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The Journal of Neuroscience, April 1, 2003, 23(7):3001
Switching Memory Systems during Learning: Changes in Patterns of
Brain Acetylcholine Release in the Hippocampus and Striatum in Rats
Qing
Chang and
Paul E.
Gold
Department of Psychology, University of Illinois at
Urbana-Champaign, Champaign, Illinois 61820
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ABSTRACT |
This experiment measured acetylcholine (ACh) release simultaneously
in the hippocampus and striatum while rats were trained in a cross
maze. Consistent with past findings, rats initially showed
learning on the basis of place (i.e., turning to the correct position relative to the room), but after extensive training, rats
shifted to learning on the basis of response (i.e., turning to the
right/left to find the food). Profiles of ACh release in the
hippocampus and striatum were markedly different during training. In
the hippocampus, ACh release increased by ~60% at the onset of
training and remained at that level of release throughout training, even after the rats began to show learning on the basis of turning rather than place. In the striatum, increases in ACh release occurred later, reaching asymptotic increases of 30-40%, coincident with a
transition from expressing place learning to expressing response learning. These findings suggest that the hippocampal and striatal systems both participate in learning in this task, but in a manner characterized by differential activation of the neural systems. The
hippocampal system is apparently engaged first before the striatum is
activated and, to the extent the hippocampus is important for place
learning, promotes the use of a place solution to the maze. Later in
training, although the hippocampus remains activated, the striatum is
also activated in a manner that may enable the use of a response
strategy to solve the maze. These findings may offer a neurobiological
marker of a transition during skill learning from declarative to
procedural learning.
Key words:
hippocampus; striatum; learning strategies; interactions between memory systems; acetylcholine and regulation of
memory; spatial versus response learning systems
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Introduction |
Different classes of memory appear
to be processed by relatively distinct memory systems (Cohen and
Squire, 1980 ; Gabrieli, 1998 ; Kesner, 1998 ; Willingham, 1998 ; Gold et
al., 2001 ; Kim and Baxter, 2001 ; Packard, 2001 ; White and McDonald,
2002 ). The principal evidence comes from studies of multiple
dissociations of brain structure and memory functions. However, there
are also demonstrations showing that damage to one system can
enhance learning mediated by another system (Matthews and Best,
1995 ; McDonald and White, 1995 ; Matthews et al., 1999 ; White and
Wallet, 2000 ; Ferbinteanu and McDonald, 2001 ). These findings support
the view that multiple memory systems at times compete with each other
for control over learning.
Most studies of multiple memory systems use tasks that are dependent on
one but not another neural system. One task in which the contributions
of two systems can be contrasted is a cross maze. Rats are trained in a
T-configuration of the maze, in which they are trained, for example, to
go from the south arm to the east arm for reward. This simple task
requirement can be solved using either response (egocentric) or place
(allocentric) mechanisms. This task has a long history (Tolman et al.,
1946 , 1947 ) with detailed analyses of the impact of many variables on
learning (Restle, 1957 ). The solution used by each rat is revealed on a probe trial on which the rat begins from an arm
180o (e.g., north) from the original start
arm. The cross maze can be used to address the issue of whether rats
preferentially use learning on the basis of habit (i.e., turn right to
approach the goal) or on the basis of place (i.e., go to a particular
part of the room to approach the goal). Recent evidence indicates quite clearly that both types of learning contribute to acquisition of this
task. In particular, rats generally use place solutions early in
training and response solutions later in training (Packard and McGaugh,
1996 ). Lidocaine-induced inactivation of the hippocampus or striatum
decreases the expression of place and response solutions, respectively
(Packard and McGaugh, 1996 ). Conversely, glutamate-induced activation
of the hippocampal and striatal systems increases the expression of
place and response solutions, respectively (Packard, 1999 ).
Additionally, profiles of acetylcholine (ACh) release in the
hippocampus and striatum, evident even before initial exposure to the
maze, predict the preferred solution at the time rats reach criterion
performance (McIntyre et al., 2003a ). However, this predilection to use
place or response learning does not provide a full explanation of the
behavior because, after extensive training, most rats eventually select
response strategies at the time of a probe trial (Packard and McGaugh,
1996 ; Packard, 1999 ). Therefore, rats switch from place to response
[or from cognitive to habit (Packard, 1999 )] solutions with extensive
training. The issue for the present report is whether the switch in
strategy used to solve the maze is reflected in changes in the profiles
of ACh release in the hippocampus and striatum, used in this study to mark changes in the activation of these neural systems.
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Materials and Methods |
Subjects. Six male Sprague Dawley rats (Hilltop
Laboratories, Scottdale, PA), weighing 380-430 gm at the time
of surgery, were used as subjects. The rats were housed individually in
translucent cages, with food and water available ad libitum
until food restriction began. The rats were maintained in a 12 hr
light/dark cycle (lights on at 7:00 A.M.) throughout the experiment.
Surgery. Each rat was anesthetized with sodium pentobarbital
(50-60 mg/kg, i.p.). The rats were placed in a stereotaxic apparatus with horizontal skull (Paxinos and Watson, 1986 ). Two plastic guide
cannulas (3 mm, CMA/12; Carnegie Medicin, Stockholm, Sweden) were lowered into the hippocampus (coordinates, 5.0 mm posterior to
bregma, 5.0 mm lateral and 4.2 mm ventral from the surface of the
skull) and the lateral striatum (0.3 mm posterior to bregma, 4.3 mm
lateral and 3.7 mm ventral from the surface of the skull). The use of
ventral (vs dorsal) hippocampal placement was based on evidence showing
that, at least in terms of amygdala-dependent tasks, the ventral
hippocampus appears to be important for competition during learning
(Ferbinteanu and McDonald, 2001 ). Recent findings obtained with
measures of ACh release in the ventral hippocampus are consistent with
this view (McIntyre et al., 2002 ).
One-half of the subjects had cannulas in the left hippocampus and the
right striatum, and one-half had the converse implantation. The guide
cannulas were anchored in place with dental cement and skull screws.
Stylets made to be flush with the cannula tips were inserted into the
cannulas until the start of microdialysis procedures.
Behavioral procedures. Approximately 1 week after surgery,
the rats were placed on a food-restriction schedule such that their body weights were gradually reduced to and maintained at 80%. During
this 7-10 d period, the animals were weighed and handled (5 min/d)
every day.
The training apparatus was an elevated plus-shaped cross maze with a
black Plexiglas floor and clear Plexiglas walls. The maze had four
identical arms (length × width × height, 45 × 12.5 × 15 cm) containing food wells at their ends; the arms
extended from a central platform (12.5 × 12.5 × 15 cm).
Training was conducted in a lighted training room containing
moderate-density extramaze cues (e.g., posters on the walls, door, and
polygraph in a corner of the room).
On training trials, the arm facing the start arm was always blocked,
creating a T-maze. Rats were trained to turn right to obtain a half
piece of Frosted Cheerio (General Mills, Minneapolis, MN) located at
the end of one arm. Thus, each rat could use either an allocentric
spatial strategy (go to the arm in a fixed position of the room), or
egocentric nonspatial strategy (turn right) to obtain the food reward.
On each trial, a rat was placed at the end of start arm, facing the
center of the maze, and given up to 45 sec to find and to eat the food.
After the food was eaten or the time expired, the rat was placed in a
holding cage for an interval such that the time from the start of one
trial to the next was 60 sec. This was done to synchronize training
with collection of microdialysis samples so that a 5 min microdialysis
sample represented five trials. To avoid possible unintended influences
of intramaze cues, the maze was turned 90o
clockwise on every trial.
A probe test was administered after each block of 20 trials. On the
probe trial, the cross maze was configured as a T-maze with the start
arm 180o from the original start arm. Both
arms at the ends of the T-maze were baited on the probe trial. If, on
the probe trial, the rat turned in the direction that was correct
during training, the behavior was termed a response solution. If the
rat turned instead toward the arm now located in the correct place in
the room, the behavior was termed a place solution.
Probe trials were administered near the middle of a 5 min interval
between trials 20 and 21, 40 and 41, 60 and 61, 80 and 81, and after
100. Except for the time spent on the probe trial, each rat was kept in
the holding cage for the remainder of the 5 min. Thus, for each rat,
there were five training blocks of 20 trials each (total = 100 trials) and five probe trials. Training was completed on a single day
within a single session.
Microdialysis procedures. One microdialysis probe was
inserted through a guide cannula into the hippocampus, and another
probe was inserted into the contralateral striatum. The dialysis probes were perfused continuously at a rate of 2.0 µl/min with artificial CSF (in mM: 128 NaCl, 2.5 KCl, 1.3 CaCl2, 2.1 MgCl2, 0.9 NaH2PO4, 2.0 Na2HPO4, 1.0 dextrose,
adjusted to pH 7.4) that contained a 100 nM
concentration of the acetylcholinesterase inhibitor neostigmine.
To allow equilibration with brain extracellular fluid and to avoid
temporary changes in extracellular neurotransmitter levels caused by
acute tissue damage (Westerink and Timmerman, 1999 ), the first hour of
dialysate was discarded. During this hour, the animals were kept in a
holding cage with fresh bedding. Next, dialysate samples were collected
every 5 min into small vials by an automatic refrigerated fraction
collector (CMA/170; Carnegie Medicin). The first four samples were
collected while rats remained undisturbed in the holding cage and
comprised the samples for baseline values. After the baseline sampling
period, rats were trained while samples continued to be collected every
5 min. At the conclusion of behavioral testing, samples were sealed and stored at 20°C until assay for ACh content.
After in vivo sampling was completed, each microdialysis
probe was removed from the rat and placed into a 100 nM ACh standard solution for 10-15 min to
determine relative recovery.
ACh assay procedures. ACh content in each dialysate sample
was assayed by HPLC in combination with an electrochemical detector (BAS; Bioanalytical Systems, West Lafayette, IN). The
assay system included an ion-exchange microbore analytical
column (BAS P/N MF-8904, 530 × 1 mm), a microbore ACh/choline
immobilized enzyme reactor containing acetylcholinesterase and
choline oxidase (BAS P/N MF-8903, 50 × 1 mm), an auxiliary
electrode with radical flow electrochemical thin-layer cell and 13 mm
thin-layer gasket, a wired enzyme electrode kit (a redox polymer film
containing horseradish peroxidase coated on the surface of a 3 mm
glassy carbon working electrode), and a low-dispersion injection valve
with a 5 µl polyetheretherketone loop (Rheodyne
model 9125-087). Stable and relatively pulse-free flow was achieved
with a Shimadzu (Tokyo, Japan) LC-10ADvp pump with
microstep plunger.
The potential held by the working electrode was 100 mV versus an
Ag/AgCl reference electrode. The mobile phase contained 50 mM Na2HPO4, pH
8.5, and 0.5% Kathon (BAS P/N CF-2150). The flow rate was 140 µl/min. Injection volume in this experiment was 2.5 µl. The
detection limit was <5 fmol. The assay was completed within 13 min.
Histology. After training was completed, rats were deeply
anesthetized with sodium pentobarbital and perfused with saline followed by 10% formalin solution. The brains were removed and placed
in 10% formalin solution for 1-2 weeks before sectioning. Each brain
was then frozen ( 20°C) and sliced (50 µm) with a
Leica (Nussloch, Germany) 1800 cryostat. Sections
through probe sites were mounted on slides, dried, and stained with
cresyl violet. Figure 1 illustrates
acceptable placement locations for the probes.

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Figure 1.
Examples of acceptable placements of microdialysis
probes in the hippocampus (A) and striatum
(B). [Adapted from Paxinos and Watson
(1986) .]
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Results |
As shown in Figure 2, the rats
learned to approach the correct arm quite rapidly. Accuracy improved
from 50% during the first 10 trials to 87% in the second 10 trials,
and then reached and stayed at >95% throughout the rest of training.
The mean number of trials taken before beginning a run of 9 of 10 correct choices was 20.2 ± 2.3.

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Figure 2.
Rate of acquisition on cross maze. All rats
reached 9 of 10 correct choices by trial 30 regardless of strategy
shown on nearest probe trials.
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The performance observed on the probe trials administered after each 20 trials showed a steady change from place to response strategies (Fig.
3). The first probe trial occurred when
mean performance was between 87 and 95% correct (Fig. 2). On
this probe trial, five of the six rats made place selections. With
continued training through and beyond criterion performance, the rats
changed their selection on the probe trials until, after 100 trials,
all six rats made response selections (probe 1 vs 6;
2 = 8.571; p < 0.005).

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Figure 3.
Transition from place strategy to response
strategy during 100 training trials. A probe trial was administered
after every 20 training trials.
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A key issue in this experiment was whether the profile of changes in
ACh release during training was different in the hippocampus and
striatum. Concentrations of ACh in baseline samples were 7.3 ± 2.1 and 37.3 ± 12.3 fmol/µl for the hippocampus and striatum, respectively. As shown in Figure 4,
release of ACh in the hippocampus increased by ~60% immediately on
the start of training and remained at that level throughout the
training trials. In marked contrast, ACh release in the striatum
increased much more slowly, reaching its asymptotic increase of
30-40% after trial 25. For both hippocampal and striatal samples, the
magnitudes of ACh release during the 5 min samples taken at the time of
the probe trials were not different from those seen on the trials
immediately before and after and are therefore not shown here.

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Figure 4.
Changes in ACh release across 100 training trials.
Each sample represents 5 min before and during training. During
training, the samples correspond to five trials per sample. ACh release
in the hippocampus increased at the onset of training and remained
stable. In contrast, ACh release in the striatum grew gradually over
trials as the rats switched from place to response strategy.
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Of particular interest, the different times at which release of ACh
increased in the hippocampus versus striatum corresponded to the
changes in the preferred solution displayed by rats on the probe
trials. Early in training, when the rats exhibited a place strategy on
probe trials, release of ACh had already increased to its asymptote in
the hippocampus but was still low in striatum. Later in training, when
the rats switched to the use of a response strategy on the probe trial,
release of ACh in the striatum had also increased. Importantly, ACh
release in the hippocampus did not decline late in training but rather
remained high throughout training.
In past work from our laboratory, the ratio of baseline ACh release in
the hippocampus versus striatum predicted the performance on a single
probe test given immediately after rats reached criterion performance
(McIntyre et al., 2003a ). In the present experiment, the corresponding
probe trial could come between 1 and 20 trials after the criterion was
reached. Although an identical measure was not available in the present
experiment, it was possible to examine the relationship between
baseline release of ACh and the probe test number at which the subject
first used a response strategy. As shown in Figure
5, the ratio of baseline release of ACh
in the hippocampus/striatum was significantly correlated with the number of trials to the first selection of a response strategy on a
probe trial (r = 0.83; p < 0.05).
Those rats with the lowest ratio of ACh release in the hippocampus
versus striatum were the first to switch from a place to a response
strategy, and those with the highest ratio of ACh release in the
hippocampus versus striatum were the last to switch to a response
strategy.

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Figure 5.
Relationship between the ratio of baseline
(pretraining) release of ACh in the hippocampus and striatum and the
probe on which the rat first switched from a place to a response
solution to the maze.
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Discussion |
The main finding of this experiment is that the pattern of changes
in ACh release in the hippocampus and striatum during learning provides
a neurochemical marker of differential activation of these systems in a
manner associated with differential expression of learned responses for
a task that has two effective solutions. Rats quickly learned to enter
one arm of the maze to obtain food. However, consistent with previous
findings (Packard and McGaugh, 1996 ; Packard, 1999 ), the basis by which
the rats selected the correct arm changed from place to response
attributes after extended training. The present results provide
evidence that increases in ACh release in the hippocampus precede
increases in ACh release in the striatum during training on a task in
which learning proceeds sequentially from place to response strategies.
These findings provide the first neurobiological measures obtained
during training marking the transition in the memory systems
controlling learned performance during training.
The present findings used release of ACh to monitor the extent and
timing of participation of different brain regions during learning. ACh
release in the hippocampus increased to its maximum extent on the first
trials and remained at that maximum throughout training, suggesting
that the hippocampus was engaged at the outset of learning and remained
engaged throughout extended training. In contrast, ACh release in the
striatum increased more gradually, with the increase appearing as rats
made their transition from selecting place solutions to selecting
response solutions on probe trials. Thus, it appears that the
hippocampus was activated before the striatum (i.e., at the time rats
used place solutions to solve the maze). The striatal system was
activated later, at the time rats began to use response solutions.
Furthermore, the present findings suggest that the hippocampus remained
activated, but that the use of hippocampal processing was overridden
when the striatum became fully engaged. This interpretation is
consistent with the finding that inactivation of the striatum late in
training leads not to chance performance but to correct performance on
the basis of place learning (Packard and McGaugh, 1996 ). According to
this view, the hippocampus retains the capacity to provide a place
solution to the task and, in terms of ACh release as a marker, remains
activated during performance of the task. However, this capacity to
provide a place solution is obscured late in training by striatal
contributions, unless the later striatal contribution is diminished or
removed by pharmacological manipulation as in Packard and McGaugh
(1996) . Importantly, on the basis of both measures of ACh release and
manipulations of the striatum, hippocampal participation during
learning does not appear to wane even after extensive training. It is
intriguing to consider the possibility that the sequential activation
of the hippocampal and striatal systems may reflect a transition from
declarative to procedural memories.
Confirming previous findings (McIntyre et al., 2003a ), the relative
release of ACh in the hippocampus and striatum assessed before the
beginning of training predicts which individual rats will switch from
place to response solutions early and late in training. This aspect of
the results suggests that individual differences in the profiles of ACh
release across neural systems reflect the extent of bias between
competing memory systems during learning. The present findings indicate
that the bias, as well as relative release of ACh in the hippocampus
and striatum, can change during training.
In many circumstances, training-related increases in release of
acetylcholine in different neural systems provide a marker of the
degree of activation of those systems during learning (Ragozzino et
al., 1994 , 1996 , 1998 ; Fadda et al., 1996 , 2000 ; Orsetti et al., 1996 ;
Stancampiano et al., 1999 ; Nail-Boucherie et al., 2000 ; Gold et al.,
2001 ; Hironaka et al., 2001 ; McIntyre et al., 2002 , 2003a ,b );
findings within and across these studies show that locomotor activity
per se does not define well the conditions when increases in ACh
release are evident. These findings, like those of the present study,
do not deal directly with the issue of how ACh release regulates the
participation of different neural systems in learning and memory. More
generally, the findings do not determine whether ACh release is an
initiator or a consequence of activation. At a general level, the
findings are consistent both with views applying modulation of memory
formation to a systems-level understanding of memory processing (Gold
et al., 2001 ) and with views considering ACh to be a regulator of
attention (Everitt and Robbins, 1997 ; Wenk, 1997 ). Also, although there
are findings suggesting that lesions of forebrain cholinergic systems
have little or no impact on learning and memory (Baxter et al., 1996 ;
Perry et al., 2001 ), these findings may in part reflect limited damage
to cholinergic functions (Wrenn and Wiley, 1998 ; Gutiérrez et
al., 1999 ; Miranda and Bermúdez-Rattoni, 1999 ).
At a mechanistic level, the seemingly analogous actions of ACh in the
hippocampus and striatum are somewhat surprising given the major
differences in neuroanatomical organization of the cholinergic systems
in these brain areas. Although hippocampal ACh is derived entirely from
diagonal band/medial septum projection neurons, striatal ACh is
primarily derived from intrinsic cholinergic neurons (Woolf and
Butcher, 1981 ; Woolf, 1991 ; Calabresi et al., 2000 ). However, in both
instances, it may be important that the axonal fields for these cells
are very extensive in both the hippocampus and striatum, keeping open
the possibility of similar neurobiological functions for ACh in both
neural systems. For example, the extensive distribution of terminal
fields seems consistent with a modulatory function for ACh released in
both neural systems studied here, perhaps upregulating local processing
important for these systems to contribute to performance on this task.
Using a variety of techniques, many experiments have shown that
multiple memory systems are responsible for learning in the rat
(McDonald and White, 1995 ; Gold et al., 2001 ; Kim and Baxter, 2001 ;
Packard, 2001 ). The nature by which these systems interact is still
under active exploration. The interactions at times appear to be
competitive in nature; for example, the removal of the hippocampus appears to enhance learning mediated by other systems (Matthews and
Best, 1995 ; McDonald and White, 1995 ; Matthews et al., 1999 ; White and
Wallet, 2000 ; Ferbinteanu and McDonald, 2001 ). In past experiments
using ACh release to approach this issue, there is evidence that
the magnitude of ACh release in the hippocampus is inversely related to
acquisition of a task dependent on the amygdala (McIntyre et
al., 2002 ). However, competition is not the only form evident for
interactions between memory systems. ACh release in the amygdala is
positively correlated with performance on a hippocampus-dependent
task (McIntyre et al., 2003b ). These findings suggest that the
hippocampus and the amygdala have a nonreciprocal interaction in which
the hippocampus competes with the amygdala but the amygdala cooperates
with the hippocampus during learning. The present findings add
significantly to an understanding of the relationships between neural
systems important for processing different classes of learning by
adding both time (the stage of training) and shifts in the relative
extent of ACh release in different memory systems as features important
in understanding the coordination of multiple memory systems in
producing learned behavior.
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FOOTNOTES |
Received Aug. 12, 2002; revised Oct. 10, 2002; accepted Dec. 27, 2002.
This work was supported by United States Public Health Service research
grants from the National Institute on Aging (AG 07648) and the National
Institute of Neurological Disorders and Stroke (NS 32914), by the
United States Department of Agriculture (00-35200-9839), and by
the Alzheimer's Association.
Correspondence should be addressed to Dr. Paul E. Gold, Department of
Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel
Street, Champaign, IL 61820. E-mail: pgold{at}uiuc.edu.
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