Soc. R. Sci. Med. Nat. Brux. 6,
351–407 (in French) (1897).
Stefanowska, M. Sur les appendices des dendrites.
Bull. Soc. R. Sci. Med. Nat. Brux. 55, 76–81 (inFrench) (1897).
Hebb, D. O. The Organization of Behavior: A
Neuropsychological Theory (Wiley, 1949).
Volkmar, F. R. & Greenough, W. T. Rearing complexity
affects branching of dendrites in the visual cortex of
the rat. Science 176, 1445–1447 (1972).
Moser, M. B., Trommald, M. & Andersen, P. An
increase in dendritic spine density on hippocampal
CA1 pyramidal cells following spatial learning in
adult rats suggests the formation of new synapses.
Proc. Natl Acad. Sci. USA 91, 12673–12675(1994).
Muller, D., Toni, N. & Buchs, P. A. Spine changes
associated with long-term potentiation. Hippocampus
10, 596–604 (2000).
Bosch, M. & Hayashi, Y. Structural plasticity ofdendritic spines. Curr. Opin. Neurobiol. 22, 383–388(2012).
Day, J. J. & Sweatt, J. D. Epigenetic mechanisms in
cognition. Neuron 70, 813–829 (2011).
Sacktor, T. C. How does PKMζ maintain long-term
memory? Nat. Rev. Neurosci. 12, 9–15 (2011).
Lisman, J., Schulman, H. & Cline, H. The molecularbasis of CaMKII function in synaptic and behaviouralmemory. Nat. Rev. Neurosci. 3, 175–190 (2002).
Silva, A. J., Kogan, J. H., Frankland, P. W. & Kida, S.
CREB and memory. Annu. Rev. Neurosci. 21,
127–148 (1998).
Josselyn, S. A. & Nguyen, P. V. CREB, synapses andmemory disorders: past progress and futurechallenges. Current Drug Targets CNS Neurol. Disord.
4, 481–497 (2005).
Guzowski, J. F. Insights into immediate-early genefunction in hippocampal memory consolidation
using antisense oligonucleotide and fluorescent

33.
34.
35.

36.
37.

38.
39.

40.

41.
42.
43.
44.

45.
46.
47.

48.

49.

50.

51.

52.
53.

54.

55.

56.
57.

imaging approaches. Hippocampus 12, 86–104(2002).
Horn, G. Pathways of the past: the imprint of memory.
Nat. Rev. Neurosci. 5, 108–120 (2004).
Horn, G. Memory, Imprinting, and the Brain: An
Inquiry into Mechanisms (Clarendon Press, 1985).
Whitlock, J. R., Heynen, A. J., Shuler, M. G. &Bear, M. F. Learning induces long-term potentiationin the hippocampus. Science 313, 1093–1097(2006).
Rumpel, S., LeDoux, J., Zador, A. & Malinow, R.
Postsynaptic receptor trafficking underlying a form ofassociative learning. Science 308, 83–88 (2005).
Rogan, M. T., Staubli, U. V. & LeDoux, J. E. Fearconditioning induces associative long-term
potentiation in the amygdala. Nature 390, 604–607(1997).
McKernan, M. G. & Shinnick-Gallagher, P. Fearconditioning induces a lasting potentiation of synaptic
currents in vitro. Nature 390, 607–611 (1997).
Oh, M. M., Kuo, A. G., Wu, W. W., Sametsky, E. A. &Disterhoft, J. F. Watermaze learning enhances
excitability of CA1 pyramidal neurons.
J. Neurophysiol. 90, 2171–2179 (2003).
Dias, B. G. & Ressler, K. J. Parental olfactory
experience influences behavior and neural structure in
subsequent generations. Nat. Neurosci. 17, 89–96(2014).
Graff, J. & Mansuy, I. M. Epigenetic codes incognition and behaviour. Behav. Brain Res. 192,
70–87 (2008).
Barria, A. & Malinow, R. NMDA receptor subunit
composition controls synaptic plasticity by regulating
binding to CaMKII. Neuron 48, 289–301 (2005).
Kristensen, A. S. et al. Mechanism of Ca2+/calmodulindependent kinase II regulation of AMPA receptor
gating. Nat. Neurosci. 14, 727–735 (2011).
Barth, A. L., Gerkin, R. C. & Dean, K. L. Alteration ofneuronal firing properties after in vivo experience in a
FosGFP transgenic mouse. J. Neurosci. 24,
6466–6475 (2004).
Dudai, Y. in Science of Memory: Concepts (eds
Roediger, H. L., Dudai, Y. & Fitzpatrick, S. M.) 13–16(Oxford Univ. Press, 2007).
Wilson, M. A. & McNaughton, B. L. Reactivation ofhippocampal ensemble memories during sleep.
Science 265, 676–679 (1994).
Kudrimoti, H. S., Barnes, C. A. & McNaughton, B. L.
Reactivation of hippocampal cell assemblies: effects of
behavioral state, experience, and EEG dynamics.
J. Neurosci. 19, 4090–4101 (1999).
Nadasdy, Z., Hirase, H., Czurko, A., Csicsvari, J. &Buzsaki, G. Replay and time compression of recurring
spike sequences in the hippocampus. J. Neurosci. 19,
9497–9507 (1999).
Karlsson, M. P. & Frank, L. M. Network dynamics
underlying the formation of sparse, informative
representations in the hippocampus. J. Neurosci. 28,
14271–14281 (2008).
Carr, M. F., Jadhav, S. P. & Frank, L. M. Hippocampal
replay in the awake state: a potential substrate formemory consolidation and retrieval. Nat. Neurosci.
14, 147–153 (2011).
A comprehensive review of neural replay studies inrodents, which describe how replay of patterns ofneuronal activity in wakefulness and sleep
contribute to memory retrieval and consolidation.
Skaggs, W. E. & McNaughton, B. L. Replay of neuronalfiring sequences in rat hippocampus during sleep
following spatial experience. Science 271,
1870–1873 (1996).
Ji, D. & Wilson, M. A. Coordinated memory replay inthe visual cortex and hippocampus during sleep. Nat.
Neurosci. 10, 100–107 (2007).
Dupret, D., O’Neill, J., Pleydell-Bouverie, B. &Csicsvari, J. The reorganization and reactivation ofhippocampal maps predict spatial memory
performance. Nat. Neurosci. 13, 995–1002 (2010).
Nakashiba, T., Buhl, D. L., McHugh, T. J. &Tonegawa, S. Hippocampal CA3 output is crucial for
ripple-associated reactivation and consolidation ofmemory. Neuron 62, 781–787 (2009).
Girardeau, G., Benchenane, K., Wiener, S. I.,
Buzsaki, G. & Zugaro, M. B. Selective suppression ofhippocampal ripples impairs spatial memory. Nat.
Neurosci. 12, 1222–1223 (2009).
Ego-Stengel, V. & Wilson, M. A. Disruption of rippleassociated hippocampal activity during rest impairs spatial
learning in the rat. Hippocampus 20, 1–10 (2010).
Jadhav, S. P. & Frank, L. M. Reactivating memories forconsolidation. Neuron 62, 745–746 (2009).

532 | SEPTEMBER 2015 | VOLUME 16

58. Johnson, A., van der Meer, M. A. & Redish, A. D.
Integrating hippocampus and striatum in decisionmaking. Curr. Opin. Neurobiol. 17, 692–697(2007).
59. Steiner, A. P. & Redish, A. D. Behavioral andneurophysiological correlates of regret in rat decisionmaking on a neuroeconomic task. Nat. Neurosci. 17,
995–1002 (2014).
60. Wu, X. & Foster, D. J. Hippocampal replay captures
the unique topological structure of a novel
environment. J. Neurosci. 34, 6459–6469 (2014).
61. Jadhav, S. P., Kemere, C., German, P. W. &Frank, L. M. Awake hippocampal sharp-wave ripples
support spatial memory. Science 336, 1454–1458(2012).
62. Singer, A. C., Carr, M. F., Karlsson, M. P. &Frank, L. M. Hippocampal SWR activity predicts
correct decisions during the initial learning of analternation task. Neuron 77, 1163–1173 (2013).
63. Karlsson, M. P. & Frank, L. M. Awake replay of remoteexperiences in the hippocampus. Nat. Neurosci. 12,
913–918 (2009).
64. Foster, D. J. & Wilson, M. A. Reverse replay of
behavioural sequences in hippocampal place cells
during the awake state. Nature 440, 680–683(2006).
65. Diba, K. & Buzsaki, G. Forward and reverse
hippocampal place-cell sequences during ripples. Nat.
Neurosci. 10, 1241–1242 (2007).
66. Davidson, T. J., Kloosterman, F. & Wilson, M. A.
Hippocampal replay of extended experience. Neuron
63, 497–507 (2009).
67. Peigneux, P. et al. Are spatial memories strengthenedin the human hippocampus during slow wave sleep?
Neuron 44, 535–545 (2004).
68. Maquet, P. et al. Experience-dependent changes incerebral activation during human REM sleep. Nat.
Neurosci. 3, 831–836 (2000).
69. Peigneux, P. et al. Offline persistence of memoryrelated cerebral activity during active wakefulness.
PLoS Biol. 4, e100 (2006).
70. Deuker, L. et al. Memory consolidation by replay ofstimulus-specific neural activity. J. Neurosci. 33,
19373–19383 (2013).
71. Staresina, B. P., Alink, A., Kriegeskorte, N. &Henson, R. N. Awake reactivation predicts memory inhumans. Proc. Natl Acad. Sci. USA 110,21159–21164 (2013).
72. Tambini, A., Ketz, N. & Davachi, L. Enhanced brain
correlations during rest are related to memory forrecent experiences. Neuron 65,
280–290 (2010).
A human fMRI study showing that patterns ofhippocampal–cortical connectivity after anassociative encoding task during rest are
task-specific and predict subsequent memory
performance for these associations at retrieval.
73. Watrous, A. J., Fell, J., Ekstrom, A. D. & Axmacher, N.
More than spikes: common oscillatory mechanisms forcontent specific neural representations during
perception and memory. Curr. Opin. Neurobiol. 31,
33–39 (2015).
74. Tatsuno, M., Lipa, P. & McNaughton, B. L.
Methodological considerations on the use of templatematching to study long-lasting memory trace replay.
J. Neurosci. 26, 10727–10742 (2006).
75. Greenberg, M. E. & Ziff, E. B. Stimulation of 3T3 cells
induces transcription of the c‑fos proto-oncogene.
Nature 311, 433–438 (1984).
76. Curran, T. & Morgan, J. I. Superinduction of c‑fos bynerve growth factor in the presence of peripherally
active benzodiazepines. Science 229, 1265–1268(1985).
77. Morgan, J. I. & Curran, T. Stimulus-transcription
coupling in neurons: role of cellular immediate-earlygenes. Trends Neurosci. 12, 459–462 (1989).
78. Link, W. et al. Somatodendritic expression of animmediate early gene is regulated by synaptic
activity. Proc. Natl Acad. Sci. USA 92, 5734–5738(1995).
79. Lyford, G. L. et al. Arc, a growth factor and activityregulated gene, encodes a novel cytoskeletonassociated protein that is enriched in neuronaldendrites. Neuron 14, 433–445 (1995).
80. Guzowski, J. F., McNaughton, B. L., Barnes, C. A. &Worley, P. F. Environment-specific expression of theimmediate-early gene Arc in hippocampal neuronalensembles. Nat. Neurosci. 2,1120–1124 (1999).
An elegant application of IEG technology to identify
neuronal ensembles coding different contexts.

www.nature.com/reviews/neuro© 2015 Macmillan Publishers Limited. All rights reserved

REVIEWS
81. Reijmers, L. G., Perkins, B. L., Matsuo, N. &Mayford, M. Localization of a stable neural correlate of
associative memory. Science 317, 1230–1233 (2007).
This study introduced the influential TetTag approachthat allows permanent labelling of neuronalensembles that are activated during fear memory
encoding. These authors showed that tagged
neurons were reactivated at above chance levels
when the corresponding memory is later recalled.
82. Denny, C. A. et al. Hippocampal memory traces aredifferentially modulated by experience, time, and adultneurogenesis. Neuron 83, 189–201 (2014).
83. Guenthner, C. J., Miyamichi, K., Yang, H. H.,
Heller, H. C. & Luo, L. Permanent genetic access totransiently active neurons via TRAP: targetedrecombination in active populations. Neuron 78,
773–784 (2013).
84. Tayler, K. K., Tanaka, K. Z., Reijmers, L. G. &Wiltgen, B. J. Reactivation of neural ensembles during
the retrieval of recent and remote memory. Curr. Biol.
23, 99–106 (2013).
85. Liu, X. et al. Optogenetic stimulation of a hippocampal
engram activates fear memory recall. Nature 484,
381–385 (2012).
The first example of an experiment using the
tag-and-manipulate approach to convincingly
demonstrate that stimulation of a fear memory
engram induces artificial memory expression in theabsence of external cues or internally guided
retrieval attempts.
86. Polyn, S. M., Natu, V. S., Cohen, J. D. & Norman, K. A.
Category-specific cortical activity precedes retrieval during
memory search. Science 310, 1963–1966 (2005).
87. Rugg, M. D., Johnson, J. D., Park, H. &Uncapher, M. R. Encoding–retrieval overlap in humanepisodic memory: a functional neuroimaging
perspective. Prog. Brain Res. 169, 339–352 (2008).
88. Frankland, P. W. & Bontempi, B. The organization ofrecent and remote memories. Nat. Rev. Neurosci. 6,
119–130 (2005).
89. Komiyama, T. et al. Learning-related fine-scalespecificity imaged in motor cortex circuits of behaving
mice. Nature 464, 1182–1186 (2010).
90. Yassin, L. et al. An embedded subnetwork of highly
active neurons in the neocortex. Neuron 68,
1043–1050 (2010).
91. McIntosh, A. R. Towards a network theory of cognition.
Neural Netw. 13, 861–870 (2000).
92. Maren, S. Neurotoxic basolateral amygdala lesions
impair learning and memory but not the performanceof conditional fear in rats. J. Neurosci. 19,
8696–8703 (1999).
93. Winocur, G., Moscovitch, M., Fogel, S.,
Rosenbaum, R. S. & Sekeres, M. Preserved spatial
memory after hippocampal lesions: effects ofextensive experience in a complex environment. Nat.
Neurosci. 8, 273–275 (2005).
94. Scoville, W. B. & Milner, B. Loss of recent memory
after bilateral hippocampal lesions. J. Neurol.
Neurosurg. Psychiatry 20, 11–21 (1957).
95. Milner, B., Squire, L. R. & Kandel, E. R. Cognitive
neuroscience and the study of memory. Neuron 20,
445–468 (1998).
96. O’Keefe, J. & Dostrovsky, J. The hippocampus as a
spatial map. Preliminary evidence from unit activity inthe freely-moving rat. Brain Res. 34, 171–175 (1971).
97. Morris, R. G., Garrud, P., Rawlins, J. N. & O’Keefe, J.
Place navigation impaired in rats with hippocampal
lesions. Nature 297, 681–683 (1982).
98. Milner, P. M. Cell assemblies: whose idea?
Psycholoquy [online], http://www.cogsci.ecs.soton.ac.
uk/cgi/psyc/newpsy?10.053 (1999).
99. Han, J. H. et al. Neuronal competition and selection
during memory formation. Science 316, 457–460(2007).
This study shows that neurons with higher CREB
activity in the LA are more likely than theirneighbours with lower CREB activity to be allocatedto a fear memory engram.
100. Josselyn, S. A. et al. Long-term memory is facilitatedby cAMP response element-binding protein
overexpression in the amygdala. J. Neurosci. 21,
2404–2412 (2001).
101. Davis, M. The role of the amygdala in fear and anxiety.
Annu. Rev. Neurosci. 15, 353–375 (1992).
102. Maren, S. The amygdala, synaptic plasticity, and fear
memory. Ann. NY Acad. Sci. 985, 106–113 (2003).
103. Fanselow, M. S. & Gale, G. D. The amygdala, fear, andmemory. Ann. NY Acad. Sci. 985, 125–134 (2003).
104. Frankland, P. W. & Josselyn, S. A. Memory allocation.
Neuropsychopharmacology 40, 243 (2015).

105. Zhou, Y. et al. CREB regulates excitability and theallocation of memory to subsets of neurons in the
amygdala. Nat. Neurosci. 12, 1438–1443 (2009).
106. Hsiang, H. L. et al. Manipulating a “cocaine engram” inmice. J. Neurosci. 34, 14115–14127 (2014).
107. Sano, Y. et al. CREB regulates memory allocation in
the insular cortex. Curr. Biol. 24, 2833–2837(2014).
108. Sekeres, M. J. et al. Increasing CRTC1 function in thedentate gyrus during memory formation orreactivation increases memory strength withoutcompromising memory quality. J. Neurosci. 32,
17857–17868 (2012).
109. Yiu, A. P. et al. Neurons are recruited to a memory
trace based on relative neuronal excitability
immediately before training. Neuron 83, 722–735(2014).
Along with reference 105, this study establishes
that allocation of neurons to the engram isgoverned by neuronal excitability; that is, more
excitable cells are more likely than their lessexcitable neighbours to become part of an engram
for a fear memory.
110. Armbruster, B. N., Li, X., Pausch, M. H., Herlitze, S. &Roth, B. L. Evolving the lock to fit the key to create afamily of G protein-coupled receptors potently
activated by an inert ligand. Proc. Natl Acad. Sci. USA
104, 5163–5168 (2007).
111. Deisseroth, K. Optogenetics. Nat. Methods 8, 26–29(2011).
112. Gouty-Colomer, L. A. et al. Arc expression identifies
the lateral amygdala fear memory trace. Mol.
Psychiatry http://dx.doi.org/10.1038/mp.2015.18(2015).
113. Kim, D., Pare, D. & Nair, S. S. Assignment of model
amygdala neurons to the fear memory trace depends
on competitive synaptic interactions. J. Neurosci. 33,
14354–14358 (2013).
114. Han, J. H. et al. Selective erasure of a fear memory.
Science 323, 1492–1496 (2009).
Using an allocate-and-manipulate approach, thispaper is the first to show that fear memories may
be ‘erased’ by ablating engram neurons in the LA.
115. Tanaka, K. Z. et al. Cortical representations arereinstated by the hippocampus during memory
retrieval. Neuron 84, 347–354 (2014).
A recent study showing that optogenetic silencing
of engram neurons in the hippocampus prevents
reactivation of engram ensembles in the cortex,
leading to retrieval failure.
116. Koya, E. et al. Targeted disruption of cocaineactivated nucleus accumbens neurons prevents
context-specific sensitization. Nat. Neurosci. 12,
1069–1073 (2009).
117. Bossert, J. M. et al. Ventral medial prefrontal cortex
neuronal ensembles mediate context-induced relapse
to heroin. Nat. Neurosci. 14, 420–422 (2011).
118. Marr, D. Simple memory: a theory for archicortex.
Phil. Trans. R. Soc. Lond. B 262, 23–81 (1971).
119. Alvarez, P. & Squire, L. R. Memory consolidation andthe medial temporal lobe: a simple network model.
Proc. Natl Acad. Sci. USA 91, 7041–7045 (1994).
120. Treves, A. & Rolls, E. T. Computational analysis of therole of the hippocampus in memory. Hippocampus 4,
374–391 (1994).
121. van den Heuvel, M. P. & Sporns, O. Network hubs inthe human brain. Trends Cogn. Sci. 17, 683–696(2013).
122. Wheeler, A. L. et al. Identification of a functional
connectome for long-term fear memory in mice. PLoS
Comput. Biol. 9, e1002853 (2013).
123. Penfield, W. & Perot, P. The brain’s record of auditory
and visual experience. A final summary discussion.
Brain 86, 595–696 (1963).
124. Hamani, C. et al. Memory enhancement induced byhypothalamic/fornix deep brain stimulation. Ann.
Neurol. 63, 119–123 (2008).
125. Hamani, C. et al. Deep brain stimulation of theanterior nucleus of the thalamus: effects of electricalstimulation on pilocarpine-induced seizures andstatus epilepticus. Epilepsy Res. 78, 117–123(2008).
126. Wang, J. X. et al. Targeted enhancement of cortical–
hippocampal brain networks and associative memory.
Science 345, 1054–1057 (2014).
127. Redondo, R. L. et al. Bidirectional switch of thevalence associated with a hippocampal contextual
memory engram. Nature 513, 426–430 (2014).
128. Ramirez, S. et al. Activating positive memory engrams
suppresses depression-like behaviour. Nature 522,
335–339 (2015).

NATURE REVIEWS | NEUROSCIENCE

129. Garner, A. R. et al. Generation of a synthetic memory
trace. Science 335, 1513–1516 (2012).
130. Cowansage, K. K. et al. Direct reactivation of acoherent neocortical memory of context. Neuron 84,
432–441 (2014).
This study shows that stimulation ofengram-associated neurons in a single corticalregion (of a distributed engram) is sufficient for
retrieval of the corresponding fear memory.
131. Penfield, W. Engrams in the human brain.
Mechanisms of memory. Proc. R. Soc. Med. 61,
831–840 (1968).
132. Tulving, E. & Thomson, D. Encoding specificity andretrieval processes in episodic memory. Psychol. Rev.
80, 352–373 (1973).
133. Richards, B. A. & Frankland, P. W. The conjunctive
trace. Hippocampus 23, 207–212 (2013).
134. Bartlett, F. C. Remembering: A Study in Experimental
and Social Psychology (Cambridge Univ. Press,
1932).
135. Schacter, D. L. Constructive memory: past and future.
Dialogues Clin. Neurosci. 14, 7–18 (2012).
136. Ramirez, S. et al. Creating a false memory in the
hippocampus. Science 341, 387–391 (2013).
In this study, a ‘false’ memory was generated bypairing artificial activation of engram neurons
coding for a safe (non-shocked) context with afootshock.
137. Ohkawa, N. et al. Artificial association of pre-stored
information to generate a qualitatively new memory.
Cell Rep. 11, 261–269 (2015).
138. Nader, K., Schafe, G. E. & LeDoux, J. E. Fearmemories require protein synthesis in the amygdala
for reconsolidation after retrieval. Nature 406,
722–726 (2000).
139. Kim, J., Kwon, J. T., Kim, H. S., Josselyn, S. A. &Han, J. H. Memory recall and modifications byactivating neurons with elevated CREB. Nat. Neurosci.
17, 65–72 (2014).
This study established that artificially expressedfear memories also undergo protein synthesisdependent reconsolidation and, therefore, shareproperties with natural fear memories.
140. Allen, T. A., Morris, A. M., Mattfeld, A. T., Stark, C. E.
& Fortin, N. J. A sequence of events model of episodic
memory shows parallels in rats and humans.
Hippocampus 24, 1178–1188 (2014).
141. Eichenbaum, H. & Fortin, N. J. Bridging the gap
between brain and behavior: cognitive and neuralmechanisms of episodic memory. J. Exp. Anal. Behav.
84, 619–629 (2005).
142. Tulving, E. Episodic memory: from mind to brain.
Annu. Rev. Psychol. 53, 1–25 (2002).
143. Lashley, K. S. Integrative functions of the cerebral
cortex. Physiol. Rev. 13, 1–42 (1933).
144. Lashley, K. S. Studies of cerebral funciton in learning.
XI. The beahvior of the rat in latch-box situations.
Comparative Psychol. Monographs 11, 5–42
(1935).
145. Lewis, D. J. Psychobiology of active and inactive
memory. Psychol. Bull. 86, 1054–1083 (1979).
146. Tronel, S., Milekic, M. H. & Alberini, C. M. Linking new
information to a reactivated memory requires
consolidation and not reconsolidation mechanisms.
PLoS Biol. 3, e293 (2005).
147. Debiec, J., Doyere, V., Nader, K. & LeDoux, J. E.
Directly reactivated, but not indirectly reactivated,memories undergo reconsolidation in the amygdala.
Proc. Natl Acad. Sci. USA 103, 3428–3433(2006).
148. O’Keefe, J. & Nadel, L. The Hippocampus as a
Cognitive Map (Clarendon Press, 1978).
149. Olds, J., Disterhoft, J. F., Segal, M., Kornblith, C. L. &Hirsh, R. Learning centers of rat brain mapped bymeasuring latencies of conditioned unit responses.
J. Neurophysiol. 35, 202–219 (1972).
150. Weinberger, N. M. & Bakin, J. S. Research on
auditory cortex plasticity. Science 280, 1174
(1998).
151. Pascoe, J. P. & Kapp, B. S. Electrophysiologicalcharacteristics of amygdaloid central nucleus neurons
during Pavlovian fear conditioning in the rabbit.
Behav. Brain Res. 16, 117–133 (1985).
152. McCormick, D. A., Clark, G. A., Lavond, D. G. &Thompson, R. F. Initial localization of the memory
trace for a basic form of learning. Proc. Natl Acad. Sci.
USA 79, 2731–2735 (1982).
153. LeDoux, J. E., Cicchetti, P., Xagoraris, A. &Romanski, L. M. The lateral amygdaloid nucleus:
sensory interface of the amygdala in fear conditioning.
J. Neurosci. 10, 1062–1069 (1990).

VOLUME 16 | SEPTEMBER 2015 | 533© 2015 Macmillan Publishers Limited. All rights reserved

REVIEWS
154. Campeau, S. & Davis, M. Involvement of subcorticaland cortical afferents to the lateral nucleus of theamygdala in fear conditioning measured with fearpotentiated startle in rats trained concurrently withauditory and visual conditioned stimuli. J. Neurosci.
15, 2312–2327 (1995).
155. Mishkin, M. Memory in monkeys severely impaired by
combined but not by separate removal of amygdala
and hippocampus. Nature 273, 297–298 (1978).
156. Brown, M. W. & Xiang, J. Z. Recognition memory:
neuronal substrates of the judgement of prioroccurrence. Prog. Neurobiol. 55, 149–189 (1998).
157. Fuster, J. M. & Alexander, G. E. Neuron activity
related to short-term memory. Science 173, 652–654(1971).

158. Miyashita, Y., Kameyama, M., Hasegawa, I. &Fukushima, T. Consolidation of visual associative longterm memory in the temporal cortex of primates.
Neurobiol. Learn. Mem. 70, 197–211 (1998).
159. Sakai, K. & Miyashita, Y. Neural organization for the
long-term memory of paired associates. Nature 354,
152–155 (1991).
160. Rey, H. G. et al. Single-cell recordings in the human
medial temporal lobe. J. Anat. http://dx.doi.org/10.1111/
joa.12228 (2014).
161. Squire, L. R. Memory and Brain (Oxford Univ. Press, 1987).
162. Moscovitch, M. et al. Functional neuroanatomy ofremote episodic, semantic and spatial memory: aunified account based on multiple trace theory.
J. Anat. 207, 35–66 (2005).

534 | SEPTEMBER 2015 | VOLUME 16

163. Rissman, J. & Wagner, A. D. Distributed
representations in memory: insights from functional
brain imaging. Annu. Rev. Psychol. 63, 101–128(2012).

Acknowledgements

This project was supported by Canadian Institutes of HealthR e s e a rc h g ra n t s to P. W. F. ( M O P ‑ 8 6 7 6 2 ) , S . A . J .
(MOP‑74650) and S.K. (MOP‑93644). The authors thankA. Santoro for artwork, and N. Insel for comments on earlier
drafts of the manuscript.

Competing interests statement

The authors declare no competing interests.

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