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Amygdala oscillations and the
consolidation of emotional memories
Denis Paré, Dawn R. Collins and Joe Guillaume Pelletier
The amygdala receives multi-modal sensory inputs and projects to virtually all
levels of the central nervous system. Via these widespread projections, the
amygdala facilitates consolidation of emotionally arousing memories. How the
amygdala promotes synaptic plasticity elsewhere in the brain remains
unknown, however. Recent work indicates that amygdala neurons show theta
activity during emotional arousal, and various types of oscillations during
sleep. These synchronized neuronal events could promote synaptic plasticity
by facilitating interactions between neocortical storage sites and temporal lobe
structures involved in declarative memory.
Even in the absence of sensory stimulation, the
spontaneous activity of the brain is not random.
Rhythmic population events, measurable in the
extracellular space as currents, emerge from complex
interactions between the intrinsic properties of
neurons [1] and properties of the network in which
they are embedded. Rhythms of various frequencies
occur in different brain regions and these oscillations
change depending on the behavioral state [2,3].
The importance of these oscillations derives from
the fact that neuronal events underlying cognitive
activity, from sensory perception to memory, are
embedded in these endogenous population rhythms.
In other words, the study of oscillations and coding in
large neuronal ensembles are inextricable. Moreover,
during sleep, when the brain is largely disconnected
from the outside world, neurons generate patterns of
oscillations and synchronized population bursts that
are believed to play a crucial role in memory
consolidation (see Box 1). Finally, because related
parts of the brain tend to produce similar oscillations,
the analysis of spontaneous oscillatory activity can
reveal functional kinship among brain structures.
This review focuses on the neuronal oscillations
shown by the amygdala. The importance of this issue
derives from data indicating that the amygdala
facilitates consolidation of emotionally arousing
memories [4]. Thus, oscillations in the amygdala
might play a crucial role in this respect. Besides, the
amygdala presents us with an interesting problem in
that it receives inputs from parasensory neocortical
areas as well as from phylogenetically older temporal
cortices involved in declarative memory. Hence, the
question emerges as to whether the amygdala
exhibits spontaneous rhythms typical of only one,
or both of these regions.
Multiple functions of the amygdala
As a group, amygdala nuclei receive inputs from and
project to virtually all levels of the central nervous
system (Box 2). Indeed, they have access to sensory
inputs of all modalities, and they innervate cortical
Box 1. Memory consolidation during sleep: the role of synchronized neuronal activity
Denis Paré*
Joe Guillaume Pelletier
Center for Molecular and
Behavioral Neuroscience,
Aidekman Research
Center, Rutgers State
University, 197 University
Ave, Newark, NJ 07102,
USA.
*e-mail:
[email protected]
Dawn R. Collins
Dept of Physiology,
University College
London, Royal Free
Campus, Rowland Hill
Street, London,
UK NW3 2PF.
Much evidence suggests that sleep plays a pivotal role in
synaptic plasticity and memory. For instance, slow-wave
sleep (SWS) enhances cortical reorganization of ocular
dominance columns in developing visual cortex following
monocular deprivation [a]. Moreover, it has been shown
that sleep is essential after visual training for the
consolidation of some forms of procedural memory, such
as visual discrimination skills [b,c]. However, the facilitating
effect of sleep is not limited to procedural memory, as sleep
deprivation produces marked impairments of episodic
memory [d].
It was proposed that the facilitating effect of sleep on
memory consolidation depends on the synchronized
neuronal activity of SWS. For instance, one model of
episodic memory [e] postulates that during waking,
information is initially stored in the CA3 region of the
hippocampus, through changes in the strength of
connections between pyramidal neurons. Later, during
SWS, synchronized population discharges of CA3 neurons
in relation to events known as sharp waves (see main text)
would ‘replay’ the representations stored in the CA3
network and, via the rhinal cortices, reactivate associative
cortical neurons representing features of the event of
interest. Ultimately, this replay of stored representations
would lead to long-term synaptic changes in associative
cortical networks.
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Such models are consistent with neuropsychological
data indicating that the medial temporal lobe plays a
time-limited role in memory [f]. Moreover, they are
supported by single-unit studies in which evidence of
replay of waking activity patterns during sleep has been
obtained [g].
References
a Frank, M.G. et al. (2001) Sleep enhances plasticity in the
developing visual cortex. Neuron 30, 275–287
b Gais, S. et al. (2000) Early sleep triggers memory for early
visual discrimination skills. Nat. Neurosci. 3, 1335–1339
c Stickgold, R. et al. (2000) Visual discrimination learning
requires sleep after training. Nat. Neurosci. 3, 1237–1238
d Plihal, W. and Born, J. (1999) Effects of early and late
nocturnal sleep on priming and spatial memory.
Psychophysiology 36, 571–582
e Buzsáki, G. (1989) Two-stage model of memory formation:
a role for noisy brain states. Neuroscience 31, 551–570
f Squire, L.R. and Cohen, N. (1979) Memory and amnesia:
resistance to disruption develops for years after learning.
Behav. Neural Biol. 25, 115–125
g Wilson, M.A. and McNaughton, B.L. (1989) Reactivation of
hippocampal ensemble memories during sleep. Science 265,
676–679
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Box 2. Connections of the amygdala
References
a McDonald, A.J. (1992) Cell types and intrinsic connections of
the amygdala. In The Amygdala: Neurobiological Aspects of
Emotion, Memory, and Mental Dysfunction (Aggleton, J.P.,
ed.), pp. 67–96, John Wiley & Sons
b Swanson, L.W. and Petrovich, G.D. (1998) What is the
amygdala? Trends Neurosci. 21, 323–331
c Russchen, F.T. (1986) Cortical and subcortical afferents of the
amygdaloid complex. In Excitatory Amino Acids and Epilepsy
(Schwarz, R. and Ben–Ari, Y., eds), pp. 35–52, Plenum Press
d Amaral, D.G. et al. (1992) Anatomical organization of the
primate amygdaloid complex. In The Amygdala:
Neurobiological Aspects of Emotion, Memory, and Mental
Dysfunction (Aggleton, J.P., ed.), pp. 1–66, John Wiley & Sons
e Pitkänen, A. et al. (1997) Organization of intra-amygdaloid
circuitries in the rat: an emerging framework for understanding
functions of the amygdala. Trends Neurosci. 20, 517–523
f Paré, D. and Smith, Y. (1998) Intrinsic circuitry of the
amygdaloid complex: common principles of organization in
rats and cats. Trends Neurosci. 21, 240–241
g Davis, M. (2000) The role of the amygdala in conditioned and
unconditioned fear and anxiety. In The Amygdala: a
Functional Analysis (Aggleton, J.P., ed.), pp. 213–287, Oxford
University Press
h Pitkänen, A. (2000) Connectivity of the rat amygdaloid
complex. In The Amygdala: a Functional Analysis (Aggleton,
J.P., ed.), pp. 31–115, Oxford University Press
The amygdala is a heterogeneous collection of
interconnected nuclei located in the depth of the temporal
lobe. Early anatomists divided the amygdala into three
groups of nuclei (see Fig. I): the basolateral (BL)
complex, comprising the lateral (LA), BL and basomedial
(BM) nuclei; the corticomedial group including the
central (CE), cortical and medial (ME) nuclei [a]; and
a third, anterior group. Although the validity of this
classification has been questioned [b], it is used in this
article. Subsequent work showed that information
about all sensory modalities is relayed to the amygdala
from the thalamus and cerebral cortex [c,d]. Most of
these sensory inputs end in the BL complex and are
then conveyed to the corticomedial group by a large
network of glutamatergic intra-amygdaloid projections
[e,f]. In turn, the corticomedial group projects to brainstem
and hypothalamic structures involved in autonomic
control and in the elaboration of species-specific
emotional behaviors [g]. In addition to these descending
efferent projections, the amygdala has ascending
projections to the cerebral cortex [h]. Amygdalocortical
axons originate mostly from the BL complex and the
majority terminate in higher-order cortical areas. Thus, as
a function of the emotional significance of sensory events,
amygdalofugal axons are able to modulate neuronal
operations at nearly all CNS levels, from brainstem
cardiovascular centers to the highest computational levels
of the brain.
Bed nucleus of Stria Terminalis
Massive brain stem projections
Lateral hypothalamus
Basal forebrain
Prefrontal cortex
Thalamus (posterior and midline nuclei)
Rhinal cortices, insula
Prefrontal cortex
Central (CE)
Lateral (LA)
Rhinal cortices, insula
Hippocampal formation
Accumbens
PU
CE
OT
ME
LA
Prefrontal cortex, insula
Bed nucleus of Stria Terminalis
Hypothalamus
Medial (ME)
BL
BM
AHA
D
L
Hypothalamus
Insula
Brain Stem
Bed nucleus of Stria Terminalis
Olfactory system
Bed nucleus of Stria Terminalis
Hypothalamus
Thalamus (midline nuclei)
M
V
Prefrontal cortex
Rhinal cortices, insula
Temporal and cingulate cortex
Hippocampal formation
Thalamus (posteior and midline nuclei)
Basolateral (BL)
Prefrontal cortex
Rhinal cortices, insula
Hippocampal formation
Various cortical fields
Striatum
Mediodorsal thalamus
Bed nucleus of Stria Terminalis
Light brainstem projections
Prefrontal cortex
Various temporal cortical fields
Thalamus (posterior and midline)
Hypothalamus
Basomedial (BM)
Rhinal cortices, insula
Hippocampal formation
Prefrontal cortex
Striatum
Bed nucleus of Stria Terminalis
Hypothalamus (ventromedial)
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Fig. I. The main connections of the amygdala. Inputs are represented by green arrows; outputs by purple arrows. Note that for simplicity,
inputs from and projections to neuromodulatory systems of the brainstem and basal forebrain have been omitted. AHA,
amygdalohippocampal area; OT, optic tract; PU, putamen. D, dorsal; V, ventral; L, lateral, M, medial.
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Box 3. Consolidation of emotional memories
Long-term memory for an event can be enhanced or reduced by
manipulations performed in the hours after learning. Susceptibility of
recently formed memories to post-learning manipulations was seen
with electroconvulsive shocks, protein synthesis inhibitors, electrical
stimulation or drug injections in discrete brain regions [a]. Various
interpretations were proposed for these results. However, the
observation that emotionally arousing events are remembered
vividly whereas others are forgotten led Gold and McGaugh [b] to
suggest that post-learning treatments might be interfering with, or
potentiating, a mechanism that regulates memory consolidation.
They reasoned that there would be a biological advantage in delaying
memory consolidation until the significance of an experience could be
evaluated. Thus, they hypothesized that the brain is endowed with
modulatory systems that affect the development of memories, but do
not store them.
Consistent with this, administration of adrenal stress hormones after
learning was found to facilitate retention in apetitively or aversively
motivated tasks [c]. As predicted by the consolidation hypothesis, the
effects of stress hormones were time-dependent, their impact on
retention decreasing as the interval between training and treatment
increased. Moreover, systemic administration of β-adrenergic-receptor
antagonists blocked the effects of emotional arousal on long-term
declarative memory [d]. These results raised the possibility that, when
released during a stressful episode, these hormones could act
retrogradely to affect memory of that event. In other words, the extent of
consolidation would depend on the arousing consequences of an
experience, as expressed by the release of stress hormones [b].
Later, it was shown that the basolateral (BL) amygdala mediates the
effects of stress hormones on memory. Indeed, lesion or inactivation of
the BL amygdala, but not of the central amygdaloid nucleus, blocked the
memory modulating effects produced by adrenalectomy or peripheral
administration of adrenaline [c]. In addition, post-learning treatments
that presumably reduced or enhanced excitability of the BL neurons,
respectively decreased or improved retention on a variety of
emotionally charged learning tasks [c]. However, the memory
modulating effects of these manipulations do not result from alterations
of memory storage in the but in other structures that represent the
storage site of particular forms of memories [e].
The modulation of memory by the BL amygdala can also be seen in
humans. For instance, emotionally arousing stories are normally better
recalled than neutral ones, but this effect is absent in subjects with
amygdala lesions [f]. Moreover, imaging studies have found a high
correlation between long-term recall of emotionally arousing versus
neutral material and the degree of amygdala activation observed when
these stimuli were first presented [g,h]. Thus, in emotionally arousing
conditions, the amygdala facilitates memory-storage processes in brain
areas that are involved in declarative memory.
References
a McGaugh, J.L. and Gold, P.E. (1976) Modulation of memory by electrical
stimulation of the brain. In Neural Mechanisms of Learning and Memory
(Rosenzweig, M.R. and Bennett, E.L., eds), pp. 549–560, MIT Press
b Gold, P.E. and McGaugh, J.L. (1975) A single-trace, two process view of
memory storage processes. In Short-Term Memory (Deutsch, D. and
Deutsch, J.A., eds), pp. 355–378, Academic Press
c McGaugh, J.L. (2000) Memory: a century of consolidation. Science 287, 248–251
d Cahill, L. et al. (1994) Beta-adrenergic activation and memory for emotional
events. Nature 371, 702–704
e Cahill, L. and McGaugh, J.L. (1998) Mechanisms of emotional arousal and
lasting declarative memory. Trends Neurosci. 21, 294–299
f Cahill, L. et al. (1995) The amygdala and emotional memory. Nature 377,
295–296
g Cahill, L. et al. (1996) Amygdala activity at encoding correlated with longterm, free recall of emotional information. Proc. Natl. Acad. Sci. U. S. A. 93,
8016–8021
h Hamann, S.B. et al. (1999) Amygdala activity related to enhanced memory
for pleasant and aversive stimuli. Nat. Neurosci. 2, 289–293
and subcortical structures involved in functions as
diverse as memory, perception, behavioral state
control and homeostatic regulation [5]. Accordingly,
lesion and imaging studies indicate that the
amygdala takes part in wide variety of functions.
These include learning in positively and negatively
motivated tasks, the expression of unconditioned fear
responses, identification of the emotional content of
sensory stimuli, and aspects of social cognition [6].
Moreover, much data suggest that the amygdala
enhances memory consolidation in emotionally
arousing conditions [4]. Briefly, neuromodulators
released in emotionally arousing conditions appear to
alter the activity of basolateral amygdala neurons in
the hours after the learning episode. In turn, these
changes would facilitate synaptic plasticity elsewhere
in the brain (see Box 3).
At present, the contribution of the amygdala to
these multiple functions is unclear. One possibility is
that the amygdala simply relays the results of
computations performed by afferent structures to
cortical and subcortical effectors. According to this
view, the functional heterogeneity of the amygdala
would reflect its promiscuous connections. Alternatively,
the amygdala might perform computations that are
critical to these functions. To gain insight into this issue,
one approach is to examine how faithfully the amygdala
reflects neuronal events taking place in its cortical and
thalamic afferents. The former ‘relay’view would predict
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close similarities between corticothalamic and amygdala
activity. The latter view would be more consistent
with the presence of relatively independent rhythms.
Because most cortical and thalamic inputs end in
the basolateral (BL) complex of the amygdala (namely
the lateral, basolateral and basomedial nuclei), the
rest of this review will focus on this group of nuclei.
In terms of cortical connectivity, the BL complex is
intriguing because it is reciprocally connected to
cortical regions of differing phylogenetic origins.
On the one hand, it derives inputs from high-order
parasensory associative neocortical areas [7].
On the other hand, it also has strong connections with
phylogenetically older cortical structures of the
temporal lobe that are believed to play a crucial role in
declarative memory. These include the rhinal cortices,
and all fields of the hippocampus with the exception of
the dentate gyrus [8]. Therefore, an intriguing question
is to determine whether the BL complex exhibits
spontaneous oscillations characteristic of parasensory
neocortical areas or of these more ancient temporallobe structures. Before we turn to this issue, however,
we will review the neocortical and hippocampal EEGs.
EEG correlates of behavioral states in the neocortex
and hippocampus
The neocortex and hippocampus show contrasting
activity patterns depending on the subject’s state
of vigilance.
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TRENDS in Cognitive Sciences Vol.6 No.7 July 2002
Neocortex
During the states of wakefulness and paradoxical
sleep, the neocortical EEG is dominated by
low-amplitude, high-frequency activity (so-called
‘activated EEG’). By contrast, slow waves of high
amplitude dominate the neocortical EEG during
slow-wave sleep (SWS) (called ‘synchronized EEG’).
Although spectral analyses of the neocortical EEG
reveal a continuum of frequencies during SWS, it
includes readily identifiable components.
The lowest frequency component (<1 Hz) is termed
‘slow oscillation’ [2]. This oscillation was first
described in the neocortex of anesthetized animals [9]
and, later, during SWS in cats [10] and humans [11].
Intracellular recordings have shown that the slow
neocortical oscillation consists of an EEG depthnegative phase coinciding with increased firing in all
classes of cortical cells, and an EEG depth-positive
phase associated with neuronal silence [2]. This
oscillation also occurs in subcortical structures, such
as the thalamus and striatum [12,13], but is
dependent on cortical inputs [14].
A second readily identifiable component are delta
waves (1–4 Hz), which seem to become more
prominent as SWS progresses [15,16]. The origin of
delta waves remains unclear. Single thalamocortical
cells can intrinsically oscillate at this frequency by
virtue of the interplay between two of their ionic
currents [17]. However, delta waves would not
emerge in the EEG as a spatially synchronized
phenomenon unless the activity of thalamocortical
neurons were synchronized. Cortical feedback and
activity of the reticular thalamic nucleus are among
the likely synchronizing influences [18].
A third component of the neocortical EEG during
SWS are sleep spindles. Spindles are brief periods
(1–2 s) of waxing and waning oscillations at 7–14 Hz,
which recur more or less synchronously every 3–10 s
in much of the neocortex, but are especially obvious in
Brodmann areas 4–6 and areas 5–7 [19,20]. Spindles
are generated in the thalamus: they disappear from
cortical areas whose thalamic inputs have been
severed [19], and persist in the thalamus after
decortication coupled to an upper brainstem
transection [21]. Although the intrathalamic
mechanisms underlying spindle genesis are still
debated [2,22], they are believed to involve reciprocal
interactions between GABAergic reticular thalamic
neurons and thalamocortical cells [2].
The slow oscillation component can often be seen
to entrain faster EEG components [23]. Indeed, the
likelihood of observing sleep spindles or delta waves
increases during the depth-negative phase of the
slow oscillation, as if the synchronized discharge
of cortical neurons triggered spindles and delta
oscillation. In addition, even faster rhythms (beta
and gamma oscillations) are also more readily
observed during the depth-negative phase of the
slow oscillation [10]. However, these faster
oscillations seem more prominent in waking and
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paradoxical sleep, because of the disappearance of
slow EEG components [2].
To the best of our knowledge, no attempt has been
made to determine whether the various rhythms
observed in SWS differentially recruit cortical cells
that were involved in prior adaptive computations
during the waking state. Because neuronal activity in
SWS is hypothesized to play a crucial role in memory
consolidation (Box 1), this issue constitutes an
important challenge for future investigations.
Hippocampus
During arousal (e.g. produced by noxious stimuli),
locomotion and paradoxical sleep, the hippocampal
EEG is dominated by a high-amplitude oscillation in
the theta range (4–8 Hz), which modulates the
activity of essentially all types of hippocampal
neurons [3,24]. Despite intense investigation, the
mechanisms underlying theta generation remain
unclear [25]. However, it is established that
hippocampal theta requires intact connections with
the medial septum [26], and that it depends on the
rhythmic activity of entorhinal afferents and CA3
Schaffer collaterals [25]. Moreover, hippocampal
theta is associated with cyclical amplitudemodulation of gamma waves in the hilus, entorhinal
cortex and CA1 [27–29].
During SWS, the hippocampal EEG displays highamplitude slow waves of various frequencies but no
spindles. In further contrast to the neocortical EEG,
hippocampal recordings obtained during SWS,
immobility and consummatory behaviors (e.g. eating,
grooming) exhibit population events, termed ‘sharp
waves’, believed to result from population bursts in
CA3 and CA1 pyramidal neurons [30]. Sharp waves
appear to trigger, or at least be associated with, an
increase in the amplitude of fast oscillations
(≈200 Hz), termed ‘ripples’ [31,32]. Ripples are
believed to result from the synchronized discharges of
inhibitory interneurons.
A significant correlation between the occurrence of
spindles in the neocortex and sharp waves/ripples in
the hippocampus has been reported [33]. However,
this correlation accounted for only a small change in
firing probability. This is in contrast to the dramatic
increases in firing probability evident in hippocampal
neurons in relation to sharp-wave ripples, and in
neocortical neurons in relation to spindles.
Thus, different behavioral states have different
EEG correlates in the neocortex and hippocampus.
As the BL complex of the amygdala receives afferents
from these two sets of structures, it has, in principle
at least, the possibility of expressing both sets of
EEG rhythms. If, as is currently believed (Box 1),
neuronal oscillations do contribute to memory
consolidation, understanding how neocortical and
hippocampal rhythms interact with amygdala
activity is of prime importance, as this interaction will
shed light on how the amygdala facilitates
consolidation of emotional memories.
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(a)
(c)
LA1
0.5 mV
LA
LA2
12
1
2
PRH1
PRH
3
PRH2
PRH3
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(b)
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0
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40
80
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0.8
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0
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Fig. 1. Synchronized slow oscillatory activity in the EEG in lateral amygdaloid (LA) nucleus and perirhinal
(PRH) cortex. (a,b) Slow EEG oscillation shown at two different speeds. Data obtained in a cat
anesthetized with ketamine and xylazine. In (b), the top trace in each of the five recordings shows the
same bandwidth as in (a); the lower trace was digitally filtered between 20 and 35 Hz. This shows the
systematic temporal relationship between the different phases of the slow oscillation and the
amplitude of fast rhythms. (c) Position of recording sites on a ventral view of the cat brain. (d) Spectral
composition of the focal activity recorded in the LA (top) and PRH cortex (bottom). (Units on the
ordinate are arbitrary.)
Oscillations in the BL amygdala
We will now compare oscillatory activity observed in
the neocortex, hippocampal formation and BL
amygdala during different behavioral states. As the
amygdala and hippocampus receive many of their
neocortical inputs indirectly by way of the perirhinal
cortex [34], we will also consider spontaneous EEG
rhythms displayed by this cortical field.
Slow sleep oscillation
Although the slow oscillation has been observed in
anesthetized rats in the hippocampal formation
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(D. Henze, personal communication), the phase
relationship existing between the hippocampal and
neocortical rhythms was not determined. Such an
analysis was, however, carried out for the slow
oscillations of the neocortex and perirhinal cortices
[35]. Although distant neocortical sites showed a
coherent slow oscillation, the relationship between
neocortical and perirhinal rhythms was irregular. By
contrast, the lateral nucleus of the amygdala (LA) and
perirhinal cortex generate a highly synchronized slow
oscillatory activity despite the fact that the distance
between the LA and different longitudinal levels of
the perirhinal cortex varies widely (Fig. 1) [36]. In the
light of previous findings [12–14], these results
suggest that the rhinal cortices can generate slow
oscillations independently of the neocortex and
impose this slow rhythm on the amygdala. However,
more work will be required to settle this issue.
Importantly, both perirhinal and LA oscillations
are associated with prominent fluctuations in firing
probability (Fig. 2), which indicates that these focal
oscillations are generated locally and are not volumeconducted from the cortex [36]. Moreover, as in the
neocortex, the slow amygdala oscillation is associated
with cyclical fluctuations in the amplitude of beta and
gamma waves (Figs 1b,d and 2b). However, whereas
the slow oscillation remains synchronized even at
distant (up to 10 mm) amygdala and perirhinal sites,
the coherence of gamma oscillations decreases
abruptly with distance [36].
BL amygdala neurons exhibit a clear tendency to
oscillate at the delta frequency during SWS [37].
Moreover, the phase relationship is tightly coupled to
the delta oscillation of the rhinal cortices. Because a
previous study revealed that correlation between
rhinal and neocortical oscillations tended to be low
[35], it is likely that amygdala delta oscillations also
bear little relationship to those in the neocortex.
Sleep spindles
Whereas sleep spindles are prevalent in the
neocortex, they are absent from the BL amygdala
[37,38] and rhinal cortices [36]. During neocortical
spindles, the amygdala exhibits trains of slow delta
waves [37,38]. The lack of spindles in the rhinal
cortices is consistent with the comparatively meager
thalamic projections to these cortical fields [39].
Moreover, the dorsal thalamic nuclei that project to
the entorhinal cortex, namely the reuniens and
anterior thalamic nuclei [39,40], do not receive inputs
from the reticular thalamic nucleus [41–43], which,
as mentioned above, plays a crucial role in the genesis
of spindles. Similarly, most of the thalamic nuclei that
project to the BL complex [44] do not receive inputs
from the reticular thalamic nucleus [41,43].
Thus, compared with the neocortex, the rhinal
cortices and BL amygdala depend largely on
cortico–cortical connections for the transfer of
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(a) (i)
1s
(ii)
0.5 s
Normalized frequency
(iii)
3.0
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nR = 104
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1500
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(ii)
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nR = 712
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50
100
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Fig. 2. The slow focal oscillation of the lateral nucleus of the amygdala
(LA). Data recorded in a cat anesthetized with ketamine and xylazine.
(a) Unit activity and superimposed focal activity recorded in the LA
shown with a slow (i) and a fast (ii) time base. (iii) Peri-event histogram
(PEH) of neuronal discharges for the same cell using the negative peak
of slow oscillations in focal waves as zero on the time axis. nS, number
of spikes; nR, number of reference peaks. (b) Gamma-related
modulation of firing probability in the LA. (i) Firing of a LA neuron
(top trace) and fast focal activity (bottom trace) recorded
simultaneously by the same microelectrode. (ii) PEH of neuronal
discharges (1 ms bins) using the negative peak of gamma waves
as zero time.
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311
thalamically generated spindle oscillations. In this
context, the lack of spindle oscillations in these
areas suggests that the rhythmic thalamic volleys
accompanying spindles are gradually disorganized as
they are transmitted through successive cortico–cortical
links. Alternatively, it is possible that the neocortical
inputs converging in the amygdala and rhinal
cortices are insufficiently synchronized for
EEG spindles to emerge.
To our knowledge, the relationship between
hippocampal sharp waves and amygdala activity has
not been investigated. However, it has been found
that during SWS, and under barbiturate anesthesia,
the BL amygdala generates synchronized population
bursts (Fig. 3a) [45]. These synchronized population
discharges give rise to brief, large-amplitude
potentials (termed ‘sharp potentials’) in the rhinal
cortices [35,45] and, after a brief delay, in the dentate
gyrus [35]. These sharp dentate potentials are
associated with a marked increase in the amplitude of
fast oscillations around 80 Hz in the dentate gyrus
and rhinal cortices (Fig. 3b) [45]. These events might
correspond to the dentate spikes previously described
in rats [46].
Theta
During paradoxical sleep, theta activity is readily
observed in the BL amygdala [37] and perirhinal
cortex [35], although in both structures it remains less
prominent than the theta oscillation of the entorhinal
cortex and hippocampus. For instance, Collins et al.’s,
found that as many as 46% of entorhinal neurons
displayed a statistically significant modulation in
firing rate in this frequency range compared with only
16% in the perirhinal cortex [35]. In the perirhinal
cortex at least, the theta oscillation is related to a
cyclical modulation in the amplitude of gamma waves,
as in the hippocampus. Moreover, perirhinal and
amygdala theta is phase locked to entorhinal [35,37],
and thus to hippocampal, theta.
During the waking state, the theta oscillation is
prominent in the amygdala only during periods of
intense arousal, as produced by the anticipation of a
noxious stimulus (Fig. 4) [47] or alimentary
instrumental conditioning [48]. Moreover, it was
reported that arousal was associated with an
increased coherence of theta activity in the amygdala
and frontal cortex [48].
Three non-exclusive factors probably contribute to
the appearance of theta oscillations in the BL complex
during anticipation of noxious stimuli. First,
BL neurons are endowed with intrinsic membrane
properties that predispose them to oscillate in this
range of frequencies [49–51]. Second, the BL complex
receives synaptic inputs from the rhinal cortices and
hippocampal formation (reviewed in [7]) where
rhythmic neuronal activity in the theta range has
been observed [3,35,52,53]. Third, the BL amygdala
receives inputs from thalamic nuclei, such as the
anterior thalamic nuclei and nucleus reuniens, that
312
Fig. 3. Recordings from
the basolateral
amygdaloid nucleus (BL)
during slow-wave sleep.
(a) Simultaneously
recorded BL neuron and
bipolar entorhinal EEG.
The firing rate of the BL
neuron is closely
correlated with the
entorhinal sharp
potentials. (b) Sharp
potential recorded in the
rhinal cortex shown here
to coincide with an
increase in the amplitude
of the underlying fast
rhythms. Entorhinal EEG
was digitally filtered
between 70 and 120 Hz.
The traces were aligned
with reference to the peak
of sharp potentials.
Review
TRENDS in Cognitive Sciences Vol.6 No.7 July 2002
(a)
(b)
BL
Entorhinal cortex EEG
0.1 s
0.1 s
TRENDS in Cognitive Sciences
could transmit the hippocampal theta rhythm to the
amygdala [44,54].
Fast activities during arousal
Several studies have reported that arousal is
accompanied by increases in the amplitude of fast
focal activities in general [55], and of ‘amygdala
spindles’ in particular [56]. Although they have the
typical spindle shape, these events should not be
confused with sleep spindles because they occur
during a different behavioral state and comprise
much faster waves (in the beta/gamma range), as
previously described in the adjacent pre-pyriform
cortex [57]. Whether amygdala spindles are volume
conducted from the pre-pyriform cortex or reflect a
true amygdala rhythm remains unknown.
Significance of oscillatory activity
The findings reviewed above indicate that the
amygdala reflects a unique pattern of statedependent oscillations. Like the rest of the brain, focal
waves recorded in the amygdala during slow-wave
sleep are dominated by waves of high amplitude and
low frequencies. By contrast, faster activities of lower
amplitude are predominant during wakefulness and
paradoxical sleep. Similarities end here however. The
lack of sleep spindles in the amygdala, the variable
temporal relations seen between the slow amygdala
and faster neocortical oscillations, and the presence of
theta during EEG-activated states, all suggest that
the amygdala is functionally closer to the
hippocampal formation and rhinal cortices than to
the neocortex.
These findings take on a particular significance
when considered in the light of data indicating that
the amygdala facilitates consolidation of emotionally
arousing memories [4]. Although previous work has
emphasized the individual contributions of the
amygdala and hippocampal system to distinct forms
of memory, the functional similarities and reciprocal
http://tics.trends.com
connections between these structures suggest that
they engage in cooperative interactions. Because
theta oscillations are present in the amygdala only
during emotional arousal, they represent a likely
physiological substrate for the facilitated
consolidation of emotional memories by the
amygdala. Importantly, it should be noted that
amygdala theta occurs in conditions that can have a
negative [47] or a positive [48] valence, which is
consistent with anecdotal reports of improved
memory for circumstances surrounding both
traumatic and happy events. Therefore, we propose
that the theta activity of amygdala neurons during
emotional arousal promotes memory by facilitating
interactions between neocortical storage sites and the
declarative memory system of the temporal lobe.
How would periodic amygdala activity at the theta
frequency (4–8 Hz) play this role? First, it should be
noted that glutamatergic projection neurons of the
BL complex have extremely low firing rates [37], even
during emotional arousal [47]. Thus, the temporal
clustering of neuronal discharges at the theta
frequency greatly enhances the depolarization
produced by BL activity on target structures. Second,
much of the temporal lobe shows theta frequency
oscillation during emotional arousal [37,53], and
amygdala and hippocampal theta are highly
correlated [37]. Third, coherent oscillations cause
short recurring time windows that facilitate synaptic
interactions between phase-locked oscillators. And
fourth, coincident pre- and post-synaptic activity is
crucial to synaptic plasticity [58].
Thus, we suggest that, by telescoping the periods
of effective synaptic interactions in short time
windows, amygdala oscillations at the theta
frequency exert a depolarizing action that promotes
synaptic plasticity in co-active structures of the
temporal lobe and neocortex. Consistent with this
idea, the conduction times of BL axons to the rhinal
cortices adjust to compensate for variations in
Review
TRENDS in Cognitive Sciences Vol.6 No.7 July 2002
Tone on
(a)
313
(b)
Pre-tones
Silence
160
Power
Arterial pressure
Tone off
120
80
0
10
15
20
Time (s)
25
0
30
Pre-tones
5
10
15
Frequency (Hz)
20
Silent period
n = 59
nR = 442
nT = 517
6
4
2
Relative frequency
Relative frequency
(c)
5
n = 59
nR = 885
nT = 972
6
4
2
0
0
–400
–200
0
200
ms
Cross-correlation
400
–400
–200
0
200
ms
Cross-correlation
400
TRENDS in Cognitive Sciences
Acknowledgements
We thank P. Giguère and
D. Drolet for technical
support. Supported by
research grants to D.P.
from the Canadian
Institutes of Health
Research and the Center
for Molecular and
Behavioral Neuroscience
of Rutgers University.
J.G.P. was supported by a
scholarship from FCAR.
consolidation of emotional memories. According to
this view, despite storage facilitation by amygdala
theta during wakefulness, representations would
remain labile. Subsequent sleep activity would,
through a still undefined mechanism, consolidate
these representations. This view is analogous to the
two-stage model of episodic memory (Box 1). However,
in contrast with that model, we do not hypothesize
that the amygdala stores a trace of waking activity
patterns. Sleep events would not ‘replay’ waking
activities, but would recruit cortical neurons
randomly. Specificity of the consolidation process
might be ensured by activity-dependent ‘labeling’ of
particular groups of synapses in wakefulness.
Fig. 4. Theta rhythm in the lateral amygdala (LA) associated with
anticipation of a noxious stimulus. (a) Behavioral paradigm: cats
learned that a series of tones interrupted by a period of silence (5 s)
preceded the administration of a footshock. Changes in arterial blood
pressure (mm Hg) observed in naive (lower trace) and trained cats
(top trace). During the silent period, trained cats showed increases in
blood pressure, indicating that they anticipated the noxious stimulus, a
state anthropomorphically interpreted as fear. (b) Simultaneously
recorded sites in the basolateral amygdala complex showing increased
correlation in the theta band during fear. Cross-correlograms of local LA
field potentials before the tones and during the silent period. Focal
waves were digitally filtered from 2 to 55 Hz and divided in 1 s segments
sliding in steps of 100 ms over the 5 s epoch preceding the tones or the
silent period. Note marked increase in the theta frequency range
(4–8 Hz). (c) Cross-correlation of neuronal discharges generated by
simultaneously recorded LA neurons in control conditions (left) and
during anticipation of the noxious stimulus (right). Note increased
synchrony and theta rhythm in the anticipatory state. n, number of cell
pairs; nR, number of spikes generated by the reference cells;
nT, number of spikes generated by the test cells.
Conclusion
distance between the BL complex and distinct
rostrocaudal rhinal sites [59]. As a result, BL neurons
can generate simultaneous rhythmic depolarizations
at spatially distributed rhinal sites and facilitate
Hebbian associations between coincident activity
patterns.
In rats, intra-amygdala lidocaine injections up to
six hours post-learning interfere with the facilitating
effects of emotion on recall days later [60]. Because
rats normally spend significant amounts of time
sleeping, and undoubtedly would have slept in the six
hours post-learning, this finding raises the possibility
that the synchronized neuronal activity of amygdala
neurons during sleep also contributes to the
Compared with the neocortex and hippocampus, the
study of neuronal oscillations in the amygdala is in its
infancy. However, recent progress indicates that, like
these better known structures, the amygdala exhibits a
rich repertoire of oscillations. Understanding the role
of these oscillations in synaptic plasticity is a major
challenge. Undoubtedly, studying the relationship
between population rhythms and coding by amygdala
neurons will generate valuable insights into this
issue. In addition, the study of neuronal oscillations
might offer important clues about the much-debated
affiliations of the various amygdala nuclei. That is,
studying the coherence of oscillations in different
amygdala nuclei might serve as a functional assay to
examine the degree of kinship between them.
http://tics.trends.com
314
Review
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