Aversive learning enhances perceptual and cortical discrimination of indiscriminable odor cues.
ABSTRACT Learning to associate sensory cues with threats is critical for minimizing aversive experience. The ecological benefit of associative learning relies on accurate perception of predictive cues, but how aversive learning enhances perceptual acuity of sensory signals, particularly in humans, is unclear. We combined multivariate functional magnetic resonance imaging with olfactory psychophysics to show that initially indistinguishable odor enantiomers (mirror-image molecules) become discriminable after aversive conditioning, paralleling the spatial divergence of ensemble activity patterns in primary olfactory (piriform) cortex. Our findings indicate that aversive learning induces piriform plasticity with corresponding gains in odor enantiomer discrimination, underscoring the capacity of fear conditioning to update perceptual representation of predictive cues, over and above its well-recognized role in the acquisition of conditioned responses. That completely indiscriminable sensations can be transformed into discriminable percepts further accentuates the potency of associative learning to enhance sensory cue perception and support adaptive behavior.
- SourceAvailable from: Bernard W Balleine[show abstract] [hide abstract]
ABSTRACT: Recent studies suggest that there are multiple 'reward' or 'reward-like' systems that control food seeking; evidence points to two distinct learning processes and four modulatory processes that contribute to the performance of food-related instrumental actions. The learning processes subserve the acquisition of goal-directed and habitual actions and involve the dorsomedial and dorsolateral striatum, respectively. Access to food can function both to reinforce habits and as a reward or goal for actions. Encoding and retrieving the value of a goal appears to be mediated by distinct processes that, contrary to the somatic marker hypothesis, do not appear to depend on a common mechanism but on emotional and more abstract evaluative processes, respectively. The anticipation of reward on the basis of environmental events exerts a further modulatory influence on food seeking that can be dissociated from that of reward itself; earning a reward and anticipating a reward appear to be distinct processes and have been doubly dissociated at the level of the nucleus accumbens. Furthermore, the excitatory influence of reward-related cues can be both quite specific, based on the identity of the reward anticipated, or more general based on its motivational significance. The influence of these two processes on instrumental actions has also been doubly dissociated at the level of the amygdala. Although the complexity of food seeking provides a hurdle for the treatment of eating disorders, the suggestion that these apparently disparate determinants are functionally integrated within larger neural systems may provide novel approaches to these problems.Physiology & Behavior 01/2006; 86(5):717-30. · 3.16 Impact Factor
Article: Odor maps in the olfactory cortex.[show abstract] [hide abstract]
ABSTRACT: In the olfactory system, environmental chemicals are deconstructed into neural signals and then reconstructed to form odor perceptions. Much has been learned about odor coding in the olfactory epithelium and bulb, but little is known about how odors are subsequently encoded in the cortex to yield diverse perceptions. Here, we report that the representation of odors by fixed glomeruli in the olfactory bulb is transformed in the cortex into highly distributed and multiplexed odor maps. In the mouse olfactory cortex, individual odorants are represented by subsets of sparsely distributed neurons. Different odorants elicit distinct, but partially overlapping, patterns that are strikingly similar among individuals. With increases in odorant concentration, the representations expand spatially and include additional cortical neurons. Structurally related odorants have highly related representations, suggesting an underlying logic to the mapping of odor identities in the cortex.Proceedings of the National Academy of Sciences 06/2005; 102(21):7724-9. · 9.74 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: Historically, sensory systems have been largely ignored as potential loci of information storage in the neurobiology of learning and memory. They continued to be relegated to the role of "sensory analyzers" despite consistent findings of associatively induced enhancement of responses in primary sensory cortices to behaviorally important signal stimuli, such as conditioned stimuli (CS), during classical conditioning. This disregard may have been promoted by the fact that the brain was interrogated using only one or two stimuli, e.g., a CS(+) sometimes with a CS(-), providing little insight into the specificity of neural plasticity. This review describes a novel approach that synthesizes the basic experimental designs of the experimental psychology of learning with that of sensory neurophysiology. By probing the brain with a large stimulus set before and after learning, this unified method has revealed that associative processes produce highly specific changes in the receptive fields of cells in the primary auditory cortex (A1). This associative representational plasticity (ARP) selectively facilitates responses to tonal CSs at the expense of other frequencies, producing tuning shifts toward and to the CS and expanded representation of CS frequencies in the tonotopic map of A1. ARPs have the major characteristics of associative memory: They are highly specific, discriminative, rapidly acquired, exhibit consolidation over hours and days, and can be retained indefinitely. Evidence to date suggests that ARPs encode the level of acquired behavioral importance of stimuli. The nucleus basalis cholinergic system is sufficient both for the induction of ARPs and the induction of specific auditory memory. Investigation of ARPs has attracted workers with diverse backgrounds, often resulting in behavioral approaches that yield data that are difficult to interpret. The advantages of studying associative representational plasticity are emphasized, as is the need for greater behavioral sophistication.Learning & memory (Cold Spring Harbor, N.Y.) 01/2007; 14(1-2):1-16. · 4.08 Impact Factor
, 1842 (2008);
, et al. Wen Li
of Indiscriminable Odor Cues
Aversive Learning Enhances Perceptual and Cortical Discrimination
This copy is for your personal, non-commercial use only.
clicking here. colleagues, clients, or customers by
, you can order high-quality copies for your
If you wish to distribute this article to others
The following resources related to this article are available online at
here. following the guidelines
can be obtained by
Permission to republish or repurpose articles or portions of articles
Updated information and services,
): February 24, 2012 www.sciencemag.org (this infomation is current as of
version of this article at:
including high-resolution figures, can be found in the online
can be found at:
Supporting Online Material
32 article(s) on the ISI Web of Science
This article has been
19 articles hosted by HighWire Press; see:
This article has been
This article appears in the following
registered trademark of AAAS.
is a Science2008 by the American Association for the Advancement of Science; all rights reserved. The title
CopyrightAmerican Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005.
(print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the Science
on February 24, 2012
28. S. Katada, T. Nakagawa, H. Kataoka, K. Touhara,
Biochem. Biophys. Res. Commun. 305, 964 (2003).
29. We thank P. Rivkin for technical assistance; K. Lee, J. Klun,
K. Touhara, and members of the Vosshall Lab for comments
on the manuscript; and P. Howell and M. Q. Benedict of the
Centers for Disease Control and Prevention and MR4 for
mosquitoes. DNA clones were provided by T.-Y. Chen (CNGs),
A. G. Kovacs (CFTR), A. Patapoutian (mTRPM8), G. Wilson
(EAG), and L. Zwiebel (GPROR8). M.P. and L.B.V. thank
D. Gadsby and Gadsby Lab members M. Mense, P. Artigas,
N. Reyes, and P. Hoff for valuable discussion and advice,
training, and access to instrumentation. M.D. was
supported by a Marie-Josée and Henry Kravis Postdoctoral
Fellowship. This work was funded in part by a grant to
R. Axel and L.B.V. from the Foundation for the NIH through
theGrand ChallengesinGlobal Health Initiative and byNIH
grant DC008600 to L.B.V. Author contributions: M.D.
carried out the experiments in Figs. 1 to 3, M.P. carried out
the experiments in Fig. 4, and L.B.V. supervised the work
and wrote the paper.
Supporting Online Material
Materials and Methods
Figs. S1 to S3
19 November 2007; accepted 14 February 2008
Published online 13 March 2008;
Include this information when citing this paper.
Aversive Learning Enhances Perceptual
and Cortical Discrimination of
Indiscriminable Odor Cues
Wen Li,1* James D. Howard,1Todd B. Parrish,1,2Jay A. Gottfried1,3,4
Learning to associate sensory cues with threats is critical for minimizing aversive experience. The
ecological benefit of associative learning relies on accurate perception of predictive cues, but how
aversive learning enhances perceptual acuity of sensory signals, particularly in humans, is unclear. We
combined multivariate functional magnetic resonance imaging with olfactory psychophysics to show
that initially indistinguishable odor enantiomers (mirror-image molecules) become discriminable after
aversive conditioning, paralleling the spatial divergence of ensemble activity patterns in primary
olfactory (piriform) cortex. Our findings indicate that aversive learning induces piriform plasticity with
corresponding gains in odor enantiomer discrimination, underscoring the capacity of fear conditioning
to update perceptual representation of predictive cues, over and above its well-recognized role in the
acquisition of conditioned responses. That completely indiscriminable sensations can be transformed
into discriminable percepts further accentuates the potency of associative learning to enhance
sensory cue perception and support adaptive behavior.
learning, organisms can use sensory information
in the environment to predict impending danger
and initiate fight-or-flight responses. The behav-
ioral efficacy of associative learning thus hinges
sensory signals. In particular, the ability to dis-
criminate between biologically meaningful cues
(e.g., smell of a 175-kg lion) and similar but ir-
relevant stimuli (e.g., smell of a 3-kg housecat)
maximizes an organism’s response sensitivity
while minimizing hypervigilant and impulsive
of associations between a sensory cue [the con-
ditioned stimulus (CS)] and a biologically salient
event [the unconditioned stimulus (US)] (1, 2),
paying scant attention to perceptual changes in
he ability to minimize contact with aver-
sive experience is a hallmark of adaptive
behavior. Via mechanisms of associative
associative learning modifies cue-related tuning
profiles in sensory cortex (3–8), although none
has provided concomitant measures of sensory
perception. As a consequence, direct links relat-
perceptual gains in cue discrimination are un-
available, such that the functional importance of
these neural effects on behavior remains poorly
characterized. To the extent that conditioning can
transform indiscriminable sensations into distinct
percepts, such a mechanism would constitute a
unique and potent means of optimizing adaptive
We combined functional magnetic resonance
conditioning on perceptual and neural discrimi-
nation of predictive odor cues. The use of per-
(9, 10) enabled us to determine whether humans
can acquire the ability to distinguish between
odorous stimuli that initially smell the same.
Twelve healthy human subjects (age range, 22 to
35 years; 8 female) were presented with four
enantiomers (two different pairs), one of which
(the target CS+, “tgCS+”) was repetitively paired
phase, whereas its chiral counterpart (“chCS+”)
was notaccompaniedby shock (Fig.1) (10).The
second pair of odor enantiomers served as
nonconditioned control stimuli (“CS–” and
“chCS–”). The central prediction was that
associative learning would enhance behavioral
discrimination of related CS+ odorants, in
parallel with reorganization of neural coding in
human primary olfactory (piriform) cortex.
We first examined the behavioral effects of
aversive conditioning on perceptual discrimina-
tion between the conditioned cue (tgCS+) and its
related enantiomer (chCS+). We administered a
triangular (triple-forced-choice) odor discrimina-
odor identity (i.e., the quality or character of a
trial, subjects smelled sets of three bottles (two
containing one odorant, the third containing its
chiral opposite) and selected the odd stimulus. Be-
chance (33%) for both CS+ and CS– enantiomer
pairs, confirming that each pair was initially in-
distinguishable (Fig.2A).After conditioning, be-
and chCS+ rose by more than a factor of 2, sig-
nificantly exceeding both chance and precondi-
tioning performance (Ps ≤ 0.01; Wilcoxon test,
two-tailed), without any improvement in distin-
guishing between CS– and chCS–. Subjective
ratings of odor intensity, valence, or familiarity
(11) did not vary across conditions (Ps > 0.4),
ruling out confounds of the triangular test due to
these extraneous variables and accentuating the
change in perceived odor identity. Associative
learning thus can enhance perceptual discrimina-
bility between initially indistinguishable odors,
and these effects are specific for the CS+.
We next clarified the neural mechanisms un-
derlying learning-inducedperceptual enhancement
of the predictive cue (11). Because neural rep-
resentations of odor identity are maintained in
posterior piriform cortex (12–14), and given the
highly distributed spatial organization of afferent
projections into the piriform region (15–17), we
used multivariate fMRI (18, 19) to test the hy-
pothesis that spatially distributed patterns of neu-
ral activity in piriform cortex evoked by tgCS+
and chCS+ would be reorganized as a conse-
quence of associative learning (fig. S1).
By extracting the raw fMRI signal intensity
from every activated piriform voxel (fig. S2), we
ing to the high perceived similarity within each
School of Medicine, Northwestern University, Chicago, IL
60611, USA.2Department of Radiology, Feinberg School of
Medicine,NorthwesternUniversity, Chicago, IL60611, USA.
3Department of Neurology, Feinberg School of Medicine,
ofPsychology,Northwestern University,Evanston, IL60208,
*To whom correspondence should be addressed. E-mail:
28 MARCH 2008 VOL 319
on February 24, 2012
comparison to the CS– pair (P < 0.05; Wilcoxon
inducedbehavioralenhancement inodor discrim-
ination between tgCS+ and chCS+. Additional
significantly higher than across-pair correlations
at preconditioning (P < 0.005, f = 0.66), which
suggests that our multivariate technique has sat-
isfactory discriminant validity for distinguishing
respiratory differences acrossconditions(11) sug-
gests that the imaging effects were not due to
Condition-specific odor maps from one sub-
ject (Fig. 3) illustrate how spatial patterns of
piriform activity were selectively reorganized
from pre- to postlearning for the CS+ pair,
whereas the patterns for the CS– pair remained
right column) further show that there was mini-
piriform voxel could change in either direction
(activation or deactivation); this exemplifies the
sensitivity of multivariate pattern-based fMRI ap-
proaches to characterizing neural information in
human sensory cortex (20).
The postlearning changes described above
were paralleled by robust evidence for aversive
ments (11) of the odor-evoked skin conductance
to tgCS+ at post- versus preconditioning when
compared to the CS– odorants (Fig. 4A). These
Fig. 1. Experimental paradigm. (A) Chemical structures of the
enantiomer pairs. (B) Learning task. Odorants included a target CS+
(tgCS+) destined for aversive conditioning, its chiral counterpart
(chCS+), a nonconditioned control (CS–), and its chiral counterpart
(chCS–). A baseline condition consisted of odorless air. Stimuli were
sessions. During conditioning, tgCS+ presentation coterminated with
electric shock (the US). During postconditioning, the US was
presented with tgCS+ on 4 of 19 trials to prevent extinction. On
each trial, participants indicated whether odor was present or absent
(asterisks). SCR and respiration were continuously recorded.
Fig. 2. Parallelenhance-
ment of perceptual and
Odor discrimination ac-
curacy was at chance
(dashed line) for CS+
and CS– pairs before
conditioning, but selec-
tively improved for the
ing. Error bars, ±SEM.
(B) Spatial patterns of
fMRI activity inposterior
piriform cortex between
tgCS+ and chCS+ were
highly correlated before
conditioning but be-
came more distinct (less
tial activity in OFC (left)
tex (right) indicated that
became more correlated
(although not significantly) for both CS+ and CS– pairs.
VOL 31928 MARCH 2008
on February 24, 2012
tgCS+, because tgCS+ and chCS+ changes did
not significantly differ (P > 0.2). In fact, there
was a small but nonsignificant SCR increase to
frontal cortex (OFC) (analyzed using conven-
tional fMRI approaches) (11) paralleled the SCR
effects. A condition × time interaction (11) dem-
onstrated progressive decreases in amygdala ac-
tivity evoked by tgCS+ (versus CS– odors) as
learning proceeded (Fig. 4B and table S1), con-
sistent with prior studies of aversive learning that
parison of post- to preconditioning revealed in-
creased mean responses to tgCS+ (versus CS–
odors) in the OFC bilaterally (Fig. 4, C and D),
another region implicated in associative learning
(23, 24). Interestingly, fear conditioning partially
generalized to the chCS+ odorant, which at re-
duced threshold (P < 0.005 uncorrected) showed
similar profiles in amygdala and OFC (table S2).
These findings validate the efficacy of our para-
supporting the idea that the perceptual and neural
changes in sensory discriminability were a con-
show that fear conditioning to an odor cue recruits
many of the same regions involved in conditioning
to visual and auditory cues, emphasizing the multi-
modal versatility of these learning networks.
The shock-dependent spatial modifications in
posterior piriform cortex were seen in the ab-
sence of changes in the magnitude of mean ac-
tivation. Although the conventional (univariate)
fMRI analysis revealed increased mean activity
in OFC (Fig. 4C), there was no evidence for
similar mean changes in posterior piriform cor-
tex, even at reduced threshold (P < 0.01 uncor-
rected). At the same time, fMRI multivariate
(pattern) analysis of OFC (Fig. 2C, left) showed
no evidence for enhanced spatial discrimination
between the CS+ odorants, but rather suggested
further loss of coding specificity (more highly
changes for the CS+ pair significantly differed
between posterior piriform cortex and OFC (P =
ificity for the ensemble learning effect. This an-
atomical/functional double dissociation suggests
that fear conditioning recruits functionally distinct
networks acting in concert to maximize adaptive
behavior: an emotion system (e.g., amygdala
and OFC) optimized to detect threat signals
with high sensitivity, and a perceptual system
(e.g., posterior piriform cortex) optimized to
encode signal specificity.
We considered that aversive conditioning
could have heightened attention (or arousal) to
tgCS+, evoking response changes in olfactory
cortex.However,anterior piriformcortex,the pur-
ported target of human olfactory attention (25),
was not modulated in response to associative
learning, either in univariate (at P < 0.01 uncor-
rected) or multivariate (Fig. 2C, right) analysis.
By comparison, the idea that aversive learning
updates odor quality representations in posterior
in coding odor identity in both animal (13, 26)
and human (12, 14) models of olfactory process-
ing. It is therefore unlikely that attention or arous-
al directly modulates odor coding in posterior
piriform, although it remains possible that these
mechanisms could mediate olfactory perceptual
Aversive conditioning therefore has a direct
influence on how perceptual information about a
a potent neural substrate to guide the behavioral
discrimination of predictive cues. The spatial reor-
reflect changes in olfactory receptive-field tuning,
leading to improved perception of odor cues, such
that unique or “tagged” piriform representations
might gain privileged access to critical nodes un-
derlying aversion-minimizing behaviors.
Knowing what to avert presents behavioral
challenges that an organism must solve to sur-
conditioned) responses, rather than how condi-
tioning alters sensory processing of the CS itself,
resulting inperceptual learning and enhanced dis-
crimination. We hypothesize that the substantial
effectof emotionalexperienceon perceptual pro-
cessing in sensory cortices should have a vital
impact on adaptive behavior and should thus be
els of learning and decision-making (4, 27, 28).
that neurobiological derangements in the ability
to distinguish between salient cues and percep-
tually related inconsequential stimuli may
underlie the emergence of anxiety disorders
characterized by exaggerated sensory sensitivity
and hypervigilance. This may provide a unique
mechanistic framework for the development of
new therapeutic interventions.
References and Notes
1. B. J. Everitt, R. N. Cardinal, J. Hall, J. A. Parkinson,
T. W. Robbins, in The Amygdala: A Functional Analysis,
J. Aggleton, Ed. (Oxford Univ. Press, Oxford, 2000),
2. B. W. Balleine, Physiol. Behav. 86, 717 (2005).
3. J. M. Edeline, Prog. Neurobiol. 57, 165 (1999).
4. N. M. Weinberger, Learn. Mem. 14, 1 (2007).
5. D. B. Polley, M. A. Heiser, D. T. Blake, C. E. Schreiner,
M. M. Merzenich, Proc. Natl. Acad. Sci. U.S.A. 101,
6. F. W. Ohl, H. Scheich, Curr. Opin. Neurobiol. 15, 470
Fig. 3. Spatial maps of posterior piriform activity from one subject. Condition-specific spatial patterns
(left two columns) for the CS+ pair (A), but not the CS– pair (B), diverged after conditioning. Difference
conditioning. Each square in the grid represents fMRI signal intensity from a different piriform voxel (n =
86 voxels), arranged in columns from top left to bottom right, in ascending order of signal intensity for
tgCS+ in the preconditioning phase.
28 MARCH 2008 VOL 319
on February 24, 2012
7. J. S. Morris, K. J. Friston, R. J. Dolan, Proc. Biol. Sci. 265,
8. E. A. Phelps, J. E. LeDoux, Neuron 48, 175 (2005).
9. C. Linster et al., J. Neurosci. 21, 9837 (2001).
10. M. Laska, P. Teubner, Chem. Senses 24, 161 (1999).
11. See supporting material on Science Online.
12. J. A. Gottfried, J. S. Winston, R. J. Dolan, Neuron 49, 467
13. M. Kadohisa, D. A. Wilson, Proc. Natl. Acad. Sci. U.S.A.
103, 15206 (2006).
14. W. Li, E. Luxenberg, T. Parrish, J. A. Gottfried, Neuron 52,
15. L. B. Haberly, in The Synaptic Organization of the Brain,
G. M. Shepherd, Ed. (Oxford Univ. Press, New York,
16. K. R. Illig, J. Comp. Neurol. 488, 224 (2005).
17. Z. Zou, F. Li, L. B. Buck, Proc. Natl. Acad. Sci. U.S.A. 102,
18. J. V. Haxby et al., Science 293, 2425 (2001).
19. S. M. Polyn, V. S. Natu, J. D. Cohen, K. A. Norman,
Science 310, 1963 (2005).
20. N. Kriegeskorte, P. Bandettini, Neuroimage 38, 666
21. K. S. LaBar, J. C. Gatenby, J. C. Gore, J. E. LeDoux,
E. A. Phelps, Neuron 20, 937 (1998).
22. C. Buchel, J. Morris, R. J. Dolan, K. J. Friston, Neuron 20,
23. G. Schoenbaum, A. A. Chiba, M. Gallagher, J. Neurosci.
19, 1876 (1999).
24. P. C. Holland, M. Gallagher, Curr. Opin. Neurobiol. 14,
25. C. Zelano et al., Nat. Neurosci. 8, 114 (2005).
26. D. A. Wilson, R. J. Stevenson, Learning to Smell: Olfactory
Perception from Neurobiology to Behavior (Johns Hopkins
Univ. Press, Baltimore, 2006).
27. G. Hall, Q. J. Exp. Psychol. 56, 43 (2003).
28. I. P. L. McLaren, N. J. Mackintosh, Anim. Learn. Behav.
28, 211 (2000).
29. We thank T. Egner, M. M. Mesulam, J. S. Winston, and
R. E. Zinbarg for helpful comments; E. Featherstone,
E. Davchev, and V. Djoev for stimulator assembly; and
M. Benton for assistance in collecting data. Supported by
National Institute on Deafness and Other Communication
Disorders grant DC007653 (J.A.G.).
Supporting Online Material
Materials and Methods
Figs. S1 to S3
Tables S1 and S2
9 November 2007; accepted 21 February 2008
Electric Fields Due to
Synaptic Currents Sharpen
Sergiy Sylantyev,1* Leonid P. Savtchenko,1,2* Yin-Ping Niu,3* Anton I. Ivanov,4*
Thomas P. Jensen,1* Dimitri M. Kullmann,1Min-Yi Xiao,3Dmitri A. Rusakov1†
The synaptic response waveform, which determines signal integration properties in the brain, depends on
the spatiotemporal profile of neurotransmitter in the synaptic cleft. Here, we show that electrophoretic
interactions between AMPA receptor–mediated excitatory currents and negatively charged glutamate
molecules accelerate the clearance of glutamate from the synaptic cleft, speeding up synaptic responses.
This phenomenon is reversed upon depolarization and diminished when intracleft electric fields are
weakened through a decrease in the AMPA receptor density. In contrast, the kinetics of receptor-mediated
currents evoked by direct application of glutamate are voltage-independent, as are synaptic currents
mediated by the electrically neutral neurotransmitter GABA. Voltage-dependent temporal tuning of
excitatory synaptic responses may thus contribute to signal integration in neural circuits.
lthough ion currents through postsyn-
aptic receptors are small (~10−11A),
they can exert a lateral voltage gradient
(electric field) of ~104V/m inside the synaptic
cleft (1, 2), which raises the possibility that
they can affect the dwell time of electrically
charged neurotransmitters (3). Does electro-
diffusion, therefore, play any role in synaptic
The excitatory neurotransmitter glutamate
is negatively charged at physiological pH (pK =
4.4), which implies that postsynaptic depo-
larization should, in principle, retard its escape
EPSCs) decay more slowly at positive than at
negative holding voltages in dentate basket
cells (4) and in cerebellar granule cells (5). How-
ever, this has not been reported for AMPAR
EPSCs generated at perisomatic synapses on
CA1 or CA3 pyramidal cells (6–8). We evoked
dendritic AMPAR EPSCs in CA1 pyramidal
cellsby stimulatingSchaffer collaterals;theEPSC
decay time t (defined here as the area/peak
ratio) increased monotonically with depolar-
ization (Fig. 1B). The ratio between t recorded
at +40 mVand at –70 mV (t+40/t–70) was con-
n = 49, P < 0.001; (fig. S1A)]. This asymmetry
Fig. 4. Effectsofaversiveolfactoryconditioning.(A)SCRsignificantlyincreasedfortgCS+atpost-versus
Activations superimposed on coronal T1-weighted scans (display threshold, P < 0.001). (C) From pre- to
postconditioning, bilateral OFC showed enhanced responses to tgCS+ relative to CS– (axial T1 section;
threshold, P < 0.005). (D) Plots of percent signal change for peak activity in left OFC for each condition.
VOL 31928 MARCH 2008
on February 24, 2012