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An information-processing approach

The second part of this chapter describes in some detail the approach we have used in the assessment of cognitive function in two studies on the functional consequences of iron deficiency (47, 57). This approach differs somewhat from what has been done in other studies of malnutrition and cognition, in that we do explicitly postulate the existence of a continuity in the participation of mental processes that intervene between the onset of a signal (information) and the production of a specific response. Figure 9.1 (see FIG. 9.1. Information-Processing Paradigm (Linear, Serial, Independent Process Model) (58).)(58) is a representation of a simple information-processing model. It is a linear, serial, independent process model. A basic assumption in its use is that there is a sequential ordering of the mental processes involved in carrying the signals from input to output. The model also assumes that these processes have some distinctive characteristics that can be identified through the analysis of the behaviour of an individual in specific problem-solving situations, and that this analysis can lead to the identification of specific cognitive disturbances.

The reason for this approach is our interest in pointing out the locus of cognitive disturbances in children with iron deficiency (59). This interest developed from our reading of the relevant literature which suggests that iron deficiency is more likely to affect the organism's capacity for receiving, rather than for processing, information.

The battery of tests used in previous investigations on malnutrition and cognition generally were built more or less on intuitive grounds by the accumulation of a series of sensitive tests that would reflect performance in different psychological processes. This psychometric approach led to the delineation of particular "profiles of performance." No explicit assumptions were made on the interrelationships among these processes.

In describing the rationale for the attempts to measure information-processing components rather than to obtain a measure of general intelligence, it is important to point out that these two approaches do not yield the same information. This point is illustrated in table 9.1, where we present the correlation coefficients between the

TABLE 9.1. Correlations between Stanford Binet IQ and Discrimination Learning Tasks (Z Scores).


Objects Figures















N = 110 (3- to 6-year-old children from Cambridge, Mass. USA).

Stanford Binet IQ and three discrimination learning tests among 110 preschool children tested in Cambridge, Massachusetts, USA. In the best of circumstances a learning task only explains about five per cent of the variance in the IQ measure.

Specifically, the information-processing paradigm we have chosen for our studies is that of Fisher and Zeaman (60). The most precise description of this theoretical approach has focused on a discrimination learning task. In its most simple form this task calls for the presentation of two three-dimensional objects (i.e., car, ball) mounted on 3 x 3 inch bases. A yellow "happy face" is pasted on the bottom of only one of the bases. The child's task is to discover which stimulus "hides" the happy face underneath it. After each trial the stimuli are rearranged out of the child's view, and the procedure continues until a learning criterion of seven correct responses in a row is met. The reverse problem is then administered-with the previous incorrect simulus now correct-to the same learning criterion.

Figure 9.2 (see FIG. 9.2. Block Diagram of Attention-Retention-Theory (61).)presents the simplified version of the structure of the theory. The attention selector will first lead to a response of a choice of the two stimuli presented (car or ball). The result of this choice will be the first association between the cues of a specific stimulus (which may be position, color, form, etc.) and the rewardoutcome. That is, the cue or cues may be associated with the happy face or not. This association will then be stored within the trial in a tripartite storage memory system. This storage will decay unless there is a continuation of the task and of the associations between attention-selector or response and reward outcome. The stimulus reward information may, however, go into a rehearsal buffer compartment, or the information may pass directly into a long-term storage. The buffer output also goes into long-term store.

In more complicated tests there may be conflicting information in the memory stores. Either of the two stimuli objects may have multiple cues, some of which are remembered as having been associated with reward and some as associated with nonreward. According to the authors, this dilemma is solved by a choice mechanism or decision rule called the Response Generator, which takes the information and converts this to an overt response of selection of one of the two stimulus objects,

An important component of this theory is the distinction made between "processes" and "structural components." The former refers to elements in the theoretical structure that undergo change as the task is learned; this is clearly illustrated by the significance of the cue as the task progresses, and the rehearsal that the subject may make as a function of the cue-reward association that is established. The structural features of the organism reflect fixed capacities, possibly related to fixed components of intelligence; the memory capacity of the organism identifies one of the structural features.

In our own work on the functional consequences of iron deficiency we have used three discrimination-learning and four oddity-learning tasks and a series of memory tests. A description of all these is presented in an annex. In connection with the use of these tests there are two theoretical and methodological issues that concern us here. The first deals with the extent to which these tests, derived from the information-processing paradigm I have presented, tap the same psychological constructs in different populations. This paradigm may be conceptually attractive, but it may be practically meaningless for field studies if these tests do not assess the same cognitive processes when applied to different groups of children. The second issue is how to analyse the results from the tests according to the different sequential steps proposed by the paradigm in order to detect the locus of a disturbance.

In this chapter we will restrict ourselves to the first issue, and the reader is referred to a paper recently completed on the use of these tests (47). A discussion of such an analysis would require the presentation of results, and goes beyond the limits set for the present exercise.

A comparison of the extent to which the tests tap the same constructs in different populations is facilitated by our use of exactly the same battery with two very different samples of children of the same age range. One study was conducted in Cambridge, Massachusetts with an urban group, while the other was carried out in two lowland villages in Guatemala. For our purposes we will restrict this analysis to two types of comparisons that have been suggested as the most robust approaches for cross-cultural comparisons of test constructs (61). One looks at the range of difficulty of the same test in different groups. The other compares factors and factor scores, which may be derived from a factor analysis of all the tests included in the battery, between cultures.

Figures 9.3 (see FIG. 9.3. Discrimination Learning Tasks: Estimate of Difficulty of Tasks for Preschool Children in Two Cultures: United States (urban) and Guatemala (rural).) to (see FIG. 9.4. Oddity Learning Estimate of Degree of Difficulty for Preschool Children in Two Cultures: United States (urban) and Guatemala (rural)) 9.5 (see FIG. 9.5. Short Term Memory Tasks: Estimate of Degree of Difficulty for Preschool Children in Two Cultures: United States (urban) and Guatemala (rural). ) present the degrees of difficulty in the discrimination. oddity, and memory tests. Although the Guatemalan and the Cambridge children have a different level of performance in most tasks, the shapes of the curves of performance as a function of the nature of the tasks themselves is very much alike for both groups. In fact, there are no difference-scores between any two tasks, within the discrimination and the oddity learning sets, that may be statistically different in one cultural group and not in the other. Accordingly, the changes in degrees of difficulty of these tests were the same in both cultures. Time-decay in the Cambridge sample is statistically significant, but this is not the case in Guatemala. Thus, it would appear that in this particular instance the changes in the nature of the responses from one to the other tasks did not follow the same trend in both cultural groups.

Table 9.2 (see TABLE 9 2. Factor Analysis* (with Varimax Rotation) of Scores on Discrimination Learning, Memory and Oddity Learning Tasks for Preschool Children in Cambridge, MA (Urban) and Guatemala (Rural)) presents the data from the factor analysis. For the purposes of this analysis all test scores were transformed into Z scores to facilitate the comparability of the results within and between culture groups. There are two main reasons for this factor analysis. The first and most obvious is to see whether the factors thus formed in both cultures include the same test items. This obviously is to be expected, given that the scores entered in the analysis correspond to each of the tasks within each of the three sets of tests: discrimination, oddity, and memory. An issue here, however, is whether there is any cross-over of particular items from one set to another. For instance, it would be conceptually significant to find that some of the discrimination learning items are included in the oddity learning set in one culture and not in the other. A second reason for this analysis is to compare the eigen values and amount of variance explained by each factor between cultural groups. If these comparisons showed no between-group differences, then we may tentatively conclude that the psychological constructs underlying each set tend to have similar roles within the information processing sequence.

TABLE 9 2. Factor Analysis* (with Varimax Rotation) of Scores on Discrimination Learning, Memory and Oddity Learning Tasks for Preschool Children in Cambridge, MA (Urban) and Guatemala (Rural)


Factor 1

Factor 2

Factor 3

Factor 4

  Cambridge Guatemala Cambridge Guatemala Cambridge Guatemala Cambridge Guatemala
Object Initial     0.742         0.456
Reversal     0.624 0.548        
Picture Initial     0.486   0.378     0.604
Reversal     0.683 0.779       0.475
Color-Form Initial       0.312 0.964      
Reversal       0.602 0.430      
Memory 0         0.598 0.566    
Memory 4         0.528 0.633    
Memory 8         0.661 0.493    
Non-Repeated 0.843              
Repeated 1 0.889 0.566            
Repeated 2 0.876 0 872            
Repeated 3 0.849 0.702            
Eigen Values 3.84 2.55 1.75 1 52 1 19 0.98 0 77 0.52
(PCT of Variance) (51.1 %) (45.7%) (230%) (27.2%) (157%) (17.7%) (10.1 %) (94%)

* Only those factor scores > 0.30 are included

A finding that needs to be pointed out first is that the oddity (factor 1) and the memory learning (factor 3 in Guatemala, factor 4 in Cambridge) tasks have each formed a separate factor in both groups. Moreover, the discrimination learning tasks have also been broken into two factors in Guatemala and in Cambridge.

The composition of the oddity learning factor is almost identical in both cultures, except that in Guatemala one task (oddity non-repeated) was excluded from the factor. Moreover, in both instances this factor has the highest eigen value, and accounts for the largest amount of variance (Cambridge = 51.1 per cent; Guatemala = 45.7 per cent) for the whole battery of tests. These data added to the curves on the degrees of difficulty tell us, then, that we are on safe ground in assuming that this particular set of tasks is tapping the same constructs and is dominant in both cultures.

In connection with the memory tests, there are some differences between cultures worth noting, although overall the composition of the memory factor is identical in both places. In Guatemala the memory items formed the third factor; in Cambridge they make the fourth and last factor. This difference explains in part why there are some slight differences in the degree of variances accounted for by this memory construct in one and the other place. In Guatemala memory accounts for 17.7 per cent of the total variance, while in Cambridge it only explains 10.1 per cent of the variance. Thus, memory seems to have a slightly more central cognitive function role in Guatemala than it does in Cambridge. Although this is an important finding in connection with the overall functioning of the children, in no way does it suggest that these tests are not tapping the same constructs in both cultures.

The discrimination learning tasks show differences and similarities in factor formation between cultures. The object and the picture learning tasks have tended to cluster together in both groups of children (except for object reversal in Guatemala). However, whereas in Cambridge the factor that includes these tasks accounts for 23.0 per cent of the total variance, in Guatemala it only accounts for 9.4 per cent of the variance. Thus, although the constructs behind these tasks may be the same in both groups, they seem to have very different roles in their relationships to other cognitive processes.

Moreover, in Guatemala, factor 2 is comprised of four tasks, three of which are the reversal-shift component of these tasks. However, in Cambridge we do not see this pattern or arrangement. In fact, Factor 3 in Cambridge, which may be taken as the counterpart of Factor 2 in Guatemala, only includes one of the reversal shift (colour-form) components.

In summary, the factor analysis shows that in both cultures the memory, the oddity learning, and part of the discrimination learning tasks seem to tap the same constructs. However, in Guatemala there is one additional construct involved in the solution of the reversal learning tasks that is not apparent in the Cambridge sample. This will be a question that we must deal with in the interpretation of our data.

Annex: Behavioural test battery

The behavioural test battery will consist of the following tests, divided into two consecutive days of approximately equal length.


Discrimination Learning Tasks

Two-choice discrimination learning with three dimensional "junk" objects: the child is presented two three-dimensional objects (toy car, toy whistle, for example) mounted on 3 x 3 inch wooden bases. A yellow happy face is pasted on the bottom of only one of the bases. The child's task is to discover which stimulus "hides" the happy face underneath it. After each trial the stimuli are rearranged (for possible left-right position alternation) out of the child's view and the procedure continues until a criterion of seven correct in a row is met. The reverse problem (the previous incorrect stimulus is now correct) is then administered to the same criterion.

Two-choice discrimination learning with two dimensional "junk" pictures: the procedure is identical to the three dimensional problem except that the two stimuli are two-dimensional pictures cut from children's books, pasted on black posterboard with a happy face attached to the back of the appropriate stimulus.

Two-choice discrimination learning with two-dimensional color-form pictures: identical to the two-dimensional problem above except that the two stimuli are two-dimensional colored forms. The same two colors and two forms are randomly paired on each trial (Trial 1: blue X. red 0; Trial 2: red X, blue 0) but only the form (always X or always 0) is consistently correct.

These three tasks will be analysed for differences in the number of trials needed to reach a learning criterion. Two parameters, direction of attention (Po) and learning rate (°a) determine performance. Po determined the length of the initial chance performance before learning begins. H determines the speed of learning (slope of the learning curve), once attention has been focused. Po is a control process, tt is a structural feature. Since forward learning curves have grouping errors which mask the actual performance of individual subjects. backward learning curves will be constructed to differentitate variations in these two parameters.


Memory Test

A large number of two-choice visual discrimination learning problems consisting of " junk" pictures are presented concurrently for a total of four trials each. Trials l and 2 are massed (consecutive). Trials 2 and 3 have either 0, 4, or 8 interpolated items separating them. Trial 4 occurs on the next day, 24 hours later. A happy face is pasted on the back of the correct stimulus.

This task measures a variety of aspects of short-term memory, short-term buffer (a rehearsal memory) and long-term memory as a function of the particular trial and spacing condition. Performance on trials 2, 3 and 4 following differential spacing intervals will be compared. Trials on massed presentations (consecutive trials on the same problem) measure attention and the amount of information entering the memory system. Trial 3 performance following 4 and 8 interpolated items measures short-term memory buffer capacity, and rehearsal strategies. Trial 4 measures long-term memory and comparison among trial 4 performance following different trial 2-trial 3 spacing intervals indicates differential strategies in memory rehearsal.

The specific parameters that will be used for computer simulation if between-group differences occur are outlined below.

Attention (Po) - dimensional attention on massed presentations (control process)
Buffer size (beta) - capacity of the rehearsal buffer (structural feature of memory)
Buffer replacement (alpha) - rehearsal strategy employed when the short term memory system is overloaded (control process)
Learning (Oa) - rate of acquisition of information into a long term memory store. The rate averaged over all spacing conditions is governed by a control process.


Recognition Memory

"Junk" pictures are presented one at a time and the child is instructed to look at the pictures. Following presentation of the entire set, these pictures are paired with new pictures and the child must identify "which one did I just show you?" Sets of 8, 16, and 32 stimuli (linear increments on a log scale) are presented to determine whether or not there are differences in the amount of information that can be tagged as familiar in the long-term memory store (structural feature). The number of correct trials in each set is the outcome measure.


Short-term Memory Time Decay

Two identical stimuli are presented, one with and one without a happy face. At the beginning of each trial the child is shown the position of the correct stimulus and then both stimuli are hidden from the child's view. The barrier is removed either 0, 5, or 10 seconds following the initial presentation, and the child must turn over the correct stimulus to reveal the "happy face". Input into short-term memory (Po) and decay rate (6) in memory are investigated as a function of performance following immediate (Po) and delayed (ts) response. Po is a control process, (ts) a structural feature.


Continuous Performance Test

Six distinct pictures are presented one at a time on a 2tt x 2tt inch screen in a darkened room at the rate of 1 every 1.35 seconds for a total of 8 minutes. One of the six stimuli is designated as the target, and each time the target appears the child must press a hand-held button. Correct responses, errors of omission and commission are recorded electronically over time. This task measures the child's ability to sustain a high degree of attention over a long period of time (control process) when other cognitive processing demands are low.


Oddity Learning

Three stimuli ("junk" pictures), two of which are identical, are presented simultaneously on a 7 x 18 inch black posterboard. The child must point to the correct picture, the one different (oddity) from the other two. The only instructions given are "to find the winner." In the first series of problems, new stimuli are used on every trial. In the remaining series, the same stimuli are repeated every trial in an AAB ABB manner. In this task, the specific make-up of a stimulus does not determine its correctness, but rather its relationship to other stimuli in the array. Although this complex form of learning is beyond the scope of the original theory, AttentionRetention Theory has been extended (Greenfield, 1 975) to cover this domain. Attention to relational dimensions (Po [rel]), frequency preference (A Pr Irel]). and learning rate lO [rel]) will be investigated.


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