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Emotional brain states carry over and enhance future memory formation

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Emotional arousal can produce lasting, vivid memories for emotional experiences, but little is known about whether emotion can prospectively enhance memory formation for temporally distant information. One mechanism that may support prospective memory enhancements is the carry-over of emotional brain states that influence subsequent neutral experiences. Here we found that neutral stimuli encountered by human subjects 9-33 min after exposure to emotionally arousing stimuli had greater levels of recollection during delayed memory testing compared to those studied before emotional and after neutral stimulus exposure. Moreover, multiple measures of emotion-related brain activity showed evidence of reinstatement during subsequent periods of neutral stimulus encoding. Both slow neural fluctuations (low-frequency connectivity) and transient, stimulus-evoked activity predictive of trial-by-trial memory formation present during emotional encoding were reinstated during subsequent neutral encoding. These results indicate that neural measures of an emotional experience can persist in time and bias how new, unrelated information is encoded and recollected.
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We form lasting, vivid and detailed memories for only a subset of
our experiences. Emotion is one key factor that influences the fate of
our memories1,2. Compared to their neutral counterparts, emotional
events and stimuli are more robustly remembered, with higher levels
of confidence, vividness and detail1–4. The presence of emotion not
only increases recollection of emotionally arousing experiences them-
selves but also has been shown to retroactively modulate recollection
of neutral information preceding emotional arousal5,6. Despite such
findings documenting the impact of emotion on memory for informa-
tion before and during manipulations of emotional arousal, little work
has examined whether emotion can prospectively enhance memory
for subsequently encountered information minutes later. Moreover, it
is unknown whether the persistence of emotional arousal is capable of
impacting future brain states and modifying the neural structures that
support memory formation for subsequently encountered stimuli.
Here we assessed whether exposure to emotionally arousing stimuli
prospectively enhances memory for subsequently encountered stimuli
by biasing future states of brain activity.
A robust body of literature indicates that emotional arousal during
an experience enhances the consolidation of memory for that particu-
lar event, resulting in more persistent, vivid and detailed emotional
memories over time1–4. Mechanistically, emotional arousal has been
linked with the release of norepinephrine and epinephrine, which,
in concert with the amygdala, are thought to modulate hippocampal
processes during both the encoding and subsequent consolidation of
emotional experiences1,7–9. Supporting this notion, activity within
and connectivity between the amygdala, hippocampus and medial
temporal lobe cortex reliably predicts successful emotional memory
formation and consolidation10–13. In addition to enhancing memory
for emotional events themselves, emotional learning and exposure
to emotional stimuli—or the induction of arousal pharmacologically
or with shock—can retroactively enhance long-term retention of
preceding neutral information5,6,14–18 (but see refs. 15,19).
But what about unrelated neutral information that follows an
emotional experience? Can extended periods of emotional arousal
bias future brain states and, in doing so, prospectively modify the
neural structures supporting memory formation for unrelated, neu-
tral information? Prior work has examined the influence of emotion
on memory for information encountered seconds after emotional
arousal6,15,19, and a recent study found that individual differences
in arousal induced by a block of emotional stimuli were related to
enhanced memory discrimination for similar visual images pre-
sented a few minutes later20. Previous studies have also examined
the impact of stress on memory formation for both emotional and
neutral stimuli. Memory for both emotional and neutral images is
enhanced when encoding blocks are interleaved with a stress manipu-
lation21. At the neural level, amygdala connectivity remains altered
after stress induction22–24, and stress induction can alter activation
in brain regions related to memory formation for both emotional
and neutral stimuli21. However, to our knowledge, no prior investiga-
tions have examined how extended periods of emotional arousal can
prospectively bias future brain states and thereby modify the manner
in which unrelated, neutral information is encoded into memory.
Here, we tested whether arousal and brain states associated with
an extended (~20 min) emotional experience can carry-over and
bias the encoding of neutral stimuli encountered approximately
9 to 33 min later and thereby modulate how those stimuli are encoded
into memory (Fig. 1).
1Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, USA. 2Department of Basic Neurosciences, University of Geneva Campus
Biotech, Geneva, Switzerland. 3Department of Psychology, New York University, New York, New York, USA. 4Center for Neural Science, New York University, New York,
New York, USA. 5Nathan Kline Institute, Orangeburg, New York, USA. 6These authors equally contributed to this work. Correspondence should be
addressed to L.D. (lila.davachi@nyu.edu).
Received 21 June; accepted 23 November; published online 26 December 2016; doi:10.1038/nn.4468
Emotional brain states carry over and enhance future
memory formation
Arielle Tambini1,6, Ulrike Rimmele2,6, Elizabeth A Phelps3–5 & Lila Davachi3,4
Emotional arousal can produce lasting, vivid memories for emotional experiences, but little is known about whether emotion
can prospectively enhance memory formation for temporally distant information. One mechanism that may support prospective
memory enhancements is the carry-over of emotional brain states that influence subsequent neutral experiences. Here we found
that neutral stimuli encountered by human subjects 9–33 min after exposure to emotionally arousing stimuli had greater levels
of recollection during delayed memory testing compared to those studied before emotional and after neutral stimulus exposure.
Moreover, multiple measures of emotion-related brain activity showed evidence of reinstatement during subsequent periods of
neutral stimulus encoding. Both slow neural fluctuations (low-frequency connectivity) and transient, stimulus-evoked activity
predictive of trial-by-trial memory formation present during emotional encoding were reinstated during subsequent neutral
encoding. These results indicate that neural measures of an emotional experience can persist in time and bias how new, unrelated
information is encoded and recollected.
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To this end, two groups of subjects underwent blood-oxygen-level-
dependent (BOLD) functional MRI (fMRI) scanning during inciden-
tal encoding of extended (23 min) blocks of emotional and neutral
complex scenes (emotional and neutral encoding conditions; Fig. 1a),
returning 6 h later for a surprise memory test. One group of subjects
first encountered an extended block of emotional stimuli followed by
neutral stimuli (‘E-N encoding order’), while a different group of sub-
jects encountered neutral stimuli followed by emotional stimuli (‘N-E
encoding order’). A separate group of subjects incidentally encoded
blocks of neutral stimuli under the same procedures as the fMRI
subjects (but outside of the MRI scanner), and two other groups of
subjects incidentally encoded blocks of emotional and neutral stimuli
(E-N and N-E encoding orders) outside of the MRI scanner (Fig. 1a).
We reasoned that the prospective influence of emotion, or a carry-
over of an emotional state into subsequent neutral encoding, should
be present when subjects encoded a long block of emotional stimuli
first and neutral stimuli second (E-N encoding order) but not for the
opposite encoding order (N-E encoding order) or when only neutral
stimuli were encoded outside of the context of emotional stimuli
(N-N encoding order). We first assessed the persistence of emotional
arousal from emotional encoding into subsequent neutral encoding
blocks by measuring skin conductance levels (SCL) as a proxy for sym-
pathetic nervous system activation25. Behaviorally, we asked whether
the carry-over of an emotional state would enhance the subjective
recollection of subsequently encountered neutral stimuli (in the
E-N encoding order relative to the other encoding orders). Finally,
using fMRI, we examined whether emotion would prospectively bias
future encoding-related brain activity in at least two ways (Fig. 1b):
first, we asked whether BOLD activity patterns during emotional
and neutral encoding were more similar when neutral stimuli were
encoded after versus before emotional stimuli (E-N versus N-E encod-
ing order) and second, whether brain regions supporting emotional
memory (for example, amygdala and anterior hippocampus) were
more active and showed greater levels of connectivity when neutral
stimuli were encoded after versus before emotional stimuli (i.e., when
a carry-over of emotional arousal may have been present).
RESULTS
Skin conductance
If emotional arousal following an extended block of emotional encod-
ing persists into neutral encoding, then overall SCL, which is related to
sympathetic nervous system activation25, should track this persistence
and differ based on emotion and encoding order. To account for indi-
vidual differences in baseline skin conductance, SCL was computed
as the change relative to a baseline rest period obtained before the
first encoding block (referred to as ‘relative SCL’; Online Methods).
When assessing relative SCL in the fMRI study, we found a significant
interaction between emotion (emotional versus neutral encoding)
and encoding order (Fig. 2a; F1,42 = 8.72, P = 0.0051; permutation
test, P = 0.0036). Elevated SCL showed evidence of persistence from
long-lasting blocks of emotional into subsequent neutral encoding
(Fig. 2a). Specifically, SCL increased during emotional encoding
compared to the preceding baseline rest scan (t21 = 3.21, corrected
P = 0.0167; permutation test, corrected P = 0.004) and remained height-
ened during a block of subsequent neutral encoding (SCL relative
to baseline rest scan, t21 = 3.06, corrected P = 0.0239; permutation test,
corrected P = 0.0096). Thus SCL levels were equivalent between emo-
tional and neutral encoding when neutral stimuli were encoded tens
of minutes after emotional stimuli (E-N encoding order, t21 = 0.51,
P = 0.61; permutation test, P = 0.65), despite the temporal separation of
these encoding blocks. By contrast, SCL was significantly greater during
emotional versus neutral encoding when neutral stimuli were encoded
before emotional stimuli (N-E encoding order; Fig. 2a; t21 = 3.19,
P = 0.0044; permutation test, P = 0.0022).
We next directly tested whether relative SCL during neutral encod-
ing was enhanced when neutral stimuli were encountered after emo-
tional stimuli, compared to before emotional stimuli (N-E encoding
order) or after neutral stimuli (N-N encoding order). Relative SCL
during neutral encoding was marginally enhanced for E-N versus N-E
(t42 = 1.62, P = 0.056, one-tailed t-test; one-tailed permutation test,
P = 0.053) and N-N encoding orders (comparison with second block,
t43 = 1.32, P = 0.097, one-tailed t-test; one-tailed permutation test,
P = 0.098; comparison with first block, t43 = 1.50, P = 0.071, one-tailed
t-test; one-tailed permutation test, P = 0.073). However, relative SCL
during emotional encoding did not differ between encoding orders
(t42 = 0.82, P = 0.42; permutation test, P = 0.41). These results provide
evidence for enhanced SCL when neutral stimuli were encountered
after emotional stimuli, supporting the notion that a block of emo-
tional stimuli can induce arousal that persists tens of minutes later,
into and during an extended block of subsequent neutral encoding.
Time
~23 min
Emotional
encoding
Neutral
encoding
9 min 9 min~23 min
Neutral
encoding
Emotional
encoding
Rest
Rest
Rest
Rest E N
N E
Emotional
encoding
Neutral
encoding
Neutral
encoding
Emotional
encoding
Memory
Arousal
Neural pattern similarity
Emotion-related activity
Neu :
Neu
fMRI +
behavior
Behavior
Neutral
encoding
Neutral
encoding
Rest Rest N N
fMRI +
behavior
Neutral
encoding
Neutral
encoding
Neu
vs.
a
b
Figure 1 Experimental design and predictions. (a) Experimental design:
separate groups of subjects performed blocks of incidental emotional
and neutral encoding (EN, subjects that performed emotional followed
by neutral encoding; NE, subjects that performed neutral followed by
emotional encoding): two groups encoded stimuli during fMRI scanning
(EN and NE encoding orders), while two other groups of subjects
underwent EN and NE encoding blocks under behavioral testing
conditions (Supplementary Fig. 1) and one other group encoded neutral
stimuli outside of the context of emotional stimuli under behavioral
testing conditions (NN). Encoding blocks were separated by rest periods
(cream boxes). (b) We predicted that arousal associated with emotional
encoding would persist and carry over, prospectively biasing brain activity
during subsequent neutral (neu) encoding and enhancing memory for
neutral stimuli for the EN encoding order. No emotional bias or
carry-over of emotion should be present in the other encoding orders.
A prospective influence of emotion on subsequent neutral encoding
predicts that several factors listed should be differentially present during
neutral encoding for the EN vs. NE encoding order (greater memory,
arousal, emotion-related activity and neural pattern similarity between
emotional and neutral encoding).
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Memory performance
Next, we compared memory for neutral stimuli as a function of
encoding order, to assess whether a long block of emotionally arous-
ing stimuli is capable of prospectively enhancing memory for neutral
stimuli encountered 9 to 33 min later. Memory for stimuli encoun-
tered during the encoding sessions was assessed in a surprise memory
test 6 h later using a remember (R)–know (K) procedure26. We first
assessed whether emotional and neutral memor y differed based
on encoding order in the fMRI study (reported below), as well as
in separate groups of behavioral participants that did not undergo
fMRI scanning (Supplementary Fig. 1). As expected, overall memory
accuracy (proportion of total R and K hits minus false alarms) was
higher for emotional versus neutral stimuli (main effect of emotion:
F1,42 = 16.0, P = 0.00025). However, memory accuracy differed as
a function of encoding order (Fig. 2b and Supplementary Fig. 1;
encoding order by emotion interaction: F1,42 = 10.6, P = 0.0022). As
in the SCL data reported above, no reliable difference in emotional
versus neutral memory was found in the fMRI study when neutral
stimuli were encountered after emotional stimuli (E-N encoding
order; Fig. 2b; t21 = 0.66, P = 0.52), during which emotional arousal
showed evidence of persistence into subsequent neutral encoding (via
enhanced SCL; Fig. 2a). However, a robust enhancement in emotional
memory was found for the opposite N-E encoding order (Fig. 2b;
t21 = 4.37, P = 0.00027), in which no carry-over of emotional arousal
could be present. Our main question concerned whether exposure to
extended blocks of emotionally arousing stimuli could prospectively
enhance memory for neutral stimuli encountered tens of minutes
later. Memory for neutral stimuli was significantly greater when
they were encoded after versus before emotional stimuli and out-
side of the context of emotional stimuli (Fig. 2b and Supplementary
Fig. 1): corrected recognition rates of 62.7% were found in the
E-N encoding order compared to 53.5% in the N-E encoding order
(t42 = 2.06, P = 0.045) and 52.0% and 46.5% in the N-N encoding
order (first and second blocks of N-N encoding order; first block,
t43 = 2.41, P = 0.02; second block, t43 = 3.31, P = 0.002; permutation
test, P = 0.0022). In contrast to neutral stimuli, memory accuracy
for emotional stimuli did not differ between E-N and N-E encoding
orders (Fig. 2b; t42 = −0.78, P = 0.44). Note that the same pattern of
results was observed in separate behavioral groups, with enhanced
levels of memory for neutral stimuli when they were encountered
after emotional stimuli (E-N encoding order) relative to the other
encoding orders (Supplementary Fig. 1). These results demonstrate
that emotion can prospectively enhance memory for neutral stimuli
encountered tens of minutes later.
Given prior work indicating that emotion specifically enhances
the subjective sense of recollection (for example, see ref. 3) we asked
whether the memory benefit for neutral stimuli encountered after
emotional encoding blocks showed the same specificity. Comparing
emotional and neutral memory based on encoding order in the fMRI
study, a significant triple interaction was found between R versus
K responses, emotional versus neutral stimuli and encoding order
(F1,42 = 14.0, P = 0.0006). As predicted, R responses differed for
emotional versus neutral stimuli based on encoding order (emotion
by encoding order interaction: F1,42 = 20.7, P = 4.5 × 105; Fig. 2b
and Supplementary Fig. 1). Consistent with a carry-over or persist-
ence of emotional arousal into subsequent neutral encoding, levels
of emotional and neutral R responses were similar when neutral
stimuli were encountered after emotional stimuli in the fMRI study
(E-N encoding order; Fig. 2b; t21 = 0.49, P = 0.63). However, in
the opposite N-E encoding order, R responses were significantly
higher for emotional compared to neutral stimuli (Fig. 2b; t21 = 5.99,
P = 6 × 10−6). Crucially, similar to the combined memory measure
reported above, R responses were significantly greater for neutral
stimuli when they were encountered after versus before long blocks
of emotional stimuli (Fig. 2b and Supplementary Fig. 1; t42 = 2.16,
P = 0.037) and versus neutral stimuli in the N-N encoding order
(Fig. 2b and Supplementary Fig. 1; first block, t43 = 2.20, P = 0.03;
second block, t43 = 2.87, P = 0.006). This enhancement in neutral R
responses was found for both the fMRI study (reported here) and
the behavioral participants (Supplementary Fig. 1). However, in
contrast to neutral stimuli, R responses for emotional stimuli did
not reliably differ across E-N and N-E encoding orders (t21 = −1.38,
P = 0.17; Fig. 2b and Supplementary Fig. 1). In contrast to recol-
lection-based R responses, K responses did not significantly differ
for neutral versus emotional stimuli across encoding orders (Fig. 2b
and Supplementar y Fig. 1; emotional stimuli, t42 = 0.97, P = 0.34;
neutral stimuli, t42 = −0.48, P = 0.64; emotion by encoding order
interaction, P = 0.09).
Emo
R
~
Relative SCL (µS)
Time (blocks)
~
E N
Overall Memory (R+K)
b
0
0.2
0.4
0.6
0.8
Memory accuracy (hits − FAs)
Emotional
Neutral (E N)
Neutral (N E)
Neutral (N N)
−4
−2
0
2
4
6
8
N E N N
RR
Neu Neu
RRR
Emo Neu
R R R
Neu
E N N E N N
E N N E N N E N N E N N
a
KnowRemember
**
*
*
*
** **
*
**
*
**
**
**
Figure 2 Skin conductance levels and behavioral results. (a) Mean
galvanic SCLs are shown for each encoding order in the fMRI study
(n = 22 for each NE and EN encoding order) and for the NN encoding
order for the behavioral study (n = 23), with each data point representing
data from each subject. Larger (filled) data points indicate means across
subjects. SCL is plotted relative to each subjects’ baseline SCL during the
first rest period. Each encoding block (emotional, emo; neutral, neu) has
three measurements, corresponding to the mean relative SCL during three
encoding scans (or 7.7 min epochs) for that block. Asterisks above data
points denote significant differences in SCL from the first baseline rest
scan (corrected for multiple comparisons in each encoding order).
(b) Memory was assessed for stimuli seen during encoding using a remember
(R)–know (K) procedure. Memory accuracy (hits minus false alarms) is
shown for all hits (combined R and K responses, left bars), R responses
(middle bars) and K responses (right bars) for the fMRI study (EN and
NE encoding orders; n = 22 for each encoding order) and the NN
encoding order (behavioral study, n = 23). See Supplementary Figure 1
for similar results for EN and NE encoding orders in the behavioral
study. All error bars represent s.e.m. across subjects and individual dots
represent data from each subject. ~P = 0.053, *P < 0.05, **P < 0.005.
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The above results indicate that subjective recollection of neutral
stimuli was relatively greater when they were encountered 9 to 33 min
after blocks of emotional stimuli, mirroring enhanced SCL found
during neutral encoding. In contrast to differences in neutral memory
and SCL during neutral encoding, levels of subjective recollection
and SCL during emotional encoding did not consistently differ as a
function of encoding order. This pattern of results was observed in
two independent data sets (during fMRI scanning and in a separate
behavioral study). Together, these findings are consistent with the
notion that long-lasting blocks of emotional arousal can persist on an
extended timescale and prospectively enhance the later recollection
of neutral stimuli encountered at least 9 to 33 min later.
Low-frequency connectivity carry-over effects
Next, we sought to examine evidence for the hypothesis that exposure
to long blocks of emotional stimuli created a specific, arousal-related
brain state that could bias subsequent BOLD activity patterns during
neutral encoding. Given the extended time period of the encoding
sessions (~23 min) as well as the temporal gap between emotional and
neutral encoding (~9 min), the carry-over of such an emotional brain
state may have occurred at a relatively slow timescale (for example, on
the order of minutes). Thus, we reasoned that this brain state might be
manifest in low-frequency (LF) fluctuations in the BOLD signal, i.e.,
BOLD signal changes that were slower than trial-by-trial evoked activ-
ity. Such slow LF fluctuations have previously been shown to track
different behavioral states27–29. To test this hypothesis, we examined
whether patterns of LF connectivity that characterized emotional
encoding blocks carried over or showed evidence of reinstatement
during subsequent neutral encoding blocks (Fig. 3a).
Given the importance of the amygdala in mediating the influence
of emotion on memory and cognition30–32, we asked whether large-
scale patterns of LF amygdala connectivity representative of an emo-
tional brain state showed evidence of reinstatement during neutral
encoding blocks. Such reinstatement would result in greater simi-
larity between emotional and neutral encoding LF amygdala con-
nectivity patterns when neutral stimuli are encountered after versus
before emotional stimuli (E-N versus N-E encoding order). To this
end, we computed LF connectivity across cortical and subcortical
voxels using the amygdala as a seed region. Connectivity was com-
puted separately for each encoding scan in each subject, resulting
in distinct multivariate images or vectors representing LF amy-
gdala connectivity patterns during emotional and neutral encoding
(Fig. 3b). We then asked whether these global patterns of LF amy-
gdala connectivity were more similar (i.e., exhibited higher levels
of correlation) between emotional and neutral encoding blocks
for the E-N encoding order (in which a carry-over of emotional
arousal into subsequent neutral encoding was found) versus the N-E
encoding order (in which no carry-over of emotional arousal should
be present). LF amygdala connectivity patterns were significantly more
correlated (i.e., more similar) during emotional and neutral encod-
ing for the E-N versus the N-E encoding order (Fig. 3b; t38 = 2.42,
P = 0.02). This result indicates that large-scale, multivoxel patterns of
LF amygdala connectivity representative of emotional encoding can
carry over and manifest tens of minutes later when unrelated neutral
stimuli are later encountered.
At a more fine-grained level, we next examined specific interac-
tions between the amygdala and anterior hippocampus, which are
thought to underlie the memory benefit for emotional stimuli9,12,32.
We targeted the anterior hippocampus since it is expected to show
the strongest interactions with the amygdala, based on anatomy33–36
and prior reports of functional correlations between amygdala and
anterior hippocampal BOLD activity37 and since anterior hippoc-
ampal activation is consistently predictive of successful emotional
encoding10. As shown in Figure 4, levels of LF amygdala–anterior
hippocampal connectivity also showed evidence of being rein-
stated or carrying over from emotional to neutral encoding blocks.
First, connectivity during emotional versus neutral encoding differed
as a function of encoding order (emotion by encoding order interac-
tion, F1,38 = 4.57, P = 0.039). Mirroring our behavioral and SCL find-
ings, similar levels of LF amygdala–anterior hippocampal connectivity
were found during emotional and neutral encoding when neutral
stimuli were encountered tens of minutes after emotional stimuli (E-N
encoding order, t19 = −0.82, P = 0.42), but a significant enhancement
in LF connectivity was found during emotional versus neutral encod-
ing for the opposite encoding order (N-E encoding order, t19 = 2.12,
P = 0.048). Moreover, LF amygdala–anterior hippocampal connec-
tivity was significantly greater during neutral encoding blocks when
neutral stimuli were encountered after versus before emotional stimuli
(E-N versus N-E encoding orders; t38 = 2.38, P = 0.023). Yet no reli-
able difference in connectivity was found during emotional encoding
blocks between encoding orders (t38 = 0.97, P = 0.34). This pattern of
results suggests that LF amygdala–anterior hippocampal connectivity,
like overall levels of skin conductance, showed evidence of carrying
over from temporally extended blocks of emotional encoding into
subsequent neutral encoding.
Lastly, we found similar evidence for a carry-over effect in levels of LF
connectivity from emotional into neutral encoding within the ventral
a
Task frequency
Low-frequency fluctuations
Amygdala power
0.05 0.1 0.15 0.2 0.25
Frequency (Hz)
r = 0.73
Low-frequency
filtered BOLD
60 120 180 240
Time during encoding (s)
Amygdala
Anterior hippocampus
b
Emotional-neutral amygdala
correlation pattern similarity (z)
E N N E
0
0.2
0.4
0.6
0.8
1
Emo Neu
Neu Emo
r = 0.77
r = 0.46
Amygdala
seed
*
Figure 3 Low-frequency connectivity as a function of encoding order.
(a) Low frequency connectivity analysis approach. Left: plot shows the
power spectrum of amygdala BOLD encoding data for an example subject.
A peak in the power spectrum can be seen for the task frequency, 0.0714 Hz.
To examine LF connectivity, BOLD data were filtered below 0.06 Hz.
Right: plot shows LF filtered time courses of amygdala and anterior
hippocampus BOLD data from one subject during emotional encoding.
(b) Similarity of multivoxel LF amygdala connectivity patterns between
emotional and neutral encoding blocks as a function of encoding order.
Example data from one subject from the EN encoding order (top left)
and one subject from the NE encoding order (bottom left) are shown.
An example amygdala ROI (used as the seed region) is shown in the left
inset. Images show sagittal slices containing LF connectivity patterns
with the amygdala. Vectors next to each image depict the analysis
approach; the similarity of multivoxel connectivity patterns in each
subject was computed between emotional and neutral encoding blocks.
Right plot shows group data (n = 20 subjects in each encoding order)
for the similarity of multivoxel LF amygdala correlation patterns between
emotional and neutral encoding. Individual data points represent the
similarity (correlation) for each subject. Error bars, s.e.m. *P < 0.05
© 2016 Nature America, Inc., part of Springer Nature. All rights reserved.
nature neurOSCIenCeADVANCE ONLINE PUBLICATION 5
a r t I C l e S
anterior insula (vAI) network (Supplementary Fig. 2). We additionally
probed connectivity in this network as emotion-related activity has
consistently been shown in the vAI (refs. 38–41), and greater levels
of vAI network connectivity have been related to heightened arousal
ratings of the emotional stimuli used in this experiment38.
Taken together, these results provide evidence that emotional brain
states, measured by correlations in LF BOLD fluctuations present dur-
ing emotional encoding, can carry-over and become reinstated tens
of minutes later when participants encountered unrelated, neutral
information. Multiple signatures of emotion-related LF connectiv-
ity showed evidence of carrying over from emotional encoding into
subsequent neutral encoding and were present in both local networks
(for example, amygdala–anterior hippocampal connectivity) and in
global pattern similarity across the brain (in multivoxel amygdala
connectivity patterns).
Event-related subsequent memory carry-over effects
In addition to asking whether correlations in LF fluctuations in the
BOLD signal showed evidence of carry-over from blocks of emo-
tional to subsequent neutral encoding, we also examined whether
emotional encoding prospectively influenced transient, stimulus-
evoked or event-related BOLD activity during subsequent exposure
to neutral stimuli. Given our data suggesting that emotion prospec-
tively enhanced behavioral signatures of memory for subsequently
encountered neutral stimuli, we asked whether the neural structures
supporting memory formation for neutral stimuli were modulated
on a trial-by-trial basis by the prior induction of an emotional state.
Specifically, we compared stimulus-evoked activity related to subse-
quent recollection-based memory (i.e., greater activation for stimuli
later labeled as R versus K) during emotional and neutral encoding
blocks based on the order of encoding blocks, using both univariate
and multivariate approaches. As a function of encoding order, we
compared (i) the similarity of global, multivoxel patterns support-
ing later recollection between emotional and neutral encoding and
(ii) univariate activation predicting subsequent recollection between
emotional and neutral encoding.
First, we asked whether global, multivoxel patterns that charac-
terize recollection-based emotional memory formation were rein-
stated and similarly supported the later recollection of neutral stimuli
encountered after emotional stimuli. Such a reinstatement would
result in greater similarity between multivoxel patterns supporting
later recollection during emotional and neutral encoding when neu-
tral stimuli are encountered after versus before emotional stimuli.
To test this prediction, we measured activation patterns related to
successful recollection-based memory formation (differences in
activation estimates for trials later labeled as R versus K) separately
for emotional and neutral stimuli in each participant (Fig. 5a).
This resulted in multivoxel activity patterns across cortical and sub-
cortical voxels that were characteristic of recollection-based memory
formation, which we then compared between emotional and neutral
stimuli as a function of encoding order. Enhanced levels of similarity,
or correlation, were found between multivoxel patterns supporting
recollection-based memory for emotional and neutral stimuli when
neutral stimuli were encountered after versus before emotional stimuli
(in the E-N versus N-E encoding order; Fig. 5b; t40 = 3.00, P = 0.0046).
A nonparametric permutation test was performed to ensure that this
difference in multivoxel pattern similarity was not driven by differ-
ences in R versus K bin sizes between encoding orders (P = 0.00083;
Supplementary Fig. 3). This result demonstrates that spatially broad
activation patterns related to recollection-based memory formation
were more similar between emotional and neutral stimuli when neu-
tral stimuli were encountered after versus before emotional encoding
blocks. This result suggests that patterns of brain activity support-
ing successful recollection-based memory formation of neutral
Amygdala–anterior
hippocampus correlation (z)
Emo Neu EmoNeu
0
0.5
1
**
Amygdala
Anterior hippocampus
a b
NE
NE
Figure 4 Low-frequency amygdala–anterior hippocampal connectivity as
a function of encoding order. (a) Anatomically defined amygdala (red) and
anterior hippocampus (blue) ROIs are shown for an example subject.
(b) LF amygdala–anterior hippocampus connectivity as a function of
encoding order across n = 20 subjects per encoding order. LF amygdala–
anterior hippocampal connectivity is greater during neutral encoding for
the EN vs. NE encoding order (red vs. blue bars). Individual data
points represent connectivity for each subject. Error bars, s.e.m. *P < 0.05.
SRM emotional–neutral
pattern similarity (z)
Emo Neu
r = 0.22
Neu Emo
r = 0.004
Whole-brain Hippocampus
–0.08
0
0.08
0.16
0
0.1
0.2
0.3 ** *
a
b
N E
E N
N E N EE NE N
Figure 5 Similarity of multivoxel subsequent recollection-based memory
differences between emotional and neutral encoding as a function of
encoding order. (a) Example data are shown from one subject of the
EN encoding order (top) and one subject of the NE encoding order
(bottom). Sagittal slices depict subsequent recollection patterns
(R – K activity estimates) across cortical and subcortical voxels. (b) Group
data for the similarity of multivoxel encoding patterns (activity patterns
supporting subsequent recollection memory (SRM)) between emotional
and neutral encoding based on encoding order (n = 21 subjects per
encoding order). Greater similarity of patterns supporting subsequent
emotional and neutral recollection was found for the EN vs. NE
encoding orders for both global patterns across cortical and subcortical
voxels (whole-brain, left bar plot) and within the hippocampus (right bar
plot). Individual data points represent similarity (correlation) for each
subject. Error bars, s.e.m. *P < 0.05, **P < 0.005.
© 2016 Nature America, Inc., part of Springer Nature. All rights reserved.
6  ADVANCE ONLINE PUBLICATION nature neurOSCIenCe
a r t I C l e S
stimuli were prospectively biased by the presence of prior emo-
tional stimuli tens of minutes earlier, with activation patterns sup-
porting later neutral stimulus recollection being more similar to
emotional encoding patterns when neutral stimuli were preceded by
emotional stimuli.
Next, we examined whether similar effects were found within the
hippocampus, as emotion is thought to enhance recollection-based
memory formation via hippocampal mechanisms1,7–9. Hippocampal
activity patterns showed evidence of carry-over effects or reinstate-
ment of activity patterns representative of emotional encoding dur-
ing subsequent neutral encoding blocks, both in multivoxel patterns
predictive of later recollection (Fig. 5b; t40 = 2.02, P = 0.049) and
in the anterior versus posterior localization of hippocampal voxels
contributing to subsequent recollection36,37 (Supplementary Fig. 4
and Online Methods). These findings indicate that patterns of hip-
pocampal activity supporting recollection-based memory formation
of neutral stimuli were also biased by the presence of prior emotion,
specifically by enhancing the contribution of the anterior hippocam-
pus to memory formation.
Lastly, we asked whether individual brain regions supporting suc-
cessful recollection-based memory formation were more similar
between emotional and neutral stimuli when neutral stimuli were
encountered after emotional stimuli than when neutral stimuli were
encountered before emotional stimuli. To this end, we identified
regions that showed significant subsequent recollection effects (R > K
BOLD responses) for emotional stimuli as well as greater R > K activity
when neutral stimuli were encountered after versus before emotional
stimuli (E-N versus N-E encoding order). This carry-over recollection-
based memory effect was operationalized as brain regions that showed
a conjunction between six contrasts, depicted in Figure 6a (Online
Methods; note that this analysis also controls for differences in R and
K bin sizes based on encoding order). Six regions emerged from this
whole brain conjunction analysis (Fig. 6b; family-wise error (FWE)-
corrected, P < 0.05): the left amygdala, the right perirhinal cortex, the
right posterior inferior temporal gyrus and three regions in bilateral
inferior prefrontal cortex. Similar regions have previously been shown
to predict successful memory formation for emotional versus neutral
stimuli10, and a formal decoding analysis performed on the uncor-
rected conjunction map revealed the highest similarity with terms
“emotional stimuli,” “affect” and “salient” (using neurosynth.org42,
http://neurosynth.org/decode/?neurovault=JOYXPMRX-26012).
Here we found that regions associated with emotional processing and
memory formation were predictive of subsequent neutral memory
when neutral stimuli were encountered after, but not before, extended
blocks of emotional stimuli. The engagement of these additional brain
regions subserving neutral memory formation after emotional arousal
supports the idea that emotion- and encoding-related mechanisms were
reinstated and thus impacted memory formation 9 to 33 min later.
DISCUSSION
It is widely acknowledged that emotion can modulate what and
how we remember. Although prior work has shown that emotion
can retroactively influence memory for preceding neutral experi-
ences5,6,14,15, less is known about how emotional experiences can
linger and prospectively enhance memory formation for neutral infor-
mation encountered many minutes later. We found that exposure to
extended blocks of emotion-evoking stimuli induced a lasting emo-
tional state that enhanced participants’ later recollection of neutral
images encountered 9 to 33 min later, suggesting that the impact of
emotion carried over into and biased subsequent stimulus process-
ing and encoding. We directly queried the persistence or carry-over
of an emotional brain state into subsequent neutral encoding blocks
by analyzing global multivoxel patterns across the brain and activ-
ity in emotion- and arousal-related brain regions. First, we found
that LF fluctuations of the BOLD signal previously shown to track
behavioral or neural states27–29 carried over from emotional encod-
ing into subsequent neutral encoding blocks. These included global
multi voxel amygdala–whole-brain connectivity patterns, as well as
correlated activity in targeted circuits (amygdala–anterior hippoc-
ampus and ventral anterior insula network). Second, we found that
brain regions exhibiting successful encoding effects for neutral stimuli
were also modulated by preceding emotional experiences. Thus, both
large-scale patterns and overall levels of BOLD activity supporting
recollection-based memory formation were reinstated during neutral
encoding after emotional encoding blocks. Together, these findings
provide evidence that the induction of a relatively lasting emotional
state was associated with brain states that could later be reinstated,
biasing the way future neutral events were encoded and potentially
imbuing neutral experiences with emotional properties that enhance
their recollection.
Previous studies of emotion’s influence on memory have demon-
strated that the neurohormonal changes underlying physiological
arousal are critical for mediating emotion-enhanced memory7,8, spe-
cifically subjective recollection43, although these might not be the
only contributing factors. In the present study, we induced an emo-
tional state through the use of stimuli previously rated as subjectively
negative and arousing (compared to stimuli rated as neutral).
We then used SCL, a noninvasive assessment of autonomic arousal,
as our primary measure of emotion25. Notably, increased levels of
emotional arousal induced by the exposure to emotional stimuli
Left IT cortexInferior PFC
Left amygdala Right perirhinal
cortex
y = –6 x = 34
y = 22 y = –60
a b
R R
K K
* *
*
E N
N E
BOLD responseBOLD response
Figure 6 Subsequent recollection-based memory carry-over effects.
(a) Schematic of response patterns required for a subsequent recollection
carry-over effect, or reinstatement of emotional subsequent recollection
effects during later neutral encoding (six-way conjunction analysis).
Regions showed significant subsequent recollection effects or significantly
greater activity estimates for R vs. K trials during emotional encoding
(both encoding orders) and neutral encoding when neutral stimuli were
encountered after emotional stimuli (EN encoding order, red bars).
Regions also showed significantly greater R – K differences between the
three conditions with arrows. Individual contrasts were thresholded at
*P < 0.05. (b) Brain regions showing emotional subsequent recollection
effects that carry over during later neutral encoding, isolated from the
conjunction analysis shown in a. Six regions emerged from this analysis
(shown in red): left amygdala (P = 0.013), right perirhinal cortex
(P = 0.004), left inferior temporal (IT) cortex (P = 0.0088) and three
inferior prefrontal cortex (PFC) regions (two shown; left P = 0.0006,
right P = 0). Results are FWE-corrected at P < 0.05, and the resulting
map was smoothed for visualization. Statistical map is displayed on the
group template anatomical image and can be found in MNI space on
neurovault.org (http://neurovault.org/collections/JOYXPMRX/).
© 2016 Nature America, Inc., part of Springer Nature. All rights reserved.
nature neurOSCIenCeADVANCE ONLINE PUBLICATION 7
a r t I C l e S
persisted in time and likely influenced the encoding, and perhaps
consolidation, of subsequently encountered neutral stimuli, resulting
in increased levels of subjective recollection when the neutral memory
was assessed 6 h later. This enhancement in recollection of neutral
stimuli was observed across two independent data sets. Crucially,
mirroring our behavioral findings, SCL was distinctly higher when
neutral stimuli were encountered 9 to 33 min after emotional stim-
uli versus before emotional stimuli as well as after neutral stimuli.
For these reasons, together with prior evidence linking emotion-
related neurohormonal changes with subjective recollection43, we
believe the subsequent influence of emotion on memory for future
neutral events may be mediated by noradrenergic activation triggered
by the emotional images.
It is important to note that our finding of enhanced memory for
neutral stimuli encoded after emotional stimuli is similar to, but dis-
tinct from, prior demonstrations that emotional arousal or adrenergic
agonists administered after the encoding of neutral stimuli retroac-
tively enhances later memory for neutral information5,16,18,44,45. Post-
learning arousal is proposed to heighten memory consolidation of
preceding neutral information5,16,45. Here we show that pre-encoding
emotional arousal that persists during exposure to neutral stimuli can
prospectively influence both their initial encoding and their recollec-
tion 6 h later. Notably, BOLD activity during neutral encoding tens of
minutes after emotional encoding in many respects resembled BOLD
activity when participants viewed and processed emotional stimuli.
Correspondingly, neutral stimuli encoded during heightened arousal
showed the same mnemonic profile as emotional stimuli (enhanced
recollection) relative to neutral stimuli encoded before and outside
the context of emotional arousal. Taken together, these findings paint
a picture of emotion as capable of biasing neutral memory via multiple
mechanisms: retroactively enhancing the consolidation of previously
encoded information, as well as prospectively biasing future brain
states and mechanisms underlying the encoding of new experiences
into memory.
Our findings that LF connectivity (amygdala–hippocampus and
ventral anterior insula network correlations), subsequent recollec-
tion effects in individual brain regions (amygdala, perirhinal cortex,
inferior prefrontal cortex, inferior temporal cortex) and patterns of
hippocampal recollection effects characteristic of emotional encoding
carried over into subsequent neutral encoding blocks are consistent
with prior work showing that emotion is related to BOLD activity
and connectivity in similar regions10,11,37, 38,41,46,47 (assessed using a
reverse analysis in neurosynth.org42). Notably, however, the present
data extend these findings in several ways. First, consistent with a
carry-over hypothesis, brain regions related to emotional processing
and memory formation were not only engaged when participants
viewed emotional stimuli but also during the subsequent encoding
of neutral stimuli. This result suggests that emotion can bias BOLD
activity over an extended time period (at least 9 to 33 min later).
Second, differences in LF connectivity during emotional and neutral
encoding in the N-E encoding order suggested that emotion mod-
ulated not only trial-by-trial evoked brain activity but also lower-
frequency background BOLD activity. This modulation of background
BOLD activity by emotion complements previous findings showing
that background BOLD activity reflects specific types of information
processing, such as distinct memory states29 and the processing of
distinct stimulus classes27,28.
Although the present study found evidence that an extended
emotional experience could bias future brain states and memory
encoding, we note that it is unclear which specific aspects of our
experimental design were critical for this effect to emerge. In our
design, encoding blocks lasted for 23 min; thus, it is unclear how
much time is necessary to induce a state of emotional arousal that will
persist and bias future behavior. Moreover, it is also unclear how long
emotional arousal may potentially last and whether this is related to
the duration of the initial arousal induction. It is also noteworthy that
participants performed the same task when they encountered emo-
tional and neutral stimuli in our study (rating of visual complexity), so
it is unknown whether this similarity in task context was necessary for
eliciting a carry-over of an emotional state into later neutral encod-
ing. Lastly, it is also unknown how expectations or explicit strategies
developed by participants may have facilitated the reinstatement of
emotional arousal or brain states during neutral encoding. Future
work is needed to understand how these different factors contributed
to the present findings.
The present results add to our understanding of the many ways
emotion can influence memory for unrelated neutral events. When
examining memories for events themselves, there is evidence that
more neutral details of an emotional event may be less well remem-
bered48,49, suggesting a trade-off in memory49,50. However, the
influence of emotion on memory can also extend over time, between
events. Not only can emotional arousal following a neutral event influ-
ence the storage of that event but, to the extent that arousal persists, it
can also influence memory for future neutral events that are tempo-
rally and semantically distinct. Our results suggest that this prospec-
tive memory enhancement may be due to a carry-over of the brain
states that underlie arousal and its influence on memory.
METHODS
Methods, including statements of data availability and any associated
accession codes and references, are available in the online version of
the paper.
Note: Any Supplementary Information and Source Data files are available in the
online version of the paper.
ACKNOWLEDGMENTS
We thank E. Bar-David for expert assistance with data collection for the fMRI
study and A. Patil, M. Kelemu, C. Brennan and D. Antypa for assistance with
behavioral data collection. This work was supported by Dart Neuroscience (L.D.);
NIMH grants MH074692 (L.D.), MH062104 (E.A.P.) and MH092055 (A.T.); and
by grants from the Swiss National Science Foundation (PZ00P1_137126), the
German Research Foundation (DFG RI 1894/2-1), and the European Community
Seventh Framework Programme (FP7/2007-2013) under grant agreement
334360 to U.R.
AUTHOR CONTRIBUTIONS
A.T., U.R., E.A.P. and L.D. designed the experiment and wrote the paper. A.T. and
U.R. collected and analyzed the data.
COMPETING FINANCIAL INTERESTS
The authors declare no competing financial interests.
Reprints and permissions information is available online at http://www.nature.com/
reprints/index.html.
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nature neurOSCIenCe
doi:10.1038/nn.4468
ONLINE METHODS
Subjects. fMRI Study. Fifty right-handed native English speakers with normal or
corrected-to-normal vision participated in the study. Six subjects were excluded,
two due to a high rate of spike artifacts in the fMRI data and four due to very poor
memory performance (miss or false alarm rates > two s.d. above the mean of all
subjects). The average age of the remaining 44 subjects was 24.1 years (range:
19–34) and included 23 male and 21 female participants. Informed consent was
obtained from all participants in a manner approved by the institutional review
board at New York University. No a priori sample size calculations were per-
formed, but the sample size was chosen based on common practices in the field43.
Subjects were assigned to groups (E-N and N-E encoding orders) in alternating
fashion as the data was collected. Age and gender were approximately matched
across encoding orders (E-N: 11 female, 11 male, mean age = 24.9; N-E: 10 female,
12 male, mean age = 23.4).
Behavioral groups. Eighty-two participants with normal or corrected-to-normal
vision participated in the behavioral studies. The E-N and N-E encoding order
groups were collected simultaneously, with participants assigned to groups in
alternating fashion as the data was collected (n = 55 participants total). Most of
the participants were recruited at New York University (31/55, 16 in E-N encod-
ing order, 15 in N-E encoding order) while the rest of the participants were
recruited at the University of Geneva (24/55 participants, 12 in each encoding
order). The N-N encoding order was run as a separate study and consisted of 27
participants, all recruited at New York University. In total, 11 participants were
excluded: one who did not follow the instructions (N-N group) and ten due to
very poor memory performance (miss or false alarm rates > two s.d. above the
mean of all subjects; three N-N participants, four E-N participants and three N-E
participants). Of the remaining 71 participants, 46 were female (mean age: 24.5
years, range: 18–33), resulting in a total of 23 participants for the N-N encoding
order and 24 participants for each of the N-E and E-N encoding orders. Age and
gender were approximately matched across the N-N, E-N and N-E encoding
orders (N-N: 18 female, mean age = 24.96; E-N: 13 female, mean age = 24; N-E:
15 female, mean age = 24.5). Informed consent was obtained from all participants
in a manner approved by the institutional review boards at New York University
and the University of Geneva.
Procedure. fMRI study (E-N and N-E encoding orders). Before entering the scan-
ner, subjects were informed about the scanning procedures and performed a
brief practice session of the image complexity task to be performed during the
encoding sessions as well as a one-back task used for localizer scans. Prior to
scanning, electrodes were placed on the index and middle fingers of the subject’s
right hand to measure galvanic SCL.
During the scanning session, subjects performed incidental encoding blocks
(emotional and neutral encoding) interleaved with rest scans (Fig. 1a). The order
of the encoding blocks was counterbalanced across subjects, such that half of
the subjects performed emotional followed by neutral encoding (referred to as
the E-N encoding order) and the other half of the subjects performed neutral
before emotional encoding (referred to as the N-E encoding order). Additional
scans were collected after the last rest scan but were not used in the present
analyses (localizer scans in which subjects viewed scenes, objects and other stimu-
lus categories). A high-resolution anatomical scan was collected after all func-
tional scans. After the scanning session, subjects returned to the lab to perform
a surprise memory test for stimuli encountered during emotional and neutral
encoding, approximately 6 h after the last encoding session. Subjects were not
informed before the scanning session that their memory would be tested for
stimuli encountered during the encoding sessions.
By necessity, data collection and analysis were not performed blind to the
conditions of the experiments. However, subjective outcome assessments were
not performed.
Behavioral groups (N-N, N-E and E-N encoding orders). The same experimental
procedures used in the fMRI study were used in the behavioral groups, except
that all procedures took place outside of the MRI scanner and participants in the
N-N encoding order incidentally encoded two blocks of neutral stimuli instead
of blocks of emotional and neutral stimuli. Subjects were exposed to an auditory
stimulus of white noise during encoding and during rest periods in between
encoding blocks to resemble the constant noise during fMRI scanning. A surprise
memory test for neutral stimuli was administered with the same delay (6 h) as
the fMRI study.
Encoding sessions. All fMRI participants and E-N and N-E behavioral groups
incidentally encoded both emotional and neutral stimuli in separate blocks (emo-
tional and neutral encoding). In the N-N behavioral group, subjects incidentally
encoded two separate blocks of neutral stimuli. During encoding, subjects rated
the visual complexity of complex scenes. Each block consisted of three 7.7-min
scans or epochs and contained a total of 99 trials (33 trials in each scan). The
order of stimulus presentation was randomized for each subject. Each trial lasted
for 14 s and included a 1-s fixation cue, presentation of a complex scene for 2 s, a
response window of 1 s, followed by the performance of a baseline ‘arrows’ task for
10 s in between trials51. Subjects were instructed to view each image for as long as
it remained on the screen and examine the visual complexity of each image. The
response window contained the words “Complexity?” and “High Medium Low.”
Subjects pressed their ring, middle or index finger of their left hand to indicate
complexity ratings of high, medium or low, respectively. During the arrows task,
a series of arrows were presented pointing either left, up, or right on the screen.
Subjects were instructed to push their ring finger when the arrow pointed to the
left, their middle finger when the arrow pointed up and their index finger when
the arrow pointed to the right.
Memory test. Approximately 6 h after the end of the last encoding session,
all subjects completed two separate memory tests (one for each encoding
session) outside of the scanner. The order of the memory tests matched the order
of their presentation during encoding, to roughly equate the study–test inter-
vals across the two encoding sessions. Each trial consisted of the presentation
of a complex scene, and subjects performed a remember (R), know (K) or new
(N) judgment.
Subjects were trained on R, K and N decisions before the start of the memory
test26. After reading detailed instructions, participants explained the meaning
of R and K judgments in their own words. During the practice trials, subjects
indicated why they judged a scene as remembered or known out loud to the
experimenter. The recognition test was administered once the participants had
correctly understood the instructions, i.e., they judged a scene as remembered
when it brought back to mind a specific detail from the episodic context in which
the scene had been experienced, such as a sensory detail, a thought or a feeling.
Memory tests were self-paced and contained 198 trials each. Half of the stimuli
(99) in the memory test were novel distractor scenes and half were those pre-
sented during the encoding session. For the fMRI study and the E-N and N-E
behavioral groups, the stimulus sets presented at encoding and test were coun-
terbalanced across encoding orders: for half of the subjects stimulus set 1 was
used during the encoding session and stimulus set 2 was used as distractors in the
memory test; the other half of the subjects viewed stimulus set 2 during encoding
set 1 as distractors in the memory test. For the N-N behavioral group, four neutral
stimulus sets were created and counterbalanced across subjects with respect to
the first versus second stimulus set during encoding and with respect to serving
as encoding or distractor sets during memory testing. Stimulus sets for both the
fMRI and behavioral studies were matched for image complexity and the presence
of people, animals, inanimate objects and scenes.
Stimuli. The complex scenes used in all encoding sessions spanned 465 ×
620 pixels.
fMRI study and E-N and N-E behavioral groups. The complex scenes used in
the encoding sessions were drawn from the International Affective Picture Set
(IAPS)52 as well as a few in-house stimuli (Supplementary Table 1). Stimuli
were classified as emotional or neutral based on the normative ratings provided
for emotional arousal (emotional scenes: M = 5.65, s.d. = 0.82; neutral scenes:
M = 3.92, s.d. = 0.96) and valence (emotional scenes: M = 2.83, s.d. = 0.92; neutral
scenes: M = 5.94, s.d. = 1.00) assessed with the Self-Assessment Manikin (SAM)
scale (1 = calm, 9 = excited; 1 = unhappy, 9 = happy)52. Stimuli used for emo-
tional and neutral encoding as well as for the encoding versus distractor sets in
the memory test were matched for image complexity and the presence of people,
animals, inanimate objects and scenes.
N-N behavioral group. In addition to the 198 neutral stimuli used in the fMRI
study, another 198 neutral complex scenes were added to the stimulus set to
construct two blocks of stimuli for neutral encoding for the N-N encoding order.
Stimuli were taken from the IAPS52, the Necki Affective Picture System53 and our
own images. As in the fMRI study, stimuli were selected based on normative rat-
ings provided for emotional arousal (M = 3.98, s.d. = 0.79) and valence (M = 5.99,
© 2016 Nature America, Inc., part of Springer Nature. All rights reserved.
nature neurOSCIenCe doi:10.1038/nn.4468
s.d. = 0.95) assessed with the SAM scale described above. Note that arousal and
valence ratings for neutral stimuli were well-matched across the E-N/N-E encod-
ing orders and the N-N behavioral group. The stimuli were classified into four sets
of 99 neutral photos, which were matched for image complexity, the presence of
people/animals, inanimate objects and scenes and which did not differ between
emotional arousal and valence (all P-values > 0.85).
Rest scans. Each rest scan lasted for 9 min. Subjects were instructed to close
their eyes and simply rest and think about anything that they wanted but to try to
remain awake54,55. We used only the fMRI data from the first rest scan in the cur-
rent analyses, to isolate regions in the ventral anterior insula (vAI) network38.
Behavioral analyses. Memory for emotional and neutral stimuli was assessed
by examining proportions of hits and false alarms for each encoding order (E-N,
N-E and N-N), collapsed across R and K responses (overall memory accuracy),
as well as separately for R and K responses. To analyze memory as a function of
emotion and encoding order (fMRI study and behavioral groups), mixed-effects
ANOVAs were performed on corrected memory accuracy rates (proportion of
hits minus false alarms) with a within-subjects factor of emotion (emotional and
neutral stimuli) and a between-subjects factor of encoding order (E-N and N-E
encoding orders). Separate ANOVAs were performed for all hits and false alarms
(combined R and K responses) and for R and K responses separately. Follow-up t-
tests were performed to investigate differences in memory between emotional and
neutral stimuli within encoding orders (paired t-tests) as well as between encod-
ing orders (unpaired t-tests). To assess whether neutral memory was enhanced
when they were encoded after emotional versus after neutral stimuli (E-N ver-
sus N-N encoding orders), we performed planned comparisons between cor-
rected neutral memory accuracy (combined R and K responses and R responses
alone) in the E-N encoding order versus both blocks in the N-N encoding order
(behavioral study) using an unpaired t-test. All memory data were determined
to be normally distributed (using a Lilliefors test; see “Statistics” below) with the
exception of overall memory accuracy (combined R and K responses) for the
second block of neutral stimuli in the N-N encoding order. We thus additionally
performed nonparametric permutation tests when statistically evaluating this
data (when comparing neutral memory in the N-N encoding order to the E-N
encoding order, for both the fMRI and behavioral studies). To do so, we com-
puted the true difference in memory across each of these comparisons. We then
derived a null distribution of the difference in memory across these conditions
by performing 10,000 null simulations in which the group labels (E-N or N-N
encoding order labels) were randomly shuffled and the difference in memory for
each null permutation of the data was computed. The true difference in memory
was compared to this null distribution to estimate a P-value for these comparisons
(see “Results” and Supplementary Fig. 1).
Skin conductance level analyses. In order to examine differential levels of arousal
based on encoding order, mean skin conductance levels (SCL) were analyzed,
which have been related to sympathetic nervous system activation (see ref. 25
for a review). Specifically, mean SCL was computed in each subject for each rest
and encoding scan (fMRI study) or each rest and encoding block (N-N behav-
ioral study). Relative SCL changes were then used as our dependent measure of
interest, which were computed for each encoding and rest block by subtracting
mean SCL measured during the pre-encoding baseline rest period from mean
SCL during each encoding and rest block (for both the fMRI and N-N behavioral
group). This procedure of computing SCL changes relative to a baseline period
controlled for individual differences in SCL and allowed us to compare SCL
across different groups of subjects (E-N encoding order versus other encoding
orders). To compare relative SCL during emotional versus neutral encoding as a
function of encoding order (in the fMRI study), a mixed-effects two-way ANOVA
was performed with a within-subjects factor of emotion (emotional and neutral
encoding blocks) and a between-subjects factor of encoding order (E-N/N-E).
Follow-up t-tests were used to examine elevated SCL relative to baseline rest
before encoding (t-test in relative SCL versus zero, corrected for multiple com-
parisons across encoding and rest blocks) and differences in relative SCL during
neutral encoding in the E-N versus N-E and N-N encoding orders (unpaired
t-tests). One-tailed t-tests were used to assess differences in relative SCL during
neutral encoding as a function of encoding order, as we specifically hypothesized
that the presence of prior emotional encoding would enhance SCL during neutral
encoding compared to the opposite encoding order (i.e., neutral encoding SCL
would be higher for the E-N versus N-E and N-N encoding orders). However,
relative SCL data distributions were found to be not normally distributed for sev-
eral blocks of interest. We thus also performed nonparametric permutation tests
for all statistical tests involving SCL. The same methods were applied as in the
permutation tests as described for the memory analyses (see “Behavioral analy-
ses”). Null simulations were performed in which the data labels were randomly
permuted and the comparison of interest was computed. The true difference of
interest was then compared to the null distribution generated for that particular
test. To assess the significance of the encoding order by emotion interaction
observed in SCL, we computed the effect of interest as the difference in emotional
versus neutral encoding SCL across encoding orders (E-N emotional encoding
SCL – E-N neutral encoding SCL – (N-E emotional encoding SCL – N-E neutral
encoding SCL)) and compared this true difference to a null distribution derived
from permuting E-N and N-E encoding order labels for each participant.
MRI data acquisition. Scanning was performed using a 3T Siemens Allegra MRI
system with a whole-head coil. Functional (BOLD) data were collected using
a gradient-echo planar pulse (EPI) sequence (repetition time (TR) = 2 s, echo
time = 30 ms; field of view = 192 mm; 31 slices oriented perpendicular to the long axis
of the hippocampus; 3 × 3 × 3 mm voxel size; 0.6 mm interslice gap; flip angle = 80°).
Functional scans contained 231 or 270 volumes or TRs for the encoding and rest
scans, respectively, after discarding the first four volumes to allow for T1 equili-
bration. High-resolution T1-weighted (magnetization-prepared rapid-acquisition
gradient echo) images were acquired after the last functional scan.
MRI preprocessing. The imaging data were preprocessed using SPM5 (Wellcome
Department of Cognitive Neuroscience, University College London, London,
UK). The BOLD data were first corrected for differences in slice timing acquisi-
tion followed by motion correction across all runs and the removal of low fre-
quency trends (< 0.009 Hz) from each scan. Each subject’s functional data were
then co-registered to their own T1-weighted anatomical image. For the definition
and analysis of anatomically defined regions of interest (ROIs; for example, amy-
gdala) as well as the analysis of whole-brain activity and connectivity patterns, the
functional data were analyzed in a subject-specific space and spatially smoothed
with a 6-mm full-width at half-maximum (FWHM) isotropic Gaussian kernel.
For group-level analyses, a group-level anatomical template was created using
advanced normalization tools (ANTs)56 based on the T1-weighted anatomical
images of all 44 subjects. Statistical maps from native subject spaces were then
transformed into this template space for group analyses.
Noise corrections were applied to the BOLD data from all encoding and rest
scans based on methods from Behzadi et al. (aCompCor)57. A nuisance ROI was
generated from white matter (WM) and cerebrospinal fluid (CSF) probabilistic
maps (see “Anatomical masks,” below). The WM and CSF maps were converted
to functional resolution and thresholded at probability values of 0.98 or 0.99 for
the WM maps and at 0.97, 0.98 or 0.99 for the CSF maps. After thresholding,
the WM mask was eroded by two voxels to avoid contaminating the WM signal
with GM signal57. We used an iterative procedure for defining the probability
threshold for each subject, such that the highest threshold was used with the
stipulation that the resulting CSF or eroded WM mask contained a minimum
of 10 voxels at functional resolution. On each iteration (for a given probability
threshold) we additionally excluded voxels from the nuisance ROI if their time-
course during any one encoding scan was modestly correlated (P < 0.2) with a
model of task activity57 (with task activity modeled as a 4-s boxcar corresponding
to fixation, stimulus presentation and the response window, convolved with the
canonical hemodynamic response function, HRF). The resulting voxels from
the thresholded WM and CSF maps were then combined to form one nuisance
ROI for each subject.
In order to extract dominant signals accounting for substantial variance in the
BOLD signal from the nuisance ROI, principal components analysis (PCA) was
performed on the BOLD data from the nuisance ROI. PCA was performed on the
z-scored BOLD data (note that LF trends were already removed from the data),
separately for each encoding scan and rest scan. We then performed simulations
to determine the number of principal components (PCs) to extract from the
nuisance ROI data for each scan. A null distribution of the expected eigenvalues
was generated separately for the encoding and rest data for each subject by per-
forming PCA on normally distributed data of equal rank to the encoding and rest
© 2016 Nature America, Inc., part of Springer Nature. All rights reserved.
nature neurOSCIenCe
doi:10.1038/nn.4468
nuisance ROI data57. PCs from the true nuisance ROI data were then selected for
a given encoding or rest scan if their associated eigenvalues exceeded the 99%
confidence interval of the eigenvalues from the simulations. However, if different
numbers of PCs were chosen across any of the encoding and rest scans for each
subject, then the minimum number of PCs selected across all scans was used
for all scans. This procedure ensured that removal of any nuisance signals was
consistent across all encoding and rest scans, to avoid differentially biasing the
data in any particular scan. After selecting the number of PCs for the encoding
and rest data for the nuisance ROI, the associated temporal projection of each
selected PC was removed from the whole-brain BOLD data, in conjunction with
the six motion parameters estimated during processing, using linear regression
in a voxelwise fashion. TRs surrounding time periods of sudden motion (see
below for definition) were not included in the estimation of beta coefficients in
this regression58,59.
Additional measures were taken to address the influence of motion on BOLD
data and connectivity estimates, which was not completely addressed by the nui-
sance regression approach taken above60,61. All encoding and rest BOLD data
were temporally censored or ‘scrubbed’, such that TRs surrounding time peri-
ods of sudden motion were removed from the analyzed data61. To accomplish
this, we calculated frame-wise displacement (FD) of head motion based on the
motion parameters estimated during preprocessing61, and TRs including and
surrounding (1 TR before, 2 TRs after) FD values greater than 0.5 mm were
flagged to be scrubbed.
The scrubbing procedure was first performed at multiple levels: first, in the
estimation of beta coefficients when regressing nuisance signals from the BOLD
data58,59. For the encoding data analyzed via the general linear model (GLM;
analyses shown in Figs. 5 and 6 and Supplementary Figs. 2 and 3), the flagged
time points were removed from the BOLD data and the design matrices. For LF
connectivity analyses, the flagged data points were removed after the time-series
were low-pass filtered but before the estimation of correlation values. After this
scrubbing procedure was performed, a substantial number of time points were
missing for a small subset of subjects. Subjects were excluded from LF connec-
tivity analyses if less than 5 min of data were remaining in any given scan60. For
the encoding data, this included n = 2 subjects for emotional encoding and n = 1
subject for neutral encoding; for the data from the first rest scan, this included n
= 1 subject. Since a major goal was to compare connectivity between emotional
and neutral encoding as a function of encoding order (see below), we excluded
n = 4 total subjects from LF connectivity analyses (2 from each encoding order)
to obtain equal bin sizes across E-N and N-E encoding orders (one additional
subject from the E-N encoding order that had the most censored time points
was excluded).
Anatomical ROI definition. FSLs FIRST segmentation was used to define the
amygdala and hippocampus, based on each subject’s high-resolution T1-weighted
scan. All ROIs were manually inspected and edited when appropriate to ensure
proper definitions according to Pruessner et al.62. The hippocampus was then
divided into anterior, middle and posterior portions by splitting the coronal sec-
tions into thirds along the anterior–posterior axis.
Anatomical masks. SPM5 was used to create white matter (WM), cerebrospinal
fluid (CSF) and gray matter (GM) probabilistic maps based on each subject’s
T1-weighted anatomical image. To create a mask of voxels in the cerebral cortex,
each subject’s anatomical image was parcellated using FreeSurfer, and all voxels
labeled in any structure in the cerebral cortex were combined to create a mask
of the cortex63. To create a mask of voxels in subcortical structures, FSL’s FIRST
segmentation was used and all voxels in any subcortical structure were combined
to form one subcortical mask.
Ventral anterior insula network analyses. The BOLD data from the first rest
scan was used to define regions in the ventral anterior insula (vAI) network38. To
accomplish this, the rest data were low-pass filtered (< 0.1 Hz) after the removal of
nuisance signals. MNI coordinates from a previously reported study were used to
define a seed region in the right vAI (ref. 38). To extract the time-course of the vAI
from these coordinates, we co-registered our group template brain to the MNI
template brain, computed the location of the MNI coordinates in our group tem-
plate space and then extracted the time course of the vAI in native subject space
using the inverse normalization procedure in ANTs. The correlation between this
vAI seed and all voxels in the brain were computed in native space, after discard-
ing time points flagged from the scrubbing procedure (see “MRI preprocessing”).
The resulting correlation values were Fisher z-transformed, transformed into
our group template space and averaged across subjects. This average correlation
map was thresholded at z > 0.35 to define four regions in the vAI network (bilat-
eral vAI, medial prefrontal cortex and posterior cingulate cortex, as in ref. 38;
Supplementary Fig. 2). To compute connectivity within this network during
encoding blocks, the group level ROIs comprising the vAI network were inverse-
normalized into native subject space, and the average of the pairwise correlations
between these ROIs was computed for each encoding scan.
Low-frequenc y encoding connectivity analyses. To examine low-frequency
(LF) connectivity during encoding blocks, the BOLD data were low-pass
filtered (< 0.06 Hz) below the task frequency of 0.0714 Hz (Fig. 3a). Before
computing connectivity, time points flagged from the scrubbing procedure
(see “MRI preprocessing”) were removed. Since each encoding block was
comprised of three scans, the scrubbed data were first z-scored within each
scan and then the data was concatenated across scans for each encoding block.
Pearson correlation coefficients were then computed between the concatenated
BOLD time-courses in each encoding block and correlation coefficients were
Fisher z-transformed.
First, we compared the global similarity (correlation) of multivoxel LF amy-
gdala connectivity patterns between emotional and neutral encoding blocks as
a function of encoding order (Fig. 3b). Multivoxel LF connectivity (correla-
tion) patterns with the amygdala were computed using the bilateral amygdala
LF filtered time-course. The Fisher z-transformed correlation value (measur-
ing connectivity with the amygdala) was then extracted for all voxels that were
labeled as gray matter (value of 0.3 or greater using the probabilistic GM mask
created in SPM5) and fell within a mask of cortical or subcortical structures (see
Anatomical masks”). Voxels that fell in the amygdala ROI were excluded from
this analysis, although the exclusion of these voxels did not modify the results.
To measure the similarity of multivoxel LF amygdala connectivity patterns
between emotional and neutral encoding blocks, the Pearson correlation was
computed between the LF amygdala connectivity patterns during emotional and
neutral encoding across these cortical and subcortical voxels. These correlation
values (representing similarity of amygdala connectivity patterns between emo-
tional and neutral encoding blocks) were Fisher z-transformed, and the difference
between multivoxel pattern similarities for E-N versus N-E encoding orders was
assessed using an unpaired t-test (Fig. 3b).
To compare levels of LF connectivity between ROIs as a function of encod-
ing order (Fig. 4 and Supplementary Fig. 2), two-way mixed-effects ANOVAs
were performed on the z-transformed correlation values in each encoding block
using a within-subjects factor of emotion (emotional/neutral) and a between-
subjects factor of encoding order (E-N/N-E). Additional follow-up t-tests were
performed to assess differences based on emotion within encoding order as well
as differences between neutral encoding connectivity as a function of encoding
order. Paired t-tests were used to evaluate differences within an encoding order
as a function of emotion (between emotional and neutral encoding blocks), and
unpaired t-tests were used to evaluate differences across encoding orders between
condition types (i.e., neutral encoding connectivity as a function of encoding
order).
Subsequent memory analyses. GLMs were used to measure BOLD activation
associated with different levels of subsequent memory, specifically activity that
tracked future levels of recollection-based memory. To do so, separate regressors
were included for: (i) subsequent R, K and missed (M) trials (trials labeled ‘new’ at
test), modeled as 2-s boxcars; (ii) stimulus-preceding fixation periods (modeled
as 1-s boxcars); and (iii) response periods (modeled as 1-s boxcars), such that the
arrows task served as an implicit baseline. Each regressor was convolved with the
canonical HRF. GLMs were estimated for emotional and neutral encoding blocks
in native subject specific space (Fig. 5). For group level analyses, the resulting
contrasts (R – K trials) were normalized into our group template space (Fig. 6).
Two subjects were excluded from all subsequent recollection analyses: one
subject in the E-N encoding order had less than two K responses for emotional
stimuli and another subject from the N-E encoding order with the fewest number
of R or K responses whose exclusion served to match the number of subjects
from both encoding orders.
© 2016 Nature America, Inc., part of Springer Nature. All rights reserved.
nature neurOSCIenCe doi:10.1038/nn.4468
To assess multivoxel patterns of subsequent recollection effects across the brain
and whether subsequent recollection patterns were more similar between emo-
tional and neutral encoding for the E-N versus N-E encoding order, subsequent
recollection effects were computed as the difference in activity estimates (beta
coefficients) for subsequent R – K trials. This R – K effect was then extracted
for all voxels that were labeled as gray matter (value of 0.3 or greater in a proba-
bilistic GM mask) and fell within a mask of cortical or subcortical structures
(see “Anatomical masks”). The Pearson correlation was then computed for each
subject between the emotional and neutral subsequent recollection patterns
across these voxels. Resulting correlation values were Fisher z-transformed and
the difference between the similarities for the E-N versus N-E encoding order
was assessed using an unpaired t-test (Fig. 5).
To ensure that differences in multivoxel subsequent recollection patterns
between emotional and neutral encoding based on encoding order were not
potentially driven by differences in R and K bin sizes across encoding orders
(as an interaction between R versus K responses, emotion and encoding order
was observed), a nonparametric permutation test was used that controls for dif-
ferent bin sizes across comparisons. Simulations were performed (n = 1,000) to
generate a null distribution of the expected effect size of interest (difference in
similarity between emotional and neutral R – K patterns between the E-N and
N-E encoding orders) that would arise by chance based on the properties of the
data while shuffling the conditions of interest (activity related to true subsequent
recollection differences). For each simulation, a new design matrix was created for
each subject by randomly shuffling the subsequent memory labels. The GLM was
then recomputed, the resulting subsequent recollection effects (R K activity esti-
mates) were recorded and the similarity between the null multivoxel emotional
and neutral subsequent recollection patterns was computed for each simulation
in each subject. The true difference was then compared to the null distribution
of differences to assess statistical significance (Supplementary Fig. 3).
To examine the presence of univariate carry-over on subsequent recollection
effects (Fig. 6), i.e., subsequent recollection effects that were present during
emotional encoding and persisted into subsequent neutral encoding for the E-N
encoding order, we performed a series of conjunctive tests. Based on the R versus
K activity estimates, a carry-over effect on subsequent recollection was operation-
alized as a conjunction of the following effects (depicted in Fig. 6a):
• Emotional encoding R > K for E-N encoding order;
• Emotional encoding R > K for N-E encoding order;
• Neutral encoding R > K for E-N encoding order;
Neutral encoding R – K for E-N encoding order > neutral encoding R – K
for N-E encoding order;
Emotional encoding R – K for E-N encoding order > neutral encoding
R – K for N-E encoding order;
Emotional encoding R – K for N-E encoding order > neutral encoding
R – K for N-E encoding order.
In other words, regions emerging from this contrast had to demonstrate sig-
nificant emotional subsequent recollection effects for both encoding orders, a
significant subsequent recollection effect during neutral encoding for the E-N
encoding order, with the stipulation that all of these subsequent recollection
effects had to be greater than the subsequent recollection effect when this emo-
tional carry-over effect should not be present (during neutral encoding when
it occurred before emotional encoding). All individual tests were thresholded
at P < 0.05 using a one-tailed t-test, as the directionality of all differences was
uniquely specified, and the conjunction of the above contrasts was performed.
Null simulations described above were performed to determine the voxel extent
that resulted in a whole-brain family-wise error (FWE) rate of P < 0.05 for this
conjunction analysis64. These null simulations were performed in normalized
template space rather than native subject space (used for null simulations for
subsequent recollection pattern analyses). For each null simulation, a new design
matrix was created by shuffling the subsequent memory labels of each subject,
GLMs were recomputed for each encoding order, the above contrasts were per-
formed and the cluster sizes resulting from the above conjunction analysis were
recorded. This approach generated a null distribution of cluster sizes associated
with a specific contrast (in this case a conjunction analysis). The cluster size
(73 voxels) was chosen as the smallest cluster for which the probability of observ-
ing this cluster size was less than 0.05 across 1,000 simulations.
We also assessed whether emotion-related activity predictive of subsequent
recollection was localized within the anterior versus posterior hippocampus,
based on prior notions that the amygdala should predominantly influence the
anterior hippocampus during emotional memory formation33,36,37. We then
examined whether such an anterior versus posterior bias was present dur-
ing neutral encoding when neutral stimuli were encountered after extended
blocks of emotional stimuli (E-N encoding order). To do so, we simply meas-
ured the anterior versus posterior position all voxels showing subsequent
recollection-based encoding effects (all voxels showing R > K activity esti-
mates) in each subject on a scale of −1 (fully posterior) to +1 (fully anterior).
This resulted in an anterior versus posterior bias score for all subjects, sepa-
rately for emotional and neutral encoding blocks. This measure was found to
not be normally distributed (using the Lilliefors test) for emotional encoding
in the N-E encoding order. We thus computed both parametric and nonpara-
metric permutation tests when assessing differences in the anterior–poste-
rior hippocampal subsequent recollection memory bias score as a function
of encoding order. Permutation tests were performed in the same manner as
described for memor y performance and SCL (see “Behavioral analyses” and
“Skin conductance level analyses”).
Statistics. To examine the impact of encoding order on SCL, memory accuracy
and neural measures, the data were first analyzed using mixed-effects ANOVAs
including within-subjects factors of emotion and between-subjects factors of
encoding order. Follow-up t-tests were used to examine differences between
emotional and neutral encoding within each encoding order (paired t-tests) and
between encoding orders (unpaired t-tests). All of the t-tests performed were two-
tailed, with the exception of the SCL data (as described in “Skin conductance level
analyses” and noted in the “Skin conductance” subsection of “Results”), as well
as when examining carry-over subsequent recollection effects at the whole-brain
level, since the direction of the subsequent memory effects were uniquely speci-
fied (Fig. 6; described in “Subsequent memory analyses”). Multiple comparison
corrections were performed for the SCL data (comparing relative SCL across
multiple scans versus zero in each encoding order in Figure 2a; described inSkin
conductance level analyses”) as well as for the whole-brain analysis in Figure 6
(described in “Subsequent memory analyses”). The normality of data distribu-
tions was tested using the Lilliefors test. All data were found to be normally
distributed (did not reach significance to reject the null hypothesis that the data
were derived from a normal distribution) with the exception of mean SCL during
several blocks, overall memory accuracy (R + K hits) for the second block of the
N-N encoding behavioral group and the anterior–posterior bias scores of hip-
pocampal subsequent recollection memory for one of the four encoding blocks
(emotional encoding in N-E encoding order). Thus, tests of statistical significance
involving these data were performed using both parametric and nonparametric
permutation tests (both statistical tests were reported and resulted in the same
interpretation for all data). Note that nonparametric permutation tests were also
used for subsequent memory analyses (see “Subsequent memory analyses”).
Data and code availability. The data that support the findings of this study
are available on reasonable request from the corresponding author (L.D.).
The data are not publicly available because they contain information that could
compromise research participant privacy/consent. The statistical map associ-
ated with the whole brain conjunction analysis in Figure 6 is available (in MNI
space rather than group template space) on neurovault.org (http://neurovault.
org/collections/JOYXPMRX/). Standard software packages (SPM5 and FSL)
were used for processing the MRI data in addition to custom Matlab scripts.
Custom-written code is available upon reasonable request to the corresponding
author (L.D.).
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... Nevertheless, how visual signals modulate spatial representations in the hippocampus and how information propagates to the hippocampus is still unknown. To investigate this, we advocate that widefield cortical voltage recordings may provide important details on the visual integration mechanism [16,32,33]. Towards this goal, we show here that the activity from the visual cortex propagates to other higher cortical areas that are interconnected, such as the hippocampus, retrosplenial, cingulate and parietal cortices [32,34]. ...
... Here, we showed that activity in the hippocampus can have different temporal and spatial dynamics to cortical activity. On a broad neocortical level, the reactivation of memory has previously been observed [33,35]. Together with our result, we can speculate that information about hippocampal events such as replays or the formation of cell assembles are transmitted to specific cortical circuits. ...
... This line of transgenic mouse expresses a GEVI specifically in pyramidal neurons across all cortical layers. Macroscopic epifluorescence imaging restricts the optical access to the superficial cortex [16,17,32,33]. Animals were housed under a 12 h light/dark cycle with ad libitum water and food access. ...
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A new generation of optogenetic tools for analyzing neural activity has been contributing to the elucidation of classical open questions in neuroscience. Specifically, voltage imaging technologies using enhanced genetically encoded voltage indicators have been increasingly used to observe the dynamics of large circuits at the mesoscale. Here, we describe how to combine cortical wide-field voltage imaging with hippocampal electrophysiology in awake, behaving mice. Furthermore, we highlight how this method can be useful for different possible investigations, using the characterization of hippocampal–neocortical interactions as a case study.
... More generally, social information 19,20 and emotional experiences [21][22][23] tend to exert long-lasting influences on our mental context, in many cases intruding on our thoughts against our will 24,25 . Intuitively, it seems that these meaningful, real-world experiences affect our subsequent thoughts in a manner that goes beyond lexical or semantic priming. ...
... Beyond improving memory, stories also have lasting consequences on how we behave and what we believe [49][50][51][52] . Other examples of situationlevel information, like social interactions and emotions, also share this sticky or enduring quality: persisting in our thoughts [19][20][21] and shaping how we learn and remember [22][23][24][25] . Critically, by using free association and a story-scrambling procedure, we were able to directly quantify this lingering phenomenon in spontaneous thought while relating it to one's ability to extract situation-level meaning. ...
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Some experiences linger in mind, spontaneously returning to our thoughts for minutes after their conclusion. Other experiences fall out of mind immediately. It remains unclear why. We hypothesize that an input is more likely to persist in our thoughts when it has been deeply processed: when we have extracted its situational meaning rather than its physical properties or low-level semantics. Here, participants read sequences of words with different levels of coherence (word-, sentence-, or narrative-level). We probe participants’ spontaneous thoughts via free word association, before and after reading. By measuring lingering subjectively (via self-report) and objectively (via changes in free association content), we find that information lingers when it is coherent at the narrative level. Furthermore, and an individual’s feeling of transportation into reading material predicts lingering better than the material’s objective coherence. Thus, our thoughts in the present moment echo prior experiences that have been incorporated into deeper, narrative forms of thinking.
... Additionally, enduring characteristics like personal preferences, personality traits, expectations, or cultural constraints may impact the recalled episodes and how individuals relate to them (Higgs, 2016;Nisbett and Wilson, 1977). Interestingly, perceptions that were encoded together with an arousing emotional state have a higher probability to be vividly and confidently recalled and are forgotten more slowly (Berntsen and Rubin, 2002;Plutchik and Kellerman, 2013;Tambini et al., 2017). In other words, emotions are components of episodes that survive extinction over time, as they are consolidated more strongly and retrieved more quickly than perceptual components alone (LeDoux, 1996). ...
... In the lapse of three months, they may have had several opportunities to re-visit (recall) together stored episodes of food from long-term memory, to share and bring their opinions about dishes into agreement, or to re-consider their experience and their emotions about it (e.g., Barsade, 2002;Barthomeuf et al., 2009). The outcome might be an implicit post-experience process of re-elaboration and re-stored back into long-term memory, and a final re-consolidation and strengthening (Cowley, 2007;Tambini et al., 2017). However, we have to concede that our evidence about the effect of social communication on emotional episodic memory is indirect and the suggested conclusions are speculative. ...
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For theoretical and practical reasons, it is of great interest to understand how accurate and persistent episodic memories of enjoyable experiences are formed and maintained, for example, in the context of gastronomy and other instances of experience design. Here, we investigated factors that might affect the quality (a measure of coherence) of immediate and long-term emotional episodic memories of individual dishes of a long and complex dinner in a fine-dining restaurant. We also assessed long-term recognition memory for pictures of the dishes. Intra-class correlations revealed good immediate emotional episodic memory, which remained stable over three months. Contributing factors to these kinds of memory were assessed with path modelling. The quality of emotional episodic memory was enhanced by the hedonic intensity of the most valued dishes during the meal and was impaired with the hedonic intensity of the least valued dishes. Enjoying the final dish positively affects emotional memory after the experience. Interestingly, when diners reported to have been distracted from the meal, presumably by communicating with their meal companions about the food, it had a positive effect on the long-term emotional episodic memory. Personality traits of the diners had no substantial impact on either type of memory. Alcohol intake during the meal modestly affected recognition memory but – interestingly – had no statistically significant effect on emotional episodic memory. Altogether, this study provides novel information about the main determinants of the precision and temporal stability of emotional episodic memory and nonemotional recognition memory for a meal. These findings contribute to the psychological foundations of designing memorable experiences in gastronomy and other areas. Implications for gastronomy Knowing what factors may determine whether a gastronomic experience would be memorable to diners is the holy grail of any chef. The design of a gastronomic experience should provide intense emotional moments to the diners aiming to increase the quality of emotional memory of those moments. Different factors contribute to this stability, for instance, how the diner interacts with the food and the food itself. In this regard, serving in a dining course very tasty and less delicious dishes thereafter can enhance the memorability of the former, but not so much of the latter, as it may be disturbing for the diner. Critically, enjoying the final dish positively affects emotional memory after the experience. In addition, most gastronomic events are shared with companions. Far from being a distracting element, social relationships in a table seem to increase the memorability of the experience, as communication deeply elaborates and reinforces memory traces. In the reinforcement of emotional memories for foods, alcohol has a negligible effect. Although our findings have been obtained in a fine-dining context, the implications of our current findings might be generalizable to other, more standard contexts. The critical point is to focus on having positive specific episodes rather than having a positive global valuation. All these outcomes would converge to increase the probability of repeating the gastronomic experience, regardless of whether it is a high-level restaurant or a standard one.
... For example, Storbeck and Maswood (2015) carried out two experiments to investigate the impact of emotion on working memory and found that positive mood generally enhances verbal and spatial working memory capacities. Neuroscientists Tambini et al. (2017) reported that "neural measures of an emotional experience can persist in time and bias how new, unrelated information is encoded and recollected" (p. 271). ...
... First, it would be beneficial to carry out a partial replication at a different education level, for example, secondary education. Second, inspired by the reading of Tambini et al. (2017) and Bueno i Torrens (2021), it would be worthwhile investigating whether a warm-up activity intended to create a positive learning environment in the classroom can enhance second language learners' performance in a task carried out right after the warm-up. ...
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The pandemic has made it clearer than ever that health issues impact education and that schools play a key role in supporting the wellbeing of learners. As emotion and cognition are interconnected, educators should use educational strategies that generate positive emotions so that learning is associated with pleasure. The aim of this study was to investigate if a warm-up activity with Flipgrid could contribute to creating a positive learning environment in the online classroom in times of Covid-19. Flipgrid is a free platform that allows video-based asynchronous discussion. It fosters educator-student contact, cooperation among learners, active-learning techniques and student engagement. A total of 37 MA students participated in the study. Informants were selected by non-probabilistic sampling. The data collection strategies were observation during the Flipgrid warm-up activity, a Moodle survey, and the institution student satisfaction survey. Students' engagement was high and their attitude was mostly positive or neutral. The warm-up was highly rated in terms of creating a positive learning environment by the participants, and informants wrote positive remarks about their experience using the platform. The results suggest that a warm-up activity with Flipgrid is an effective educational strategy to generate positive emotions during the pandemic. Finally, the limitations of the study are addressed, and some directions for future research are proposed.
... Carryover effects Emotional experiences have a lasting impact on mental processing that may carry forward in time to affect how subsequent neutral experiences are encoded. Tambini and colleagues [52] found that human subjects who encoded a block of emotional pictures showed improved memory for neutral items encoded up to~33 minutes afterwards, as compared to when the encoding order was reversed. Brain states measured in patterns of low-frequency correlations in background connectivity between the amygdala and the rest of the brain, including the anterior hippocampus, were recapitulated between emotional and neutral item encoding. ...
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The long-term fate of a memory is not exclusively determined by the events occurring at the moment of encoding. Research at the cellular, circuit, and behavioral levels is beginning to reveal how neurochemical activations in the moments surrounding an event can retroactively and proactively rescue weak memory for seemingly mundane experiences. We review emerging evidence showing enhancement of weakly formed memories encoded minutes to hours before or after a related motivationally relevant experience. We discuss proposed neurobiological mechanisms for strengthening weak memories formed in temporal proximity to a strong event, and how this knowledge could be leveraged to improve memory for information that is prone to forgetting.
... After presenting each video once, all videos were played a second time in the same order to encourage accurate memory performance, without the entertainment rating. Following prior work in the motivated cognitive control literature (Chiew & Braver, 2014;da Silva Castanheira, LoParco, & Otto, 2021;Otto & Vassena, 2020;Parro, Dixon, & Christoff, 2018), videos were blocked to minimize carry-over effects between the high and low reward conditions (Tambini, Rimmele, Phelps, & Davachi, 2017), such that all videos assigned to the same reward condition were presented together, and the order of presentation (i.e., high-low or lowhigh) was counterbalanced. ...
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Much of the evidence suggesting that rewards improve memory performance has focused on how explicit rewards facilitate encoding of simplistic stimuli. To expand beyond this focus, the current study tested how explicit rewards presented at encoding as well as retrieval facilitate memory for information contained within complex events. In a single experimental session, participants (N = 88) encoded videos depicting naturalistic events (e.g., getting dressed) and then completed a recognition test probing their memory for different detail types (i.e., event, perceptual, or contextual) from the video stimuli. We manipulated the explicit reward associated with each video, such that accurate memory responses for half the videos were associated with high monetary incentives and half were associated with low monetary incentives. This reward manipulation was presented at either encoding or retrieval during a recognition memory test. The reward manipulation only affected memory when presented at encoding and this effect did not depend on the type of detail probed. Drift Diffusion Modelling further revealed that presenting reward information at encoding engendered greater encoding fidelity—indexed by an increase in drift rate—but did not change response caution at the time of retrieval—indexed by response threshold. Together, our results suggest that presenting reward information when encoding but not retrieving complex events has a general facilitatory effect, likely via attentional processing, on the ability to later remember precise details from the event.
... Electrophysiological studies have examined temporal brain dynamics involved in the initial orienting, appraisal, and regulation of the emotional elicitor that occur within hundreds of milliseconds to seconds of stimulus onset (e.g., (Luo, Jiang, Chen, Zhang, & You, 2019;Paul, Simon, Kniesche, Kathmann, & Enrass, 2013;Pourtois, Delphanque, Michel, & Vuilleumier, 2008)). Some functional magnetic resonance imaging (fMRI) studies have shown carryover effects that reflect residual processing of an emotional event several seconds after its termination (e.g., (Heller et al., 2015;Siegle, Steinhauer, Thase, Stenger, & Carter, 2002;Walter et al., 2009) or the lingering impact of an emotional state minutes later during a subsequent cognitive task (Tambini, Rimmele, Phelps, & Davachi, 2017;Wang, LaBar, & McCarthy, 2006). Even less is known about the emergence and sequencing of intrinsic emotional states during unconstrained periods of spontaneous thought (P. A. Kragel, Knodt, Hariri, & LaBar, 2016), although it is hypothesized that, during these periods of quiescent self-reflection, ruminative thinking impacts negative affect perseveration in depression, anxiety and other disorders (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008;Northoff, Wiebking, Feinberg, & Panksepp, 2011). ...
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Temporal processes play an important role in elaborating and regulating emotional responding during routine mind wandering. However, it is unknown whether the human brain reliably transitions among multiple emotional states at rest and how psychopathology alters these affect dynamics. Here, we combined pattern classification and stochastic process modeling to investigate the chronometry of spontaneous brain activity indicative of six emotions (anger, contentment, fear, happiness, sadness, and surprise) and a neutral state. We modeled the dynamic emergence of these brain states during resting-state fMRI and validated the results across two population cohorts—the Duke Neurogenetics Study and the Nathan Kline Institute Rockland Sample. Our findings indicate that intrinsic emotional brain dynamics are effectively characterized as a discrete-time Markov process, with affective states organized around a neutral hub. The centrality of this network hub is disrupted in individuals with psychopathology, whose brain state transitions exhibit greater inertia and less frequent resetting from emotional to neutral states. These results yield novel insights into how the brain signals spontaneous emotions and how alterations in their temporal dynamics contribute to compromised mental health.
... Temporal context influences emotional perception and neural responses (Pastor et al., 2008;Fujimura et al., 2013;Czekóová et al., 2015). For example, the perception of neutral images is more negative if they are preceded by negative images or descriptions than when they are preceded by non-negative ones (Pastor et al., 2008;Tambini et al., 2017;Grupe et al., 2018). Moreover, emotion regulation might have enduring behavioral and neural effects (Foti and Hajcak, 2008;MacNamara et al., 2011). ...
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Why are some people more susceptible to interference from previous emotional stimuli? Neural mechanisms underlying emotion regulation are typically studied with one-off positive or negative stimuli. Less is known about how they operate during dynamic emotional experiences, which more closely resemble how emotions occur in real life. Therefore, we investigated the interaction among temporal context, stimulus content, and regulatory strategy. Image sequences included either neutral to negative emotion or negative to neutral emotion. Participants were instructed to either passively watch the emotional stimuli or apply cognitive reappraisal during the image sequences presentation. Participants also reported their habitual use of cognitive reappraisal in their daily lives on a standard scale. We measured functional connectivity (FC) with electroencephalography (EEG) source localization. A three-way interaction suggested that, in addition to momentary emotional content and regulatory effort, the temporal context of stimuli impacts the FC between the ventromedial prefrontal cortex (vmPFC) and the ventral anterior cingulate cortex (ACC) in both alpha and beta frequency bands. In the reappraisal condition—but not the passive watch conditions—, individual differences in habitual reappraisal were manifested in the FC of vmPFC-ACC in alpha band. Emotion transitions may be more demanding because prefrontal-posterior FC in the beta band decreased during emotion transitions regardless of emotional content or regulation efforts. Flexible emotion regulation enables the recruiting of neural activities in response to the content of dynamic, ever-changing experiences encountered in daily life. Studying brain responses to dynamic emotional stimuli may shed light on individual differences in adaptation and psychological health. It also provides a more ecologically valid assessment of emotion regulation.
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Variation in the language experience of bilinguals has consequences for cognitive and affective processes. In the current study, we examined how bilingual experience influences the relationship between language and emotion in English among a group of Spanish–English heritage bilinguals on an emotion–memory task. Participants rated the emotionality of English taboo, negative and neutral words and then completed an unexpected recognition test. To account for language experience, data were gathered on the participants’ language dominance and proficiency. Results showed emotion–memory effects in the Spanish–English heritage bilinguals’ English (the societal language): taboo words were recognized significantly better than neutral words, while the emotionality of negative words carried over and significantly affected the recognition of preceding neutral words. Furthermore, such effects were modulated by language dominance scores with more pronounced emotion–memory effects in more English-dominant bilinguals. The findings contribute to a growing body of evidence showing that emotions are not necessarily restricted to the first acquired home language. Critically, for heritage speakers, there is often a shift in language dominance from the home language to the societal language. The present study demonstrates that the effects of emotion on memory are seen in the acquired societal language.
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In the age of people aspiring after sense experiences, encouraging long-term health behaviour changes to prevent future disorders that are, without previous personal experiences, unimaginable threats for the public, maybe one of the greatest challenges preventive medicine has to face. In order to become trusted sources, and influence public health behaviour in an experience-oriented manner, we need to formulate strategies offering emotionally evocative sense inputs that elicit self-relatedness. The current narrative review discusses the relevance of personal experiences in contemporary health behaviour by focusing on three major areas: 1) the importance of personal sources of health-related information, 2) cognitive and neurobiological background of personal experiences, 3) potential strategies to induce health behaviour changes through personal experiences. Based on the reviewed body of knowledge, three potential “rules” are proposed to increase the effectiveness of health promotion programs through sense or personal experiences: 1) Rule of Senses (stressing the importance of multisensory learning); 2) Rule of Affect (emphasizing the motivational significance of evoking positive emotions); and 3) Rule of Self-relatedness (highlighting the role of the self-referential composition of human experiences).
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Neurobiological models of long-term memory propose a mechanism by which initially weak memories are strengthened through subsequent activation that engages common neural pathways minutes to hours later. This synaptic tag-and-capture model has been hypothesized to explain how inconsequential information is selectively consolidated following salient experiences. Behavioural evidence for tag-and-capture is provided by rodent studies in which weak early memories are strengthened by future behavioural training. Whether a process of behavioural tagging occurs in humans to transform weak episodic memories into stable long-term memories is unknown. Here we show, in humans, that information is selectively consolidated if conceptually related information, putatively represented in a common neural substrate, is made salient through an emotional learning experience. Memory for neutral objects was selectively enhanced if other objects from the same category were paired with shock. Retroactive enhancements as a result of emotional learning were observed following a period of consolidation, but were not observed in an immediate memory test or for items strongly encoded before fear conditioning. These findings provide new evidence for a generalized retroactive memory enhancement, whereby inconsequential information can be retroactively credited as relevant, and therefore selectively remembered, if conceptually related information acquires salience in the future.
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Determining how the hippocampus supports the unique demands of memory encoding and retrieval is fundamental for understanding the biological basis of episodic memory. One possibility proposed by theoretical models is that the distinct computational demands of encoding and retrieval are accommodated by shifts in the functional interaction between the hippocampal CA1 subregion and its input structures. However, empirical tests of this hypothesis are lacking. To test this in humans, we used high-resolution fMRI to measure functional connectivity between hippocampal area CA1 and regions of the medial temporal lobe and midbrain during extended blocks of associative encoding and retrieval tasks. We found evidence for a double dissociation between the pathways supporting successful encoding and retrieval. Specifically, during the associative encoding task, but not the retrieval task, functional connectivity only between area CA1 and the ventral tegmental area predicted associative long-term memory. In contrast, connectivity between area CA1 and DG/CA3 was greater, on average, during the retrieval task compared with the encoding task, and, importantly, the strength of this connectivity significantly correlated with retrieval success. Together, these findings serve as an important first step toward understanding how the demands of fundamental memory processes may be met by changes in the relative strength of connectivity within hippocampal pathways.
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Selecting appropriate stimuli to induce emotional states is essential in affective research. Only a few standardized affective stimulus databases have been created for auditory, language, and visual materials. Numerous studies have extensively employed these databases using both behavioral and neuroimaging methods. However, some limitations of the existing databases have recently been reported, including limited numbers of stimuli in specific categories or poor picture quality of the visual stimuli. In the present article, we introduce the Nencki Affective Picture System (NAPS), which consists of 1,356 realistic, high-quality photographs that are divided into five categories (people, faces, animals, objects, and landscapes). Affective ratings were collected from 204 mostly European participants. The pictures were rated according to the valence, arousal, and approach–avoidance dimensions using computerized bipolar semantic slider scales. Normative ratings for the categories are presented for each dimension. Validation of the ratings was obtained by comparing them to ratings generated using the Self-Assessment Manikin and the International Affective Picture System. In addition, the physical properties of the photographs are reported, including luminance, contrast, and entropy. The new database, with accompanying ratings and image parameters, allows researchers to select a variety of visual stimulus materials specific to their experimental questions of interest. The NAPS system is freely accessible to the scientific community for noncommercial use by request at http://naps.nencki.gov.pl. Electronic supplementary material The online version of this article (doi:10.3758/s13428-013-0379-1) contains supplementary material, which is available to authorized users.
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Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects.
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Humans remember emotional events not only better but also exhibit a qualitatively distinct recollective experience, that is, emotion intensifies the subjective vividness of the memory, the sense of reliving the event, and confidence in the accuracy of the memory [Phelps, E. A., & Sharot, T. How (and why) emotion enhances the subjective sense of recollection. Current Directions in Psychological Science, 17, 147-152, 2008]. Although it has been demonstrated that activation of the beta-adrenergic system, linked to increases in stress hormone levels and physiological arousal, mediates enhanced emotional memory accuracy, the mechanism underlying the increased subjective sense of recollection is unknown. Behavioral evidence suggests that increased arousal associated with emotional events, either at encoding or retrieval, underlies their increased subjective sense of recollection. Using a double-blind, placebo-controlled, within-subject design, we showed that reducing arousal at encoding through oral intake of 80-mg of the beta-adrenergic receptor antagonist propranolol decreases the subjective sense of recollection for both negative and neutral stimuli 24 hr later. In contrast, administration of propranolol before memory retrieval did not alter the subjective sense of recollection. These results suggest that the neurohormonal changes underlying increased arousal at the time of memory formation, rather than the time of memory retrieval, modulate the subjective sense of recollection.