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10.1146/annurev.psych.56.091103.070239
Annu. Rev. Psychol. 2005. 56:1–23
doi: 10.1146/annurev.psych.56.091103.070239
c 2005 by Annual Reviews. All rights reserved
Copyright First published online as a Review in Advance on June 10, 2004
IN SEARCH OF MEMORY TRACES
Richard F. Thompson
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Neuroscience Program, University of Southern California, Los Angeles,
California 90089-2520; email: [email protected]
Key Words learning, hippocampus, cerebellum, inactivation, localization
■ Abstract The key issue in analyzing brain substrates of memory is the nature of
memory traces, how memories are formed, stored, and retrieved in the brain. In order
to analyze mechanisms of memory formation it is first necessary to find the loci of
memory storage, the classic problem of localization. Various approaches to this issue
are reviewed. A particular strategy is proposed that involves a number of different
techniques (electrophysiological recording, lesions, electrical stimulation, pathway
tracing) to identify the essential memory trace circuit for a given form of learning and
memory. The methods of reversible inactivation can be used to localize the memory
traces within this circuit. Using classical conditioning of eye blink and other discrete
responses as a model system, the essential memory trace circuit is identified, the basic
memory trace is localized (to the cerebellum), and putative higher-order memory traces
are characterized in the hippocampus.
CONTENTS
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Simplified Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Strategies to Study Memory Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
OUR MODEL SYSTEM: EYEBLINK CONDITIONING . . . . . . . . . . . . . . . . . . . . . 6
Motor Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
The Hippocampus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
The Essential Circuitry: The Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
INTRODUCTION
A major achievement of recent research on brain substrates of learning and memory, to which our work has contributed, is the recognition that there are several
different forms or aspects of memory involving different brain systems (Figure 1).
Squire (1992) has argued eloquently for the distinction between declarative and
nondeclarative forms of memory, as has Schacter (1987). The distinction between episodic and semantic memory—“What did you have for breakfast?” versus
“Where is the Eiffel Tower?”—has been stressed by Tulving (1985).
0066-4308/05/0203-0001$14.00
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Figure 1 A current view of the various forms of learning and memory and their putative brain substrates.
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Implicit or nondeclarative memory is very much a grab bag. In general, explicit
memory involves awareness of the memory whereas implicit memory does not
necessarily involve being aware of the memory (aware meaning verbal report).
The schema of Figure 1 is of course oversimplified. When an organism learns
something, a number of brain systems can become engaged. However, in most
cases there is one critical brain system, which when damaged causes permanent
impairment in the particular form of learning and memory.
Many readers will recall Lashley’s (1950) pessimistic conclusion that his series
of experiments “has yielded a good bit of information about what and where
the memory trace is not” in his famous article, “In Search of the Engram.” In
all fairness to Lashley, the existence of several different forms of memory with
differing neuronal substrates was not recognized at that time, nor were modern
analytic techniques available then.
We adopt the following definitions from an earlier review (Lavond et al. 1993).
The essential memory trace, together with its associated circuitry, is necessary and
sufficient for the basic aspects of a given form of learning (e.g., acquisition and
retention). Other brain structures may also form memory traces, defined loosely as
learning-induced changes in neuronal activity, but these may not be essential for
the basic learning. Thus, in eyeblink conditioning, long-lasting learning-induced
increases in neuronal activity develop in the hippocampus (Berger et al. 1976), but
the hippocampus is not necessary for basic delay associative learning and memory
(Schmaltz & Theios 1972).
Aversive classical conditioning can modify the receptive-field properties of neurons in sensory systems. Particularly striking are the studies of Weinberger and
associates (Edeline & Weinberger 1991, Weinberger et al. 1984) showing that neurons in secondary areas of auditory thalamus and cortex shift their best frequencies
toward the frequency of the conditioning stimulus in aversive Pavlovian conditioning (see also Bao et al. 2003). The motor area of the cerebral cortex provides yet
another example. Classical eyeblink conditioning results in marked and persisting increases in excitability of pyramidal neurons in motor cortex (Woody et al.
1984). However, the motor cortex is not necessary for either learning or memory of
the conditioned eyeblink response (Ivkovich & Thompson 1997). These “higherorder” memory traces appear to play important roles in the adaptive behavior of
the organism.
The obvious point here is that the organism can learn, remember, and perform the basic learned response following destruction of nonessential memory
trace systems, but destruction of the essential memory trace system abolishes this
ability. We draw a distinction between the essential memory trace and the essential memory trace circuit. The latter includes the necessary input and output
circuits as well as the essential memory trace itself. These are all identified by
lesions. But lesions, per se, cannot distinguish between the essential trace and the
essential circuitry; lesions of either completely prevent and abolish the learned
response.
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Simplified Systems
How does one go about finding memory traces? One very productive approach is
the use of simplified “model” systems, emphasized early by Thompson & Spencer
(1966) (see also Kandel & Spencer 1968). Thus, vertebrate spinal reflexes and the
gill-withdrawal reflex circuit in Aplysia have both served as very productive models
to analyze processes of habituation and sensitization. In the case of habituation,
at least, the memory trace is embedded within the reflex pathway under study so
lesions abolish the reflex as well as the trace. For monosynaptic pathways in both
Aplysia and spinal cord the mechanism of short-term habituation appears to be
simply a decrease in the probability of transmitter release as a result of repeated
activation, a presynaptic process of synaptic depression (Farel & Thompson 1976,
Kandel 1975).
But even for a simple behavioral phenomenon like habituation, the neural substrate can prove to be complex, particularly for long-lasting habituation, e.g., between sessions as opposed to within session response decrements. In the Aplysia
cellular monosynaptic system, Ezzeddine & Glanzman (2003) have shown that
prolonged habituation depends on protein synthesis, protein phosphatase activity, and postsynaptic glutamate receptors. Indeed, their data indicate that stimuli
inducing habituation of the gill-withdrawal reflex appear to activate sensitizing
processes as well, as proposed in the “dual-process” theory of habituation by
Groves & Thompson (1970).
Thus, much is still not known about the detailed mechanisms of memory traces
in this simplest form of learning. By mechanisms we mean the physical-chemical
substrate of memory store. Although there are many candidate mechanisms, as of
this writing we do not yet know the detailed physical bases of memory storage for
any form of learning and memory in the mammalian brain. But understanding the
mechanisms of memory storage will not inform us of what the memories are. The
actual memories are coded by the neuronal circuits that code, store, and retrieve
the memories, what I term here the “essential circuits.”
Strategies to Study Memory Formation
There appear to be two general strategies for the study of memory storage. One
approach is to pick a mechanism of neural plasticity such as long-term potentiation
(LTP) in a structure known to be important for memory and attempt to show that it
is a substrate for memories. Richard Morris and associates published a heroic effort
to demonstrate that activity-dependent synaptic plasticity, particularly LTP (and
LTD, long-term depression), “is both necessary and sufficient for the information
storage underlying the type of memory mediated by the brain area in which that
plasticity is observed” (Martin et al. 2000). They established several “formal” criteria by which to judge this hypothesis. We examine these criteria below but here
we simply note their conclusion that “synaptic plasticity is necessary for learning and memory, but that little data currently supports the notion of sufficiency”
(p. 649).
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Actually, there are many forms of plasticity in the nervous system, synaptic plasticity being only one. There are also changes in neuron excitability due
to factors intrinsic to the neurons, as in decreases in after-hyperpolarization, as
well as structural changes in dendrites, formation of new neurons, and actions
of glial cells. LTP has been the most intensely studied putative synaptic mechanism of memory storage, particularly in the hippocampus (e.g., Martin et al.
2000), but the evidence is still far from clear. There is a vast literature analyzing mechanisms of LTP but very little work attempting to show that it is a basis
for the storage of memories (see Shors & Matzel 1997, Wilson & Tonegawa
1997).
The alternative strategy is to begin with a well-characterized form of learning
and memory and determine the memory traces involved. In order to do this it is first
necessary to find where in the brain the memories are stored, the classical problem
of localization. Because learning involves changes in behavior as a result of exposure to stimuli that do not change, there must be alterations at some loci in the brain.
A given form of learning may involve one or multiple loci of memory storage, but
they must exist. We have used this strategy in our search for memory traces.
How does one go about finding a memory trace in the behaving mammal? Olds,
Disterhoft, and associates wrestled with this issue in pioneering studies (Olds et al.
1972). Their basic approach was to record extracellular unit cluster discharges in
many brain areas in freely moving rats, looking for increases in unit response on
the conditioning day that were significantly greater than responses to the stimuli
on the preceding pseudoconditioning day, i.e., a learning-induced increase in unit
activity. The behavioral situation was simply an auditory conditioned stimulus
(CS+) followed after 2 sec by a food pellet unconditioned stimulus (US) versus a
CS− with no food pellet. The studies were very well controlled.
The initial criterion they set for identification of the memory trace was shortest
latency learned responses:
The “earliest” conditioned brain responses (i.e., those appearing with the
shortest latencies after application of the CS) might thus be considered to be
“at the site” of conditioning, and other later conditioned brain responses might
be considered to be secondary to them. Similarly (and hopefully validating
this supposition) “early” new brain responses might be expected to emerge at
the site of old responses indicating this site to be a junction point between old
and new (Olds et al. 1972, p. 202).
In a most interesting thought piece, Michael Gabriel (1976) argued against the
use of the shortest latency response as the criterion for identification of the memory
trace. He proposed an alternative “bias” hypothesis. In essence, he suggested that a
tonic flow of impulses originating from a distant neuronal locus biased the activity
of the neurons being recorded as the shortest latency learned response. So the
increase of the shortest latency unit response could be due to tonic actions on
these neurons from a distant site where learning has resulted in a tonic increase
in activity. Gabriel draws the following rather strong conclusion: “clearly the bias
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hypothesis argues against the idea of mapping the brain for short-latency neuronal
responses in order to localize engrams” (p. 279).
In a companion piece to the Olds et al. (1972) article, Disterhoft & Olds (1972)
do consider the possibility of tonic influences, as Gabriel notes. They suggest an
additional criterion, namely the earliest increase in neuronal activity that develops
over the trials of training. I return to this issue below.
In the late 1960s and early 1970s we tried several different types of model
systems to analyze neural substrates of mammalian associative learning and memory. Because of our success in using spinal reflexes for analysis of habituation
we tackled classical conditioning of the flexion reflex in the acute spinal animal,
with some success (Patterson et al. 1973). However, I concluded it was not a good
model of associative learning in the behaving mammal.
OUR MODEL SYSTEM: EYEBLINK CONDITIONING
Thanks in part to efforts by Michael Patterson, then a postdoc in my lab who had
obtained his Ph.D. with Isadore Gormezano, and because of the elegant and comprehensive behavioral studies by Gormezano, we adopted his preparation: classical
conditioning of the nictitating membrane (NM) eyeblink response in the restrained
rabbit. We have detailed the advantages of this preparation elsewhere (Thompson
et al. 1972, Thompson et al. 1976). Perhaps the most important advantages are:
(a) The unconditioned response (UR) provides an independent measure of performance against which to compare effects of variables acting on the conditioned
response (CR), and (b) the behavioral conditioned response is robust, reliable, and
discrete, and the exact amplitude-time course of the response is measurable. There
were a number of other advantages as well: no sensitization, pseudoconditioning,
or alpha responding; many trials required to learn; and extensive parometric data on
the properties of the CR (see Gormezano et al. 1983, and the important theoretical
analyses by Wagner and associates, e.g., Wagner & Donegan 1989).
Motor Control
We began our analysis with a focus on the motor nerves and nuclei that generated the reflex and learned eyeblink responses (Cegavske et al. 1976, Cegavske
et al. 1979, Young et al. 1976). To oversimplify from our work and the work of
others, the sixth nerve was critically important for the nictitating membrane (NM)
response, but the third and fourth nerves were also involved and the seventh nerve
was critical for closure of the external eyelid (obicularis oculi muscles). In terms
of motor nuclei, the seventh nucleus controlled external eyelid closure and the
accessory portion of the sixth nucleus innervated the retractor bulbous muscle,
which retracted the eyeball and forced the nictitating membrane out across the
front surface of the eye. The fourth and sixth nuclei acted synergistically with
the accessory sixth and seventh. We showed with simultaneous recordings that
NM extension and external eyelid closure [actually electromyographic (EMG)
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activity of the obicularis oculi muscles] were essentially perfectly correlated over
the course of learning (McCormick et al. 1982b). Indeed, obicularis oculi EMG
appears to be the most robust and sensitive measure of learning (Lavond et al.
1990). Recordings from the relevant motor nuclei, particularly the sixth, accessory sixth, and seventh, showed essentially identical patterns of learning-induced
increases in neuronal activity.
It is important to stress the fact that the pathways mediating the reflex eyeblink are in the brain stem and do not involve “higher” brain systems such as the
cerebellum and hippocampus. Specifically, there are direct projections from the
trigeminal nucleus (activated by stimulation of the cornea and surrounding tissues)
to the relevant motor nuclei and indirect projections relaying via the brain stem
reticular system to the motor nuclei (Hiraoka & Shimamura 1977).
The basic logic of our approach seemed reasonable—identify the critical motor
neurons involved in control of the learned response and trace the essential circuitry
backward to the source, the “engram.” The fact that several motor nuclei showed the
same pattern of learning-induced activation argued against any plasticity unique
to one motor nucleus (e.g., the accessory sixth) or to processes of plasticity at
the level of the motor nuclei. Instead, it seemed most likely that the learninginduced response in the motor nuclei was driven from a common central source.
The pattern of learning-induced increase in the activity of neurons in the motor
nuclei in the CS period in paired trials and on CS-alone trials (i.e., the neuronal
CR) was strikingly similar in form to the amplitude-time course of NM extension,
external eyelid closure, and of course the EMG recorded from the obicularis oculi
muscles. Indeed, an envelope of increased frequency of discharge of neurons in
the motor nuclei preceded in time and closely predicted the form of the behavioral
eyeblink-NM response (Figure 2). This close predictive parallel was most evident
with unit cluster recordings but was also true for single unit recordings in the motor
nuclei.
Our initial logic—to work backward from the motor nuclei—was not as simple as it might have seemed because of
the very large number of central brain systems that project to the motor and premotor nuclei. So we adopted a different strategy. It was apparent that the amplitudetime course form of the conditioned eyeblink-NM response closely paralleled and
followed the pattern of increased unit activity in the motor nuclei. So we focused
on this behavioral model of the learning-induced increase in neural activity in
the motor nuclei and used it as a template or model (Figure 2). The higher brain
systems that acted to generate and drive the learning-induced neuronal CR, the
“model” in the motor nuclei, must show the same pattern of learning-induced activity as do the motor nuclei, and hence the amplitude-time course of the learned
eyeblink-NM response. Thus, we searched through higher brain systems looking
for learning-induced neuronal activity that correlated closely with and preceded in
time the form of the learned eyeblink-NM response. In essence, we mapped virtually the entire brain of the rabbit in 1 mm steps, searching for neuronal models
USE OF THE MOTOR NEURON NEURONAL MODEL
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Figure 2 Histograms of unit cluster recordings from the ABD and simultaneous recording of
the eyeblink response (NM, the “third eyelid”) in classical conditioning in the rabbit summed
and averaged over eight trials before (A) and after (B) learning. First cursor onset of tone CS,
second cursor onset of corneal airpuff US, trace duration 750 msec, upward movement of
the NM trace indicates extension (eyelid closure). Note that the pattern of neural discharges
precedes and models the amplitude-time course of the behavioral response. ABD, abducens
motor nucleaus; CS, conditioned stimulus; NM, nictitating membrane; US, unconditioned
response. (From Cegavske et al. 1979.)
of the learned behavioral response (see, e.g., McCormick et al. 1983, Thompson
et al. 1976). We did not search blindly but rather system-by-system.
The basic assumption is that the neuronal sites of memory trace formation will
show a pattern of increased frequency of unit cluster and single-unit discharges
that precedes and closely predicts the pattern of response in the motor nuclei and
hence in the amplitude-time course of the behavioral CR. We felt this criterion
was preferable to the earlier ideas of shortest latency response, earliest response
over trials, or first site to show increased tonic responses. This assumption proved
to be the key that permitted us to localize a memory trace.
The Hippocampus
Because of its involvement in memory, we began with the hippocampus (Berger
et al. 1976). To our delight, both unit cluster recordings and single-unit responses
recorded from CA1 and CA3 showed the requisite learning-induced responses, i.e.,
pattern of increased discharge frequency that preceded in time (within trials) and
correlated virtually perfectly with the amplitude-time course of the behavioral CR
(Figure 3).
We showed that this neuronal model of a memory is generated by identified
pyramidal neurons (Berger & Thompson 1978b). Furthermore, the hippocampal
unit response began to develop in the US period within just a few trials of training
(a criterion by Olds et al. 1972) and moved into the CS period in close association
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Figure 3 Behavioral eyeblink (nictitating membrane) and hippocampal unit response
averaged over 100 trials in a well-trained rabbit. The unit response is of a single, identified pyramidal neuron in CA1. Upper trace, raw single 100-msec sweep to show the
neuron response, middle trace averaged NM response, lower trace cumulated histogram
of unit activity; cursors and durations in middle and lower traces as in Figure 2. Note
that the pattern of response of this neuron both precedes and models the amplitude-time
course of the behavioral response. (From Berger & Thompson 1978b.)
with the development of the behavioral CR (Berger & Thompson 1978a). It seemed
like a perfect candidate for the engram. In addition, electroencephalogram (EEG)
activity recorded from the hippocampus at the beginning of training predicted the
rate of learning (Berry & Thompson 1978). We characterized this learning-induced
response in the hippocampus in some detail (see Berger et al. 1986). Unfortunately,
as we noted above, animals could learn the basic delay-conditioned NM-eyeblink
response following hippocampal lesions (Schmaltz & Theios 1972).
This apparent enigma illustrates a fundamental limitation of using neuronal
recordings to localize memory traces. The fact that a neuronal model of the learned
response occurs at a given locus does not necessarily mean it originates there.
Indeed, the learning-induced neuronal model in the hippocampus, at least in the CS
period, is abolished by appropriate cerebellum lesions (Clark et al. 1984). Actually,
a number of loci in the brain exhibit the learning-induced neuronal model of the
learned behavioral response. I return to this issue below.
The breakthrough insofar as the hippocampus is concerned came in a study in
our laboratory by Paul Solomon and Donald Weisz using the trace-conditioning
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paradigm, where a 500-msec period of no stimuli separated CS offset from US
onset (Solomon et al. 1986). In brief, large bilateral hippocampal lesions made
before training markedly impaired subsequent learning of the trace (but not delay)
eyeblink CR, a result replicated exactly by Moyer et al. (1990). If the hippocampal
lesions are made immediately after learning, the trace CR is abolished (with no
effect on the delay CR), but if the lesions are made a month after training the trace
CR remains intact (Kim et al. 1995).
In sum, hippocampal lesions induced anterograde amnesia (impairment of
postlesion learning) and marked but time-limited retrograde amnesia for the trace
eyeblink CR. These are precisely the effects that such lesions have on declarative
memory in humans (Squire 1987). These results suggest that trace eyeblink conditioning provides a simple model of hippocampal-dependent declarative memory,
a possibility strongly supported by studies of humans with hippocampal-medial
temporal lobe amnesia. Such patients are markedly impaired on acquisition of trace
eyeblink conditioning if the trace interval is sufficiently long but not impaired at
all on delay conditioning (see McGlinchey-Berroth et al. 1997).
Clark & Squire (1998, 1999) made the striking observation that awareness of
the training contingencies in normal human subjects correlated highly with the
degree of learning of trace eyeblink conditioning. Recall that awareness is a key
defining property of declarative memory. They also showed that awareness played
no role in delay conditioning, and that expectancy of US occurrence influenced
trace but not delay conditioning (Clark & Squire 2000, Clark et al. 2001). They
conclude that delay and trace conditioning are fundamentally different phenomena,
with delay conditioning inducing nondeclarative or procedural memory and trace
conditioning inducing declarative memory. Hence, trace eyeblink conditioning
in rabbits would seem to provide a very elementary instantiation of declarative
memory in animals.
These strikingly parallel results of hippocampal lesions in rabbits and humans
for trace eyeblink conditioning suggest the possibility that a memory trace(s) may
develop in the hippocampus in trace conditioning, but do not prove it. Recall that
delay eyeblink conditioning results in the development of a pronounced neuronal
model of the learned response in the hippocampus (as does trace training).
Several lines of evidence support the view that localized changes do develop
in the hippocampus in eyeblink conditioning. Thus, the properties of increased
neuronal activity are strikingly similar to the properties of LTP (Berger et al. 1986,
Thompson 1997, Weisz et al. 1984), and induction of LTP in the hippocampus
can enhance eyeblink learning (Berger 1984). There is also a dramatic learninginduced decrease in the after-hyperpolarization in pyramidal neurons in eyeblink
conditioning, most evident in trace conditioning, which leads to increased excitability. This alteration is intrinsic to the neurons due to a decrease in one or more
calcium-dependent outward potassium currents (Disterhoft et al. 1986, Disterhoft
& McEchron 2000). There is also a dramatic increase in dendritic membraneassociated protein kinase C after eyeblink conditioning (Olds et al. 1989). After
trace eyeblink conditioning there is a substantial increase in the number of multiple
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synapse boutons in hippocampal neurons (Geinisman et al. 2001). Finally, there
is a dramatic increase in the number of new neurons in the hippocampus in trace,
but not delay, eyeblink conditioning (Gould et al. 1999, Shors et al. 2001).
These sets of structural and chemical changes are certainly consistent with the
formation of higher-order memory traces in the hippocampus. But recall that cerebellar lesions can abolish both the behavioral learned response and the increased
neuronal response in the CS period in the hippocampus in both delay and trace
learning (see below and Clark et al. 1984, Woodruff-Pak et al. 1985). So doubts
remain. Interestingly, the early (over trials)-developing increase in neuronal activity in the hippocampus in the US period is not completely abolished by cerebellar
lesions (Clark et al. 1984). In my view, it is necessary to identify the entire essential
circuitry from stimulus input to motor output in order to establish definitively that
the essential memory trace, e.g., for trace conditioning, develops and is stored,
albeit temporarily, in the hippocampus (see below). To date, not all the essential
circuitry has been identified (see Thompson & Kim 1996). Yet another remaining
puzzle is where the trace memories go after the hippocampus is no longer necessary.
The Essential Circuitry: The Cerebellum
So the hippocampus is not the locus of the essential memory trace for standarddelay classical eyeblink conditioning. In a detailed mapping study of the brain stem
we identified several loci where neurons exhibited the requisite neuronal model
of the CR—increase in frequency of discharge that preceded the onset of the USUR and modeled the amplitude time source of the behavioral CR, just as did the
neuronal response in the hippocampus (McCormick et al. 1983). The following
brain areas showed this neuronal response predictive of the learned behavioral
CR: the relevant motor nuclei (as noted above), a region in the vicinity of the fifth
nucleus, various reticular regions, the cerebellar cortex (ansiform and anterior
lobes), the cerebellar interpositus nucleus, the pontine nuclei, and the red nucleus.
The response in the interpositus nucleus was particularly robust (Figure 4).
The fact that a neuronal model of the behavioral CR developed in the cerebellum
was suggestive of a memory trace but we knew from our earlier work on the hippocampus that neuronal recordings, per se, could not identify the essential memory
trace. We completed a series of lesion studies, initially involving large cerebellar
lesions and later lesions limited to the interpositus nucleus (e.g., McCormick &
Thompson 1984a,b; Clark et al. 1984), all of which completely prevented learning
and completely and permanently abolished the CR with no effect on the UR (thus
ruling out performance variables).
In a long series of studies completed while we were at Stanford, we identified virtually the entire essential memory trace circuit using electrophysiological
recordings, electrical stimulation, lesions (aspiration, electrolytic, and chemical),
and anatomical pathway tracing methods (see Chapman et al. 1988; Christian &
Thompson 2003; McCormick et al. 1982a, 1985; Lavond et al. 1985; Mauk et al.
1986; Steinmetz et al. 1986, 1987; J.K. Thompson et al. 1985; Woodruff-Pak et al.
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Figure 4 Neuronal model of learned eyeblink response recorded from the cerebellar interpositus nucleus. Each graph shows nictitating membrane movement (top trace) and a
histogram of multiple unit activity (bottom trace) averaged and summed over 100 trials.
Animals that received explicitly unpaired presentations of the conditioning stimuli do not
develop altered patterns of neuronal activity (left column). Trained animals develop a neuronal model of the learned behavior. Total trace duration 750 msec. (From McCormick &
Thompson 1984b.)
1985). In brief, the efferent CR pathway projects from the interpositus nucleus ipsilateral to the trained eye, via the superior cerebellar peduncle, to the contralateral
magnocellular red nucleus and to the relevant motor nuclei ipsilateral to the trained
eye. The cerebellar interpositus lesion abolition of the eyeblink CR is strictly ipsilateral and is due to damage to neuron somas, not fibers of passage. The inferior
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olive-climbing fiber system appears to be the critical US reinforcing or teaching
pathway and the pontine nuclei and mossy fiber system appears to convey the
necessary CS information to the cerebellum.
A particularly satisfying aspect of our discovery of the essential role of the cerebellum in classical conditioning of discrete responses is the relevance of our work
to the human condition. Irene Daum and associates, working in Germany, replicated in humans the fact that appropriate cerebellar damage completely prevents
learning of the eyeblink CR (Daum et al. 1993), since replicated in many other
studies. Christine Logan (a former graduate student of mine) and Scott Grafton, a
neurologist then at the University of Southern California, completed an extensive
positron emission tomography (PET) study of eyeblink conditioning in humans.
They found significant activation in the cerebellar interpositus nucleus and several
loci in cerebellar cortex, in close agreement with our recording studies in the rabbit
cerebellum (Logan & Grafton 1995), again replicated in many other studies.
A point that is obvious from our studies but seems not to be widely understood
is that our results on the role of the cerebellum in classical conditioning apply to the
learning of any discrete movement: eyeblink, head turn, forelimb flexion, hindlimb flexion, etc. (see Shinkman et al. 1996). Eyeblink conditioning is simply
a convenient response to measure. Our findings to date seem to have identified
perhaps the critical function of the cerebellum, namely the learning of discrete
skilled movements, a basic notion proposed in classic theories of the cerebellum
as a learning machine (see Albus 1971, Eccles 1977, Ito 1984, Marr 1969). Indeed,
our work constitutes a compelling verification of these theories.
Our data to this point strongly supported the hypothesis that the essential memory trace was formed and stored in the cerebellum, but did not prove it. Hence we
adapted use of methods of reversible inactivation to localize the memory trace.
The logic is straightforward. Having identified the essential memory trace circuit,
reversibly inactivate each key locus in the circuit during training. If this completely
prevents learning at a given locus, then this locus either conveys essential afferent information to the memory trace or is the site of the memory trace. However,
if reversible inactivation of a given locus does not prevent learning at all, then
this locus is efferent from the memory trace. But remember that inactivation of
all these essential loci will completely prevent expression of the CR. We infused
muscimol for inactivation of neuron cell bodies—it acts on gamma amino butyric
acid (GABAA) receptors as an agonist and completely shuts down (hyperpolarizes)
the neurons for several hours, after which they fully recover. To inactivate axons
we infused tetrodotoxin (TTX) (see, e.g., Krupa et al. 1993; Krupa & Thompson
1995, 1997; Krupa et al. 1996; Thompson & Krupa 1994). David Lavond and his
students completed parallel studies using reversible cooling (e.g., Clark et al. 1992,
Clark & Lavond 1993).
Results are completely consistent and have since been replicated in other laboratories. In brief (see Figure 5) inactivation limited to the anterior interpositus nucleus
completely prevented learning. After removal of inactivation animals showed no
signs of learning; with subsequent training they learned normally as though they
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Figure 5 Highly simplified schematic of the essential memory trace circuit for delay classical conditioning of the eyeblink response to illustrate the use of reversible inactivation to
localize memory traces. Shading in a, b, and c indicate reversible inactivation of the key region of each structure during training using muscimol; d indicates inactivation of the axonal
pathway exiting from the cerebellum, the superior cerebellar peduncle, using tetrodotoxin.
Inactivation of the interpositus (c) completely prevents learning, but inactivation of the superior peduncle (d), the red nucleus (b), and the motor nuclei (a) does not prevent learning
at all. (Modified from Thompson & Krupa 1994.)
had no prior training; there was no savings. In complete contrast, inactivation of the
superior peduncle (the immediate efferent projection from the interpositus/dentate
nuclei), the red nucleus, and the relevant motor nuclei, although completely preventing expression of the CR, did not prevent learning at all. After removal of
the inactivation the animals had fully learned to asymptote. Thus, inactivation
localized to the anterior interpositus nucleus completely prevented learning but inactivation of its immediate output pathway did not prevent learning at all. The fact
that after interpositus inactivation there was no savings argues strongly that no part
of the memory trace developed in structures afferent to the interpositus. Similarly,
the fact that inactivation of structures efferent from the interpositus did not prevent
learning at all argues that no part of the memory is formed in these structures.
I noted above that several loci in the brain exhibited the neuronal model of the
learned behavioral CR, e.g., trigeminal nuclear region, pontine nuclei, etc. In a
series of studies Lavond and associates (and we) showed that with inactivation of
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the interpositus nucleus, all these models disappeared, i.e., they are all driven from
the interpositus (Bao et al. 2000, Lavond & Cartford 2000).
Because muscimol acts only on neuron cell bodies and not on axons, the inactivation of the interpositus nucleus does not prevent normal activation of cerebellar cortex by the two major afferent systems, climbing fibers from the inferior
olive and mossy fibers from many sources. The fact that no learning at all occurred with inactivation limited to the interpositus nucleus would seem to argue
against formation of memory traces in the cerebellar cortex. However, this inactivation blocks the direct projections from the interpositus nucleus to the cerebellar
cortex.
When we first discovered the essential role of the cerebellum in eyeblink conditioning I had hoped the memory traces would be formed and stored in the cerebellar
cortex. The cellular machinery in the cortex is vast (each Purkinje neuron receives
up to 200,000 synapses from granule neurons). However, we were never able to
completely prevent or abolish the CR by lesions limited to the cerebellar cortex.
Other workers, particularly Yeo and associates (Yeo et al. 1984), claimed to have
done so. The problem is with the lesion method—it is impossible to remove all
of the cerebellar cortex without damaging the critical region of the interpositus
nucleus (see detailed discussion in Christian & Thompson 2003). However, we
consistently found that with large cerebellar cortical lesions or reversible inactivation, learning was much slower and to a lesser degree and adaptive timing of the
CR was lost. Normally the eyeblink closure CR peaks at the onset of the US; it is
a maximally adaptive response. After large cortical lesions, the CR peaks earlier
in time and is no longer adaptive (Garcia et al. 1999, McCormick & Thompson
1984b). So the cortex is critically important for normal adaptive learning and it
seemed very likely that higher-order memory traces were established there. But
again the lesion method is inconclusive.
Fortunately nature provided us with an ideal preparation, the Purkinje cell
degeneration (pcd) mutant mouse. The brain of this mutant develops normally
until about two weeks after birth. Then over the next several weeks, all Purkinje
neurons in the cerebellar cortex die; as a result the animals have no functional
cerebellar cortex. But the interpositus nucleus remains functional. Results were
clear: The pcd mice were able to learn (L. Chen et al. 1996). They learned much
more slowly and to a lesser degree than normal mice of the same strain (littermates),
but they still showed significant and substantial learning. The CRs were shorter
latency in the pcd mice. They also showed rapid extinction with CS-alone training.
The possibility that the memory trace was somehow formed in loci other than the
cerebellum was ruled out by lesioning the interpositus nucleus bilaterally in pcd
mice before training. The lesioned pcd mice were unable to learn the conditioned
eyeblink response (L. Chen et al. 1999).
These results were very similar to the effects of large cerebellar cortical lesions
we had found earlier in rabbits. So the cortex is critically important for normal
learning, and higher-order memory traces are likely formed there. There is considerable evidence supporting the view that a process of long-term potentiation
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(LTD) at the parallel fiber-Purkinje neuron dendritic synapses, discovered by Ito
(see 1984), plays a key role in initial plasticity (C. Chen & Thompson 1995, C.
Chen et al. 1995, Shibuki et al. 1996, Kim & Thompson 1997). Indeed, Purkinje neurons show substantial changes in CS-evoked discharge frequency over the
course of training, with many showing learning-induced decrease in discharge frequency, as could be expected if LTD developed (Christian et al. 2002, Christian
& Thompson 2003). Other lines of evidence also support the view that memory
traces are formed in cerebellar cortex (Cooke et al. 2004).
The evidence is now very strong that the basic essential memory trace is formed
and stored in the anterior interpositus nucleus for classical conditioning of the eyeblink response. Indeed, the reversible inactivation studies provide the key evidence
(Figure 5). It is clear that long-lasting changes in the critical neurons in the anterior
interpositus nucleus do develop. Thus, infusion of protein synthesis inhibitors in
this locus completely prevents learning (Bracha et al. 1998, G. Chen & Steinmetz
2000, Gomi et al. 1999). Further, training results in selective expression of a protein
kinase in this locus, KKIAMRE, an enzyme for the cell division cycle (Gomi et al.
1999). Pharmacological isolation of the interpositus from the cerebellar cortex reveals clear learning-induced increases in excitability of interpositus neurons (Bao
et al. 2002, Garcia & Mauk 1998). Perhaps most convincing, eyeblink conditioning
results in a dramatic and highly significant increase in the number of excitatory
synapses (but not inhibitory synapses) in the interpositus nucleus (Kleim et al.
2002).
CONCLUSION
The essential circuitry for classical conditioning of the eyeblink response is shown
in Figure 6, along with the site of memory trace formation in the interpositus
nucleus and a putative site of plasticity in the cerebellar cortical neurons. The nature
of the memory is defined by this circuit; the circuit is the memory. The CS activates
the sensory afferent pathways to the site(s) of trace storage in the cerebellum,
which activates the efferent pathways to the motor nuclei and the learned behavior.
The content of the memory, the conditioned eyeblink response, is completely
defined and completely predictable from the essential circuit.
The formal criteria developed by Richard Morris and associates to demonstrate
that a given set of phenomena establish what they term the “synaptic plasticity and
memory” (SPM) hypothesis are as follows (Martin et al. 2000):
1. DETECTABILITY: If an animal displays memory of some previous experience, a change in synaptic efficacy should be detectable somewhere in its
nervous system.
2. MIMICRY: Conversely, if it were possible to induce the same spatial pattern
of synaptic weight changes artificially, the animal should display “apparent”
memory for some past experience which did not in practice occur.
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Figure 6 Simplified schematic (most interneurons omitted) of the putative essential circuitry
for delay classical conditioning of eyeblink (and other discrete responses) learned with an
aversive US. (The sensory and motor nuclei activated depend of course on the nature of the
CS and US; the more central portions of the circuit appear to be general.) The reflex US-UR
pathway involves direct and indirect projection from the trigeminal nucleus to the motor nuclei
(for the eyeblink UR and CR, primarily accessory 6 and 7). The tone CS pathway projects
from auditory nuclei to the pontine nuclei and to the cerebellum as mossy fibers. The US
pathway includes projections from the trigeminal to the inferior olive and to the cerebellum
as climbing fibers. The CR pathway projects from the interpositus to the red nucleus and on
to premotor and motor nuclei. There is also a direct GABAergic inhibitory projection from
the interpositus to the inferior olive. Solid cell bodies and bar terminals indicate inhibitory
neurons; open cell bodies and fork terminals indicate excitatory neurons. Stars indicate sites
of plasticity based on current evidence. See text for details. (From Christian & Thompson
2003.) CR, conditioned response; CS, conditioned stimulus; UR, unconditioned response;
US, unconditioned stimulus.
3. ANTEROGRADE ALTERATION: Interventions that prevent the induction
of synaptic weight changes during a learning experience should impair the
animal’s memory of that experience.
4. RETROGRADE ALTERATION: Interventions that alter the spatial distribution of synaptic weights induced by a prior learning experience (see detectability) should alter the animal’s memory of that experience (p. 651).
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I would expand the SPM notion to include nonsynaptic mechanisms of plasticity
and memory as well, referring to all as the memory trace. I would also note that
these criteria cannot be met unless the putative memory trace has been localized.
Evidence to date on localization of the memory trace(s) for classical conditioning of eyeblink and other discrete responses would seem to satisfy Morris’ criteria.
1. DETECTABILITY: There is a dramatic increase in neuronal/synaptic efficacy in the cerebellum, both in the cortex of lobule HVI and in the anterior
interpositus nucleus as a result of training (see, e.g., Shinkman et al. 1996,
Bao et al. 2002). Indeed, long-term potentiation (LTP) has been reported to
occur in the interpositus nucleus (Racine et al. 1986).
2. MIMICRY: Electrical microstimulation of the locus of the memory trace in
the anterior interpositus nucleus can evoke the response to be learned before
training (McCormick & Thompson 1984a, Chapman et al. 1988).
3. ANTEROGRADE ALTERATION: Infusion of muscimol into the site of
the memory trace in the anterior interpositus nucleus completely prevents
learning, i.e., induction of the memory trace.
4. RETROGRADE ALTERATION: Infusion of muscimol into the site of the
memory trace in the anterior interpositus nucleus in a well-trained animal
alters the synaptic weights (shuts them down) and abolishes the animal’s
memory for that experience.
These of course are only opinions of what constitutes demonstration of a memory trace. In my view the key is that the essential circuit defines the memory, as I
noted above. But we still do not know the detailed nature of the memory trace in the
interpositus and how it is formed. It will be necessary to identify all the steps in the
causal chain from initial activation of the neurons at the beginning of training to the
final form of the memory trace, from the biochemical/genetic processes to the structural changes in the synapses and neurons that code the permanent memory trace.
ACKNOWLEDGMENTS
Work described in this paper was supported in part by National Science Foundation
Grant IBN 92,15069, National Institutes of Aging Grant AG14751, a grant from
the Sankyo Company, and funds from the University of Southern California.
The Annual Review of Psychology is online at http://psych.annualreviews.org
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Annual Review of Psychology
Volume 56, 2005
CONTENTS
Frontispiece—Richard F. Thompson
xviii
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PREFATORY
In Search of Memory Traces, Richard F. Thompson
1
DECISION MAKING
Indeterminacy in Brain and Behavior, Paul W. Glimcher
25
BRAIN IMAGING/COGNITIVE NEUROSCIENCE
Models of Brain Function in Neuroimaging, Karl J. Friston
57
MUSIC PERCEPTION
Brain Organization for Music Processing, Isabelle Peretz
and Robert J. Zatorre
89
SOMESTHETIC AND VESTIBULAR SENSES
Vestibular, Proprioceptive, and Haptic Contributions
to Spatial Orientation, James R. Lackner and Paul DiZio
115
CONCEPTS AND CATEGORIES
Human Category Learning, F. Gregory Ashby and W. Todd Maddox
149
ANIMAL LEARNING AND BEHAVIOR: CLASSICAL
Pavlovian Conditioning: A Functional Perspective,
Michael Domjan
179
NEUROSCIENCE OF LEARNING
The Neuroscience of Mammalian Associative Learning,
Michael S. Fanselow and Andrew M. Poulos
207
HUMAN DEVELOPMENT: EMOTIONAL, SOCIAL, AND PERSONALITY
Behavioral Inhibition: Linking Biology and Behavior Within a
Developmental Framework, Nathan A. Fox, Heather A. Henderson,
Peter J. Marshall, Kate E. Nichols, and Melissa A. Ghera
235
BIOLOGICAL AND GENETIC PROCESSES IN DEVELOPMENT
Human Development: Biological and Genetic Processes,
Irving I. Gottesman and Daniel R. Hanson
263
vii
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CONTENTS
SPECIAL TOPICS IN PSYCHOPATHOLOGY
The Psychology and Neurobiology of Suicidal Behavior,
Thomas E. Joiner Jr., Jessica S. Brown, and LaRicka R. Wingate
287
DISORDERS OF CHILDHOOD
Autism in Infancy and Early Childhood, Fred Volkmar,
Kasia Chawarska, and Ami Klin
315
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CHILD/FAMILY THERAPY
Youth Psychotherapy Outcome Research: A Review and Critique
of the Evidence Base, John R. Weisz, Amanda Jensen Doss,
and Kristin M. Hawley
337
ALTRUISM AND AGGRESSION
Prosocial Behavior: Multilevel Perspectives, Louis A. Penner,
John F. Dovidio, Jane A. Piliavin, and David A. Schroeder
365
INTERGROUP RELATIONS, STIGMA, STEREOTYPING,
PREJUDICE, DISCRIMINATION
The Social Psychology of Stigma, Brenda Major
and Laurie T. O’Brien
393
PERSONALITY PROCESSES
Personality Architecture: Within-Person Structures and Processes,
Daniel Cervone
423
PERSONALITY DEVELOPMENT: STABILITY AND CHANGE
Personality Development: Stability and Change, Avshalom Caspi,
Brent W. Roberts, and Rebecca L. Shiner
453
WORK MOTIVATION
Work Motivation Theory and Research at the Dawn of the Twenty-First
Century, Gary P. Latham and Craig C. Pinder
485
GROUPS AND TEAMS
Teams in Organizations: From Input-Process-Output Models to IMOI
Models, Daniel R. Ilgen, John R. Hollenbeck, Michael Johnson,
and Dustin Jundt
517
LEADERSHIP
Presidential Leadership, George R. Goethals
545
PERSONNEL EVALUATION AND COMPENSATION
Personnel Psychology: Performance Evaluation and Pay for Performance,
Sara L. Rynes, Barry Gerhart, and Laura Parks
571
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ix
PSYCHOPHYSIOLOGICAL DISORDERS AND PSYCHOLOGICAL EFFECTS
ON MEDICAL DISORDERS
Psychological Approaches to Understanding and Treating Disease-Related
Pain, Francis J. Keefe, Amy P. Abernethy, and Lisa C. Campbell
601
TIMELY TOPIC
Psychological Evidence at the Dawn of the Law’s Scientific Age,
David L. Faigman and John Monahan
631
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INDEXES
Subject Index
Cumulative Index of Contributing Authors, Volumes 46–56
Cumulative Index of Chapter Titles, Volumes 46–56
ERRATA
An online log of corrections to Annual Review of Psychology chapters
may be found at http://psych.annualreviews.org/errata.shtml
661
695
700