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The Journal of Neuroscience, March 1, 1999, 19(5):1876-1884
Neural Encoding in Orbitofrontal Cortex and Basolateral Amygdala
during Olfactory Discrimination Learning
Geoffrey
Schoenbaum1,
Andrea A.
Chiba2, and
Michela
Gallagher1
1 Department of Psychology, Johns Hopkins University,
Baltimore, Maryland 21218, and 2 Cognitive Science
Department, University of California at San Diego, La Jolla, California
92093
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ABSTRACT |
Orbitofrontal cortex (OFC) is part of a network of structures
involved in adaptive behavior and decision making. Interconnections between OFC and basolateral amygdala (ABL) may be critical for encoding
the motivational significance of stimuli used to guide behavior.
Indeed, much research indicates that neurons in OFC and ABL fire
selectively to cues based on their associative significance. In the
current study recordings were made in each region within a behavioral
paradigm that allowed comparison of the development of associative
encoding over the course of learning. In each recording session, rats
were presented with novel odors that were informative about the outcome
of making a response and had to learn to withhold a response after
sampling an odor that signaled a negative outcome. In some cases,
reversal training was performed in the same session as the initial
learning. Ninety-six of the 328 neurons recorded in OFC and 60 of the
229 neurons recorded in ABL exhibited selective activity during
evaluation of the odor cues after learning had occurred. A substantial
proportion of those neurons in ABL developed selective activity very
early in training, and many reversed selectivity rapidly after
reversal. In contrast, those neurons in OFC rarely exhibited selective
activity during odor evaluation before the rats reached the criterion
for learning, and far fewer reversed selectivity after reversal. The
findings support a model in which ABL encodes the motivational
significance of cues and OFC uses this information in the selection and
execution of an appropriate behavioral strategy.
Key words:
basolateral amygdala; orbitofrontal cortex; amygdala; prefrontal cortex; olfaction; discrimination learning; learning and
memory; electrophysiology; single units; rats
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INTRODUCTION |
Patients with damage to the orbital
region of prefrontal cortex characteristically fail to use available
information to appropriately guide their actions (Damasio, 1994 ;
Bechara et al., 1997). Instead they often engage in maladaptive
behavior, even when they are aware that their decisions will lead to
adverse consequences. Despite knowledge regarding the outcome of their
actions, it appears that such patients are inadequately motivated by
that information. This deficit may be attributable, at least in part,
to interruption of orbitofrontal cortex (OFC) connections with the
basolateral amygdala complex (ABL) (Krettek and Price, 1977; Kolb,
1984; Price et al., 1987; McDonald, 1991), a subcortical system widely
implicated in the ability to learn the motivational significance of
cues (Everitt et al., 1989, 1991; Davis, 1992; Gallagher and Chiba, 1996; Hatfield et al., 1996; LeDoux, 1996; Balleine et al., 1997; Killcross et al., 1997).
The importance of ABL to adaptive behavior is apparent in many tasks
that depend on associative learning. For example, in widely studied
fear-conditioning paradigms, defense responses such as freezing are
normally elicited by cues that predict an impending aversive event
(Davis, 1992). This learning is equally impaired by damage to either
ABL or the central nucleus of the amygdala. In a widely accepted model
for this form of learning, projections from ABL to central nucleus
provide access to brainstem systems that mediate conditioned fear
responses. At the same time, recent research has shown that other
learning paradigms that are sensitive to ABL damage are unaffected by
central nucleus lesions. These include deficits in higher-order
learning (second-order Pavlovian conditioning and instrumental learning
with secondary reinforcement) (Everitt et al., 1989, 1991; Hatfield et
al., 1996), an inability to adjust behavior to conditioned stimuli
based on changes in reward value (Hatfield et al., 1996; Balleine et
al., 1997), and a deficit in learning to direct behavior to avoid a negative outcome (Killcross et al., 1997). These adaptive behaviors, unlike the elicitation of species-typical responses, are likely to
require the integrative function of the amygdala and other forebrain
systems, such as ventral striatum and orbitofrontal cortex.
The current study was designed to examine the roles of OFC and ABL in
adaptive instrumental learning. We recorded neural activity in OFC and
ABL in rats as they learned novel olfactory discrimination problems. In
some sessions, this initial training was followed by reversal training
in which the response contingencies of the odors were switched.
Previously we have reported that neurons in OFC and ABL, in a subset of
these rats, fired selectively early in learning; this activity appeared
to encode the expected outcome on a trial while the rats awaited
reinforcement (Schoenbaum et al., 1998). Here we report on activity
during sampling of the cues that signaled the response contingencies.
Neurons in both OFC and ABL fired selectively during odor sampling to
reflect task contingencies during accurate performance. Further
analysis showed that the development of this activity differed in the
two brain regions. In ABL, neural activity in a substantial proportion of such cells reflected the motivational significance of the odor cues
early in training independent of the rat's choice behavior. In OFC,
however, activity in these neurons only emerged in conjunction with a reliable shift in the rat's behavioral strategy (go,
no-go) based on the significance of the cues.
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MATERIALS AND METHODS |
Subjects. Eight adult male Long-Evans rats served as
subjects. The rats were housed individually, maintained on a 12 hr
light/dark cycle, and given ad libitum access to food. Water
access was restricted during the 24 hr preceding behavioral testing to
motivate performance in the task. During testing periods, the rats
received fluid during the performance of the task, amounting to
~5-10 ml/session, and were given free access to water in a holding
cage after the session was finished. During this time, food was also available.
Electrodes, surgery, and histology. Recordings of
extracellular activity were obtained using a drivable bundle of 10 25-µm-diameter microwires (modified from Kubie, 1984). Rats weighed
325-375 gm at the time of surgery to implant the electrode bundle.
Surgical procedures were similar to those described previously
(Schoenbaum and Eichenbaum, 1995a). A single bundle was implanted in
the left hemisphere in orbitofrontal cortex of four rats (3.0 mm
anterior to bregma, 3.2 mm lateral, 4.0 mm ventral) and basolateral
complex of amygdala of four rats (3.0 mm posterior to bregma, 5.0 mm
lateral, 7.5 mm ventral). The rats were allowed two weeks to recover,
during which each animal received cephalexin (40 mg · kg 1 · d1)
to guard against infection. Once recording began, the electrode bundle
was advanced in 40 µm increments to acquire activity from new cells
for the following day. Recording was stopped in a given rat when the
estimated position of the electrode bundle was consistent with passage
beyond the region of interest. The rats were then deeply anesthetized
with sodium pentobarbital in preparation for perfusion. Immediately
before perfusion, the final electrode position was marked by passage of
a 15 µA current through each microwire for ~10 sec to create a
small iron deposit. The rats were then perfused transcardially using
physiological saline followed by 10% formalin followed by 100 ml of
10% formalin-3% potassium ferrocyanide solution to visualize the iron
deposit. The brains were then removed from the skulls and stored in a
10% formalin-20% sucrose-3% potassium ferrocyanide solution for
several days before sectioning. Brains were cut into 30 µm sections
surrounding the electrode tracks and stained with thionin, and the
electrode tracks were reconstructed to determine approximate recording
sites using the marks left by the iron at the tips of the electrodes.
Behavioral methods. Behavioral testing was performed in an
operant chamber using a go, no-go olfactory discrimination task in
which all behavioral events and data collection were controlled and
monitored by computer as described previously (Schoenbaum and
Eichenbaum, 1995a). The operant chamber was constructed of aluminum and
measured ~45 cm in height, depth, and width. An odor port and a fluid
well were located on the left wall of the chamber, and two panel lights
were located above the odor port.
The odor port consisted of a circular opening ~2.5 cm in diameter,
behind which was a small chamber through which odorized or clean air
could be passed. Air flow through the odor port was facilitated by a
vacuum line drawing 1 l/min from the chamber behind the port. Odor
delivery to the chamber behind the odor port was controlled by the
behavioral computer via a system of flow meters and solenoid valves.
The odor to be presented on a given trial was selected via activation
of the appropriate solenoid valve before the start of a trial. Opening
of the valve allowed a 0.5 l/min stream of clean air to pass over a 5%
solution of a particular odor and then to mix with a clean air stream
of 0.5 l/min. This odorized air was diverted to a vacuum dump at a
final solenoid valve just outside of the odor port. This solenoid valve was then activated to deliver the odor on detection of the rat at the
odor port. A photobeam across the opening to the odor port was
monitored by the behavioral computer to detect entry of the rat's
snout into the port. Odor delivery was terminated by inactivation of
the same solenoid when the rat left the odor port, and any remaining
odor was quickly removed by the entry of clean air from the behavioral
chamber due to the vacuum line in the port.
The fluid delivery well, located several centimeters below the odor
port, consisted of a small depression cut in a 2.5-cm-wide Plexiglas
shelf. Concealed lines in the bottom of this well allowed the delivery
of sucrose and quinine for use in the task as well as water to flush
the well between trials. The well was emptied by vacuum via a fourth
line. Fluid delivery was also controlled by the behavioral computer via
solenoid valves, and a photobeam across the top of the well was
monitored by the computer to detect the presence of the rat at the
fluid well.
Before the sessions in which recordings were made, behavioral training
was conducted using several odor discrimination problems to familiarize
the rats with the procedures of the task. Odors were chosen from a pool
of 64 distinct odorants (International Flavors and Fragrances, Union
Beach, NJ), diluted 1:20 in propylene glycol to approximately equal
intensity. In each recording session, a new odor discrimination problem
was presented involving either two or four novel odors. The task is
illustrated in a schematic provided in Figure
1. Illumination of the panel lights
signaled that a trial could be initiated, and a trial began when the
rat poked its nose into the odor port to trigger odor presentation. Actual odor onset was delayed by a variable period of ~300-800 msec
after the rat's snout interrupted a photobeam across the opening to
the odor port, so that the rat was stationary in the port when the odor
was delivered. The delivery of the odor cue was terminated by the
rat's decision to remove its snout from the odor port. The rat then
had 3 sec after withdrawal from the port to respond by entering the
nearby fluid well for reinforcement (go response). As illustrated in
Figure 1, the odor port and fluid well were separated by ~5 cm. In
the two-odor task (22 sessions), one odor, designated the positive
odor, signaled that a go response would produce ~0.05 ml of a
palatable 10% sucrose solution, whereas the other odor, designated the
negative odor, signaled that a go response would produce ~0.05 ml of
a distasteful 0.03 M quinine solution. In the four-odor
task (33 sessions), two distinct odors were associated with sucrose and
two distinct odors were associated with quinine. Each rat was
water-deprived overnight before a recording session and, therefore, was
strongly motivated to perform for fluid reward. Because novel odors
were presented in each session, the rat had to learn new associations
each day.
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Figure 1.
Schematic drawings illustrate the sequence of
behaviors in the go, no-go olfactory discrimination task. In this task,
a water-deprived rat had to sample an odor presented at a port on each
trial (odor sampling) to decide whether to respond (go response) at a
nearby fluid well. Responses at both the odor port and the fluid well
were registered by interruption of photo beams that detected entry of
the rat's snout into each port. A go response resulted in delivery of
a rewarding sucrose solution, after presentation of a "positive"
odor, or an aversive quinine solution, after presentation of a
"negative" odor. A go response after a negative odor was considered
an error and followed by a prolonged intertrial interval (9 vs 4 sec after a correct response). Novel odors were presented in each
session; thus the animal had to learn new associations each day. The
rat would begin each session by responding on every trial, irrespective
of whether a positive or a negative odor was presented. Learning was
evident when the rat began to withhold responses (no-go) after sampling
of the negative odor to avoid quinine delivery. This shift in the
rat's behavior generally began after 15-30 trials. Stable, highly
accurate performance was generally achieved after 60-100 trials,
reaching a behavioral criterion defined as 90% accurate performance
over a moving block of 20 trials. During postcriterion performance the
rat would make very few errors.
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Typically, a rat began each session by responding after sampling on
every trial, irrespective of which odor had been presented, and then
gradually learned to withhold responses (no-go) after sampling odors
that signaled that quinine would be delivered. The rats became highly
accurate within a single session at responding only to obtain sucrose
reinforcement. The shift to the adaptive behavioral strategy of
responding for the rewarding sucrose solution and withholding a
response to avoid the aversive quinine solution was reflected in the
acquisition of a behavioral criterion defined as 90% accurate
performance in a moving block of 20 trials. The rats generally met this
criterion in 60-100 trials. After reaching this criterion, rats
generally made few errors. In addition, in the sessions involving two
odor discrimination problems, postcriterion training was followed by
reversal training when the response contingencies of the two odors were
reversed so that the positive odor became associated with quinine,
whereas the negative odor became associated with sucrose.
Electrophysiological methods. At the start of each recording
session, each wire of the microelectrode bundle was screened for neural
activity. If no activity was evident, the bundle of wires was advanced
40 or 80 µm to acquire cells for the following day. If neural
activity was present on any of the wires, a recording session was
conducted. Neural activity on each microwire was passed through a
high-impedance JFET head stage, and then differential activity
on up to eight microwires was filtered at 300-3000 Hz, amplified 5000 times using Grass P5 series preamplifiers, and recorded on analog tape
along with computer-generated transistor-transistor logic pulses to
mark behavioral events using a Vetter model 400 PCM data recorder (AR
Vetter, Rebersburg, PA). Later, neural signals were digitized at 25 kHz, and then individual units were discriminated using a
template-matching algorithm (Cambridge Electronic Design, Cambridge,
England) in concert with examination of the oscilloscope tracing.
Typically one to three neurons could be discriminated on an active
electrode wire, and data were collected in 55 sessions in the
eight rats. Data from the cells in a subset of these animals (excluding
recordings in lateral nucleus) have been reported previously for a
different time interval in the training trial (during a response delay
after odor evaluation) (Schoenbaum et al., 1998).
Analysis of unit activity. Neural activity was examined
during odor evaluation on trials after the rat reached the behavioral criterion within a time window extending from 200 msec before to 150 msec after odor offset. This sampling period was synchronized to the
rat's decision to terminate odor sampling by leaving the odor port to
reflect the rat's evaluation of the odor. The inclusion of a period
200 msec before odor offset ensured that only activity at a latency of
at least 100 msec from odor onset would be included, and the sampling
interval was extended slightly after odor offset to include any
activity related to trace olfactory processing coincident with the
rat's decision to terminate odor evaluation. Neural activity (spikes
per second) within this time interval during postcriterion training was
compared on trials involving different odors using ANOVA. A
statistically significant difference (p < 0.05)
was further evaluated if the session involved four odors by post
hoc testing to compare activity on trials with each odor. Neurons
with elevated activity on trials specific to a single odor or on trials
of either of a pair of odors associated with a same reinforcer were
categorized similarly as either positive odor or negative odor
selective (see Table 1). The populations of neurons in ABL and OFC that
were selective in the postcriterion phase were further analyzed for
development of that selectivity in the precriterion phase and for the
effect of reversal training on selectivity.
Selective activity during the precriterion trials was determined using
the same statistical analysis applied to the postcriterion trials. When
a similar selectivity was evident in the analysis of the precriterion
trials, that phase was further subdivided to measure initial
selectivity during an early segment of training. This early segment,
used previously (Schoenbaum et al., 1998), included only those trials
preceding the sixth negative go response (error) and included, on
average, 15 trials. These trials were selected for analysis to examine
neural activity before the rat began to withhold responses. Finally
neural activity was also examined during reversal training, again using
ANOVA (p < 0.05).
In addition to examining selective activity for each neuron, the degree
of selectivity in the two populations was also analyzed. The analysis
included the early and late segments of precriterion training, trials
during postcriterion performance and trials during reversal training.
Selectivity for each neuron in each of those phases of a session was
quantified as the difference between the rates during evaluation of the
preferred and nonpreferred odors divided by the sum of those rates,
yielding values that ranged from  1 to 1. The contrast in activity
during each phase of training was referenced to the odor preferred by
each neuron during postcriterion performance. The contrasts for the
four phases of training were then compared within each region using
ANOVA followed by post hoc testing (p < 0.05). The population analysis (data shown in Figs. 2,
3c) included 42 neurons in ABL and 43 neurons in OFC and
comprised, on average, 16 (early), 73 (late), 114 (postcriterion), and
167 (reversal) trials for the data shown. It should be noted that only
selective neurons from sessions (n = 44 sessions) in which the rate of learning allowed an analysis of activity during the
early segment of precriterion training were included in this analysis.
Neurons recorded in 11 sessions were not included, because rats did not
commit at least 10 errors overall or 5 errors before the third no-go
response during precriterion training. In addition, 5 neurons in OFC
and 18 neurons in ABL were excluded because of a lack of activity in
the early precriterion trials that were the focus of this analysis. For
consistency, data from neurons excluded from the analysis of the early
segment were also excluded from the other phases of training in the
presentation of the results, although the values for the other phases
of training were not changed significantly by the exclusion of those
data. This analysis parallels that applied in an earlier report
(Schoenbaum et al., 1998).
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RESULTS |
Recordings were obtained from 328 neurons in OFC and 229 neurons
in ABL. Figure 2 illustrates the
electrode placement in a photomicrograph from a representative animal
in each group and drawings depicting the area within which recordings
were obtained in each region. Cells recorded in the OFC group were
located in the ventrolateral and lateral orbital regions and also
ventral agranular insular cortex. Cells recorded in the ABL group were located in the basolateral nucleus in the case of three of the rats and
in the lateral nucleus in the case of a fourth rat. Neuronal characteristics were similar between groups, and we observed no significant differences in either the characteristics or activity during odor sampling of the neurons recorded in ABL based on their localization in basolateral or lateral nucleus. Overall the cells included in this report tended to have low baseline firing rates and
relatively wide spike widths consistent with classification as regular
spiking cells thought to be pyramidal-type neurons in these areas
(McCormick et al., 1985; Connors and Gutnick, 1990; Taira and
Georgopoulos, 1993). Average baseline firing rates were 3.73 in OFC and
2.08 in ABL [F(2,552) = 10.38;
p < 0.0001]. No complex spike or intrinsic bursting
cells were included in the analyses.
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Figure 2.
Electrode recording sites. Photomicrographs of
histological sections showing the reconstruction of recording sites in
representative subjects in OFC (A) and ABL
(B). In each photomicrograph, a vertical
line represents the dorsoventral range along the electrode
track from which neurons were recorded in the case shown. Below each
photomicrograph is a drawing that shows the approximate area in which
recordings were obtained in each group. The OFC encompasses the orbital
regions and agranular insular cortex. Recordings were localized to
ventrolateral and lateral orbital regions (VLO/LO) and
ventral agranular insular cortex (AIv) in the four rats
in the OFC group. Recordings were localized to the basolateral nucleus
in three of the rats in the ABL group (pictured in photomicrograph and
as BLAn in drawing) and lateral nucleus in the fourth
rat (LAn). (Drawings adapted from Swanson, 1992;
photomicrographs adapted from Schoenbaum et al., 1998.)
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Neural activity in OFC and ABL during accurate performance
Neurons in both OFC and ABL fired differentially during odor
evaluation after rats had achieved the behavioral criterion for learning; such differences were observed in analyses based on ~100
postcriterion trials on average. During this postcriterion phase,
comparison of neural activity in trials involving different odors
revealed that 96 (or 29%) of the 328 neurons recorded in OFC and 60 (or 26%) of the 229 neurons recorded in ABL fired selectively during
evaluation of the odor cues. As indicated in Table
1, some neurons in each region had higher
rates of firing during evaluation of cues predicting sucrose delivery,
whereas other neurons fired more strongly during evaluation of cues
predicting quinine delivery. Of the neurons recorded in the four-odor
task with selectivity during odor evaluation (Table 1), 20 (41%) in OFC and 25 (60%) in ABL responded equally to either of the two odors
associated with a particular outcome; thus the outcome associated with
the odor appeared to influence firing activity in these cases during
accurate performance. In subsequent analyses, the responses of the
neurons that had selective activity during accurate performance were
examined over the course of learning before rats reached criterion and,
where possible, during reversal training.
Characteristics of the development of selective encoding
in ABL
Consistent with the proposal that ABL is involved in associative
learning, a considerable number of the ABL neurons that fired selectively in the postcriterion phase developed that selective activity during precriterion training. In fact, 22 (or 37%) of the 60 ABL neurons represented in Table 1 had selectivity during the
precriterion trials similar to that observed in the postcriterion phase. These neurons developed selectivity before accurate
postcriterion performance was achieved, as illustrated by the ABL
neuron shown in Figure 3. During initial
training this neuron had significantly higher activity when the rat
sampled the positive odor relative to the negative odor during both
precriterion and postcriterion phases of the session (Fig. 3a,
left panel). The development of this neuron's selectivity
is illustrated in the trials shown in Figure 3b, left panel.
Note that this neuron was not selective during an early segment of the
precriterion phase (Fig. 3b, left panel, arrows; see
Materials and Methods for definition of early segment) but developed
selectivity well before the behavioral criterion was achieved
(indicated by the break in the display of trials for each odor).
Furthermore, the selective activity of this neuron reversed to reflect
the new reinforcement contingencies during reversal training (Fig.
3a,b, right panels). It is apparent in the trials shown for
reversal training that the neuron initially had selectivity for the
formerly positive odor but then rapidly developed selectivity for the
formerly negative odor that signaled a positive contingency after
reversal. As observed during initial training, selectivity developed
after reversal well before the behavioral criterion for reversal
learning was achieved. Indeed, reversal of the neuron's selectivity
occurs well before the rat makes the initial no-go response to the new
contingencies.
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Figure 3.
Selective activity in ABL during odor evaluation.
a, Selective activity for an ABL neuron during
evaluation of odor 1 (open bars) and odor 2 (closed bars) represented as a percentage of the
pretrial baseline firing rate (24.1 spikes/sec). On initial training,
this neuron fired more strongly during evaluation of the positive odor
(odor 1) during postcriterion (post) performance
[F(1,86) = 83.05; p < 0.001], and similar selectivity was present during precriterion
(pre) training
[F(1,77) = 4.00; p < 0.05]. During reversal training the neuron changed selectivity based
on the new contingencies, developing a higher relative firing rate to
the odor signaling sucrose availability
[F(1,101) = 22.52; p < 0.001]. Please note that although this example shows a neuron with
greater activity to the positive odor, the data shown in Table 1
indicate that other cells in ABL fired more strongly during evaluation
of the negative odor(s). b, Raster displays showing
neural activity on 30 representative trials (n = total trials) during evaluation of each odor before and after reversal,
presented in the left and right panels,
respectively. Neural activity, with spikes shown as black tick
marks within the shaded regions, begins with odor
onset and is synchronized to odor offset corresponding to withdrawal
from the odor port (thin vertical line). Activity is
truncated at the go response when a response was made or after 1500 msec in the event of a no-go. Trials in which a no-go occurred are
evident in fading of the shaded region at
the end of each raster. Precriterion and postcriterion trials are
separated by a small empty space in the displays of both
the initial training and reversal training. Note that during initial
training, the rat begins the session responding on every trial but
gradually starts to withhold responses on the negative trials; very few
responses were made to negative odors after criterion is achieved.
During postcriterion performance, this neuron is strongly selective for
the positive odor. This selectivity is also present during precriterion
trials; however, the cell does not fire selectively during the initial
block of precriterion trials corresponding to the early segment of
training (trials preceding the arrows). During reversal
training, the selective activity of the neuron rapidly shifts after
only a few trials to reflect the new response contingencies. At that
point in reversal training, however, the rat continues to respond after
sampling of the formerly positive odor that now signals quinine. Thus
the reversal of selective activity in the neuron develops before a
reliable change in the rat's behavioral strategy. It is also clear
that this selectivity reflects the significance of an odor cue rather
than its sensory features. c, Contrast in activity
during evaluation of positive and negative odors during the early
(open bars) and late (closed bars)
segments of precriterion training, during postcriterion performance
(gray bars), and during reversal training
(striped bars) for the neurons with postcriterion
selectivity in ABL (see Materials and Methods). The activity contrast
was calculated as the difference in firing rate during the evaluation
of positive and negative odors divided by the sum of those rates,
yielding values that ranged from -1 to 1. The calculation was
referenced to the selectivity established during postcriterion
training. Firing activity between the trials was used to calculate a
baseline activity contrast of 0.01 (data not shown). The degree of
selectivity changed significantly in ABL
[F(4,184) = 39.44; p < 0.000001] during training. Post hoc tests revealed that
the degree of selectivity differed from baseline in each phase of
training except the early segment. Relative to the early segment, the
activity contrast increased significantly in the late segment of
precriterion training but was not significantly different between the
late segment and the postcriterion performance phase. During reversal
the selectivity in the ABL population reversed; the negative
values in the contrast indicate that the odor that elicited
greater firing activity after reversal differed from the odor that was
preferred during initial training. This contrast for reversal trials
differed significantly from the contrasts for each other phase,
including baseline and the early precriterion segment that showed low
selectivity.
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The example shown in Figure 3 illustrates the importance of associative
significance in the selective activity observed in ABL. Clearly the
neuron's selectivity was not tied to the sensory features of a
particular odor cue but rather depended on the associated outcome. In
fact, none of the ABL cells that developed selectivity during initial
learning maintained the same selectivity during reversal training. Of
the 18 selective ABL neurons (two-odor sessions only) that were
recorded during reversal training, 10 cells (or 55%) reversed firing
selectivity to reflect the new contingencies, as illustrated by the
neuron in Figure 3; the remainder lost the selectivity that had
developed during initial learning.
The main features of the ABL neuron illustrated in Figure 3 were
representative of the population of ABL neurons that displayed selective activity during postcriterion performance. The relative selectivity for that population of cells was examined within the early
and late segments of precriterion training (see Materials and Methods
for description), during postcriterion training, and during reversal
training. The selectivity measure for each of those phases of a
training session was calculated as the difference in firing rate during
evaluation of the preferred and nonpreferred odors divided by the sum
of these rates, yielding a measure of the contrast in activity that
ranged from 1 to 1. The calculation was referenced to the
postcriterion selectivity of each neuron for each of the other phases.
The results of this analysis for the cells in ABL are presented in
Figure 3c. As in the example of the ABL neuron shown, the
relative selectivity of the population of neurons in ABL increased
significantly between early and late precriterion segments of training
but did not change significantly between the late precriterion trials
and the postcriterion phase. Although some correct no-go responses were
observed during the late precriterion phase, the same results depicted
in Figure 3c were obtained irrespective of whether the
criterion block of 20 trials was included in the late phase
(contrast = 0.37) or not (contrast = 0.38); thus the increase
in relative selectivity appears to be independent of the emerging
change in behavioral strategy. In addition, the
relative selectivity of the population in ABL changed polarity during
reversal training relative to the postcriterion phase, indicating a
change from selectivity for one odor during initial training to
selectivity for the other odor after reversal. Indeed, the relative
selectivity during reversal training was significantly different from
that observed in each of the earlier phases of training, including both
baseline (data not shown) and the early segment of precriterion training.
Characteristics of the development of selective encoding
in OFC
The pattern of encoding in OFC differed from that observed in ABL.
Among the neurons that fired selectively in the postcriterion phase,
few exhibited similar selectivity in the precriterion phase; only 9 (or
9%) of the 96 OFC neurons represented in Table 1 had a similar
selectivity during precriterion training. Instead, the vast majority
(91%) of these neurons developed selectivity only at the phase of
training when the rat made a reliable shift to the go, no-go response
strategy. This pattern is apparent in Figure 4, a and b, left
panels, which illustrates a neuron that fired selectively during
evaluation of the positive odor but only during postcriterion training
when the rat was reliably discriminating between the odors. Also, in
contrast to the results for ABL, a smaller proportion of these neurons
reversed selectivity when the contingencies were changed. Of the 34 selective OFC neurons recorded during reversal training (two-odor
sessions), only 8 (or 23%) reversed firing selectivity, a proportion
significantly smaller than that in ABL [ 2 = 12.43;
p = 0.0004]. Rather than reversing selectivity, the majority of these cells (22 cells or 65%) lost the selectivity that
was manifest after initial learning, as was the case for the example
shown in Figure 4, a and b, right panels. Note
that this neuron fails to reverse even when the rat begins to perform well at the reversed discrimination.
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|
Figure 4.
Selective activity in OFC during odor evaluation.
a, Neural activity during evaluation of odor 1 (open bars) and odor 2 (closed bars)
represented as a percentage of the pretrial baseline firing rate (1.35 spikes/sec). This neuron fired more strongly during evaluation of the
positive odor (odor 1) during postcriterion
(post) training
[F(1,83) = 5.31 (5.08);
p < 0.05]. That selectivity was not evident
during precriterion (pre) training when the rat
had not yet adopted a reliable response strategy to reflect the learned
significance of the odors. Furthermore, the selectivity disappeared
during reversal training. Please note that although this example shows
a neuron with greater activity to the positive odor, the data shown in
Table 1 indicate that other cells in OFC fired more strongly during
evaluation of the negative odor(s). b, Raster displays
showing neural activity on 30 representative trials
(n = total trials) during evaluation of each odor
before and after reversal, presented in the left and
right panels, respectively (for details, see Fig. 3).
Again note that the rat begins the session responding on every trial
but gradually begins to withhold (striped bars) for the neurons with
postcriterion selectivity in OFC (forresponses on the negative trials.
During the precriterion phase, the rat makes several intermittent no-go
responses, but the neuron fires very little during evaluation of either
odor. The selective activity of this neuron develops only after a
reliable change in the rat's behavioral strategy; during postcriterion
performance, the neuron fires strongly during evaluation of the
positive odor (odor 1). After reversal, the activity during odor
evaluation is no longer selective either before or after the rat
achieves criterion on the reversed discrimination problem.
c, Contrast in activity during evaluation of positive
and negative odors during the early (open bars) and late
(closed bars) segments of precriterion training, during
postcriterion performance (gray bars), and during
reversal training details, see Materials and Methods and Fig. 3
legend). The degree of selectivity changed significantly in OFC
[F(4,192) = 10.16; p < 0.000001] during training. Post hoc tests revealed that
the degree of selectivity only differed from the baseline of 0.04 (data
not shown) during the postcriterion phase of training. In other words,
the activity contrast in OFC was not significantly different between
the early and late segments of precriterion training, increasing
significantly only during the postcriterion performance phase. During
reversal training, the activity contrast decreased significantly
relative to postcriterion performance, returning to a value not
significantly different from baseline or either the early or the late
segment of precriterion training.
|
|
The relative selectivity for the population of OFC cells, shown in
Figure 4c, exhibits a pattern consistent with the example shown for that region. The selectivity observed during postcriterion training was not evident in either the early or late segments of the
precriterion phase. Again selectivity during the late segment of
precriterion training did not differ significantly whether the
criterion block of trials was included (contrast = 0.09) or excluded from the analysis (contrast = 0.13). In addition, the relative selectivity in this population of OFC neurons decreased significantly from the postcriterion phase during reversal training but
did not reverse as it had in ABL (Fig. 3c). Instead,
selectivity during reversal training did not differ significantly from
the values obtained for baseline (data not shown) or during either the
early or late precriterion training phases. Notably, the loss of
selectivity in this population of OFC neurons was accompanied by the
emergence of selectivity in a separate population of neurons in OFC. Of
the 92 remaining neurons, recorded during reversal training and not
selective during initial training, 22 (or 24%) developed selective
firing after criterion was attained on the reversed discrimination.
| |
DISCUSSION |
The current findings are consistent with the interpretation that
ABL encodes the motivational significance of cues and OFC serves an
integrative function for guiding adaptive goal-directed behavior
based on information accessed through its connections with ABL and
other structures. This view agrees with other evidence that ABL
provides a critical function in associative learning and that OFC
integrates information needed for decision making.
This report differs from previous studies that have separately examined
neural activity in either OFC (Thorpe et al., 1983; Schoenbaum and
Eichenbaum, 1995a; Critchley and Rolls, 1996; Rolls et al., 1996) or
ABL (Sanghera et al., 1979; Nishijo et al., 1988; Muramoto et
al., 1993; Quirk et al., 1995). Although such studies have
reported that neurons in each region encode associative information, they provide little information about the relationship between the
development of encoding and behavior, because recordings were made in
well trained animals or in very rapidly acquired behavioral tasks.
Encoding in ABL reflects the motivational significance of
olfactory cues
In the course of training, ABL neurons developed selective
responses during odor sampling. This selective activity was not present
during the initial training trials but developed rapidly, well before
accurate choice performance was achieved. Moreover, a large proportion
of these cells also rapidly reversed selectivity when the reinforcement
contingencies were switched.
These findings support the proposal that neural activity in ABL
reflects the acquired significance of the olfactory cues based on
associations between the originally neutral odors and the motivational properties of reinforcement. Rapid conditioning of neural responses in
rat amygdala has also been reported in auditory discrimination training
(Muramoto et al., 1993) and fear conditioning (Quirk et al., 1995) and
in visual discrimination in primates (Sanghera et al., 1979; Nishijo et
al., 1988). In each of these cases neural activity was recorded in
conjunction with conditioned responses that were also rapidly acquired.
The present study extends on those reports by showing that a change in
neural activity in ABL can occur independently of a reliable change in
choice behavior. Most of the neurons reported here developed selective
firing before the rat had begun to consistently use that information in
performing the go, no-go discrimination. This was evident both during
initial training and after reversal.
The reversal of many ABL neurons in our study also extends on earlier
work in clearly demonstrating that neural encoding of cue significance
in ABL can change rapidly to reflect changes in task contingencies.
Somewhat equivocal findings have been previously reported regarding the
ability of neural correlates in amygdala to change after initial
training. Quirk et al. (1995) reported that conditioned neural
responses in the lateral nucleus of amygdala disappeared during
extinction procedures in a fear-conditioning task. Similarly, Nishijo
et al. (1988) reported that neural responses in primate amygdala to the
visual presentation of a food item were eliminated when the food item
was made unpalatable. During reversal training in a visual
discrimination task, however, Sanghera et al. (1979) reported that
neurons in primate amygdala maintained their responses to items that
were paired with either rewarding or aversive fluid delivery after
reversal. In their study, none of the nine visually selective neurons
reversed firing selectivity when the contingencies were reversed. In
the present study, 10 of the 18 selective neurons in the two-odor task
reversed, a phenomenon that often occurred rapidly after only a few
trials. In comparing our results with those of Sanghera et al. (1979),
it may be important to note that the reversal of neural activity
reported here occurred in the same session in which a new odor
discrimination was originally learned, whereas Sanghera et al. (1979)
conducted a separate reversal session after considerable experience
with the visual items used in the task. Perhaps reversal of neural
activity is more readily achieved with relatively new learning, and
extensive training makes reversal of the conditioned neural responses
more difficult. Nevertheless, our data clearly demonstrate that
encoding in ABL remains plastic for some time after modification by new learning.
Encoding in OFC reflects integration of motivational significance
into behavioral strategy
In contrast to the neural activity observed in ABL, selective
responses during odor sampling in OFC developed in a manner that was
more clearly related to the change in choice behavior. These findings
extend on previous neurophysiological studies performed in well trained
animals that have reported selective neural activity in rat and primate
OFC during stimulus sampling within discrimination tasks (Schoenbaum
and Eichenbaum, 1995a; Thorpe et al., 1983; Critchley and Rolls, 1996;
Rolls et al., 1996). As noted previously, these studies were performed
in well trained animals. In the current report, neurons in OFC that
were selective during accurate performance rarely developed that
selectivity during the earlier phases of training. Moreover, during
reversal training, the selective activity of these neurons was more
likely to be eliminated rather than reversed, and a largely separate
set of neurons emerged to perform the function that this population had
performed during initial training. Therefore, selective activity in OFC
did not consistently represent the identity of particular odors, the
motivational characteristics of the associated reinforcer, or
preparation for the motoric response. Instead it would appear that the
selective activity in OFC during accurate performance represents the
integration of information regarding the significance of a particular
cue (or cues) with subsequent behavior. These findings are consistent
with the view that neural activity in OFC reflects the information used
to guide a behavioral strategy.
Interactions between OFC and ABL
Our findings indicate that neurons encoding the associative
significance of cues predominate in ABL during odor sampling, whereas
the vast majority of OFC neurons active during odor sampling are tied
to the use of that information in the rats' behavioral strategy.
Interconnections between these regions may allow cells in ABL to signal
networks in OFC regarding the particular motivational significance of
cues as this information becomes relevant to selection of
behavioral options. Dependence of OFC on ABL for associative information is consistent with other neural correlates we have found in
this task. As reported elsewhere, a largely different (nonoverlapping)
population of neurons in OFC fired selectively in anticipation of a
particular outcome when these same rats responded at the fluid well
after odor sampling (Schoenbaum et al., 1998). Those neurons had
significantly different firing rates depending on whether sucrose or
quinine delivery was imminent during a delay instituted after the
response. The selective activity developed early in training when rats
had not yet modified their behavior; it was present before cells in OFC
had begun to fire selectively during actual sampling of the odor cues,
as reported here. Selective firing in OFC during responding may depend,
in part, on the encoding observed in ABL during odor sampling.
By the same token, reciprocal connections may allow processing in OFC
to regulate networks in ABL. In our previous report, neurons in ABL
also fired selectively during the delay after responding (Schoenbaum et
al., 1998). This population of ABL neurons might reflect a working
memory function that is supported by OFC. Moreover, neural activity in
anticipation of a response-dependent outcome, as described in our
previous report, would require registration that a response had been
executed. An indicator of responding in the task might be provided
directly or indirectly via networks in OFC. In this manner, these two
regions would function cooperatively, along with other interconnected
structures, in the production of goal-directed behavior that reflects
the motivational significance of cues.
OFC as a model for prefrontal cortex
Within prefrontal cortex, different subdivisions can be
distinguished based on anatomical and cytoarchitectonic criteria. One
view is that these subdivisions perform comparable processing functions
on domain-specific information determined by anatomical connectivity
with other neural systems (Goldman-Rakic, 1987). For example, adjacent
areas within primate dorsolateral prefrontal cortex process specialized
attributes of visual input, but a similar working memory function is
evident their operation (for review, see Goldman-Rakic, 1996).
Within this framework, the connectivity of OFC is consistent with its
role in processing information concerning the emotional and
motivational significance of cues. OFC is heavily involved in circuits
related to olfactory processing as well as limbic structures such as
the amygdala (Krettek and Price, 1977; Kolb, 1984; Price et al., 1987,
1991; McDonald, 1991). Accordingly, the response properties of cells in
OFC reflect this specialized information domain but also share certain
features with other regions of prefrontal cortex. For example, during
discrimination task performance, cells in both OFC (Thorpe et al.,
1983; Schoenbaum and Eichenbaum, 1995a) and dorsolateral prefrontal
cortex (Watanabe, 1990) encode the identity and significance of the
cues presented to the animal. Moreover, we have recently demonstrated
selective activity in OFC during a delay (Schoenbaum et al., 1998),
indicating that the cells in this region are able to maintain a
representation similar to the working memory function proposed for
other subdivisions of prefrontal cortex in primates (Goldman-Rakic,
1996). Finally, the current report and previous data (Schoenbaum and
Eichenbaum, 1995b) demonstrate that neurons in OFC, like those in
primate prefrontal cortex (Rainer et al., 1998), best represent
information of direct relevance to ongoing behavior. Viewed from this
perspective, OFC provides a potentially useful model for the study of
prefrontal systems in the rat.
| |
FOOTNOTES |
Received Aug. 27, 1998; revised Dec. 15, 1998; accepted Dec. 21, 1998.
This work was supported by funding from the National Institutes of
Health. We thank T. Lam for assistance in figure preparation and Dr. M. Burchinal and E. Neebe for statistical consultation.
Correspondence should be addressed to Dr. Geoffrey Schoenbaum, Johns
Hopkins University, Department of Psychology, 3400 North Charles
Street, 25 Ames Hall, Baltimore, MD 21218.
| |
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D. J. Calu, M. R. Roesch, T. A. Stalnaker, and G. Schoenbaum
Associative Encoding in Posterior Piriform Cortex during Odor Discrimination and Reversal Learning
Cereb Cortex,
June 1, 2007;
17(6):
1342 - 1349.
[Abstract]
[Full Text]
[PDF]
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K. M. Tye and P. H. Janak
Amygdala Neurons Differentially Encode Motivation and Reinforcement
J. Neurosci.,
April 11, 2007;
27(15):
3937 - 3945.
[Abstract]
[Full Text]
[PDF]
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M. R. Roesch, T. A. Stalnaker, and G. Schoenbaum
Associative Encoding in Anterior Piriform Cortex versus Orbitofrontal Cortex during Odor Discrimination and Reversal Learning
Cereb Cortex,
March 1, 2007;
17(3):
643 - 652.
[Abstract]
[Full Text]
[PDF]
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A. J. Tindell, K. S. Smith, S. Pecina, K. C. Berridge, and J. W. Aldridge
Ventral Pallidum Firing Codes Hedonic Reward: When a Bad Taste Turns Good
J Neurophysiol,
November 1, 2006;
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[Abstract]
[Full Text]
[PDF]
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G. Schoenbaum, B. Setlow, M. P. Saddoris, and M. Gallagher
Encoding Changes in Orbitofrontal Cortex in Reversal-Impaired Aged Rats
J Neurophysiol,
March 1, 2006;
95(3):
1509 - 1517.
[Abstract]
[Full Text]
[PDF]
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D. Dardou, F. Datiche, and M. Cattarelli
Fos and Egr1 expression in the rat brain in response to olfactory cue after taste-potentiated odor aversion retrieval
Learn. Mem.,
March 1, 2006;
13(2):
150 - 160.
[Abstract]
[Full Text]
[PDF]
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R. Gutierrez, J. M. Carmena, M. A. L. Nicolelis, and S. A. Simon
Orbitofrontal Ensemble Activity Monitors Licking and Distinguishes Among Natural Rewards
J Neurophysiol,
January 1, 2006;
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[Abstract]
[Full Text]
[PDF]
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C. A. Winstanley, D. E.H. Theobald, J. W. Dalley, R. N. Cardinal, and T. W. Robbins
Double Dissociation between Serotonergic and Dopaminergic Modulation of Medial Prefrontal and Orbitofrontal Cortex during a Test of Impulsive Choice
Cereb Cortex,
January 1, 2006;
16(1):
106 - 114.
[Abstract]
[Full Text]
[PDF]
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M. R. Roesch and C. R. Olson
Neuronal Activity in Primate Orbitofrontal Cortex Reflects the Value of Time
J Neurophysiol,
October 1, 2005;
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[Abstract]
[Full Text]
[PDF]
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Y. Masaoka, N. Koiwa, and I. Homma
Inspiratory phase-locked alpha oscillation in human olfaction: source generators estimated by a dipole tracing method
J. Physiol.,
August 1, 2005;
566(3):
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[Abstract]
[Full Text]
[PDF]
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D. I. G. Wilson and E. M. Bowman
Rat Nucleus Accumbens Neurons Predominantly Respond to the Outcome-Related Properties of Conditioned Stimuli Rather Than Their Behavioral-Switching Properties
J Neurophysiol,
July 1, 2005;
94(1):
49 - 61.
[Abstract]
[Full Text]
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L. L. Wellman, K. Gale, and L. Malkova
GABAA-Mediated Inhibition of Basolateral Amygdala Blocks Reward Devaluation in Macaques
J. Neurosci.,
May 4, 2005;
25(18):
4577 - 4586.
[Abstract]
[Full Text]
[PDF]
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M. A. McDannald, M. P. Saddoris, M. Gallagher, and P. C. Holland
Lesions of Orbitofrontal Cortex Impair Rats' Differential Outcome Expectancy Learning But Not Conditioned Stimulus-Potentiated Feeding
J. Neurosci.,
May 4, 2005;
25(18):
4626 - 4632.
[Abstract]
[Full Text]
[PDF]
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R. S. Ross, J. McGaughy, and H. Eichenbaum
Acetylcholine in the orbitofrontal cortex is necessary for the acquisition of a socially transmitted food preference
Learn. Mem.,
May 1, 2005;
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302 - 306.
[Abstract]
[Full Text]
[PDF]
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S. M. L. Cox, A. Andrade, and I. S. Johnsrude
Learning to Like: A Role for Human Orbitofrontal Cortex in Conditioned Reward
J. Neurosci.,
March 9, 2005;
25(10):
2733 - 2740.
[Abstract]
[Full Text]
[PDF]
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G. Deco and E. T. Rolls
Synaptic and Spiking Dynamics underlying Reward Reversal in the Orbitofrontal Cortex
Cereb Cortex,
January 1, 2005;
15(1):
15 - 30.
[Abstract]
[Full Text]
[PDF]
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A. Izquierdo, R. K. Suda, and E. A. Murray
Bilateral Orbital Prefrontal Cortex Lesions in Rhesus Monkeys Disrupt Choices Guided by Both Reward Value and Reward Contingency
J. Neurosci.,
August 25, 2004;
24(34):
7540 - 7548.
[Abstract]
[Full Text]
[PDF]
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C. A. Winstanley, D. E. H. Theobald, R. N. Cardinal, and T. W. Robbins
Contrasting Roles of Basolateral Amygdala and Orbitofrontal Cortex in Impulsive Choice
J. Neurosci.,
May 19, 2004;
24(20):
4718 - 4722.
[Abstract]
[Full Text]
[PDF]
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H. F. Clarke, J. W. Dalley, H. S. Crofts, T. W. Robbins, and A. C. Roberts
Cognitive Inflexibility After Prefrontal Serotonin Depletion
Science,
May 7, 2004;
304(5672):
878 - 880.
[Abstract]
[Full Text]
[PDF]
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A. Izquierdo and E. A. Murray
Combined Unilateral Lesions of the Amygdala and Orbital Prefrontal Cortex Impair Affective Processing in Rhesus Monkeys
J Neurophysiol,
May 1, 2004;
91(5):
2023 - 2039.
[Abstract]
[Full Text]
[PDF]
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S. M. Nicola, I. A. Yun, K. T. Wakabayashi, and H. L. Fields
Cue-Evoked Firing of Nucleus Accumbens Neurons Encodes Motivational Significance During a Discriminative Stimulus Task
J Neurophysiol,
April 1, 2004;
91(4):
1840 - 1865.
[Abstract]
[Full Text]
[PDF]
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C. L. Pickens, M. P. Saddoris, B. Setlow, M. Gallagher, P. C. Holland, and G. Schoenbaum
Different Roles for Orbitofrontal Cortex and Basolateral Amygdala in a Reinforcer Devaluation Task
J. Neurosci.,
December 3, 2003;
23(35):
11078 - 11084.
[Abstract]
[Full Text]
[PDF]
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A. Pears, J. A. Parkinson, L. Hopewell, B. J. Everitt, and A. C. Roberts
Lesions of the Orbitofrontal but not Medial Prefrontal Cortex Disrupt Conditioned Reinforcement in Primates
J. Neurosci.,
December 3, 2003;
23(35):
11189 - 11201.
[Abstract]
[Full Text]
[PDF]
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G. Schoenbaum and B. Setlow
Lesions of Nucleus Accumbens Disrupt Learning about Aversive Outcomes
J. Neurosci.,
October 29, 2003;
23(30):
9833 - 9841.
[Abstract]
[Full Text]
[PDF]
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I. Bohn, C. Giertler, and W. Hauber
NMDA Receptors in the Rat Orbital Prefrontal Cortex are Involved in Guidance of Instrumental Behaviour under Reversal Conditions
Cereb Cortex,
September 1, 2003;
13(9):
968 - 976.
[Abstract]
[Full Text]
[PDF]
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T. W. Buchanan, D. Tranel, and R. Adolphs
A Specific Role for the Human Amygdala in Olfactory Memory
Learn. Mem.,
September 1, 2003;
10(5):
319 - 325.
[Abstract]
[Full Text]
[PDF]
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J. A. Gottfried, J. O'Doherty, and R. J. Dolan
Encoding Predictive Reward Value in Human Amygdala and Orbitofrontal Cortex
Science,
August 22, 2003;
301(5636):
1104 - 1107.
[Abstract]
[Full Text]
[PDF]
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M. L. Fletcher and D. A. Wilson
Olfactory Bulb Mitral-Tufted Cell Plasticity: Odorant-Specific Tuning Reflects Previous Odorant Exposure
J. Neurosci.,
July 30, 2003;
23(17):
6946 - 6955.
[Abstract]
[Full Text]
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M. Juusola and G. G. de Polavieja
The Rate of Information Transfer of Naturalistic Stimulation by Graded Potentials
J. Gen. Physiol.,
July 28, 2003;
122(2):
191 - 206.
[Abstract]
[Full Text]
[PDF]
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I. Bohn, C. Giertler, and W. Hauber
Orbital Prefrontal Cortex and Guidance of Instrumental Behavior of Rats by Visuospatial Stimuli Predicting Reward Magnitude
Learn. Mem.,
May 1, 2003;
10(3):
177 - 186.
[Abstract]
[Full Text]
[PDF]
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G. Schoenbaum, B. Setlow, S. L. Nugent, M. P. Saddoris, and M. Gallagher
Lesions of Orbitofrontal Cortex and Basolateral Amygdala Complex Disrupt Acquisition of Odor-Guided Discriminations and Reversals
Learn. Mem.,
March 1, 2003;
10(2):
129 - 140.
[Abstract]
[Full Text]
[PDF]
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A. E. Kelley and K. C. Berridge
The Neuroscience of Natural Rewards: Relevance to Addictive Drugs
J. Neurosci.,
May 1, 2002;
22(9):
3306 - 3311.
[Full Text]
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S. Tronel and S. J. Sara
Mapping of Olfactory Memory Circuits: Region-Specific c-fos Activation After Odor-Reward Associative Learning or After Its Retrieval
Learn. Mem.,
May 1, 2002;
9(3):
105 - 111.
[Abstract]
[Full Text]
[PDF]
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W. H. J. Martens
Criminality and Moral Dysfunctions: Neurological, Biochemical, and Genetic Dimensions
Int J Offender Ther Comp Criminol,
April 1, 2002;
46(2):
170 - 182.
[Abstract]
[PDF]
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J. S. Rubinsztein, P. C. Fletcher, R. D. Rogers, L. W. Ho, F. I. Aigbirhio, E. S. Paykel, T. W. Robbins, and B. J. Sahakian
Decision-making in mania: a PET study
Brain,
December 1, 2001;
124(12):
2550 - 2563.
[Abstract]
[Full Text]
[PDF]
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O. K. Hassani, H. C. Cromwell, and W. Schultz
Influence of Expectation of Different Rewards on Behavior-Related Neuronal Activity in the Striatum
J Neurophysiol,
June 1, 2001;
85(6):
2477 - 2489.
[Abstract]
[Full Text]
[PDF]
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G. Schoenbaum and B. Setlow
Integrating Orbitofrontal Cortex into Prefrontal Theory: Common Processing Themes across Species and Subdivisions
Learn. Mem.,
May 1, 2001;
8(3):
134 - 147.
[Abstract]
[Full Text]
[PDF]
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B. Roozendaal, D. J.-F. de Quervain, B. Ferry, B. Setlow, and J. L. McGaugh
Basolateral Amygdala-Nucleus Accumbens Interactions in Mediating Glucocorticoid Enhancement of Memory Consolidation
J. Neurosci.,
April 1, 2001;
21(7):
2518 - 2525.
[Abstract]
[Full Text]
[PDF]
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S. J. Ramus and H. Eichenbaum
Neural Correlates of Olfactory Recognition Memory in the Rat Orbitofrontal Cortex
J. Neurosci.,
November 1, 2000;
20(21):
8199 - 8208.
[Abstract]
[Full Text]
[PDF]
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A. Qureshy, R. Kawashima, M. B. Imran, M. Sugiura, R. Goto, K. Okada, K. Inoue, M. Itoh, T. Schormann, K. Zilles, et al.
Functional Mapping of Human Brain in Olfactory Processing: A PET Study
J Neurophysiol,
September 1, 2000;
84(3):
1656 - 1666.
[Abstract]
[Full Text]
[PDF]
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W. Hauber, I. Bohn, and C. Giertler
NMDA, But Not Dopamine D2, Receptors in the Rat Nucleus Accumbens Are Involved in Guidance of Instrumental Behavior by Stimuli Predicting Reward Magnitude
J. Neurosci.,
August 15, 2000;
20(16):
6282 - 6288.
[Abstract]
[Full Text]
[PDF]
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G. Schoenbaum, A. A. Chiba, and M. Gallagher
Changes in Functional Connectivity in Orbitofrontal Cortex and Basolateral Amygdala during Learning and Reversal Training
J. Neurosci.,
July 1, 2000;
20(13):
5179 - 5189.
[Abstract]
[Full Text]
[PDF]
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M. G. Baxter, A. Parker, C. C. C. Lindner, A. D. Izquierdo, and E. A. Murray
Control of Response Selection by Reinforcer Value Requires Interaction of Amygdala and Orbital Prefrontal Cortex
J. Neurosci.,
June 1, 2000;
20(11):
4311 - 4319.
[Abstract]
[Full Text]
[PDF]
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D. Saar, Y. Grossman, and E. Barkai
Reduced Synaptic Facilitation between Pyramidal Neurons in the Piriform Cortex After Odor Learning
J. Neurosci.,
October 1, 1999;
19(19):
8616 - 8622.
[Abstract]
[Full Text]
[PDF]
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M. Gallagher, R. W. McMahan, and G. Schoenbaum
Orbitofrontal Cortex and Representation of Incentive Value in Associative Learning
J. Neurosci.,
August 1, 1999;
19(15):
6610 - 6614.
[Abstract]
[Full Text]
[PDF]
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Top
Abstract
Introduction
