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OCR for page 137
Bridging Experimental
Animal and Human
Behavioral Toxicology Studies
Deborah A. Cory-SIechta
THE SCOPE AND AGENDA OF
BEHAVIORAL TOXICOLOGY
Behavioral toxicology can be generally conceptualized as that sci-
entific discipline which strives to understand the mechanisms by which
toxicants affect behavior. In this respect, it is similar to its counterpart,
behavioral pharmacology, the goal of which is to delineate the mechanisms
by which drugs modulate behavior. Since its inception, the scope of
behavioral toxicology has expanded considerably, driven in part by
the need to ascertain the role of existing environmental contaminants
in producing functional impairment, as well as the need to develop
procedures to preclude future introduction of neurotoxic chemicals.
In this way, it differs from behavioral pharmacology which, instead,
seeks to develop compounds or agents with specific behavioral actions
for therapeutic purposes.
As the above implies, behavioral toxicology actually has dual,
overlapping agendas. One derives from the growing recognition of
the need to screen for performance impairment prior to the introduction
of new chemicals into the environment, as well as to provide infor-
mation relating to risk assessment based on neurotoxic endpoints.
The second agenda involves the more traditional role of behavioral
toxicology as the scientific discipline defined above, whose goal is to
understand both the behavioral and the biological mechanisms by
which toxicants impact behavioral function. It is primarily the latter
agenda to which the comments herein are addressed.
137
OCR for page 138
138
DEBORAH A. CORY-SLECHTA
Despite recent advances in neurobiology and the obvious utility of
in vitro approaches in the elucidation of biological substrates of behavior,
it is difficult to conceive of any substitute for assessing the ultimate
impact of a neurotoxicant on behavior, or of assessing behavioral
mechanisms of toxicant action, other than in the whole organism.
The links between molecular neurobiology or between neuropathological
alterations and behavioral impairments are still obscure. Although
the relationships between certain neurotransmitters and behavior have
become increasingly evident, such as the role of dopamine in
parkinsonism, other aspects of those relationships remain puzzling,
e.g., the extensive dopaminergic depletions noted before any overt
behavioral impairments appear. Thus, there are no substitute or
alternative procedures for evaluating the functional impact of a toxi-
cant. Put another way, behavioral toxicity cannot be reliably predicted
from molecular events.
STATE OF DEVELOPMENT
Although the experimental capabilities for more precisely delin-
eating behavioral and biological mechanisms of toxicant-induced
performance impairment are generally at hand, the discipline remains
largely at a characterization or descriptive stage of development. Much
of its scientific literature attempts little more than to ascertain whether
a particular toxicant alters a particular class of behavior, or to assess
performance impairments produced by a toxicant across a range of
behavioral endpoints; in some cases, only the barest approximation
to a hypothesis may be invoked. Furthermore, little attempt may be
made to rationalize the particular behavioral approach chosen, which
may, instead, be based predominantly on available apparatus or
technology in that laboratory. Nonetheless, owing more to the sheer
magnitude of work with certain compounds, rather than to any systematic
progression of studies within a laboratory, in certain areas these studies
have begun to provide the prerequisite foundation from which more
mechanistic approaches can now proceed.
Studies of performance impairments induced by lead exposure provide
one example. Lead may be considered a prototypical behavioral toxicant
and undoubtedly has been the most extensively studied of such com-
pounds, both at the experimental animal and at the human level.
The permanent mental retardation, which in some cases was the residual
effect of acute high-dose lead exposure in children, resulted in a
subsequent focus of these studies on issues of learning deficits at
lower lead exposure levels. Human studies of environmental lead
exposure in children have almost invariably focused on age-appropriate
IQ and other psychometric tests as their behavioral endpoint. The
OCR for page 139
BEHAVIORAL TOXICOLOGY STUDIES
139
most recent of such studies have documented decrements in IQ and
similar psychometric measures at blood lead concentrations as low as
10 ~g/dL (e.g., Bellinger et al., 1987; Fulton et al., 1987~. However,
even with the separation of verbal and motor subscales, IQ tests represent
extremently global measures of performance that encompass a variety
of different behavioral functions, as well as the involvement of multiple
sensory systems, many of which may be marginally affected or others
of which may be more dramatically affected. Such global measures
always present the possibility that particular subtle deficits may be
obscured by the sheer multiplicity of concurrently measured behaviors
or may be clouded by a reserve capacity of the organism. The specific
nature of the IQ decrements in humans thus remains unresolved.
Experimental animal studies can more readily address aspects of
lead-induced changes in learning. Table 1 summarizes those studies
that have assessed lead-induced changes in learning by using acqui-
sition of a visual discrimination as a behavioral endpoint. The various
studies are subdivided on the basis of both the type of visual cue
utilized and the developmental period of lead exposure. Plus signs
show those experiments reporting an impairment of visual discrimi-
nation learning as a result of lead exposure, whereas minus signs
accompany those that found no change. As indicated by the prepon-
derance of plus signs in each column, two types of visual discrimination
paradigms emerge as those more sensitive to lead exposures:
discriminations based on differences in brightness and on size of visual
cues. Shape-form discrimination shows little obvious impact of lead.
A within-laboratory comparison provides further support for this across-
study conclusion. Winneke et al. (1977) reported that lead-treated
rats required more trials to acquire a size discrimination than did
control rats, but were not impaired in the acquisition of a form
cliscrim~ation. Although the effects noted with color-based dis0in~nation
are suggestive, they are, at present, based on a restricted data set.
The differential lead effects based upon visual cue emphasize the
critical importance of the environmental context in modulating the
behavioral effects of a toxicant such as lead. No generalized deficit
in visual discrimination learning can be ascribed to lead; instead,
such deficits depend upon environmental cues.
Studies of visual discrimination learning following lead exposure
can direct future efforts aimed at understanding the behavioral and
biological mechanisms that might explain such differential effects.
With respect to behavioral mechanisms, the possiblity of a generalized
performance decrement for example, an increase in response bias or
an alteration in motivation level obviously fails to accommodate
the differential effects of visual cue. One explanation resides in the
possibility of differential degrees of control exerted by the stimuli
OCR for page 140
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OCR for page 141
BEHAVIORAL TOXICOLOGY STUDIES
141
over behaviors, which consequently exhibit differential behavioral
sensitivity to disruption. Numerous behavioral pharmacology stud-
ies have shown that central nervous system (CNS) drugs may exhibit
a much greater magnitude of effect on behavior that is under weak
stimulus control (Laties, 1975), i.e., performances which exhibit rela-
tively low overall accuracy levels or require an extensive number of
trials to attain criterion performance. In such cases, the stimuli may
be less salient, thus failing to generate strong control over performance
and rendering it more easily disrupted by other factors.
The fact that lead effects on visual discrimination learning depend
upon the type of visual cue, as shown in Table 1, might also reflect
differential sensory effects of lead on the visual system. In regard to
such a possibility, Fox et al. (1982) have reported persistent decreases
in both visual acuity and spatial resolution in 90-day old rats that
had been exposed from birth to weaning to 200 ppm of lead acetate
via the dam. Although these, as well as other visual system deficits
resulting from lead exposure have been reported (Bushnell et al.,
1977; Fox and Chu, 1988; Fox and Farber, 1988), their direct impact in
mediating behavioral toxicity remains to be systematically investi-
gated.
Experimental animal studies also reveal that lead impairs learning
based on the acquisition of spatial discrimination and can be catego-
rized on the basis of both the route and the developmental period of
exposure. Table 2 illustrates several additional issues of importance
TABLE 2 Lead-Induced Changes in Spatial Discrimination Learning
Developmental
Period of Lead
Exposure
Exposure Route
Oral
Intraperitoneal
Pre- or postnatal +Snowdon (1973)a -Brown et al. (1971)b
+Bushnell and Bowman (1979a) +Klein et al. (1977)
+Bushnell and Bowman (1979b) -Rosen et al. (1985)
-Overmann (1977)
+Levin and Bowman (1983)
+Laughlin et al. (1983)
Postweaning +Geist and Mattes (1979) -Brown et al. (1971)
Adult +Avery and Cross (1974) -Snowdon (1973)
+Lanthorn and Isaacson (1978) -Ogilvie (1978)
+Ogilvie (1977) -Bullock et al. (1966)
+Dietz et al. (1979) -Penzien et al. (1982)
aEffect of lead reported.
bAbsence of lead effect reported.
OCR for page 142
142
DEBORAH A. CORY-SLECHTA
in understanding the behavioral toxicity of lead, in particular, which
may apply equally to other toxicants: for example, the critical impor-
tance of the kinetics of lead to its behavioral toxicity, the detrimental
effects on spatial learning, and the consistency of the effect across a
variety of different behavioral procedures. Lead-induced impairment
of spatial discrimination learning has been observed following postnatal,
postweaning, and adult exposures, in contrast to brightness discrimi-
nation (Table 1) which appears most vulnerable in response to prena-
tal exposures. Thus, different behavioral performances may exhibit
quite different critical periods of exposure to a toxicant, or the critical
exposure period for behavioral effects produced by a toxicant may be
determined at least partly by the sensitivity of the behavioral procedure.
Comparative changes in schedule-controlled behavior induced by
lead exposure reveal additional aspects of its behavioral toxicity, as-
pects that in turn may impact on, or even underlie, other lead-induced
performance effects. The most extensively studied of such reinforcement
schedules has been the fixed-interval (FI) schedule, in which the reward
for responding is temporally based, with the contingency stipulating
that the first response occurring after a specified interval of time
elapses produces reinforcement. Figure 1 presents the dose-effect
function that summarizes the various studies of lead-induced changes
in FI schedule-controlled behavior. It plots a parameter of FI perfor-
mance (as a percentage of the corresponding control data) in relation
to treatment dose.
In constructing this summary figure, the lead exposure dosage or
concentration has been recalculated in milligrams per kilogram. Because
not all experimenters used the same dependent variables, response
rate was used where presented, but in other cases, the outcome was
based on total number of reponses, median interresponse time (IRT),
or group mean percentage of control reinforcements, all of which can
be impacted upon by response rate changes. The data were plotted
from the session or sessions in which peak effects occurred, with the
exception of data from our studies (Cory-Slechta and Thompson, 1979;
Cory-Slechta et al., 1983, 1985), which were restricted to results from
the first 30 experimental sessions so as to be comparable to the number
of sessions used in most other studies. Prenatal and oral preweaning
exposure studies could not be included in this summary figure because
it was not possible to ascertain the dose to which the developing
animals were exposed. Figure 1 reveals an inverse U-shaped function
relating dose of lead to performance on the FI schedule of reinforce-
ment. That is, exposure to lower concentrations or doses of lead
produces response rate or output increases on the FI schedule; as the
dose or exposure to lead increases, however, the rates of responding
OCR for page 143
BEHAVIORAL TOXICOLOGY STUDIES
300
250
O ~
o 150
100
50
0 I 1
-
01
3
o
10
· Rat
0 Donkey
° Shop
· Plgeon
\
8,6
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l ~ \
o. ^\
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\
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·
8 ~ 9
1
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.1 1 10
LEAN:) DOSE (mg/kg)
143
1 00 1 000
FIGURE 1 Summary of studies investigating changes In fixed-interval performance
(plotted as percent of the control group) as a function of lead dosage, taken from the
session or sessions in which peak effects occurred. Data from studies involving prena-
tal or lactational exposures could not be included because it was not possible to ascer-
tain the dose to which the developing organisms were exposed. Different experimen-
tal species are indicated by different symbols; numbers refer to different studies: (1)
Rice et al. (1979); (2) Cory-Slechta et al. (1985); (3) Cory-Slechta (1989); (4) Cory-Slechta
et al. (1983); (5) Cory-Slechta and Thompson (1979); (6) Van Gelder et al. (1973); (7)
Barthalmus et al. (1977); (8) Angell and Weiss (1982); (9) Zenick et al. (1979); (10) Rice
(1988).
SOURCE: Cory-Slechta (1984).
are depressed below control values. Plotting changes in FI response
rate against the reported blood lead values in each study produces a
similar function (Cory-Slechta, 1984~.
The potential generality of the dose-effect function is evidenced by
the similarity of the lead-induced changes in rates of responding that
have been described in other temporally based reinforcement sched-
ules. For example, Nation et al. (1983) reported a dose-effect func-
tion for lead-induced changes in variable-interval (VI) performance
comparable to that shown in Figure 1 for the FI schedule, with a
daily dose of 1.0 mg/kg of lead increasing VI response rates, whereas
both 5.0 and 10.0 mg/kg suppressed response rates. Rice and Gilbert
(1985) reported no effect of exposure to a low level of lead (associated
OCR for page 144
144
DEBORAH A. CORY-SLECHTA
with steady-state blood lead of 11-13 ,ug/dL) on response rate or on
the mean IRT value of monkeys responding on another temporally
based schedule of reinforcement, a differential reinforcement of low
rate (DRL 10 s or DRL 30 s) schedule. However, on both the DRL 10-
and the DRL 30-s schedules, they did report an increase in the num-
ber of nonreinforced responses and a decline in the number of reinforcers
received by lead-treated monkeys, an effect that would seemingly
necessitate an increased overall rate of responding. This pattern of
effects would be evident in the distribution of IRTs but might not
have impacted the measured index, mean IRT, the value of which
could be substantially influenced by a small number of very long
IRTs.
The response rate-increasing properties of low-level lead exposure
derive from a decrease in the time between successive responses (i.e.,
interresponse times). In particular, the frequency of short interresponse
times (less than 0.5 s) during the fixed interval is increased by lead
exposure, such that successive responses occur more rapidly in lead-
exposed organisms than in controls; no consistent changes in
postreinforcement pause time are noted. Figure 2 shows the proportion
of short IRTs of control rats (left panels) and of rats treated with 25
ppm of lead acetate (right panels) over the course of 40 experimental
sessions on an FI 60-s schedule of food reinforcement in two separate
replications (top panel, Cory-Slechta et al., 1985; bottom panel, Cory-
Slechta, 1989~. As can be seen, the range of short IRTs exhibited by
control and lead-exposed rats was actually quite comparable, but lead
exposure yielded a shift of the distribution toward the upper extremes
of the range (i.e., higher proportions) in both replications. Thus,
control and lead-treated animals begin to respond at the same time
during the fixed interval, but lead-exposed organisms then respond
at much higher rates than control animals, engendering more responding
per unit time.
In contrast, schedules of reinforcement based on number of re-
sponses (ratio based), rather than on temporal parameters, exhibit a
different pattern of lead effects, another indication that its behavioral
toxicity is dependent upon the environmental or behavioral context.
Although high-level exposures to lead are reliably associated with
decreases in response rate on ratio schedules, evidence for rate-enhancing
effects at lower exposure levels is not compelling (Angell and Weiss,
1982; Barthalmus et al., 1977; Cory-Slechta, 1986; Padich and Zenick,
1977; Rice, 1988~. Although Angell and Weiss (1982) reported shorter
median IRTs on an FR schedule in rats exposed to lead prenatally
only, the IRTs were actually not significantly different from those of
nonexposed controls.
OCR for page 145
BEHAVIORAL TOXICOLOGY STUDIES
80
60
40
a,
-
V1 20
IL
o
of
o
o
o
80
60
40
20
o
0 ppm
$1
0 ppm
#2
20 30 40 0
0 10
145
25 ppm
#2
10 20 30 40
SESSIONS
FIGURE 2 Proportion of short interresponse times (less than or equal to 0.5 s) of
individual control rats (left panels) and rats exposed to 25 ppm of lead acetate (right
panels) on a fixed-interval 60-s schedule of food reinforcement. Data are shown over
the course of the first 40 experimental sessions. Top panels from Cory-Slechta et al.
(1985); bottom panels, Cory-Slechta (1989~.
As with the discrimination learning literature, comparative studies
of lead-induced changes in schedules of reinforcement can guide
mechanistically based experiments. Although an elevation in the rate
of responding results from low-level lead exposure, the effect ap-
pears to be restricted to temporally based schedules of reinforcement;
no such effect is consistently noted when reinforcement delivery occurs
under response-based contingencies. Microanalysis of FI performance
reveals that if pause time can be construed as an index of timing
behavior, it remains intact. However, once responding begins, re-
sponse rates of lead-exposed rats greatly exceed those required by
the reinforcement schedule, suggesting as one possibility, a decreased
responsiveness of lead-exposed organisms to the feedback generated
by their own behavior on the schedule. Higher lead exposure levels
produce a generalized nonspecific suppression of responding, which
has been noted on the fixed-interval, fixed-ratio, and variable-interval
OCR for page 146
146
DEBORAH A. CORY-SLECHTA
schedules, raising the possibility of underlying motivational factors
(e.g., a decline in reinforcer efficacy).
Many scientists, including some behavioral scientists have diffi-
culty in understanding the rationale for studying schedule-controlled
behavior, both because of its less obvious correspondence to human
behavior than, for example, conventional learning paradigms, and
because of the ostensible difficulty in interpreting response rate changes.
It should be emphasized, however, that in the human environment,
as well as in the experimental laboratory, rewards or reinforcers for
behavioral performances, including learning, occur under various re-
inforcement schedules. The human environment obviously entails
far greater complexity, with many reinforcement schedules and various
reinforcers available concurrently. Nevertheless, human behavior occurs,
and is consequated, under schedules of reinforcement. The study of
simple schedules of reinforcement in the laboratory represents a simplified
approach to such processes in order to provide a more molecular
analysis of the variables controlling such performances. Furthermore,
the lever-press response used in experimental studies is but an arbi-
trarily chosen response. What if, instead, the particular response
increased by lead exposure involved time out of seat or time off task
in a classroom setting? Increased frequencies of such responses would
have obvious detrimental consequences for children's scholastic per-
formance.
This raises a further issue, namely, that changes in response rate
engendered by a toxicant such as lead might interact with, or even
underlie, other behavioral deficits. Consider a situation, for example,
in which lead-induced increases in rates of responding engender pre-
mature responding to stimulus cues in a learning task. The resulting
decreased level of accuracy might then be interpreted as a learning
impairment. Furthermore, the acquisition of appropriate response
patterns on schedules of reinforcement per se may represent learning
deficits, as has already been described.
As this discussion with respect to an intensively studied neurotoxicant
such as lead indicates, much of our work remains at a descriptive
stage. Nevertheless, the utilization by experimental animal studies
of more sensitive and specific behavioral endpoints than have been
incorporated into many of the human studies in this area, has led
over the past five years or so to a striking correspondence between
results in the two areas (shown in Figure 3) in the reported levels of
lead in blood at which behavioral deficits are reported. The more
recent studies in humans indicate performance impairments in children
at levels as low as 10 ,ug/dL (Bellinger et al., 1987; Fulton et al., 1987~;
studies in both rats and nonhuman primates document effects at
OCR for page 147
BEHAVIORAL TOXICOLOGY STUDIES
Animal Data
Rice et al., 1979
Rice et al., 1984
Rice, 1988
30
25
Cory-Slechta et al., 1983 20
15
Cory Slechta et al., 1985
Rice, 1985 10
5
To
Human Data
PbB
(~9/dL)
30 Needleman et al., 1979
25
20
15
10
5
o
FIGURE 3 Blood-lead levels at which behavioral effects are reported
]47
Shroeder et al., 1985
Shroeder and Hawk, 1986
Yule et al., 1981, 1987
Wigg et al., 1988
Bellinger et al., 1987
Fulton et al., 1987
comparable levels (Cory-Slechta et al., 1985; Rice, 1985~. Figure 3
further illustrates the decline in blood lead concentrations associated
with performance effects in both humans and experimental animals
over the past several years, as earlier studies paved the way for
methodological improvements in subsequent efforts.
BARRIERS TO ADVANCEMENT
What has constrained advancement and kept much of the research
in behavioral toxicology primarily at the level of characterization?
Several factors probably play a role. One is that emerging scientific
disciplines such as behavioral toxicology require reliable, systematic
characterization studies as a sound base for further efforts. Proceeding
to mechanistic-based studies in the absence of such information, or
on the basis of unreliable information, would be premature and even
counterproductive. Besides the relative youth of this area, another
factor that may impose difficulties for a more mechanistically based
science is the nonspecificity of most neurotoxicants. Many of the
chemicals of interest have a diversity of biological effects, including
CNS effects. This poses the distinct possibility that, even in the sim-
OCR for page 148
148
DEBORAH A. CORY-SLECHTA
plest case, different behavioral effects of a particular toxicant may
arise from different behavioral or biological substrates, i.e., from ef-
fects on different neurotransmitter systems or pathological lesions in
different brain regions. Thus, to fully delineate the gamut of behav-
ioral and biological mechanisms of toxicity for any given neurotoxicant
could require an extensive experimental commitment.
A further impediment to more rapid progress in understanding
the neurobiological substrates of performance impairment has been
the relative lack of systematic experimentation aimed at directly defining
the relationships between functional consequences and other neurotoxic
effects resulting from exposure. Although many studies utililze a
multidisciplinary approach, concurrently measuring various indices
of behavioral outcome and changes in neurotransmitter levels in response
to a neurotoxicant, for example, few studies undertake the types of
definitive experiments required to determine the precise nature of
such relationships, which then remain correlational in nature.
Probably one of the primary factors constraining both the scope
and the advancement of behavioral toxicology may be the prepon-
derance of "apparatus-driven" research. In many cases, research questions
are framed around the available behavioral apparatus within a labo-
ratory, be it a radial arm maze or an open field, rather than upon a
hypothesis formulated on the basis of the current scientific literature.
This can often be noted in the introduction to published studies, which
present only the barest approximation to a hypothesis and an obscure
rationale, namely, this toxicant may affect that performance. This is
likely also to be one of the factors contributing to the frequent shifts
in the toxicant of current scientific interest, known colloquially as the
poison of the month: if you cannot change the behavioral apparatus,
and thus the behavioral question, you are left with changing the toxicant.
The latter situation arises, no doubt at least in part, from limitations
of equipment availability imposed by funding restrictions over the
past several years. However, probably more importantly, it reflects
m~umal or inadequate familiarity with the breadth of behavioral sciences
in general and with contemporary state-of-the-art behavioral procedures.
In addition, it may reflect a prevalent notion among many nonbehavioral
scientists that anyone can conduct behavioral testing, a misconception
apparently based on the ostensible simplicity of endpoints such as
motor activity with which those outside the behavioral field tend to
be most familiar.
ACCELERATING THE PACE
One notion that has been advanced to expedite progress in behavioral
toxicology is the development of new behavioral tests. However, the
OCR for page 149
BEHAVIORAL TOXICOLOGY STUDIES
149
rationale for this argument is not compelling and may even be viewed
as counterproductive. For instance, consider the multitude and vari-
ety of procedures currently in use to examine learning. The number
of new procedures that could be devised just to assess this particular
function is almost limitless. However, it must be remembered that
every newly developed procedure requires extensive behavioral in-
vestigation to ascertain the variables controlling the performance, as
well as pharmacological determinations of the comparative sensitivity
of the procedure to other learning tasks. Might not a more productive
and expeditious approach emphasize systematic and comparative studies
of a toxicant's effects across existing, better-understood learning pro-
cedures, in terms of both behavioral and pharmacological variables?
A second approach to accelerating the pace would be to incorporate
some of the more complex, state-of-the-art behavioral paradigms into
behavioral toxicology. Consider again the case of learning, a much
emphasized component of neurotoxicology and of neuroscience in
general. Many of the more conventional techniques suffer from the
limitation that once the organism has mastered the problem to be
learned, only performance is being measured. For example, animals
running a maze may learn to turn toward the appropriate side or
color cue quickly. Similarly an organism may learn to lever-press
only in the presence of a red light, and not in the presence of green,
within only a few experimental sessions. This presents a particular
problem in evaluating a toxicant whose effects have a delayed onset
or which accumulates only slowly. It also makes the assessment of
reversibility of toxicant-induced learning changes difficult.
A more complex behavioral procedure known as repeated acquisition,
or acquisition of response sequences, originated partly because of
such a need (Borer, 1963~. In this particular task, the organism is
required to learn a new sequence of responses of fixed length during
each experimental session. A schematic of the apparatus configuration
for this paradigm is illustrated in Figure 4. Initially, this paradigm
engenders quite high error rates, but as the organism gains experience
with the task, the error rate stabilizes from session to session and the
organism learns each new sequence at a fairly constant rate. The
procedure has several distinct advantages over other learning techniques.
First, it allows the measurement of learning on a repeated basis, thus
providing a stable baseline rate of learning across sessions from which
perturbations can be assessed. In addition, the delineation of various
classes and patterns of errors following chemical exposure can provide
useful information about the type of learning deficit, facets which are
relevant both to the issue of behavioral mechanisms of toxicity and to
screening and risk assessment.
Furthermore, the procedure is often run in conjunction with a per-
OCR for page 150
150
DEBORAH A. CORY-SLECHTA
120
100
o
~ 80
o
C'
o 60
lo
C,
~ 40
C'
20
o
a\ ~
\ ~ B
\`
\\
\~
~ A
_
l _
· Pet
0 Pigeon
I l L I
J ~
0.1 1 10
Pb (mg/kg)
100 1 000
FIGURE 4 Schematic diagram of the intelligence panel used for the repeated acquisi-
tion procedure. In the procedure, each three-light unit serves as a discriminative
stimulus signaling the next correct response In the sequence of responses leading to
reinforcement. The lights have no fixed relationship to the lever; the association be-
tween lights and levers changes each session win the new correct sequence of responses.
SOURCE: From Pollard et al. (1981).
formance component in which the response sequence remains con-
stant from experimental session to session. During the daily experi-
mental session, the performance component alternates periodically
(e.g., every 10 minutes) with the learning component (as defined above).
Thus, both learning and performance are being concurrently assessed
during an experimental session. This is especially advantageous be-
cause the performance component allows the assessment of nonspecific
chemical effects, as would be exemplified by changes that occur in
both the learning and the performance components, whereas behavioral
alterations observed exclusively in the learning component may more
specifically reflect changes in learning. Representative performance
of a nonhuman primate responding under such a schedule is shown
in Figure 5, in which a separation of the effects of d-amphetamine on
the learning and the performance components is evident. Finally, the
OCR for page 151
BEHAVIORAL TOXICOLOGY STUDIES
151
procedure has recently been further amended (Thompson et al., 1986)
to include a memory component. This is accomplished by retesting
the acquisition of the learning component sequence at various time
intervals following the original learning.
In spite of the emphasis on toxicant and chemical-induced alter-
ations in learning, only two studies to date have utilized the repeated
acquisition baseline to evaluate to~c~cant-~nduced lear~ung deficits. Paule
and McMillan (1986) employed a variant of this procedure to track
the time course of trimethylUn (TMT) effects on learning. By separating
the various error components of repeated acquisition performance in
their analysis, a differential time course of TMT on various classes of
errors was noted. It showed that early responses in the sequences
.,, MONKEY EV / /
8~ L /
8
/
V'
d Patina A
· SPA
1 mg/kg
L
d-Amphotamine /
/
~1
/1
(j L ant,'//
/
/
FIGURE 5 Cumulative records illustrating the effects of the administration of d-am-
phetamine on the performance of a monkey working on a multiple schedule which
alternated repeated acquisiton or learning (L) and performance (P) components. Am-
phetamine affected behavior primarily during the learning component, increasing the
number of errors in a dose-related fashion, while leaving the performance component
relatively intact.
SOURCE: From Thompson and Moerschbacher (1979).
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152
DEBORAH A. CORY-SLECHTA
were disrupted to a greater extent by TMT than were later stages of
the sequences, suggesting an effect on learning, whereas the recall
necessary for the longer sequences remained relatively intact. In an
earlier study, Anger and Setzer (1979) reported that intramuscular
carbaryl administration increased both session time and error rates
of monkeys working on a four-response sequence repeated acquisition
baseline.
The acquisition of response sequences serves as but one example
of a more sophisticated procedure for evaluating learning deficits. It
emphasizes the point that increased awareness of advancements in
behavioral sciences can accelerate the progression of behavioral toxicology
toward its ultimate goal. One reason for the hesitancy on the part of
many investigators to turn to such techniques may be the more extensive
training required to produce stable baseline performances than are
required when using simpler procedures. Given the potential of these
techniques, however, future work designed to accelerate the training
process would be of great benefit to behavioral pharmacology and
toxicology.
Another strategy useful to facilitate cross-species extrapolation, that
is, to bridge experimental animal and human behavioral toxicology
studies, is to strongly emphasize the use of behavioral paradigms
that are directly applicable to both populations. Operant schedules
of reinforcement exemplify one class of such baselines. Innumerable
studies have documented the comparability of schedule-controlled
performance in a wide variety of species, including humans (e.g.,
Dews and Wenger, 1977; Holland, 1958; Kelleher and Morse, 1969;
Laties and Weiss, 1963; Richelle, 1969; Tews and Fischman, 1982), a
point documented by Figure 6. Behavioral pharmacology studies have
further shown the similarity across species of drug effects on schedule-
controlled behavior. In fact, the study of schedule-controlled behavior
was a strategy suggested by Bornschein et al. (1980) to enhance direct
extrapolation of lead-induced behavioral impairments across species.
Some of the more advanced complex techniques may be even more
applicable. The repeated acquisition paradigm described above has
been used to study learning in rodents (Schrott et al., 1980), pigeons
(e.g., Thompson, 1980), and nonhuman primates (Moerschbacher and
Thompson, 1980), as shown in Figure 5. The technique has also been
utilized with human populations, including those with developmen-
tal disabilities (Suessbrick, 1983) and, more recently, victims of Alzheimer's
disease (Gershensen, Thompson, and Gisselquist, personal communication,
1988~. Figure 7 compares the decline in the number of errors on a
five-link response sequence in normal elderly humans (top panel) to
those with Alzheimer's disease (bottom panel). The greater number
OCR for page 153
BEHAVIORAL TOXICOLOGY STUDIES
153
,
| 8 O-~Min R Gamin F! ~ 50-Min ~ / l
i} [ // a// J
Gamin Fl Gamin Fl
Pet Lever Water Rat Lever Food Pigeon Key Food
Pigeon Key Water ~
~ ~~f ~ i' ~
8 i ~ §5 '~ a i/
&( Pat Lear Food
~ | Rat Wh66' ~ O t Mob
fir ~ fir ~
Chimpanzee Lever Food ~ ~ ~ &5 ~ am/
~A a/ §/
! I
15 min
FIGURE 6 Generality of fixed-interval (PI) performance under various conditions.
The ordinate shows the cumulative number of responses, whereas time is represented
on the abscissa. The typical performance is characterized by little or no responding
after reinforcement, followed by a gradually accelerating rate of responding. In all
examples, a fixed-interval schedule of food or water presentation was in effect. The
lower left frame shows performance under a 10-minute fixed-interval schedule. Each
reinforcement delivery resets the recording pen to the baseline. The comparability of
performance of the pigeon, rat, and chimpanzee, either pecking a key or pressing a
lever, is evident. Likewise, during a 5-minute fixed-interval schedule (lower right frame),
the comparability of performance of rats, pigeons, and cats pecking a key, pressing a
lever, wheel-running, or pulling a knob is illustrated.
SOURCE: From Kelleher and Morse (1969).
of errors and slower decline in error rates in the patients with Alzheimer's
are evident. Thus, although admittedly difficult to train, the response
sequence paradigm shows comparable baseline performance across
species and evidences sensitivity both to drugs and to neurodegenerative
disease. Other learning and memory paradigms with direct cross-
species applicability include procedures such as delayed alternation
and delayed matching to sample. Obviously, the use of such behav-
ioral tasks in the case of human evaluation may not be easily implemented
OCR for page 154
154
50
40
30
10
Contrd #1-Total Baseline
O ~~ ,.~ ~ ~
0 10 20 30
TRIAL
60
co 50
o
fir 40
LU
LL
0 30
20
he
10
30 - Alz #1-Baseline, 5 Unks 40
on Q en
O \ O 30
~ 20 _ ~ ~
O \ O 20
10 _ ~ ~d
o
DEBORAH A. CORY-SLECHTA
Contrd #2-Total Baseline
O ~
0 10 20 30
TRIAL
Alz #2-Baseline, 5 Unks
_~\
10
l~:44~ ol '
0 10 20 0 10 20
TRIAL TRIAL
FIGURE 7 Performance of normal elderly humans (top panels) and Alzheimer's pa-
tients (Alz; bottom panels) working on a five-link repeated acquisition paradigm.
Total number of errors over successive trials of a session are presented. The rapid
decline in errors during initial trials of the session and the low subsequent errors over
subsequent trials of normals are in stark contrast to the slower initial decline in errors
and the higher sustained rate of errors over the remainder of the session in the Alzheimer's
patients.
1988).
SOURCE: From Gershensen, Thompson, and Gisselquist (personal communication,
when large sample populations are involved. However, one initial
alternative is to study more intensively a smaller proportion of the
more highly exposed individuals within the population.
Although multidisciplinary studies pave the way for establishing
biological mechanisms, most stop short of experimentally evaluating
and defining the nature of the connection between various param-
eters of neurotoxicity. For example, a toxicant may induce changes
in some aspect of behavior, as well as decrease the levels of some
neurotransmitter. It is common to hypothesize a causal relationship
between the two, but far less frequent to test such a hypothesis di-
rectly. More systematic research exploring the relationships between
behavioral toxicity and other parameters of neurotoxicity would expedite
OCR for page 155
BEHAVIORAL TOXICOLOGY STUDIES
155
our understanding of the biological bases of toxicant-induced behav-
ioral effects.
Finally, it should be remembered that both experimental animal
and human behavioral toxicology studies have common goals: to
understand the mechanisms by which toxicants affect behavior and
to implement procedures to screen for neurotoxic properties of chemicals.
A better base of communication and interfacing between human and
experimental animal research would accelerate progress on both fronts,
allowing each to benefit from advances made by the other.
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Representative terms from entire chapter:
behavioral toxicology
