Multivariate Analysis of Behavioral Aging Highlights Some...

BEHAVIORAL AND NEURAL BIOLOGY 61, 110-122 (1994)

Multivariate Analysis of Behavioral Aging Highlights Some Unexpected Features of Complex Systems Organization

ALESSANDRO GIULIANI, ORLANDO GHIRARDI, ANTONIO CAPRIOLI, STEFANO DI SERIO, MARIA TERESA RAMACCI, AND LUCIANO ANGELUCCI *'1

Institute for Research on Senescence, Sigma-Tau S.p.A., Via Pontina km. 30.400, 00040 Pomezia, Rome, Italy; and *Institute of Pharmacology II, School of Medicine, "La Sapienza" University of Rome, 00187 Rome, Italy

Ten different behavioral tests were performed on a population of young (n = 20) and aged (n = 20) Fischer 344 rats. The relationship structure among these tests was studied by principal component analysis applied both to the entire data set and separately to the two age groups. This analysis proved very useful in highlighting a global index of the rat "behavioral" age based on the entire test set. The analysis effected separately on the two age groups evidenced qualitative differences between them that were linked to the different meaning the same test would assume in rats of different ages. From an overall meth- odological viewpoint, this work indicates that the correlations among behavioral parameters appear to depend on the observational scale and that the spin-glass model represents an appropriate metaphor to approach the study of the correlations in biological systems. © i~4 Academic Press, Inc.

INTRODUCTION

Aging is a natural overall process jointly affecting many parameters relat ing to different biological structures. Whatever the viewpoint it is approached from (immunology, neurobiology, biochemistry, morphology, etc.), senescence appears to be a general flow of variation. This makes research on senescence a privileged field for studying biological "systems." This approach involves the recording of different parameters from the same animal to ex- ploit the pattern of relations among them.

1 We thank Mrs. Luisella Mattace and Professor Ian Mc- Gilveroy for their invaluable translational and editing help and Professor Alberto Oliverio and Dr. Assia Catalani for their help- ful criticism. Address correspondence and reprint requests to Alessandro Giuliani. Fax: 06/9107651.

While there are plenty of data evidencing quan- t i tative age-related modifications in single behavioral tests (Barnes, 1990), the issue of the effect of aging on the correlations among tests has been far less explored (Gage, Dunnett, & Bjorklund, 1989).

In this study we concentrate on the pattern of correlations among behavioral tests in young and aged animals. We rely on an objective operational meaning of the concept of correlation in terms of coherence between variables induced by internal and external force fields (Atlan, 1979; Nicolis & Prigogine, 1987; Wilson, 1979; Kauffmann, 1991).

We investigated the relationship patterns in two age groups (young and aged rats) among tests both at the great variability scale (entire data set, external field on, effect of aging on correlation structure) and at the small variability scale (each group separately considered, no effect of aging on correlation structure, external field off).

The mathematical tool we used for these studies was the principal component analysis (PCA), a mul- t ivariate technique designed to highlight and quan- tify the general trends present in a multidimen- sional data set (Benzecri, 1980; Bartholomew, 1984; Benigni & Giuliani, 1986; Lebart, Morineau, & Warwick, 1984; Preisendorfer, 1988; Gage et al., 1989). The analysis evidenced a clear "gross-scale relation structure" among the variables which was generated by the effect of aging and a seemingly chaotic "small-scale relation structure" for the correlations among different behavioral parameters when separately calculated in the two age groups.

This situation is consistent with a well-known physical model: the spin-glass model (Wilson, 1979; Stein, 1989) which gives us a theoretical frame for the heterogeneous orderings of the system at the different observation scales.

0163-1047/94 $6.00 Copyright © 1994 by Academic Press, Inc. All rights of reproduction in any form reserved.

110

MULTIVARIATE ANALYSIS OF BEHAVIORAL AGING 111

STATISTICAL METHODS

Principal Component Analysis (PCA)

PCA is a well-known mult ivariate technique orig- inally developed early this century (Spearman, 1904). This technique has had an almost universal application ranging from hydrodynamics (Preisen- dorfer, 1988; Craddock, 1965; Ghil & Vautard, 1991) to sociological (Aitkin, 1974) and biological research (Gage et al., 1989; Benigni & Giuliani, 1986; Giu- liani, Capuani, Miccheli, Aureli, Ramacci, & Conti, 1991).

The main purpose of PCA is to define the real dimensionality of the data field under study. When measuring N variables (performances) on the same units (rats in our case), a situation is delineated which appears to be N-dimensional. However, these variables may be correlated differently among them; thus, an equally satisfactory description could be obtained with a P < N number of axes.

PCA describes the data field, which is initially N-dimensional, using P dimensions, which are called factors (or components, in the case of PCA) and represent the degrees of freedom of the system. From a geometrical point of view, these dimensions (factors or components) represent the directions in the data field along which the elongation (variability) of the data cloud is maximal (Lebart et al., 1984). From a mathematical point of view, components are the eigenvectors of the correlation matrix among the original variables; they are orthogonal to each other and extracted by the algorithm in the order of percentage of explained variability; thus, the first factor will be the one explaining the highest proportion of information embedded in the original data matrix. Factors are constructed to have a mean value of zero and a uni tary standard deviation over the entire data set.

From a physical point of view, factors act as "order parameters" with respect to the data (Softky & Kammen, 1991); therefore, the direction pointed to by the first component is the direction of the main force field acting on the data, and the score of the first principal component relative to a particular unit is the value of the force field acting on the unit itself (Softky & Kammen, 1991; Wilson, 1979).

The percentage of the variance explained by a factor can be considered its relative strength of order parameter with respect to the system considered (Wilson, 1979).

Data Analysis Strategy

To analyze our data we used a two-level strategy.

(a) Single-test level. Each mult iparameter test was analyzed by PCA in order to single out the relevant information carried by the test. The variables chosen to describe the test were treated by classical inferential methods (Student t test, M a n n - Whitney U test) as well as by X 2 test following a cluster analysis (K - means) procedure (Everitt, 1980; Van Ryzin, 1977) in order to check their ability to discriminate the two age groups. The cluster analysis was proved (Bellacicco & Labella, 1979; Ghirardi, Giuliani, Caprioli, Ramacci, & Angelucci, 1992) highly suited to coping with the heterogeneity of data deriving from behavioral tests which in many instances resulted in having a discrete character. Data heterogeneity reflects important biological phenomena, such as quali tatively different pat terns of aging (Ghirardi et al., 1992).

(b) General analysis level. These variables were simultaneously analyzed by PCA in order to describe the correlation pat tern typical of each age group, as well as the global data structure.

Animals and General Plan of Experimentation

Male Fischer 344 (Charles River, Italy) rats were used for all the experiments. They were fed standard diet 4RF21 (Mucedola srl, Italy) until the age of 7 months and standard diet 4RF18 (same supplier) thereafter.

Twenty young (Y) rats were received at our fa- cilities when 1 month old and 20 aged (A) rats when 12 months old. They were housed four per cage and maintained under standard environmental conditions (22 _+ 1°C temperature; 55 _+ 15% relative humidity; 12 : 12 h light:dark cycle, 7 : 00 AM--7:00 PM light on).

Male Fischer 344 rats, under these dietary and environmental conditions, showed a median sur- vival t ime (50% mortality) of 27.2 +- 0.6 and a life span of 32.3 _+ 0.9 months.

At the beginning of experimentation, which lasted 4 months, rats were aged 3 (Y) and 20 (A) months.

In order to establish correlations, tests obviously had to be performed on the same animals and this would possibly entail some interference linked to the particular sequence chosen for the tests. To min- imize this drawback, we decided to choose a test sequence provided with an internal logic, to separate the tests into four reasonably noninteracting sequential blocks, as follows: (A) Motility and novelty, (B) passive and active avoidances, (C) tests involving swimming, and (D) noncognitive tests. Inside each block, the sequence was established to go from the simplest tests to more complex ones.

112 GIULIANI ET AL.

T A B L E 1 List of Tests and V a r i a b l e s

(in O r d e r o f E x e c u t i o n )

Experiment 1: Motor activity and novelty Associated variables: MT4, ST4, MT5, ST5

Experiment 2: Passive avoidance Associated variables: PAV

Experiment 3: Active avoidance Associated variables: AAL, AAG, AAS, ICT, ICM, ICR

Experiment 4: Swimming activity Associated variables: SAT, SAM, SAR

Experiment 5: T water maze Associated variables: TMA, TMI

Experiment 6: Complex water maze Associated variables: CMT, CME

Experiment 7: Morris water maze Associated variables: MWM

Experiment 8: Social behavior Associated variables: SCB

Experiment 9: Cold water stress Associated variables: CSB, CSD

Experiment 10: Conflict behavior Associated variables: CNF

In any case, the comparison of the results obtained in this work with those of similar experiments carried out at our laboratories does not reveal any not- able difference, thus ruling out any relevant in- terfering effect.

The order of performance of the tests is shown in Table 1; the tests were spaced out at weekly intervals. For each test, we utilized a number of animals varying from 17 to 20 rats for each age group; 17 young and 17 aged animals constituted the subset of the whole population performing all the tests. This subset was used for the second level of analysis (general analysis).

EXPERIMENT 1: MOTOR ACTIVITY AND NOVELTY

This experiment was carried out to evaluate two distinct behavioral features: (a) motor activity as the animal's response to an unknown environment and (b) the effect of introducing a novel object into the test frame, as a disturbance of an already as- sessed situation.

Materials and Methods

To evaluate motor activity we used a Digiscan Animal Activity Monitor (Omnitech Electronics) consisting of a t ransparent cage (41 x 41 x 41 cm) fitted with sensors to monitor both vertical and horizontal movements. Ten-minute recordings subdi-

T A B L E 2 M o t o r A c t i v i t y Parameters

(1) HO, horizontal activity (2) VA, vertical activity (3) TD, total distance (4) MT, movement time (5) NH, number of discrete horizontal movements (6) VT, vertical time (7) NV, number of vertical movements (8) ST, stereotypy time (9) NS, number of stereotypes (10) NR, number of revolutions

vided into two subsequent 5-min periods were taken over four consecutive days. On the fifth day a cone (diameter, 4 cm; height, 12 c m ) w a s inserted into the center of the test cage and motor activity was recorded following the same schedule. This apparatus generated 10 different features of motor ac- t ivity (Table 2).

Results

On the fourth day the 10 parameters gave rise to two factors explaining 85.7% of total variability: the first one collects all purely motor parameters (MT4), while stereotypy is linked to the second factor (ST4).

MT4 and ST4 did not show any significant difference between the two age groups (Table 5). No single parameter showed any significant difference

T A B L E 3 Experiment 4: Cluster Analysis

Cluster profiles

SAM SAR

(number of movements) (adimensional)

Mean SD Mean SD

Entire set 80.8 10.0 0.96 0.07 Cluster H 91.1 6.0 1.04 0.03 Cluster M 81.0 3.5 0.94 0.04 Cluster L 70.4 3.7 0.90 0.04

Cluster composition (number of animals)

Total Young Aged

Cluster H 13 11 (55.0) 2 (10.5) Cluster M 12 6 (30.0) 6 (31.6) Cluster L 14 3 (15.0) 11 (57.9)

Note. p < .01 (X2). The number in parentheses indicates the percentage of animals of each group of age in the particular cluster.


TABLE 4 Experiment 5: Cluster Analysis

Variable: TMA (total number of correct choices) Number of animals

Mean SD Total Young Aged

Ent i re set 39.9 5.6 36 18 18 Cluster H 45.1 1.6 15 15 (83.3) 0 (0.0) Cluster M 39.4 1.3 13 2 (11.1) 11 (61.1) Cluster L 31.1 2.3 8 1 (5.6) 7 (38.9)

Note. p < .001 (X2). The number in parentheses indicates the percentage of animals of each group of age in the par t icular cluster.

between age groups: these results point to a similar pat tern of habituat ion to a new environment for the two groups.

On Day 5, after introducing the cone into the cage, we observed an overall significant increase in the parameters measured in the Y group, while aged rats did not modify their activity with respect to the previous session.

A marked age-dependent difference was evident in terms of motor activity response when the rats were challenged with an attention cue (MT5: first factor of Day 5), while no statistically significant difference was evidenced for the stereotypy factor (ST5) (Table 5).

EXPERIMENT 2: PASSIVE AVOIDANCE

This test was performed to assess memory ca- pacity by utilizing the animal's inhibitory behavior connected to punishment avoidance. The "step- through" model was used to perform this test.


The experimental apparatus consisted of a black plastic box (42 × 42 x 40 cm) with a stainless steel grid floor through which footshock was delivered. A runway led off the front wall communicating with the box through a guillotine door. The runway was illuminated, while the box was dark.

After an adaptation period, the animals were placed on the runway and the time taken to enter the box (Latency) was measured in seconds. Once inside the box, the animal was delivered a footshock (0.5 mA x 2 s). After 24 h, the animals were again placed on the runway and the latency was measured (endpoint = 180 s).

Results

The results of this test were demonstrated to be discrete and discontinuous by means of a descriptive

analysis, thus ruling out any inferential approach other than contingency tables. The animals could be clearly subdivided into two classes: rats that en- tered the box during the observation period and rats that did not.

Fisher's exact test highlighted a marked and significant difference (p < .001) between the two age groups: 89% of group Y vs 17% of group A did not enter the box. The nonnumerical character of the results of this test prevented us from using these data directly for the second-level analysis.

EXPERIMENT 3: ACTIVE AVOIDANCE

This test is based on the animal's ability to as- sociate a st imulus (CS) with a negative experience (UCS). The animal must perform active behavior (i.e., run away) in order to avoid punishment. As well as evaluating the animals' associative ability, this test was used to measure the at t i tude of the rats toward generalization of stimuli by evaluating the response when substi tuting the initial CS (light) with another CS (tone).


The shuttlebox used (U. Basile, Italy) consisted of a rectangular cage divided into two identical com- par tments by a partition provided with an opening to allow communication. Footshock was delivered through the stainless steel grid floor.

Trial sessions were programmed on a schedule consisting of a conditioned stimulus (CS: light on) followed 3 s afterward by an unconditioned stimulus (UCS: a 4-s, 0.2-mA electric shock). Ten daily sessions of 10 trials each, separated by l-rain intervals, were performed.

Responses during CS were considered as Avoid- ances; responses during UCS were considered as

200

0 I I I I I I I I

1 2 3 4 5 6 7 8

S e s s i o n s

FIG. 1. Exper iment 6: Complex water maze. Time to reach the exit (latency) in seconds vs session number. ( I ) Young; (Q) aged.

114 GIULIANI ET AL.

TABLE 5 Summary Statistics of Derived Variables (De-

scending Order of Discriminative Power between Groups)

Young Aged

Expt. Name Mean SE Mean SE U

All FYA a 0.90 0.12 - 0.90 0.08 0.0" 7 MWM - 0.76 0.05 0.80 0.22 4.0* 5 TMA 44.53 0.53 35.82 1.15 4.5* 9 CSD 4.21 0.21 6.47 0.35 31.0" 3 ICM 5.37 0.74 1.29 0.23 36.5* 2 PAV 1 5 9 . 9 4 11 .02 6 6 . 5 3 14 .91 39.0* 6 CMT 66.19 7.53 134.08 11 .62 39.0* 8 SCB 0.62 0.19 -0.66 0.18 40.5* 4 SAM 86.71 2.46 75.32 1.56 45.5* 3 AAS 0.54 0.16 -0.51 0.22 47.0* 3 ICR 1.19 0.14 0.49 0.09 49.0* 4 SAR 1.00 0.02 0.92 0.01 62.0* 3 ICT 44.00 4.54 29.53 4.81 72.0* 1 MT5 0.44 0.24 -0.47 0.17 74.0* 3 AAG 0.29 0.22 - 0.22 0.24 77.0* 9 CSB 4.83 0.11 4.48 0.12 82.0* 4 SAT 347.94 6.46 328.24 6.88 88.0 1 ST5 0.30 0.23 - 0.32 0.22 92.0 5 TMI 21.24 1.38 17.35 1.50 94.0 3 AAL 0.34 0.20 -0.16 0.23 96.0 1 MT4 - 0.26 0.27 0.24 0.21 106.0

10 CNF -0.28 0.14 0.31 0.31 108.0 1 ST4 0.07 0.25 - 0.06 0.23 120.0 6 CME 0.01 0.23 - 0.04 0.26 138.0

° First principal component of the general analysis. * Significance level = 95% or more (Mann-Whitney U test).

Escapes; and fa i lu res to avoid shock were considered as Fa i lu res . In addi t ion, the n u m b e r of cross ings be tween the two c o m p a r t m e n t s d u r i n g the i n t e r t r i a l per iod ( In t e r t r i a l Cross ings , IC) and the s u m m a t i o n of escape la tenc ies over the 10 t r i a l s (Latency) were measu red .

Af te r these 10 sessions, the r a t s were subjected to 6 more sessions w i th tone as CS and the s a m e e x p e r i m e n t a l schedule.

Results

The first phase of t he e x p e r i m e n t (CS: l ight) showed a good l e a r n i n g r a t e for bo th g roups wi th no s ignif icant differences for Avoidances , Escapes , Fa i lu res , and L a t e n c y due to age. Both g roups r eached 70% Avoidances by Day 10 of expe r imen t .

PCA h igh l igh ted the p resence of two ma jo r factors: the f irst one (AAL, 59% of exp la ined var i - abi l i ty) un i fy ing Avoidances , Escapes , Fa i lu res , and La tency ; the second one (17% of exp la ined var i - abi l i ty) l inked to IC. For the second-level ana lys i s ,

we chose the first fac tor and the to ta l n u m b e r of IC (ICT), the m e a n va lue of IC over the l as t t h r ee sess ions (ICM), and the ra t io be tween ICM and IC m e a n va lues over the 10 sessions (ICR) (Table 5).

A s ignif icant difference be tween the two groups was ev iden t for ICM, wi th group Y showing a h ig h e r va lue t h a n g roup A. T h r o u g h o u t the sessions no decrease in IC was ev idenced in group Y, whi le aged r a t s showed a dec reas ing t r end (Table 5). The first session of the second e x p e r i m e n t a l phase (CS: tone) ev idenced a m a r k e d reduct ion of Avoidances in the two groups. Th is reduc t ion was s igni f icant ly more p ronounced in group A t h a n in g roup Y (S tuden t t test; p < .01).

PCA poin ted to a fac tor ia l s t r u c t u r e e q u i v a l e n t to the s t r u c t u r e of the f irst phase w i th two dis t inc t factors: one for Avoidances , Escapes , Fa i lu res , and L a t e n c y (AAG) and one for IC. A A G was chosen for s u b s e q u e n t ana ly s i s (Table 5). D u r i n g the suc- cessive t e s t sessions, g roup Y improved i ts performance , r e ach ing 70% Avoidances , whi le g roup A, a l t h o u g h i m p r o v i n g i ts p e r f o r m a n c e as co mp a red w i th the f irst session, r e m a i n e d cons t an t ly a t a level s igni f icant ly lower t h a n t h a t for the o the r group. P C A was i n v a r i a n t wi th respec t to the o the r two ana lyses ; the first fac tor (AAS) was s ingled out for the second-level ana lys i s . In th is e x p e r i m e n t the effect of age was ev iden t only in t e r m s of gener - a l iza t ion abi l i ty (Table 5).

E X P E R I M E N T 4: S W I M M I N G A C T I V I T Y

This t es t was used to e v a l u a t e the r a t s ' s w i m m i n g abi l i ty and t he i r p rogress ive a d a p t a t i o n to wate r . Th is was the first of a ser ies of t es t s h a v i n g w a t e r as a common e lement .


The e x p e r i m e n t a l a p p a r a t u s was a c i rcu la r wh i t e pool (41 cm d i ame te r , 60 cm depth) filled w i th w a t e r a t 21°C. Recordings of the ac t iv i ty were pe r fo rmed us ing two photoelec t r ic cells p laced pe rpen d i cu l a r to each o the r 3 cm below the w a t e r surface. The a n i m a l s were p laced in the cen te r of the pool and the n u m b e r of p h o t o b e a m in t e r rup t ions were m e a - su red over a 5-min period. The tes t was r epea t ed over four consecut ive days.

Results

This t e s t ev idenced a d i f ferent p a t t e r n of ac t iv i ty for the two groups: the first session showed a n iden- t ica l ac t iv i ty for bo th age groups (group Y = 89.9


T A B L E 6 F a c t o r M a t r i x : E n t i r e D a t a S e t

F1 F2 F3 (FYA) (F2YA) (F3YA) F4 F5 F6

MT4 - 0.25 - 0.51" 0.35 0.40 - 0.39 - 0.01 ST4 0.17 - 0.18 - 0.60* 0.04 0.04 - 0.03 MT5 0.47* - 0.11 0.21 0.44 - 0.14 - 0.13 ST5 0.41 - 0.21 - 0.48* 0.16 - 0.18 0.14 AAL 0.41 0.42 0.22 0.60* - 0.28 - 0.04 AAG 0.39 0.43 0.16 0.05 0.37 0.19 AAS 0.62* 0.29 0.34 0.07 - 0.14 0.21 ICT 0.38 0.56* 0.03 0.11 0.02 - 0.28 ICM 0.79* 0.48* - 0.16 0.08 0.03 0.00 ICR 0.74* 0.25 - 0.36 0.04 0.09 0.20 SAT 0.37 - 0.52* 0.46 - 0.09 0.49* - 0.07 SAM 0.66* - 0.54* 0.21 0.24 0.30 0.07 SAR 0.64* - 0.30 - 0.16 0.48* - 0.04 0.19 TMA 0.76* 0.06 0.24 - 0.45* - 0.04 0.10 TMI 0.34 - 0.23 - 0.19 0.16 0.38 - 0.47* CMT - 0.67* 0.15 - 0.45* 0.23 - 0.02 0.14 CME - 0.13 0.29 0.24 0.16 - 0.02 - 0.69* MWM - 0.74* 0.01 0.18 0.38 0.02 0.29 SCB 0.67* - 0.24 0.07 - 0.07 - 0.05 0.13 CSB 0.32 - 0.20 0.24 - 0.40 - 0.67* - 0.10 CSD - 0.76* 0.02 0.13 0.16 0.19 - 0.01 CNF - 0.31 0.33 0.55* 0.02 0.19 0.36

% Explained 29.1 11.1 9.9 7.7 6.5 5.6 variance

* Significance level for correlation coefficient = 99% or more.

_+ 1.6, g roup A = 95.1 _+ 3.3); d u r i n g t h e sub-

s e q u e n t sess ions , g r o u p Y r e m a i n e d c o n s t a n t ( las t s e s s ion = 87.9 _+ 3.1), w h i l e t h e aged r a t s s ign i f - i c a n t l y dec r ea sed t h e i r s w i m m i n g a c t i v i t y ( las t ses- s ion = 74.5 _+ 2.0). A c l u s t e r a n a l y s i s wa s per- f o r m e d u s i n g t he m e a n a c t i v i t y of t h e l a s t two se s s ions (SAM) a n d t h e r a t i o b e t w e e n S A M a n d t h e m e a n a c t i v i t y c o m p u t e d over t h e four sess ions (Ra-

t io = SAR) as v a r i a b l e s . T h i s p r o c e d u r e g e n e r a t e d a t h r e e - c l u s t e r s o l u t i o n w i t h a d i f f e r en t d i s t r i b u t i o n of t he two age g r o u p s a m o n g c l u s t e r s (Tab le 3): t h e

dec r ea sed a c t i v i t y o b s e r v e d i n g r o u p A could be in - t e r p r e t e d as r e v e a l i n g a k i n d of r e s i g n a t i o n (pas-

s iv i ty) . T h i s f e a t u r e could be of i m p o r t a n c e i n ex- p l a i n i n g t h e r e s u l t s of o t h e r s w i m m i n g tes ts .

S A M a n d S A R were s i n g l e d ou t for s u b s e q u e n t a n a l y s e s as w a s t h e s u m of a c t i v i t i e s over t h e four s e s s ions (SAT).

E X P E R I M E N T 5: T W A T E R M A Z E

T h i s t e s t a l lows l e a r n i n g a b i l i t y to be e v a l u a t e d i n a n i m a l s f ac ing a d i s c r i m i n a t i v e s i t u a t i o n i n t h e a b s e n c e of v i s u a l cues. W h e n a good l eve l of l e a r n i n g

is r eached , i t is poss ib le to p e r f o r m a n i n v e r s i o n

t e s t to e v a l u a t e t h e e x t i n c t i o n of t h e a c q u i r e d be- h a v i o r a n d t h e c o n c o m i t a n t l e a r n i n g of t h e oppos i te

one.


T h e T w a t e r m a z e a p p a r a t u s w a s a r e c t a n g u l a r (130 x 54 x 40 cm) pool p a r t i t i o n e d i n t o one c e n t r a l l a n e a n d two l a t e r a l ones . T h e pool w a s f i l led w i t h w a t e r a t 21°C m a d e o p a q u e by t h e a d d i t i o n of m i l k . A s q u a r e p l a t f o r m w a s p o s i t i o n e d 3 cm u n d e r t h e w a t e r su r f ace a t t h e e n d of one of t h e l a t e r a l l anes .

T h e r a t w a s i n i t i a l l y p l aced i n t h e c e n t r a l cor- r idor . I f t h e a n i m a l t u r n e d to t h e s ide c o n t a i n i n g

t he p l a t f o r m , t h e choice w a s c o n s i d e r e d correct ; if, on t h e c o n t r a r y , t h e a n i m a l chose t h e w r o n g way , i t w a s forced to r e a c h t h e p l a t f o r m by t h e exper - i m e n t e r . Six d a i l y t r i a l s a t 1 - m i n i n t e r v a l s cons t i -

t u t e d one sess ion . E i g h t s e s s ions c o n s t i t u t e d t h e

a c q u i s i t i o n phase . T w e n t y - f o u r h o u r s a f t e r t h e l a s t a c q u i s i t i o n ses-

s ion , t he second p h a s e ( i n v e r s i o n tes t ) b e g a n : t h i s p h a s e w a s t he s a m e as t he f i rs t one , except t h a t t h e p l a t f o r m w a s loca ted i n t h e o t h e r l a t e r a l l ane .

116 G I U L I A N I E T A L .

The inversion phase was performed over seven sessions.

In both phases, the number of correct choices was measured.

Results

The young rats scored a higher number of correct choices than aged rats with statistically significant differences start ing from the second session till the end of the acquisition phase. The cluster analysis performed on the total number of correct choices over the eight sessions (TMA) (Table 4) highlighted a differential distribution of the two age groups over the clusters (X2: p < .001).

Surprisingly, the inversion phase indicated no difference between the two age groups, which both reached good levels of performance (TMI, Table 5).

EXPERIMENT 6: COMPLEX WATER MAZE

This was the third experiment of the "swimming" series. It represented a further step toward greater complexity because a complex water maze implies the acquisition of strategies and cognitive maps


The rectangular pool (130 × 54 × 40 cm) used for this test resembled the Giurgea water maze (Giurgea & Mouravieff-LeSuisse, 1972) with more partitions. The maze was filled with 21 cm water at 20°C. The schedule of the test implied one daily session for 8 days.

The parameters measured were the following: (a) time to reach the exit of the maze (180-s

endpoint); (b) scores proportional to the advancement toward

the exit; (c) errors intended as the animal's entering a dead

end or reentering an arm already visited; (d) a dummy variable signaling accomplishment

of the task.

Results

As sessions progressed, the number of young rats accomplishing the task rose by 100% from session 6 to the last one. Only 67% of the aged rats found the exit of the maze. Figure i reports the mean exit times for the two age groups over the sessions. A marked difference is found between the groups with a high statistical significance start ing from session 3. Figure 2 reports the trend of the number of errors that overlapped in the two groups and showed a clear decrease during the sessions.

10

9 T

7 •

6 J"", Y

3 " ,

2 " T "" - - -0 - . . . . .0.

0 1 2 3 4 :.'.'5 6 7 8

S e s s , i o n s

FIG. 2. Expe~_ment 6: Complex water maze. Number of errors v s s e s s io n n u m b e r . ( 1 ) Y o u n g ; (O) ag ed .

PCA performed on the space spanned by the three numerical parameters of the eight sessions pointed to two main components: one collecting scores and times and the other explaining the errors. We sin- gled out the variables CMT (mean values of t imes over sessions 2-8) and CME (factor 2 of PCA) for subsequent analysis.

This test discriminated the two age groups very well in terms of exit times. Nevertheless, the number of errors was identical for the two groups. This apparent discrepancy was linked to the different meaning of the parameter measuring the number of errors for the animals reaching the exit compared with the animals which did not.

Figure 3 shows that the rats which could not reach the exit (high values of time variable) lowered the number of errors over the sessions, indicating that this parameter had the characteristics of a resig- nation index.

While errors are an index of the increasing performance reliability for the animals (predominantly young) reaching the exit within the endpoint, for the animals (predominantly aged) which did not, the number of errors is an inverse index of passivity (helplessness).

This is a very important aspect for the interpretation of the subsequent part of the work: the same index (parameter) can measure very different phenomena in the two age groups. The particular structure of this test made it possible to interpret this different meaning. However, this is not always possible and suggests a caveat for the interpretation of behavioral tests performed on different age groups.

EXPERIMENT 7: MORRIS WATER MAZE

This test allows evaluation of the animals' ability to localize an object they cannot see. The object has a fixed position and the animal must find it with


the aid of environmental visual cues. This is the last test of the water series and has a predominantly cognitive character.


A circular plastic pool (130 cm diameter) was filled to a depth of 40 cm with water (26°C) made opaque by the addition of milk.

A circular white-painted platform (10 cm diameter) was placed 2 cm below the water level. The pool was arbitrari ly subdivided into four compass quadrants (N, S, E, W) with an escape platform placed in the middle of the N - E quadrant. Many extra cues surrounded the maze and were left avail- able for the rats to localize the escape platform.

The rats were placed in the water, facing the wall of the pool at one of the four start ing locations (N, S, E, W) around the pool perimeter and were allowed to swim freely until they found the escape platform. The time (in seconds) they took to reach the platform was recorded (latency). The intertrial interval was 30 s, during which the rat remained on the platform. The animals were subjected to one four-trial session daily for 8 days: each rat had to depart from each of the four start ing locations in a randomly selected sequence. Performances were evaluated in terms of mean exit t imes over the four trials for each session.

with a central window provided with a metal grid. The animal to be tested was placed in the central compartment. The time spent by the animal at the two windows and the number of contacts with the windows were recorded during a 10-min period. A young male rat, a different one for each animal, was then introduced into one compartment, and the tested animal's activity was recorded for the following 10 min. Data were expressed in terms of differences in time and number of contacts between the occupied compartment and the empty one during the first 5 min of the second phase.

Results

In the first phase (adaptation period), there were no significant differences between the activities of the two age groups. During the second phase (so- cialization), there was a marked difference between the two groups, with the young animals showing a higher level of social activity than the aged ones.

PCA applied to this experiment highlighted a first factor explaining 80% of total variabili ty and collecting information on both time and number of contacts. This factorial variable (SCB) was used for the subsequent analyses (Table 5).

EXPERIMENT 9: COLD WATER STRESS

Results

The mean exit t imes showed a significant difference between the two age groups over the eight sessions with the Y group exhibiting much shorter exit t imes than the A group.

PCA was performed for all trials and highlighted a first component explaining a large part of variance (MWM). This component was used to parameterize the test results. This test had the maximum discriminant power with respect to age (Table 5).

EXPERIMENT 8: SOCIAL BEHAVIOR

This was the first of a three-test series having no predominantly cognitive character. The aim of this test was to evaluate the tendency toward social contact between animals and the effect of a novelty, represented by the introduction of another animal in the test environment.


The experimental apparatus consisted of a rectangular cage (90 x 30 x 44 cm) with a stainless steel grid floor. The cage was subdivided into three identical compartments by two t ransparent PVC walls

Cold water stress (CWS) has been demonstrated (Ghirardi, Caprioli, Ramacci, & Angelucci, 1992; Bodnar, Kelly, & Glusman, 1978) to induce an analgesic effect with respect to nociceptive stimuli in the rats.


The experimental apparatus consisted of a circular pool (42 cm diameter, 22 cm high) filled with water at 4°C. The animals were plunged into the water for 2 min. The nociceptive threshold was measured by the tail-flick procedure. The tail-flick test was performed both before (basal latency in seconds) the CWS and 20 min after the stress (poststress latency). Each measure was the mean of three trials at 1-min intervals. Basal latency (CSB) and the difference between basal and poststress latency (CSD) were used for the analysis.

Results

The CSB values showed only a slight difference between the two age groups. The CWS provoked a marked analgesic effect in both groups: this effect was significantly higher in the aged group (Table 5).

118 GIULIANI ET AL.

T A B L E 7

F a c t o r M a t r i x : Y o u n g

F1 (FLY) F2 F3 F4 F5 F6

MT4 - 0.56* 0.22 - 0.37 0.36 - 0.07 0.49 ST4 - 0.42 0.10 0.34 0.15 - 0.18 0.22 MT5 - 0.26 - 0.15 - 0.21 0.65* 0.38 0.35 ST5 - 0.35 0.03 0.38 - 0.27 - 0.57* 0.37 AAL 0.51 0.11 0.25 0.58* 0.13 0.27 AAG 0.42 - 0.12 0.54 - 0.25 0.59* - 0.03 AAS 0.62* 0.33 0.18 0.37 - 0.47 - 0.19 ICT 0.65* - 0.16 0.23 0.07 0.30 0.59 ICM 0.63* - 0.18 0.67* 0.14 - 0.02 0.25 ICR 0.32 - 0.22 0.76* 0.21 - 0.18 - 0.29 SAT - 0.82* 0.23 0.25 - 0.08 0.35 0.06 SAM - 0.81" 0.04 0.47 0.20 0.05 - 0.02 SAR - 0.47 - 0.17 0.53 0.42 - 0.27 - 0.10 TMA 0.21 0.82* 0.22 - 0.20 0.01 0.29 TMI - 0.36 - 0.72* 0.03 0.14 0.46 - 0.02 CMT 0.39 - 0.69* - 0.20 - 0.17 - 0.16 0.30 CME 0.40 - 0.58* - 0.53 - 0.07 - 0.28 0.16 MWM 0.19 0.43 - 0.41 0.24 0.43 - 0.25 SCB - 0.20 0.48 0.32 - 0.65* 0.15 0.26 CSB 0.08 0.72* - 0.42 0.23 - 0.26 0.20 CSD - 0.27 - 0.62* - 0.12 - 0.30 - 0.12 0.26 CNF 0.51 0.46 - 0.06 - 0.16 0.22 0.07

% Explained 22.1 17.9 15.0 10.1 9.4 7.3 variance

* Significance level for correlation coefficient = 98% or more.

E X P E R I M E N T 10: C O N F L I C T B E H A V I O R

T h i s t e s t w a s a p p l i e d to e v a l u a t e e x p e r i m e n t a l l y i n d u c e d a n x i e t y by i m p o s i n g a confl ic t s i t u a t i o n on t h e ra t .


T h e e x p e r i m e n t a l a p p a r a t u s cons i s t ed of a g r id floor cage. A d r i n k i n g b e a k was p o s i t i o n e d i n s i d e t he cage a n d c o n n e c t e d to a r e c o r d i n g sy s t e m. F o r a 2 -week per iod , t h e a n i m a l s we re m a d e t h i r s t y b y g r a d u a l l y d e c r e a s i n g t h e t i m e t h e y w e r e a l l ow e d to d r i n k , d o w n to 30 m i n / d a y .

Af t e r c o m p l e t i o n of t h i s f i r s t p h a s e ( t h i r s t i n g ) , t he a n i m a l s w e r e a d m i n i s t e r e d four d a i l y t e s t sess ions : i n t h e f i rs t t h r e e se s s ions (basal) , t h e y were a l l owed to d r i n k f rom t h e b e a k for 10 m i n ; on t h e f o u r t h day , t he b e a k w a s e lec t r i f ied , t h u s c r e a t i n g a confl ic t s i t u a t i o n b e t w e e n t h i r s t s t i m u l u s a n d e lec t r i c shock.

The p a r a m e t e r s m e a s u r e d were (1) t o t a l n u m b e r of l i cks a n d (2) w a t e r i n t a k e (ml).

Results

T h e a n a l y s i s was b a s e d on t he d i f fe rences i n t h e s e two p a r a m e t e r s b e t w e e n t h e t h i r d a n d t h e f o u r t h

day. B o t h g r o u p s showed a m a r k e d dec rea se i n n u m -

b e r of b o t h l i cks a n d w a t e r i n t a k e , t h e r e b y evi- d e n c i n g t h e g e n e r a t i o n of a confl ic t s i t u a t i o n .

P C A h i g h l i g h t e d a s t r o n g c o r r e l a t i o n b e t w e e n t h e s e two p a r a m e t e r s for b o t h t he d i r ec t a n d t h e p e r c e n t a g e v a l u e s . T h e f i rs t p r i n c i p a l c o m p o n e n t

(CNF) w a s t h e n u s e d to col lect t h e m a j o r p a r t of t h e v a r i a b i l i t y c o n n e c t e d to t h e four m e a s u r e s (di- r ec t a n d p e r c e n t a g e ones). C N F showed no s ign i f -

i c a n t d i f fe rences b e t w e e n t h e two g r o u p s n o r d id t he o r i g i n a l v a r i a b l e s (Tab le 5).

G E N E R A L A N A L Y S I S : P C A O N

S E L E C T E D V A R I A B L E S

T h e v a r i a b l e s u s e d for t h e second- l eve l a n a l y s i s ( c o r r e l a t i o n s t r u c t u r e a m o n g tes ts ) a r e r e p o r t e d i n T a b l e 5, t o g e t h e r w i t h t h e f i r s t c o m p o n e n t of t h e g e n e r a l a n a l y s i s (FYA) a n d P A V w h i c h w a s n o t

u s e d i n t h i s a n a l y s i s b e c a u s e of i t s n o n n u m e r i c a l c h a r a c t e r (see text) . As c a n be s e e n f rom t h e t ab le , v a r i a b l e s a re i n d e c r e a s i n g o rde r of d i s c r i m i n a n t pow e r w i t h r e spec t to a g i n g , w h i c h is m e a s u r e d as t h e v a l u e of M a n n - W h i t n e y ' s U.

T h e f i rs t a n a l y s i s w a s P C A over t h e g loba l d a t a

M U L T I V A R I A T E A N A L Y S I S OF B E H A V I O R A L A G I N G 119

TABLE 8 Factor Matrix: Aged

F1

( F I A ) F 2 F 3 F 4 F 5 F 6

M T 4 0 .37 0 .47 - 0 .07 - 0 .14 0 .01 0 .27

S T 4 - 0 .73* - 0 .25 0 .23 0 .21 0 .39 0 .01

M T 5 0.12 0 .55 0 .59* - 0 .16 - 0 .18 - 0 .33

S T 5 - 0 .49 0 .19 0 .46 - 0 .42 0 .39 - 0 .01

A A L 0 .15 0 .54 0 .42 0 .27 0 .47 0 .32

A A G 0 .30 - 0 .02 0 .64* - 0 .16 - 0 .03 0 .33

A A S 0 .50 0 .24 0 .48 - 0 .33 - 0 .08 0 .25

I C T - 0 .10 - 0 .04 - 0 .13 0 .83* 0 .18 0 .04

I C M - 0.57* 0.21 0 .23 0 .60* - 0 .22 0 .27

ICR - 0.65* 0.21 0 .20 - 0 .03 - 0 .41 0 .29

S A T 0 .74* - 0 .15 - 0 .21 0 .19 - 0 .13 - 0 .10

S A M 0.57* 0 .47 - 0 .34 0 .23 - 0 .17 0 .10

S A R - 0 .26 0 .86* - 0 .16 0 .03 - 0 .04 0 .27

T M A 0 .20 - 0 .59* 0 .28 - 0 .19 - 0 .53 0 .22

T M I - 0 .08 0 .07 - 0 .39 - 0 .42 0 .35 0 .28

C M T - 0 .65* 0 .34 0 .07 0 .04 - 0 .32 - 0 .48

C M E 0 .56* 0 .02 0 .07 0 .27 - 0 .54 0 .04

M W M 0.36 0 .72* 0 .04 0 .05 - 0 .12 - 0 .39

S C B 0 .05 0 .63* - 0 .40 - 0 .23 0 .07 - 0 .19

C S B 0 .02 - 0 .13 - 0 .48 - 0 .32 - 0 .05 0 .30

C S D 0 .50 - 0 .35 0 .43 0 .01 0 .27 - 0 .42

C N F 0.51 - 0.01 0 .23 0 .44 - 0 .35 0 .18

% E x p l a i n e d 20 .0 16.2 11.8 10.3 8.5 7.1

var iance

* Signif icance level for correlat ion coefficient = 9 9 % or m o r e .

field (Y + A groups): this procedure gave rise to the factorial structure depicted in Table 6, which reports the correlation coefficients between variables and factors (factor loadings) and the percentage of explained variability. PCA highlighted a first major factor explaining 29.1% of total variability: this component correlates significantly with all the variables endowed with discriminant power with relation to aging. Figure 4 depicts the strict

10

,~ 6

(3

I" 2

F I G . 3.

T

1 2 3 4 5 6 7 8

S e s s i o n s

Exper iment 6: C o m p l e x w a t e r m a z e . T r e n d s o f the number of errors are reported separate ly for the an imal s which found the exi t ( i ) and those which did n o t ( e ) with in the endpoint.

linear relation (r = - 0 . 9 5 ) between the absolute values of factor loadings on FYA and the U values.

The FYA scores discriminate the two groups with

1 5 0

1 4 0

t 3 0

t 2 0

I t O

tO0

9 0

8 0

70

6 0

50

4 0

30

2 0

IO

0

CM£

sT4

O.t

MT4 CNF

AAL TMI ST5

SAT

CS# AAG ICT MT5

SAR

A A ~ I C R

ICM CSD

I I J I I J M ~ f A I I ~PA 0 . 2 0.3 O. 4 0.5 0 . 6 0 . 7 0 , 8 0 . 9 t

LOADINGS o~ FYA

F I G . 4. Absolute va lues of loadings on F Y A vs U va lues . The M a n n - W h i t n e y U stat i s t ics is an inverse m e a s u r e of dis- cr iminat ion power be tween the two age groups.

120 GIULIANI ET AL.

0 . 8

0.7

0.6

0.5

0.4

0.3

0.2

~, 0 . !

~ -0 .1

~ - 0 . 2

~ - 0 . 3

~1 - 0 . 4

- 0 . 5

- 0 . 6

--0.7

--0.8

--0.9

CSB

CMT

uw, P IA

AAS ICM ICT

CNF AAL

CMK AAG

ICR

MT4

SCB M r 5 CSD

r lW5 ST4

SAR

. S ~ T

- -0.5 - 0 , 3 --0, I O. l 0 .3 0 .5

LOADIWGG oTt F2YA

FIG. 5. Correlation between loadings on F l Y and F2YA. F l Y corresponds to F1 in Table 7 and F2YA is F2 in Table 6: they are the first component of the young group and the second component of the entire data set, respectively.

a 100% efficiency (no overlapping between the two groups): this fact is evidenced by the corresponding U value (0.0). Therefore, PCA singles out the age of the rats as the main source of variation (the most important order parameter): FYA represents a global score of behavioral aging.

The interpretation of the other factors was made possible by the two subsequent analyses, distinct PCA's on the two groups. The PCA performed on the young rats produced the factorial structure depicted in Table 7, while Table 8 reports the factorial structure relative to the aged group. The two factorial structures are very different in terms of pattern of correlations between variables and factors.

When we compare Table 6 with Tables 7 and 8, we obtain an astonishing result: F2 of Table 6 (F2YA) significantly correlates with F1 of Table 7 (FLY) (r = 0.95) (Fig. 5), and F3 of Table 6 (F3YA) is linked with F1 of Table 7 (F1A) (r = 0.91) (Fig. 6). This feature allows us to interpret the second and third factors of the general structure as a kind of "gestalt" of youth and senescence, respectively, in behavioral terms. The computed correlations are based on factor loadings: then they point to a qualitative resemblance between factors in terms of meanings assigned to the different tests (variables).

GENERAL DISCUSSION AND CONCLUSIONS

In this work we have demonstrated the simultaneous existence of a quantitative large-scale effect

of aging in behavioral terms and a qualitative effect in terms of different meanings of tests giving rise to different relations among tests in the two groups of age.

PCA allowed us to discriminate these qualitative differences (factors 2 (F2YA) and 3 (F3YA) of the entire data set) from the quantitative ones measured by the first factor (FYA).

FYA creates a continuous linear-scale ordering of all the experimental parameters in such a way that they correlate, owing to the s imultaneous effect of aging on the measured variables. This means that even the variables which did not significantly discriminate the two age groups are influenced (or- dered) by senescence in that they have a low but not random-valued loading on the aging factor (Fig. 4). The first principal component (FYA) is the direction along which the inertia (variation) of the data cloud is maximal; it is the expression of the order imposed by the external field (aging) to the system. The percentage of total variability explained by FYA is thus the degree of order imposed to the data by the order parameter (aging). On the other hand, the correlation coefficient of each original variable with FYA (factor loading) is indicative of the extent to which that particular variable can be modified by aging.

The order imposed by senescence is superimposed on the two alternative organizations determined by the "meaning" of the variables in the young ( F I Y - F2YA) and aged (F1A-F3YA) animals, respec-

0 .8

0.7

0.6

0.5

0.4

0 . 3

0 . 2

O. f

~ ° ~ -O . t

- 0 . 2

~ - 0 . 3 ..4

~,0.4

- 0 . 5

- 0 . 6

- 0 . 7

- 0 . 0

SCB

TMI ICT

SAR

ST5

ICM

CMT ICR

ST4

-i~.7 I -~.5 I -i~.3 I -i~., I - 0 . 6 - -0 .4 - -0 .2 0

S ~ M ~ CSD AAS

MWM Mr4

AAG

TMA

CSB

SAT

CNF

o:, I 0:3 I o:5 I 0.2 0.4 0.6

L O A D I N G S a r t F 3 Y A

FIG. 6. Correlation between loadings on FIA and F3YA. F1A corresponds to F1 in Table 8 and T3YA is F3 in Table 6: they are the first component of the aged group and the third component of the entire data set, respectively.


tively. These two orderings of the system are generated by the different meanings that the same tests assume with the young and aged rats, respectively, thereby evidencing a qualitative difference between the two age groups which PCA highlights as orthogonal (i.e., unrelated) to the quanti tat ive effect of senescence (FYA).

The simultaneous presence of al ternative orderings in the same system allows us to equate the entire data set to a spin-glass model, the organization of which (in our case, the relations among tests) depends on the observation scale.

These alternative orderings correspond to qualitative and irreducible differences between young and old rats. In fact, the two groups generate two orthogonal components which remain the same in the entire data set in analogy with two immiscible chemical systems.

The spin-glass model constitutes a theoretical frame for the observations of the multiplicity of time and space scalings present in the same behavioral phenomenon (Paulus & Geyer, 1991, 1993). The model allows the effect of drugs or neurobiological manipulations to be interpreted not only in terms of modification of measured variables but also in terms of alteration of their mutual relations (Geyer, Russo, & Masten, 1986; Ljungberg & Enquist, 1987).

Many authors have raised the problem of different interpretations for the same behavioral tests when performed by animals of different ages (Barnes, Na- del, & Honig, 1980; Barnes, 1990). Our results lend quanti tat ive weight to these observations. In many instances, no quanti tat ive differences were pointed out for behavioral parameters between young and aged groups (Rigter, Martinez, & Crabbe, 1980). Nevertheless, the experimenters recognized the different strategies that the two groups used to perform the task. On the other hand, quanti tat ive differences between the age groups sometimes derive from different pat terns of relation with the factors influencing performance (strategies, latent variables such as emotion, motivation, attention, and so on) (Goodrick, 1980; Barnes, 1990) and conse- quently the difference measured derives from a frame which is unfair to the groups. We can easily appreciate this kind of situation by analyzing the results of our sixth experiment (complex water maze), where the same variable (CME) measures two different and incomparable situations for the two groups. In this case, the reason for the different meaning of the same variable was easily identifi- able, but in many situations this is not the case. These differences in meaning of the same behavioral

parameter in rats of different ages are a constitutive and noneliminable feature of behavioral studies.

In conclusion our results point to the existence of two distinct effects of aging on behavior: a quan- t i tat ive one linked to the age-dependent modifications of the scores of individual behavioral tests and a qualitative one consisting in the alteration of the correlation pat tern among tests. This second effect can only be appreciated by means of a mul- t ivariate approach.

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