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Vol. 5, No. 6, pp. 446-466, November/December 1998
Department of Biology, McGill University, Montreal, Quebec H3A 1B1, Canada
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Abstract |
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Repetitive stimulation often results in habituation of the elicited response. However, if the stimulus is sufficiently strong, habituation may be preceded by transient sensitization or even replaced by enduring sensitization. In 1970, Groves and Thompson formulated the dual-process theory of plasticity to explain these characteristic behavioral changes on the basis of competition between decremental plasticity (depression) and incremental plasticity (facilitation) occurring within the neural network. Data from both vertebrate and invertebrate systems are reviewed and indicate that the effects of depression and facilitation are not exclusively additive but, rather, that those processes interact in a complex manner. Serial ordering of induction of learning, in which a depressing locus precedes the modulatory system responsible for inducing facilitation, causes the facilitation to wane. The parallel and/or serial expression of depression and waning facilitation within the stimulus-response pathway culminates in the behavioral changes that characterize dual-process learning. A mathematical model is presented to formally express and extend understanding of the interactions between depression and facilitation.
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Origins of the Dual-Process Theory of Plasticity |
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There have been principally two different approaches to the study of
learning, the aggregate-field approach and the cellular-connection approach (see Kandel and Spencer 1968
). The aggregate-field approach maintains that plasticity cannot be studied at the cellular level because learning is a property of large groups of neurons rather than
of any single neuron. The cellular-connection approach holds the
opposite view, that learning is encoded by changes in specific neurons
and their synaptic connections to other neurons. According to the
latter approach, there are three steps of investigation: (1)
characterization of the neural circuit mediating a behavior, (2)
localization of the sites of plasticity within that circuit, and (3)
characterization of the mechanisms of plasticity at the cellular and
synaptic levels (Hawkins et al. 1987
). Over the past 30 years,
application of these steps has achieved impressive advancements in our
understanding of learning, with concurrent loss in popularity of the
aggregate-field approach.
Nowhere has the cellular connection approach been more successful than
in its application to the plasticity of withdrawal reflexes in
invertebrates, especially in Aplysia (for reviews, see Jacklet
and Lukowiak 1975
; Carew and Sahley 1986
; Byrne 1987
; Hawkins et al.
1987
, 1993
). The neural circuits mediating such reflexes are
comparatively simple and amenable to investigation. But even
"simple" circuits are not so easily understood. For instance, the
siphon-elicited siphon withdrawal reflex of Aplysia is
mediated through both monosynaptic and polysynaptic pathways.
Investigation of interneurons has led to increasing recognition of the
polysynaptic pathway's importance in mediating and modulating the
siphon withdrawal reflex and coordinating this reflex with other
behaviors (Byrne 1981
; Hawkins et al. 1981a
,b
; Trudeau and Castellucci
1992
; Cleary et al. 1995
; Frost and Kandel 1995
). This relatively low
level of network complexity is sufficient to offer multiple loci at which plasticity can occur (e.g., Frost et al. 1988
; Cohen et al.
1997
). In the gill and siphon withdrawal (GSW) reflex, the synapses
between sensory neurons (SNs) and motoneurons (MNs) exhibit homosynaptic depression and presynaptic facilitation (Castellucci et
al. 1970
; Castellucci and Kandel 1976
) as well as post-tetanic potentiation (PTP) (Clark and Kandel 1984
; Walters and Byrne 1984
). The
same homosynaptic learning processes are expressed at synapses between
SN and excitatory interneurons (IN+s) (Hawkins et al. 1981a
; Clark
and Kandel 1984
), though a heterosynaptic process like facilitation is
not necessarily equally expressed at SN-MN and SN-IN+ synapses
(Clark and Kandel 1984
; Fitzgerald and Carew 1991
; Trudeau and
Castellucci 1993b
). PTP and depression also occur, to some degree, at
downstream IN+-MN synapses (for review, see Cleary et al. 1995
).
The interconnections between IN+ and inhibitory interneurons
(IN
s) also change through a variety of mechanisms (Frost et al.
1988
; Fischer and Carew 1993
; Trudeau and Castellucci 1993a
,b
; Cleary et al. 1995
). Even the neuromuscular junction and other peripheral sites are capable of plasticity (Jacklet and Rine 1977
; Lukowiak and
Colebrook 1988-1989
; Cohen et al. 1997
). In addition to synaptic plasticity, the excitability of SNs, IN+s, IN
s, and MNs can
change consequent to past experience (e.g., Klein and Kandel 1978
; Kanz
et al. 1979
; Frost et al. 1988
; Trudeau and Castellucci 1993b
).
So, while memory storage can be considered to occur at discrete loci
(i.e., neurons and their synaptic connections), plastic loci occur
throughout the network. Memory is distributed, not in the manner held
by the aggregate-field hypothesis, but, rather, by one more consistent
with parallel distributed processing (Rumelhart and McClelland 1986
;
Frost et al. 1988
; Lockery and Sejnowski 1993
). Multiple mechanisms can
act at a single cellular locus to effect a variable level of change at
that locus; at the network level, these variable changes at discrete
loci combine in numerous permutations and allow a high degree of
behavioral flexibility through learning (e.g., Lockery and
Sejnowski 1993
; White et al. 1993
). Although much effort is spent
investigating the cellular and molecular mechanisms of plasticity, the
interactions of these mechanisms both at the cellular level and at the
network level cannot be neglected if one's ultimate goal is to explain
learning at the behavioral level. These interactions include, for
example, those between short, intermediate, and long-term memory
(Kandel 1976
; Christoffersen and Schilhab 1996
; Mauelshagen et al.
1996
; Sossin 1996
). As well, simple nonassociative forms of learning might somehow combine and interact to produce more complex associative learning (Hawkins and Kandel 1984
; Hawkins 1989
; Buonomano et al.
1990
). Even the efficacy of a particular mechanism for short-term nonassociative learning may be influenced by prior synaptic or cellular
activity that may or may not have itself caused plasticity (Marcus et
al. 1988
; Fischer et al. 1997
; for review of metaplasticity, see
Abraham and Bear 1996
); for example, spike broadening and vesicle
mobilization both contribute to facilitation, but whereas the former
mechanism is more important for effecting change at naive synapses, the
balance shifts in favor of the latter for effecting change at depressed
synapses (for reviews, see Klein 1995
; Byrne and Kandel 1996
). This
example illustrates the interactions that can occur between decremental
and incremental learning processes at the cellular level. Interactions
between these processes can also occur at the network level (e.g.,
Groves and Thompson 1970
; Fitzgerald et al. 1990
; Hawkins et al. 1998
).
The remainder of this paper will attempt to advance understanding of interactions of this last sort, namely, the interactions between short- to intermediate-term depression and facilitation at the network level. Plasticity in numerous systems representing both vertebrates and invertebrates will be reviewed. Based on the principles derived from this review and the results of a simple mathematical model, I will develop the central thesis: Depression occurs at loci early in the stimulus-response (S-R) pathway, upstream of the modulatory system necessary for the induction of facilitation, and consequently, depression not only competes directly with facilitation for the determination of behavioral change (by serial and/or parallel expression), but depression also precludes the ongoing development and maintenance of facilitation (by serial induction). The combination of these two interactions ultimately determines how the reflex will change and leads to the "bumpy" learning curves characteristic of dual-process learning.
DEFINING HABITUATION AND SENSITIZATION
Habituation can be defined as behavioral response decrement
resulting from repeated stimulation (Harris 1943
), the parametric characteristics of which were described by Thompson and Spencer (1966)
.
Only those characteristics important for the current discussion are
recounted here. First, response decrement is a negative exponential function of the number of stimulus presentations. Second, the rate and
degree of decrement are directly proportional to stimulation frequency
according to Thompson and Spencer (1966)
though later publications
(Hinde 1970
; Thompson et al. 1973
) have asserted that the number of
stimuli is really the more significant variable. Third, the rate and
degree of decrement are inversely proportional to the stimulus
intensity, though this is a less significant factor than stimulus
repetition (Groves and Thompson 1970
; Thompson et al. 1973
).
Following from the last point, strong stimuli may in fact cause
sensitization instead of habituation. Sensitization is defined as behavioral response increment resulting from novel, strong, or
noxious stimulation (Peeke and Petrinovich 1984
). In contrast to
habituation, stimulus intensity is a more important factor than
stimulus repetition in determining the rate and degree of sensitization. From a teleological standpoint, these relationships seem
logical: Habituation serves to decrease the response to a stimulus
whose informational value has decreased as a result of its
inconsequential repetition, whereas sensitization serves to rapidly
increase the response to a stimulus whose informational value is judged
as high on the basis of its initial novelty or strength, though
stimulus repetition may ultimately prove the sensitization unnecessary
and promote its reduction.
Likely because of interest in associative learning, sensitization has
most often been studied by application of a strong stimulus to a
different area on the body than the milder test stimulus. This sort of
sensitizing stimulus is referred to as a remote or extra-stimulus. However, sensitization can be induced by the
test stimulus itself (Davis and Wagner 1969
; Groves et al. 1969a
,b
; Hinde 1970
). To make the distinction, sensitization caused by stimulation remote to and/or qualitatively different
(e.g., modality) from the test stimulus is called extrinsic
sensitization (Groves and Thompson 1970
; Davis and File 1984
),
whereas sensitization caused by stimulation to the same site and of the
same modality as the test stimulus is called intrinsic
sensitization, warm-up (Hinde 1970
; Lockery and Kristan
1991
), or iterative enhancement (Brown et al. 1996
). In this
paper I refer to intrinsic sensitization simply as
sensitization and otherwise specify extrinsic.
As discussed by Peeke and Petrinovich (1984)
, definitions of
habituation and sensitization may refer to either the processes causing
change or the behavioral consequences of those processes, that is,
mechanistic and operational definitions, respectively. The definitions
presented above are operational. Mechanistic definitions are not used
in this paper. Instead, cellular plasticity is referred to as
depression or facilitation, which unless otherwise
explained (e.g., because of inhibition), confers behavioral habituation or sensitization, respectively. This terminology is not meant to
connote any mechanistic details.
Before proceeding, it is valuable to make a distinction between induction and expression of learning. For a homosynaptic process such as depression, both induction and expression occur in the S-R pathway. For a heterosynaptic process such as presynaptic facilitation, expression of the learning is in the S-R pathway, but this learning is induced by a modulatory system.
GROVES AND THOMPSON'S THEORY
The dual-process theory of plasticity claims that two opposing
processes, depression and facilitation, compete to determine the final
behavioral outcome after a stimulus series (Fig. 1). The theory was formalized and given its name in 1970 by Groves and
Thompson (see also Groves and Thompson 1973
; Thompson et al. 1973
),
though very similar concepts were presented independently by Hinde
(1970)
. The earliest conceptualization of this theory, however, dates
back to Thompson and Spencer's (1966)
review of habituation in which
they recognize that dishabituation is not the disruption of habituation
but rather "a separate facilitatory process superimposed upon the
habituated system." Groves and Thompson (1970)
also recognized the
significance of intrinsic sensitization in that the same stimulus can
simultaneously elicit depression and facilitation.
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The stimulus strength sets the balance between the opposing learning processes (Fig. 1B) and thereby determines the net magnitude and direction of plasticity at the network and behavioral levels (Fig. 1, cf. A1-A4). The bumpy shape of the curves in Figure 1, A1-A4 differs from canonical habituation learning curves and indicates that the balance between learning processes is dynamic, shifting as the stimulus is repeated. Extending beyond Groves and Thompson's discussion, is there a physiological basis in the neural network for this changing balance? The data presented herein suggest that the kinetics of dual-process learning can be explained by the relative positioning of learning processes within the neural network.
Groves and Thompson's ideas were based on investigations of the
hindlimb flexion reflex of the acute spinal cat and the startle response of the intact rat, both of which exhibit dual-process learning
(Groves and Thompson 1970
). More complex behaviors such as the mobbing
response of chaffinches (Hinde 1970
) and aggression in three-spined
sticklebacks (Peeke 1969
, 1983
; Peeke and Veno 1973
) also exhibit
plasticity consistent with the dual-process theory, as do certain human
behaviors such as infant visual attention (Bashinski et al. 1985
;
Kaplan and Werner 1986
). Dual-process learning is also common, though
not ubiquitous, amongst invertebrate withdrawal responses. These
responses include the withdrawal response in the earthworm (Roberts
1966
), whole body withdrawal in the snail Lymnaea (Cook 1975
),
tentacle withdrawal in the snail Helix (Christoffersen et al.
1981
; Zakharov and Balaban 1987
; Balaban 1993
; Prescott and Chase 1996
;
S.A. Prescott and R. Chase, in prep.), local bending in the leech
(Lockery and Kristan 1991
), escape response in the crab (Rakitin et al.
1991
), swim response in Tritonia (Brown et al. 1996
), and
tail-induced siphon and tail withdrawal in Aplysia (Stopfer
and Carew 1996
). Data also suggest that dual-process learning may occur
in the siphon-elicited GSW reflex (see below). The occurrence of
dual-process learning is not explicitly recognized in all of these
publications, but in each case, the reflex exhibits plasticity like
that described by the learning curves in Figure 1, A1-A4, namely
transient sensitization followed by habituation or, at least, a delayed
onset of net habituation.
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Review of Physiological Data |
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HINDLIMB FLEXION REFLEX IN THE CAT
The dual-process theory of plasticity stemmed largely from work on
the spinal cat. In these experiments, electrical stimulation is applied
to the skin or to a cutaneous nerve, and the reflex contraction of a
flexor muscle is measured isometrically. Habituation of the flexion
reflex occurs in the acute spinal cat with all nine parametric
characteristics described by Thompson and Spencer (1966)
. The reflex
also exhibits extrinsic sensitization (Spencer et al. 1966a
; Thompson
and Spencer 1966
) and intrinsic sensitization (Groves et al. 1969a
,b
).
Interestingly, both forms of sensitization habituate if the sensitizing
stimulus is repeatedly applied (Spencer et al. 1966a
; Thompson and
Spencer 1966
; Groves and Thompson 1970
).
To date, the polysynaptic circuit mediating the reflex remains
incompletely understood (see Moschovakis et al. 1992
; Burke 1998
),
making it impossible to localize precisely the plastic loci. Data are
consistent with depression at interneuronal sites (Spencer et al.
1966a
-c
; Thompson and Spencer 1966
; Wickelgren 1967a
,b
; Groves and
Thompson 1970
; Durkovic 1983
; for review, see Mendell 1984
). The
generalization (or transfer) of habituation between input pathways can
be interpreted to indicate depression at synapses downstream of the
primary afferent terminals; however, the generalization is incomplete
and the receptive fields for decrement are narrow (Spencer et al.
1966a
; Thompson and Spencer 1966
), suggesting that depression occurs,
in part, before pathway convergence from other stimulus input sites
(see Wickelgren 1967b
). Furthermore, depression occurs in both the
spinal S-R pathway and the ascending pathways (Spencer et al. 1966b
),
consistent with depression occurring upstream of the point where the
pathways diverge and/or depression occurring in both
pathways after divergence. Note the widespread effects if the
decremental process occurs before the central pathways diverge (which
is not to be confused with input specificity and input pathway convergence).
While some have argued that habituation is caused by alterations in
inhibitory transmission (e.g., Holmgren and Frenk 1961
; Wickelgren
1967b
; Wall 1970
), data presented by Spencer et al. (1966a
-c
) argued
that habituation is caused by reduced excitatory transmission
independent of changes in inhibition (see also Horn 1967
). More recent
data have not definitively indicated which mechanism is responsible,
and the mechanisms need not be mutually exclusive (for review see
Mendell 1984
). Stimulus parameters seem to determine which mechanism
predominates. Based on their experiments, Groves and Thompson (1970)
considered habituation to be caused by decremental changes intrinsic to
the S-R pathway and probably mediated by a process such as homosynaptic
depression. It is data from these experiments on which I will focus.
Homosynaptic mechanisms can produce sensitization with intense
stimulation (e.g., PTP; Lloyd 1949
), but Groves and Thompson (1970)
maintained that for more moderate stimulation intensities, sensitization is predominantly induced by a separate modulatory system.
In contrast to the comparative input-specificity of habituation (Hagbarth and Kugelberg 1958
; Thorpe 1963
; notwithstanding Thompson and
Spencer 1966
), a heterosynaptic mechanism allows the facilitatory effects to generalize between input pathways. Despite this, the effects
of facilitation are not ubiquitous between the central pathways
activated by a stimulus: Facilitation occurs in the spinal S-R pathway
but not in the ascending pathways (Spencer et al. 1966b
); this differs
from depression, which tends to affect all central pathways (see above).
Given the approximate localization of the plastic processes and some
understanding of the processes themselves, how do depression and
facilitation interact at the network level? In their attempts to
characterize the neural analogs of dual-process learning in the cat,
Groves et al. (1969a
; see also Groves and Thompson 1970
; Egger 1978
)
recorded from interneurons in the spinal cord whose activity changed in
markedly different ways as learning progressed (Fig.
2). There are nonplastic interneurons that exhibit a
short-latency phasic response that does not change over the course of
training. Type H interneurons, named after their tendency to habituate
(depress), also show a short-latency phasic response that invariably
decreases with training. Type S interneurons, named after their
tendency to sensitize (facilitate) but that also depress, exhibit a
phasic burst followed by a more prolonged response, suggesting that
these cells may be farther downstream in the S-R pathway than the
aforementioned interneurons. Consistent with this positioning, S neuron
response plasticity closely parallels muscle response plasticity (Fig. 2); for instance, the response of S neurons does not increase under
conditions in which the reflex fails to sensitize.
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ACOUSTIC STARTLE REFLEX IN THE RAT
The second behavior considered briefly by Groves and Thompson (1970)
was the acoustic startle reflex of the rat. This reflex has been shown
to habituate, extrinsically sensitize (Prosser and Hunter 1936
; Parker
et al. 1974
; Davis 1989b
), and intrinsically sensitize (Hoffman and
Fleshler 1963
; Davis and Wagner 1969
; Davis 1974
). The gross circuitry
underlying the acoustic startle reflex (Fig. 3A) has
been worked out (Davis et al. 1982a
; for reviews, see Davis 1989a
;
Yeomans and Frankland 1995
) thereby allowing a better localization of
plastic loci than for the spinal cat. As with repeated acoustic
stimulation, repeated electrical stimulation of the posteroventral
cochlear nucleus results in initial sensitization followed by
habituation, whereas electrical stimulation downstream, at the
reticular formation (in the nucleus reticularis pontis caudalis),
results only in sensitization (Davis et al. 1982b
) (Fig. 3B). These
data indicate that depression occurs at or downstream of the cochlear
nucleus but upstream of neurons in the reticular formation, some of
which constitute a modulatory system. This is supported by the
observation that neuronal activity in the reticular formation depresses
(Lingenhöhl and Friauf 1994
). A modulatory system contributing to
intrinsic sensitization most likely descends in parallel with the S-R
pathway to induce facilitation at the spinal level (Davis 1980
; Davis
et al. 1980
; Astrachan and Davis 1981
), though this does not rule out
modulation in the reticular formation that itself can express
facilitation (see below). Without being able to rule out facilitation
in either the reticular formation or the spinal cord, Figure 3A shows
the circuitry whereby incremental changes would be expressed at both sites.
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Continued research on this preparation has yielded an increasingly
detailed and complex story. The facilitation responsible for extrinsic
sensitization has been localized to the reticular formation (Boulis and
Davis 1989
) where there is a high degree of input pathway convergence
(Parker et al. 1974
; Groves et al. 1976
). The central nucleus of the
amygdala is necessary for induction of extrinsic sensitization
(Hitchcock et al. 1989
) in contrast to intrinsic sensitization
(Schanbacher et al. 1996
). The difference in the location of the
expression of facilitation mediating intrinsic and extrinsic
sensitization may have consequences for the behavioral expression of
learning (Pilz and Schnitzler 1996
) and for learning kinetics, which is
an important issue to be discussed again later.
What then does the acoustic startle reflex contribute to the current
discussion of dual-process learning? Davis et al. (1982b)
concluded
that "sensitization may be related to the motor side of reflex arcs,
whereas habituation may be related to the sensory side." Similar
conclusions have been reached with other vertebrate reflexes (Hagbarth
and Kugelberg 1958
; Sanes and Ison 1983
) and are generally true of
invertebrate reflexes (Menzel and Bicker 1987
; see below). This view is
consistent with the current paper's working hypothesis: The modulatory
system responsible for inducing facilitation is downstream of at least
one depressing locus. This arrangement may account for the habituation
of sensitization and, I will argue, is key to understanding
dual-process learning kinetics.
SIPHON-ELICITED GSW REFLEX IN APLYSIA
As discussed at the start of this paper, the cellular-connection
approach has been very successful in its application to simple systems
and nowhere more so than in the GSW reflex of Aplysia. This
review is not meant to be comprehensive, but rather, I will draw from
the available data those principles of the neural circuitry and its plasticity
(Fig. 4) that are relevant to dual-process learning.
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Canonical dual-process learning in the GSW reflex of naive
Aplysia has not been reported, but the system is nonetheless
relevant to the ideas presented in this paper. SNs excite the L29
interneurons that are known to cause facilitation at SN-MN synapses
(Hawkins et al. 1981a
,b
; Hawkins and Schacher 1989
). Such connectivity conceivably allows for intrinsic sensitization, though the strength of
this sensitization is not clear. Although the facilitation may be
insufficiently strong to effect a net increase in transmission at the
SN-MN synapse, this must be considered in light of the propensity of
the SN-MN synapse to undergo depression, meaning that although the
effects of facilitation may be less obvious for lack of incremental
change, an occult incremental process could have significant influence
on the net decremental change (Hawkins et al. 1981b
). Compared with
naive preparations, intrinsic sensitization is robust in preparations
expressing long-term sensitization (Pinsker et al. 1973
; for similar
observation in rat, see Davis 1972
).
Though often neglected, many invertebrate withdrawal reflexes are
mediated in part by a peripheral S-R pathway (Peretz 1970
; Peretz et
al. 1976
; Perlman 1979
; Prescott and Chase 1996
; Prescott et al. 1997
).
The central and peripheral pathways act in parallel, and each is
sufficient to induce and express its own depression. Peripheral
induction of facilitation can occur (Lukowiak and Jacklet 1972
, 1975
),
but early data suggest that a central modulatory system contributes to
peripheral expression of facilitation (Bullock and Horridge 1965
; see
also Prescott and Chase 1996
). One can speculate that under conditions
where centripetal input decreases (because of upstream depression),
centrifugal modulation would progressively wane and dual-process
learning would ensue.
The separation of mediating and modulatory roles between the peripheral
S-R pathway and the central modulatory system, respectively, is
beneficial to the investigation of dual-process learning (e.g., in the
tentacle withdrawal reflex of Helix; Prescott and Chase 1996
;
S.A. Prescott and R. Chase, in prep.). However, in most cases, the
central S-R pathway cannot be clearly delineated from the modulatory
system. In Aplysia, a single cell type such as L29 serves both
modulatory (Hawkins et al. 1981a
,b
; Hawkins and Schacher 1989
) and
mediating (Hawkins et al. 1981a
; Fischer and Carew 1993
) roles (for
review, see Frost and Kandel 1995
). Fortunately, the central S-R
pathway can be subdivided into monosynaptic and polysynaptic pathways
(Fig. 4A), as well as into the interneuron II network that will not be
given detailed consideration here. Unlike the polysynaptic pathway, the
monosynaptic pathway does not include modulatory interneurons and
therefore serves a purely mediating role. Recording from a motoneuron,
changes in the monosynaptic excitatory postsynaptic potential (EPSP)
reflect plasticity in the monosynaptic pathway, whereas changes in the
complex EPSP reflect the combined changes in both pathways.
Comparatively recent data have shown that the polysynaptic pathway
makes a significant contribution to the complex EPSP and hence to
mediation of the behavior (Trudeau and Castellucci 1992
; Fischer and
Carew 1993
). Prolonged activity in the polysynaptic pathway determines
the duration of the reflex muscle contraction (Frost and Kandel 1995
; Lieb and Frost 1997
), whereas the short-latency phasic burst
transmitted through the monosynaptic pathway is probably more
influential in the determination of the rate or latency of reflex
muscle contraction (Frost et al. 1988
).
Decreased transmitter release from SN terminals resulting from
homosynaptic depression (Castellucci and Kandel 1974
) is widely held as
the ultimate cause of habituation in this preparation. Because this
decrease works through a homosynaptic mechanism, depression occurs at
all SN output sites (Clark and Kandel 1984
). This implies decreased
input to peripheral MNs via collaterals (Bailey et al. 1979
) and
decreased input to central MNs and interneurons via projections to the
CNS. Homosynaptic processes that increase SN output, for example, PTP,
are similarly "cell wide." In contrast, heterosynaptic
facilitation is "branch specific," meaning that output from
different sites on the same SN can be facilitated to different degrees.
Clark and Kandel (1984)
showed that it is possible to facilitate
transmission at either central or peripheral SN terminals independently
based on where serotonin (5-HT) is exogenously applied. In the intact
animal, differential delivery of 5-HT (or some other modulatory
transmitter) probably depends on the patterns of projection of
facilitatory neurons and the connections with their target SN (Clark
and Kandel 1984
). Differential distribution of receptors for the
modulatory transmitter on the target cell might further contribute to
the branch specificity (Trudeau and Castellucci 1993b
; Sun et al. 1996
).
The issue of branch-specific facilitation is important for dual-process
learning because incremental changes mediating intrinsic sensitization
have the possible effect of creating a positive feedback loop to the
modulatory system, or, in other words, sensitizing sensitization. This
might occur in the GSW reflex if input to certain components of the
polysynaptic S-R pathway was facilitated, but this does not seem to be
the case. Differential facilitation not only occurs between central and
peripheral pathways (see above), but it also occurs between the central
monosynaptic S-R pathway and the central polysynaptic S-R
pathway/modulatory system. Trudeau and Castellucci
(1993b)
showed that exogenous application of 5-HT causes twice as much
facilitation at SN-MN synapses than at SN-IN+ synapses. Despite
5-HT's ability to enhance the EPSP recorded in hyperpolarized
interneurons, 5-HT has a negligible (Trudeau and Castellucci 1992
) or
even inhibitory (Fitzgerald and Carew 1991
) effect on the complex EPSP
measured in MNs. This suggests that there is a compensatory balance
after the SN-IN+ synapse to restrict incremental change (e.g.,
inhibition; see below). Interestingly, small cardioactive peptide B
(SCPB) has the opposite selectivity, specifically, enhancing
transmission through the polysynaptic pathway (Trudeau and Castellucci 1992
).
Decremental changes, on the other hand, are the same for both central
pathways given that SN depression is cell-wide (see above) and that
interneuron output does not tend to depress so that no additional
signal decrement occurs specifically in the polysynaptic pathway
(Cleary et al. 1995
; exceptions include L22 and L23). Under most
stimulation conditions, PTP is probably not significantly induced when
inhibitory pathways are intact (Trudeau and Castellucci 1993b
;
notwithstanding Frost et al. 1988
). Given the differential
facilitation, net plasticity differs between the two pathways (Fig. 4).
Differential facilitation is also found in monosynaptically and
polysynaptically mediated components of the human eye-blink reflex
(Sanes and Ison 1983
), the tentacle withdrawal reflex of Helix
(S.A. Prescott and R. Chase, in prep.), and the tail-elicited tail
withdrawal reflex of Aplysia (see below), though which
component is affected depends on the specific system.
Another difference between the monosynaptic and polysynaptic pathways
is the amount of inhibition impinging on each. For example, during the
period of L16-mediated inhibition, the amplitude of the complex EPSP is
reduced, whereas the amplitude of the monosynaptic EPSP is concurrently
enhanced, suggesting that the polysynaptic pathway (specifically, the
constituent interneurons) is subject to more inhibition (Wright et al.
1991
). Consistent with this view are the inhibitory effects of L30 on
L29 and L34. L30 is activated by a wide range of stimulus intensities
via the SNs as well as via L29. The reciprocal connections between L29
and L30 mediate recurrent inhibition that is itself plastic, undergoing what Fischer and Carew (1993)
call activity-dependent potentiation. Recurrent inhibition functions as a negative feedback mechanism to
stabilize the intensity of the neural signal passing through the
polysynapic pathway (Lieb and Frost 1997
).
This differential inhibition may account for some of the differential
facilitation described above. For example, SCPB exerts its
facilitatory effect by the reduction of inhibitory input to IN+s,
enhancing transmission specifically in the polysynaptic pathway (Trudeau and Castellucci 1993a
,b
). Fitzgerald and Carew (1991)
suggested that different 5-HT receptors may mediate opposite
facilitatory and inhibitory effects between different pathways. An
alternative proposal is that increased output from SNs may enhance
input to IN
s more than input to IN+s, the net effect being
reduced activation of the IN+s (Fitzgerald and Carew 1991
). In light
of these more recent data, the earlier assumption that facilitation
necessarily causes the same plasticity in monosynaptic and polysynaptic
pathways is inaccurate.
Other questions still remain unanswered. Given that L29's transmitter
is neither 5-HT nor SCPB, it would be interesting to investigate the specific effects of L29-mediated modulation on network
activity, including whether or not L29 modulates its own activity
thereby forming a positive feedback loop. Hawkins et al. (1981b)
reported that facilitation of the SN-MN synapse accounts for most of
the L29's modulatory effects, whereas Frost et al. (1988)
and Trudeau
and Castellucci (1993a)
proposed that the removal of inhibition from
the polysynaptic pathway contributes significantly to extrinsic
sensitization. Might disinhibition be absent for intrinsic
sensitization? This absence could help explain the comparative weakness
of intrinsic sensitization and would be consistent with intrinsic
sensitization's tendency to habituate rather than to sensitize. Figure
4B shows the likely configuration in which there is differential
facilitation and no positive feedback loop. Hawkins's (1989)
difficulty modelling sensitization's tendency to habituate might be
attributable to not considering the differential effects of
facilitation. It would also be interesting to investigate the differences between sensitization and dishabituation (see Marcus et al.
1988
) in the context of the ideas discussed above.
To summarize findings from the GSW reflex relevant to later discussion (see Fig. 4B), depression at the SN terminals causes decrement of the neural signal early in the neural circuit, resulting in decreased activity in the S-R pathway and reduced activation of the downstream modulatory system. To counteract this decrement, heterosynaptic facilitation acts at the SN terminals (and potentially elsewhere) to enhance the neural signal. Whereas the former process has cell-wide effects, the latter process has branch-specific effects, selectively enhancing transmission through certain pathways. This specificity may be determined presynaptically by the projection of facilitatory neurons or by the sensitivity of SN terminals to the modulatory transmitter, or the specificity may be determined postsynaptically by differential inhibition of monosynaptic and polysynaptic pathways. Combining specific incremental changes with ubiquitous decremental changes, it follows that the monosynaptic S-R pathway (and perhaps the peripheral S-R pathway and the interneuron II network) exhibits a net increase in transmission efficacy, whereas the polysynaptic S-R pathway/modulatory system exhibits a net decrease. This latter tendency causes sensitization to wane and also directly contributes to response habituation. So long as one contributing S-R pathway shows dual-process learning, pure decrement in the other S-R pathways serves only to dilute (to a degree consistent with the size of that pathway's contribution) the behavioral manifestation of dual-process learning.
TAIL-ELICITED TAIL AND SIPHON WITHDRAWAL REFLEX IN APLYSIA
Stronger behavioral evidence exists for dual-process learning in the
tail-elicited reflexes of Aplysia (Stopfer and Carew 1996
)
(Fig. 5A). Walters et al. (1983b)
clearly showed that
both intrinsic and extrinsic sensitization can occur in the tail
withdrawal reflex. However, the neural circuitry mediating and
modulating tail-elicited reflexes is not as well characterized as that
for siphon-elicited reflexes. As shown in Figure 4, tail-induced tail withdrawal is mediated by parallel monosynaptic (Walters et al. 1983a
)
and polysynaptic pathways (Cleary and Byrne 1993
; White et al. 1993
),
whereas tail-induced siphon withdrawal is mediated through a purely
polysynaptic pathway (Cleary and Byrne 1993
; Cleary et al. 1995
).
IN
s activated by tail stimulation have also been identified and shown to inhibit SNs, MNs, and IN
s (Buonomano et al. 1992
; Small et
al. 1992
; Xu et al. 1994
, 1995
), but the data are insufficient to allow
one to compare the inhibitory influences in monosynaptic and
polysynaptic pathways.
|
Many of the phenomena described above for the siphon-elicited GSW
reflex are similar for tail-elicited reflexes. In brief, Walters et al.
(1983a)
reported that repeated intracellular excitation of tail SNs
results in progressive depression of their synaptic output. Cutaneous
stimulation of the tail, on the other hand, does not cause an
equivalent change, because this form of stimulation elicits a
concomitant heterosynaptic facilitation to counteract the homosynaptic
depression (Walters et al. 1983b
; Stopfer and Carew 1996
). Furthermore,
the two types of S-R pathways are differentially affected by the
facilitation mediating intrinsic sensitization. Cutaneous tail
stimulation causes net incremental change in the monosynaptic pathway
while concurrently causing net decremental change in the polysynaptic
pathway (Stopfer and Carew 1996
). The dissociation of plasticity
between the pathways is evident in two ways. First, the early
monosynaptically mediated burst of spikes in the tail MN is increased,
whereas the later polysynaptically mediated firing is substantially
reduced with repeated stimulation (Fig. 5B) (see also White et al.
1993
). Second, the monosynaptic EPSP recorded in the tail MN increases
(Fig. 5C), whereas the complex EPSP decreases (Fig. 5D).
Fitzgerald et al. (1990)
stressed that the balance between inhibition
and facilitation is largely responsible for determining the net
magnitude and direction of reflex modulation. As in the GSW reflex,
different transmitters have differential effects on cells underlying
the tail withdrawal reflex (Xu et al. 1995
). For instance, 5-HT reduces
inhibition by reducing the activity of the inhibitory neuron Pl4,
whereas SCPB has the opposite effect. Understanding the
specific effects of such modulation on signal transmission through
monosynaptic and polysynaptic pathways will surely benefit the
understanding of behavioral plasticity.
SUMMARY OF PHYSIOLOGICAL DATA
On the basis of the above review of different systems and their plasticity, I will draw certain conclusions pertinent to dual-process learning. Habituation is mediated largely by a homosynaptic process (depression) acting at an upstream locus in the S-R pathway. The decremental effect is ubiquitously expressed among the pathways that diverge downstream of the depressed locus. Sensitization on the other hand is mediated largely by a heterosynaptic process (facilitation) that is induced by a modulatory system downstream of the first plastic locus. Facilitation may be expressed downstream of the depressing locus (i.e., in series) and/or upstream, at the same locus as depression (i.e., in parallel). Differential facilitation presynaptically or differential inhibition postsynaptically produces branch-specific plasticity, meaning that the incremental effect will not necessarily be the same for all pathways diverging at the plastic locus. Hence, net plasticity will vary between pathways. One consequence is that the modulatory system will tend not to cause increment of its own input but, rather, that its input will exhibit pure decrement causing sensitization to wane. It is plausible that decrement of the modulatory system's output might contribute to habituation of sensitization, but this does not seem to occur. The implications of different configurations of plasticity's induction and expression for dual-process learning will be considered in more detail below.
| |
Model of Dual-Process Learning |
|---|
|
|
|---|
In the first model of dual-process learning, Groves and Thompson
(1970)
worked backwards from dual-process learning curves (solid lines
in Fig. 1A1-A4) to compute the hypothetical component single-process
learning curves (broken lines in Fig. 1A1-A4). They assumed that
decremental and incremental changes in the neural signal are simply
added to determine the net plasticity. The present model asserts that
interactions between depression and facilitation are more complex.
The single-process habituation learning curves (Fig. 1A1-A4, broken
lines, labeled H) exhibit standard parametric features as described by
Thompson and Spencer (1966)
. Each curve decreases exponentially to a
minimum asymptote. As stimulus intensity is increased, the rate and
degree of habituation decrease. Parametric features of the hypothetical
"pure" decremental process are unaffected by sensitization.
Certain interneurons, H cells, exhibit learning curves very similar to
these hypothetical pure habituation learning curves (Fig. 2). Given the
empirically derived dual-process learning curve and a good idea of the
single-process habituation learning curve's shape, the single-process
sensitization learning curve (Fig. 1A1-A4, broken lines, labeled S)
was calculated by subtraction (i.e., linear additivity is assumed). In
simpler systems such as Helix or Aplysia,
experimental techniques are available that can facilitate the decomposition of
the dual-process learning curve (S.A. Prescott and R. Chase, in prep.).
Determining a single-process learning curve for sensitization as Groves
and Thompson did does not explain the basis for that curve, although
the curve's shape does provide some insights. The rate and degree of
sensitization are proportional to stimulus intensity (Fig. 1A).
However, these learning curves do not simply increase exponentially to
a maximum asymptote as might be expected if only pure sensitization
were taking place (Fig. 3B; Hawkins 1989
; S.A. Prescott and R. Chase,
in prep.); instead, each curve rises and peaks early in the stimulus
series but decreases, or habituates, as training progresses.
Interestingly, the rate and degree of the habituation of sensitization
parallels the rate and degree of the partner single-process habituation
curve (Fig. 1, cf. A2, A3, and A4). Such a correlation suggests that a
common decremental process might be responsible for both response
habituation and the habituation of sensitization, though this evidence
alone does not rule out multiple decremental processes acting in
parallel (see below).
MATHEMATICAL FORMALISMS
Consider the expression of learning from an arithmetic point of
view: By adjusting synaptic weights, depression reduces the signal
intensity by a certain degree (division) and facilitation increases the
signal intensity by a certain degree (multiplication) (Baxter and Byrne
1993
). Changing synaptic weights equates to adjusting the efficacy of
signal transmission through a locus. The extent of such changes is
restricted by physiological constraints. The effects of learning can be
described mathematically by differential equations.
|
(1) |
0; 
1/stimulus intensity; 0
Emin
1; Emin
stimulus instensity.
|
(2) |
0; 
stimulus intensity;
Emax
1;
Emax
stimulus intensity.
E refers to the transmission efficacy, which determines the factor by which neural signal intensity will change as the signal passes through the plastic locus. For a naive locus, E = 1 (i.e., causes no change to signal intensity), but this value can decrease or increase as a consequence of depression (habituation) or facilitation (sensitization), respectively. Subscripts identify the plasticity related to the change in E.
In equation 1, the constant of proportionality,
, sets the rate of
habituation. The degree of habituation is described by the term
Emin that sets the asymptote for allowable
change in EH (degree of
habituation
1/Emin). Therefore, the
equation as written defines exponential decrease of
EH at rate
to a minimum asymptote of
Emin. Equation 2 defines exponential increase of ES at rate
to a maximum asymptote of
Emax. Equations 1 and 2 can be analytically
integrated to give a new pair of equations allowing E to
be plotted against discrete time steps (t) that correspond
to stimulus trial number (Fig. 6A).
The matrix in Figure 6 illustrates the possible
configurations of induction and expression of depression and
facilitation; the letter in each cell corresponds to a graph below
showing the learning curve resulting from that particular configuration
(Fig. 6B-E). Although each of these graphs exhibits a learning curve seemingly consistent with dual-process learning, one can narrow the
field of possibilities by considering the physiological plausibility of
each configuration.
|
INDUCTION OF LEARNING
As a homosynaptic process, depression is both induced and expressed
in the S-R pathway. In contrast, for conditions conducive to
dual-process learning, evidence indicates that facilitation is largely
a heterosynaptic process, expressed in the S-R pathway but induced by a
separate modulatory system (Ellaway and Trott 1975
; Kandel 1976
; Davis
1980
; Astrachan and Davis 1981
; Flicker et al. 1981
).
As already described (see Fig. 1), sensitization tends to wane or
habituate. There are two potential explanations for this, both of which
imply serial induction: (1) decrement of input to the modulatory system
and/or (2) decrement of output from the modulatory
system. These conditions are not mutually exclusive, nor are the
effects equivalent: Decreased input implies habituation that is
input-specific, whereas decreased output implies habituation that is
generalized assuming convergence of input pathways to a common
modulatory system. In other words, habituation of intrinsic sensitization might generalize to cause habituation of extrinsic sensitization and dishabituation, or vice versa. Stimulation data from
the acoustic startle reflex in rats and from the tentacle withdrawal
reflex of Helix are consistent with decrement of input but not
with decrement of output. Evidence from Aplysia tends to
suggest the same conclusion: SN output exhibits robust depression, whereas the output of directly stimulated interneurons (some of which
are facilitatory) does not depress. Hence, physiological data argue
that serial induction of learning, specifically depression upstream of
(i.e., decrement of input to) the modulatory system, is largely
responsible for the habituation of sensitization's induction. The
tendency to habituate is also true for the induction of extrinsic
sensitization and dishabituation (Lehner 1941
; Thompson and Spencer
1966
; Pinsker et al. 1970
). In short, intrinsic and extrinsic
sensitizing stimulation recruits the modulatory system via SNs or
upstream interneurons whose output is prone to depression. Depending on
how the circuit is organized, it is possible that depression at some
loci causes habituation of the response, whereas depression at other
loci causes habituation of sensitization. This may help explain
differences in the rate of habituation and is easily accounted for in
the model by incorporation of a scaling factor (see below).
Given the physiological data discussed above, I will focus on the learning curves resulting from serial induction (Fig. 6D,E). The habituation of sensitization can be expressed by modifying equation 2.
|
|
(3) |
and Emax are
directly proportional to stimulus intensity (see above). Neural signal
intensity is supposed to be the neural analog of stimulus intensity,
but signal intensity can change consequent to learning despite no
change in stimulus intensity. Depression at upstream loci causes
decreased input to facilitatory neurons and therefore a decreased rate
of sensitization. This equates with a reduction of
by
EH, a factor reflecting the effects of
habituation. A scaling factor or nonlinear transformation might also be
incorporated to more accurately describe the rate at which sensitization habituates (see subsection Application of the Model). The
degree of sensitization is also influenced by habituation and is
accounted for in equation 3 by multiplying
(Emax
1 ) by EH so as to
reduce the maximum asymptote to a naive value of one. Because
EH changes over time, analytical integration of
equation 3 was not self-evident and, instead, integration was done
numerically using the fourth order Runge-Kutta method with 0.1 time
unit increments run on SigmaPlot 4.0 (SPSS, Inc.). The resulting
habituating sensitization curves are shown on Figure 6, D and E (broken
lines labeled EHS). The EHS
curve must then be combined with the EH curve to
determine the final changes to E, but the manner in which
those curves are combined depends on the configuration of the
expression of learning.
EXPRESSION OF LEARNING
In Aplysia, depression and facilitation are both expressed
in the SN terminals, but this does not exclude plasticity elsewhere, and downstream expression of facilitation may contribute significantly to effecting behavioral change (Cohen et al. 1997
). Data on the specific localization of plasticity are also inconclusive for vertebrate preparations. Without being able to eliminate either of the
possibilities, both serial and parallel expression of plasticities will
be considered to juxtapose the outcomes.
Because depression and facilitation are, respectively, dividing or multiplying the neural signal by some factor (as opposed to adding or subtracting a fixed value from the signal), the size of the neural signal influences the expression of learning in terms of absolute change in signal intensity. Configuration of the expression of learning therefore influences how one calculates the net change in transmission efficacy (Enet) for the neural circuit (see below) and gives rise to different learning kinetics (Fig. 6B-E). Changes in Enet are commensurate with changes in neural signal intensity and, ultimately, with changes in behavior.
Under conditions of parallel expression, the current model treats
depression and facilitation as acting independently but simultaneously
(i.e., at the same locus) on the neural signal with the resultant
decremental and incremental effects adding to determine
Enet. Specific subcellular changes effecting
synaptic plasticity, including vesicle depletion and mobilization as
well as calcium current down- and up-regulation (Gingrich and Byrne 1985
; Byrne et al. 1989
; Klein 1995
; Byrne and Kandel 1996
), may interact in complex ways, but given the redundancy of those changes, the ultimate decremental and incremental changes are assumed to be
additive. Detailed consideration of specific interactions at the
synaptic level is beyond the scope of this paper, but those interactions certainly warrant further investigation. Figure 6D shows
the learning curve resulting from serial induction and parallel expression.
In the instance that depression's expression precedes facilitation's expression, depression divides the neural signal such that the subsequent multiplicative effect of facilitation (now acting on a signal smaller than that at the start of the circuit) will be reduced in efficacy. In contrast to parallel expression, facilitation under these conditions is purely "restorative" in that the process does not prevent the initial signal decrement but only tries to effect some recovery after the fact. If signal decrement is severe, subsequent increment might be insufficient to restore the signal to its original intensity. This is true even before taking into account that the induction of intrinsic sensitization would be reduced, meaning that not only is a smaller signal "multiplied" by a constant facilitation, but in fact, a progressively smaller signal is multiplied by a progressively smaller facilitation. These combined actions cause exaggeration of the falling phase of the learning curve resulting from serial induction and serial expression (Fig. 6E) compared with that in Figure 6D. The reverse order of expression, that is, facilitation followed by depression, is not suggested by physiological data.
Following from the above discussion, the configuration of expression
has important implications for dishabituation. Given that
dishabituation is not mediated by removal of habituation but rather by
a separate facilitatory process (Thompson and Spencer 1966
; Carew et
al. 1971
), the cellular changes mediating habituation and
dishabituation need not be expressed at the same locus. However, the
capacity of most reflexes to readily dishabituate may suggest that
serial expression is less likely than parallel expression. Under the
latter conditions, the multiplicative effect of facilitation, acting on
the signal before that signal's decrement, will be more efficacious by
preventing signal decrement through the circuit rather than by trying
to effect recovery from that decrement. But there is a caveat:
Dishabituation, extrinsic sensitization, and intrinsic sensitization
need not be mediated by the same mechanism and/or by
changes at the same locus. Data from the rat (Schanbacher et al. 1996
)
and from Aplysia (Marcus et al. 1988
) suggest differences between these forms of incremental plasticity.
APPLICATION OF THE MODEL
Thus far, the mathematical model presented here has been used to formalize the description of interactions between depression (habituation) and facilitation (sensitization). The current section has four purposes: (1) to show how the model can be applied to empirical data; (2) to identify what sorts of data are necessary for proper application of the model; (3) to offer modifications that may improve the model; and (4) to demonstrate the potential benefits of the model.
The data presented by Groves and Thompson (1970)
demonstrate
dual-process learning at four different stimulus intensities (see Fig.
7A). When trying to fit curves to these data using
the current model, it becomes immediately obvious that too many
parameters are free to change. Although the relationships between
stimulus intensity and the parameters in equations 1-3 are known (see
above), specific functions relating those parameters to stimulus
intensity are not known, and moreover, the stimulus intensities
corresponding to each of the four curves were not published. Hence, it
is not possible to fit the curves by adjusting only stimulus intensity. To deal with this problem, I have assumed that Groves and Thompson's calculation of pure habituation curves (Fig. 1