Two-way active avoidance is a conditioning technique widely
used lo study the effects of several treatments, whether behavioral or neurophysiological,
upon the facilitation or disruption of the acquisition, retention and extinction
of learning (see, for example, De Wied, 1965; Izquierdo, 1975; Ruthrich, Wetzel
and Matthies, 1982; Van Hulzen and Coenen, 1982; Callen, 1986; Fernández
and Coll, 1987).
Due to its wide use, relatively accurate data about some parameters
influencing the level of acquisition and retention of this kind of conditioning
are available. The effects induced by variations in the duration of the inter-stimulus
interval (Low and Low, 1962, Black, 1963; Hoffman, 1966; Archer, Ogren and Johansson,
1984) and in the intensity of the electrical shock (Theios, Lynch and Lowe,
1966; McAllister, McAllister and Douglas, 1971; Tobeña, 1979; Archer
et al., 1984) are specially well known. Nevertheless, few data are available
concerning the variables influencing the retention of a task which has already
been learned. This lack of data is of special concern if we have into account
that the results reported by different laboratories have been obtained using
widely different training parameters, and this fact makes it difficult their
comparation and interpretation and imposes an important restriction to the analysis
of the mechanisms controlling this kind of behavior (Archer et al., 1984).
In that sense, we have intended to analyze whether the conditions
influencing the level of acquisition of two-way active avoidance conditioning
do exert a similar influence upon its long-term retention. Specifically, we
have studied the effects induced by variations in the intensity of the unconditioned
stimulus (US; electrical shock) and in the duration of the conditioned stimulus
(CS; tone) upon the acquisition of the task and its long-term retention (LTR;
14 days). Since in some experiments the retention of learning has been measured
by means of a session of similar characteristics to those of the learning session
(Van Hulzen and Coenen, 1982: Oniani and Lortkipanidze, 1985: Martí,
Portell and Morgado, 1988; Segura, Capdevila, Portell and Morgado, 1988; Coll,
Martí and Morgado, 1991) and, in other ones, by means of an ordinary
extinction session (i.e., without the presentation of the US) (De Wied, 1965),
we have decided to use both methods to evaluate LTR.
Another issue which, from our point of view, deserves special
atention is the use of adequate statistical methods to analyze behavioral responses.
At present new statistical tools are available allowing a marked improvement
of the analysis of data. Thus, although the analysis of variance affords us
with undoubtly valuable information to determine the existence of differences
among the treatment groups, it has, nevertheless, some limitations when carrying
out longitudinal follow-up studies in which the main variable to be analyzed
is the time interval between an initial event and a final event. In the context
of learning tasks, it can be of great interest to analyze the temporal evolution
of their acquisition and LTR and to compare such evolution in different experimental
groups. To that effect, we can use, on one hand, the survival analysis, a method
used for the first time in engineriing to study the resistence of materials,
but that has been hardly used in psychological studies. Within a learning setting,
for example, this technique makes it possible to determine the percentage of
subjects witch, in every phase or trial along a session, reach a predetermined
performance criterion, allowing in this way to analyze the speedness of learning
and to compare this speedness in different experimental groups (see, for example,
Domènech, 1988 and 1989).
Another statistical technique which is still scarcely used
in Psychology is time-series analysis (Gottman, 1981; Uriel, 1985). This technique
arose within the field of physical sciences, but it is now beggining to be used
for the analysis of behavioral studies. Briefly stated, this analysis allows
the stablishment of descriptive and predictive models about the temporal evolution
of a given variable, both in individual subjects and in groups. In addition,
it makes it possible to compare different temporal curves and to determine (with
an statistical criterion) the specific moments when the curves of two different
subjects or groups differ.
Having into account what has been said above, the present work
has a double aim: in first place, to analyze the effects of the intensity of
the US and of the duration of the CS upon both the acquisition and LTR (14 days)
of two-way active avoidance; and, in second place, to illustrate the application
of other statistical methods complementary to the traditional analysis of variance
to evidence how the analyses of results within the field of Psychology can be
Subjects were 58 albine male Wistar rats from our breeding
stock with a mean age at the beggining of the experiment ranging from 90 to
120 days. They were subjected to controlled conditions of environmental temperature
(20-25°C) and humidity (40-70%) and to a 12-12 light-darkness cycle (lights
on at 8 a.m.). Water and food was available ad libitum.
Three days before the beggining of the experimental process,
each animal was placed in an individual plastic cage (26x26x14 cm). Every one
of those three days the animals were wheighed in order to habituate them to
All subjects were given a single massed training session on
two-way active avoidance. Just prior to this session the animals were subjected
to 10 minutes of adaptation to the conditioning cage (Lafayette, LA 85150-SS),
during witch time neither the CS nor the US were presented. The training session
consisted of 60 conditioning trials. The CS used was a tone of 80 dB and 1000
Hz. The responses (going from one compartment to the other) made during the
presentation of the CS were considered as avoidance responses. In case that
an avoidance response was not made, the CS was followed, with no delay, by an
US which duration was of 30 seconds at most. The inter-trial interval lasted
1 minute. Subjects were randomly distributed into the 4 following groups depending
on both the intensity of the US (either 0.6 mA or 1 mA) and the duration of
the CS (either 3" or 10"): 1) 0.6mA-3" (n=14); 2) 0.6mA-10" (n=14); 3) 1mA-3"
(n=15), and 4) 1mA-10" (n=15).
Fourteen days after the training session, a new session (30
trials) was administered. The purpose of that session was to determine, by means
of two different methods, the LTR of learning. To that effect, subjects were
randomly assigned to one of the two following conditions: seven subjects in
each group received a new learning session consisting of 30 trials of the same
characteristics that the trials in the acquisition session (additional learning).
The remaining subjects in each group were administered an extinction session
of 30 trials, in which the presentation of the US was omitted (ordinary extinction).
Thus, having into account the different experimental conditions, 8 groups were
considered in the analysis of LTR.
During the acquisition and LTR sessions the kind of responses
(avoidance or escape) and the latency of responses for every trial were recorded.
Analysis of Variance
Figure 1 shows the mean number of total avoidances and the
mean latency of responses made by each of the 4 experimental groups during the
acquisition session. As it can be seen, the different parameters used during
conditioning seem to have influenced upon the level of learning of the subjects,
since there seem to be differences among groups. An analysis of variance showed
that the intensity of the US had a significant effect upon the level
of acquisition [F(1,54)=8.58: p=0.005], the groups trained with the lower shock
intensity (0.6 mA) achieving higher conditioning levels than the groups trained
with the higher shock intensity (1 mA). The analysis of latencies confirmed
this effect [F(1,54)=5.22; p=0.026].
Neither the duration of the CS nor the interaction factor
(intensity * duration) were significant, either for the number of avoidances
nor for the mean latencies of responses.
To analyze the evolution of conditioning throughout the acquisition
session, this session has been subdivided into 6 blocks of 10 trials each. Figures
2 and 3 show the number of avoidances and the mean latencies of responses in
each block for each experimental group.
The latter analysis indicated that the interaction block
* intensity of the US was significant. The detailed analyses of this interaction
indicated that the intensity of the US was significant only from the second
block of trials on, but not on the first block.
On the other hand, a contrast analysis (Polynomial) evidenced
that the evolution of the number of avoidances during the acquisition session
fitted, in general terms, to an ascending linial function [F(1,54)=82.71; p<0.001],
specially during the first 4 blocks, with a tendency to be maintained constant
during the last 2 blocks. During the first 40 trials the evolution of learning
depended upon the intensity of the US [interaction block * intensity of the
US: F (1,54)=4.16; p=0.046]. In general terms, those groups trained with
a 0.6mA US showed an ascending linial evolution with a higher slope than the
groups trained with a 1mA US [simple effects for 0.6mA and 1.0mA, respectively:
F(1,56)=61.77: p<0.001; F(1,56)=26.56; p<0.001], as deduced from the "F"
values. In this sense, only those groups trained with a 0.6mA US showed a significant
increase in the second block compared to the first block [F(1,56)=14.47; p<0.001],
while from trials 20 to 40 all groups showed a significant increase of performance.
On the other hand, while the groups trained with a 0.6mA US showed an asymptotic
evolution during the latter 20 trials, the ones trained with 1.0mA US showed
a decrease from the fourth to the fifth blocks [F(1,56)=5.11: p<0.028] and
a further increase from the fifth to the sixth blocks [F(1,56)=5.17; p<0.027].
The study of latencies corroborated all those results.
Figure 4 shows both the number of avoidances and the mean latencies
of response for each experimental group during the LTR test carried out 14 days
after the acquisition session (additional learning and extinction).
As seen in this figure, the parameters used during the LTR
test have also had an influence upon the performance of the subjects. An analysis
of variance indicated that the interaction intensity of the US * duration
of the CS * kind of LTR test was significant, both when analyzing the number
of avoidances [(1,50)=4.29; p=0.044], and the mean latencies [F(1,50)=7.52;
p=0.008]. Further analyses indicated that the influence of both independent
variables was only significant when LTR was measured by the use of an additional
learning session, but not when it was measured by an extinction session.
Thus, on the additional learning session the interaction
intensity of the US * duration of the CS was significant both for the number
of avoidances [F(1,50)=4.4; p=0.041] and for the mean latencies [F(1,50)=8.81;
p=0.005]. Further analyses indicated that those subjects trained with a 0.6mA
US showed higher LTR levels (both in number of avoidances and in latencies of
responses) than those subjects trained with a 1.0mA US, but only when the duration
of the CS was 10" [F(1,24)=14.24; p=0.001 for the number of avoidances and F(1,24)=10.95;
p=0.003 for the latencies of responses, respectively]. On the other hand, the
subjects trained with a 0.6n A US had a higher performance than the ones trained
with a 1.OmA US both when a 3" CS [F(1,24)=4.58; p=0.043] and a 10" CS [F(1,24)=14.24;
p=0.001] were used.
The LTR session has been subdivided into 3 blocks of 10 trials
each. Figures 2 and 3 also show the level of LTR (avoidances and latencies)
in each of the blocks for each of the experimental groups. With regard to the
number of avoidances, both on the additional learning session and in the extinction
session all the groups showed a significant ascending linial evolution throughout
the session [F(1,24)=40.12; p<0.001 and F(1,26)=9.67; p=0.005, respectively],
although the evolution during the additional learning session can also be explained
by a second degree function [F(1,24)=4.63: p=0.042]. More specifically, both
in the additional learning session and in the extinction session the number
of avoidances increased in the second block compared to the first block [F(1,24)=23.53;
p<0.001 and F(1.26)= 8.47; p=0.007, respectively]. The number of avoidances
of the groups trained with a 3" CS showed also an increase in the third block
of the additional learning session compared to the second block [F(1,26)= 15.87:
p<0.0011, while the performance of the rest of the groups was maintained.
However, this increase was not observed in the extinction session. With regard
to the latencies, a descending linial evolution was evidenced throughout the
additional learning session [F(1,24)=5.5; p=0.028], but not during the extinction
Another result deserving attention is the percentage of improvement of performance
(avoidances increase or latencies decrease) shows by the experimental groups in
the LTR with regard to the acquisition session. Those results are depicted in
Figure 5. As shows in this figure, all the experimental groups showed a significant
increase in the number of avoidances during the additional learning session compared
to the acquisition session [F(1,24)=29.11; p=0.004]. A simple effects analysis
indicated that this increase was significant in two groups: the ose that had shows
the highest level of performance during acquisition [0.6mA-10" group; F(1.24)=9.71;
p=0.005] and the one showing the lower level of performance during acquisition
[1.0mA-3" group; F(1,24)=17.18: p<0.001]. On the contrary, the performance
during the extinction session did not show significant differences compared to
that in the acquisition session.
The above indicated results were not corroborated by the analysis
of the latency of responses, since no significant differences between acquisition
and either LTR sessions were found.
To carry out the survival analysis a learning criterios of
5 consecutive avoidance responses has been choosen, and it has been analyzed
whether differences among groups existed regarding the number of trials required
to reach the stablished criterios.
Figure 6 shows the survival function of the acquisition session
for the 4 experimental groups. As it can be seen, differences seem to exist
among groups regarding the number of trials required for a given proportion
of subjects to show the learning criterion. This observation was verified by
the Mantel-Cox test, which showed the existence of significant differences among
groups [S(3)=10.614; p=0.014]. Specifically, the animals trained with a 0.6mA
US and a 10" CS acquired more rapidly the learning criterion than the subjects
trained with a 1.0mA US (regardless of the duration of the CS) [10" CS: S(1)=5.904;
p=0.0151; 3" CS: S(1)=7.035; p=0.008]. Contrarily, the intensity of the US does
not seem to be so significant when the CS lasts 3", since the subjects in 0.6mA-3"
group were not significantly different from 1.0mA-3" subjects, but did not differ
either from the group reaching the highest level of acquisition (0.6mA-10" group).
On the other hand, there were also differences regarding the
percentage of subjects reaching the learning criterios. This percentage was
higher in the groups trained with a 0.6mA US (85% in 0.6mA 10" group and 72%
in 0.6mA-3" group) than in the groups trained with a 1.OmA US (50% in 1.OmA10"
group and 40% in 1.0mA-3" group).
Another question that can be answered with this kind of analysis
is how many trials are needed for each group to reach an asymptotic level. In
the acquisition session, it can be seen that, in general terms, when an animal
has not reached the learning criterios after 40 trials, it will fail to reach
it even if the session is lengthened to 60 trials. From a qualitative point
of view, it is remarkable that the only group showing further improvements in
the level of learning after trial 40 is the 0.6mA-3" group. The intensity of
the US used with this group (0.6mA) seems to be a favourable parameter for a
high proportion of subjects to reach the learning criterion (a similar proportion
to that shown by the group having an overall better performance during that
session, 0.6mA-10" group), but, on the other hand, the duration of the CS is
the least favourable, and therefore more trials are needed to reach a level
similar to that of 0.6mA-10" group.
During the LTR tests, differences among groups were observed
only when an additional learning session was used [S(3)=9.844; p=0.019], but
not when animals were subjected to an extinction session.
The survival analysis relating to the additional learning session
showed that the groups that had shown a better acquisition level were also the
ones showing a better performance during this session (see Figure 7). In general,
the intensity of the US seems to be a significant factor, since the learning
criterion was more easily reached with a 0.6mA US than with a 1.0mA US. [S(3):
4.691; p=0.0303]. Nevertheless, this effect seems to depend upon the CS duration,
since it was only significant when the CS lasted 10" [S(1)=7.274; p=0.007],
but not when it lasted 3". lt is also remarkable that 0.6mA-3" group, which
during the acquisition session did not differ from any other group, during this
LTR test had a significantly higher performance that 1.0mA-10" group [S(1)=3.992;
p=0.045]. Thus, in general terms the Ss in 0.6mA-3" group required less trials
to reach the stablished criterios than the groups conditioned with 10mA.
During this LTR test, and similarly to what had been observed
during acquisition, there were also differences in the percentage of subjects
in each group reaching the learning criterion. A higher percentage of subjects
reached the learning criterion in those groups trained with a 0.6mA US (100%
in 0.6mA-10" group and 85% in 0.6mA-3" group) than in the groups trained with
a 1.0mA US (29% in 1.0mA-10" group and 40% in 1.OmA-3" group). Comparing those
percentages with the oses observed during the acquisition session, it can be
seen that they are increased in the groups trained with a 0.6mA US, while being
reduced in the groups trained with a 1.0mA US.
In this sense those groups trained with a 1.0mA US did not
show any improvement of performance during the additional learning session compared
to the acquisition session. On the other hand, the groups trained with a 0.6mA
US showed further improvements during this LTR session.
With regard to the extinction session, and as indicated above,
no significant differences among groups were detected on that session (see Figure
8). In spite of that, the contrast analyses between groups evidenced that subjects
in 0.6mA-10" group, which had shows the highest performance both in the acquisition
session and in the additional learning session, were also the oses requiring
a lower number of trials to reach the learning criterion during the extinction
session, specially when compared to the groups trained with a 1.0mA US [10":
S(1)=7.274; p=0.007; 3": S(3)=3.568; p=0.058].
Another remarkable issue to have into account is the fact that
the avoidance behavior did not show any evidence of extinction in any of the
groups. Furthermore, if we have into account the percentage of subjects reaching
the learning criterion during the extinction test (0.6mA-3": 64%; 0.6mA-10":
72%; 1.0mA-3": 38%; 1.0mA-10": 72%), no inverse relationship between this variable
and the acquisition level can be aduced. Nevertheless, the group showing a better
acquisition level was the ose requiring a lower number of trials (15) to reach
an asymptotic level, i.e., to stop improving its performance during the extinction
Time-Series Analysis (TSA)
As indicated in the introduction of this paper, the TSA allows
to study the evolution of a given variable over time and to compare this temporal
evolution in different groups or in different individual subjects. The first
criterion to apply the TSA is, of course, to have longitudinal data about the
variable to be studied. On the other hand, those data have to show serial dependency;
i.e, the data obtained on different times have to autocorrelate. Another important
criterion to apply this analysis is to have a high number of observations (Box
and Jenkins, 1970, recomend a minimum of 50 observations) and that the time-intervals
separating the different observations be constant. In our case, and having into
account the just-mentioned criteria, we have applied the TSA to the evolution
of the latencies of responses over the acquisition session (60 consecutive trials).
The first step to do so has been to search for an optimal model that could be
adjusted to the evolution of the latencies of responses of each group throughout
the session. To that effect, the ARIMA method (SPSS-PC) has been used. Generally,
several putative models are tried and one of them is choosen having into account
several adjustment indices given by the ARIMA method. The second step consists
of estimating (from the parameters of the choosen model) the 95% confidence
interval (95CI) of the values indicated by the model. The upper and lower limits
of this interval will be considered as the statistical criterios (see Domènech,
1985) to compare the curves corresponding to different groups or to different
subjects (see Capdevila, Cruz and Viladrich for a description of the application
of TSA to the field of Psychology).
In our case, an ARIMA model has been adjusted to the latencies
of responses during the acquisition trials for each of the 4 groups subjected
to different conditioning conditions. After that, we have analyzed whether the
temporal evolution of the acquisition of conditioning shows differences depending
on the intensity of the US.
Table 2 shows the parameters of the ARIMA models fitted to
the latencies of each of the 4 experimental groups considered during the acquisition
session, as well as the values of the adjustement indices for each model.
The top picture in Figure 9 depicts the evolution curve of
the mean latencies of subjects in 1.0mA-3" group throughout the acquisition
session. Overimposed are also the values of the lower and upper limits of the
95CI predicted by the ARIMA model (1,1,0) adjusted to 0.6mA-3" group. As seen
in this figure, the temporal evolution of the latencies of responses is very
much similar in both groups, and only in a few time points the values corresponding
to the 1.0mA-3" groups do not fit into the 95CI predicted for the 0.6mA-3" group.
In conclusion, the temporal evolution of those two groups, although not wholly
coincidental, does not show appreciable differences. Therefore, when the CS
lasts 3", the intensity of the US does not seem to have any remarkable influence
upon the subjects' performance.
Similarly, the bottom picture in Figure 9 compares the 95CI
of the ARIMA model (0,1,1) adjusted to the latencies of 0.6mA-10" group to the
mean latencies of subjects in group 1.0mA-10". As it can be observed, in a high
number of trials the latencies of the latter are situated above the upper limits
of the 95CI of the former group; this fact implies that with a 10" CS, the subjects
trained with a 1.0mA US show higher latencies (and, therefore, a worse performance)
than those trained with a 0.6mA US. In other words, the TSA indicates (coinciding
with the results of the analysis of variance) that the intensity of the US has
a significant influence upon the acquisition of conditioning depending on the
CS duration, suggering that this influence is of higher magnitude when the CS
lasts 10" that when it lasts 3", and this fact is not reflected significantly
by the analysis of variance concerning the acquisition session. The TSA allows
also to determine the specific trials when the differences between groups are
of higher magnitude. Specifically, it can be observed that in trials 21 to 31,
the curve corresponding to 1mA10" group runs near to the upper limit of the
95CI of 0.6mA-10" group. From trial 36 on, this curve is clearly above the upper
limit of this interval in most trials. Therefore, the differences between groups
are evidenced mainly during the second part of the acquisition session, specially
from trial 36 on.
It is well known that the statistical descriptives (such as
group means) are not always representative of some of the subjects belonging
to a given group. In that sense, the TSA makes it possible to analyze, based
on statistical criteria, whether the actual values of a subject fit to a model
generated from the mean data of its groups, as well as to compare within-subject
data in single case experimental designs (see, for example, Capdevila and Cruz,
1992). To illustrate this utility, Figure 10 depicts the 95CI of the ARIMA model
(1,1.0) adjusted to the latencies of 0.6mA-3" group, together with the latency
values corresponding to one of the subjects in this group, subject 36. As it
can be seen, the performance of this subject differs significantly from the
mean performance of its group, specially on the trials of the first part of
the training session, and this fact cannot be evidenced by the traditional analysis
of variance. Specifically, the latencies of response of this subject are lower
than the lower limit of the 95CI estimated for its group at the beggining of
the session, although these differences dissapear on the last trials.
The results found in the present work show that the conditioning
parameter having the most decisive influence upon the level of acquisition achieved
by the subjects is the intensity of the US. Under the conditions used by us,
the subjects' performance is considerably better with an US of 0.6 mA that with
an US of 1.0 mA. On the other hand, and according to the analysis of variance,
the duration of the CS does not seem to exert any significant influence upon
the acquisition level of the subjects. Nevertheless, this assessment cannot
be regarded categorically, since both time series and survival analyses have
shown that the superiority of performance with an US of 0.6 mA is much more
evident when the CS lasts 10 seconds than when it lasts 3 seconds. In other
words, there seems to be an interaction between the CS duration and the US intensity.
At all events, we believe that it is of great importance to apply in each case
the statistical tests which might be more sensitive to detect the potential
existence of interactions between parameters.
According to several reports about the parameters influencing
the rate of acquisition of two-way active avoidance the following outstanding
data can be remarked:
a) Most works have indicated the existence of an inverse relationship
between the intensity of the US and the number of avoidances (Theios et al.,
1966; McAllister et al., 1971; Tobeña, 1979). This seems to be also appliable
to our results, specially when a 10-sec CS is used. Nevertheless, Archer et
al. (1984) have specified that such an inverse relationship is only observed
during the first conditioning sessions, but it can dissapear or even be inverted
on consecutive sessions. Although in the present work a single training session
has been used, it can be said, as shown by time-series analysis, that the inverse
relationship between the intensity of the US and performance is specially manifested
during the second half of the acquisition session. And, as indicated by the
analysis of variance and the survival analysis, this relationship is maintained
on LTR. Therefore, in our case such a relationship does not show any sign to
dissapear with time, although there is no doubt that further conditioning sessions
would have to be performed so as to be able to formulate a reliable conclusion
about that issue.
b) In general terms, the performance of the subjects usually
improves when the duration of the CS is increased (Coll, Martí, Portell
and Morgado, 1993). Nevertheless, according to Hoffman (1966), the optimal duration
of the CS to improve the performance ranges from 5 to 10 seconds, while a shorter
CS does not allow that an adequate level of learning be achieved. The results
in our work do not completely agree with this assessment, since, as indicated
by the survival analysis, when the CS lasts only 3 seconds a relatively high
percentage of subjects achieves the learning criterion. This percentage depends
on the intensity of the US, ranging from 40%, with a US of 1 mA, to 70% with
a US of 0.6 mA.
Regarding the LTR of learning, not many differences have been
found between the two different methods used to measure it, additional learning
and extinction. In both cases, the subjects' performance during LTR session
does not show statistical differences compared to the acquisition session. As
shown in several works (Tobeña, 1979; Fernández, 1983), the omission
of the US does not seem a suficient condition to extinguish the two-way active
avoidance responses. Only those subjects trained with a 0.6 mA US and a 10-sec
CS showed a (non-significant) tendency to make a lower number of avoidance when
compared to the acquisition session. Thus, although on the one hand those subjects
needed the lowest number of trials to reach the performance criterion on the
extinction session, on the other hand they were also the subjects reaching more
rapidly an assymptotic level in that session; in other words, they were the
first ones to stop improving their performance. They were also, precisely, the
subjects that had shown a better acquisition level (see Figure 5) and this might
be the reason why they could be aware of the desaparition of the contingence
relationship between the CS and the US. Whatever that might be, the two-way
active avoidance conditioning responses seem to be specially difficult to eliminate
once acquired, and special procedures have had to be designed to reach a certain
extinction level of those responses (i.e., ordinary extinction, response prevention
or flooding, delay warning signal termination, etc) (Solomon, Kamin and Smith,
1953; Page and Hall, 1953; Katzev, 1967).
The analysis of variance does not make it possible to detect
differences between the two methods used to assess LTR. Instead, the survival
analysis seems to be sensitive to those differences. Thus, this analysis has
clearly indicated that only during the additional learning session, but not
during the extinction session, there were differences among groups. Alltogether,
it shows that in those groups with a higher percentage of subjects achieving
the predetermined performance criterion (5 consecutive avoidance responses),
i.e., the groups trained with a 0.6 mA US, this percentage continued increasing
during the additional learning session. Contrarily, this percentage was reduced
in those groups which had shown a lower percentage of subjects capable of achieving
the learning criterion, i.e., in those groups trained with a 1 mA US.
Having into account the results of the analyses which have
been carried out, the extinction procedure does not seem to be adequate to assess
the level of LTR of twoway active avoidance. It seems that an additional learning
session, in which the same contingential relationship between the intervening
stimuli than that used during the acquisition session, might be more appropiate
to that effect. At all events, the level of LTR might probably be better assessed
during the first trials of the additional learning session, thus minimizing
the learning effect associated to the additional conditioning trials.
With regard to the second objective of our work (i.e., to illustrate
the utility of certain non traditional statistical analyses within the background
of psychological studies), it has been shown that, certainly, both time-series
analysis and survival analysis, besides reinforcing some conclusions drawn from
the analysis of variance, can in several instances disclose some aspects which
are not evidenced with the traditional methods. In the present work, time-series
analysis has made it possible to evidence the existence, on the acquisition
session, of an interaction between the intensity of the US and the CS duration,
which was not shown by the analysis of variance. Furthermore, it has given useful
and detailed information about the specific trials in the acquisition session
when differences existed between the compared groups. On the other hand, it
has made it possible to analyze whether the performance of a given subject fits
to the mean performance of its group over all the session. By its turn, the
survival analysis, besides allowing to assess the percentage of subjects achieving
a predetermined learning criterion, has afforded valuable information to determine
differences between the two methods used to evaluate LTR.
Acknowledgement: This work has been made possible partly
a DGICYT grant (PB89-0315).
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Aceptado, 23 de junio de 1993.