SHORT TERM MEMORY, FLUID INTELLIGENCE AND BRAIN NERVE SPEED IN A POPULATION WITH VARIABLE CULTURAL EXPOSURE

RUNNING TITLE: Ache cognition

KEYWORDS: short-term memory, fluid intelligence, central nerve conduction velocity, acculturation, Ache

John Wagner* Robert Walker (robwal@unm.edu)

Kim Hill (kimhill2@unm.edu) Draft #2 for Human Nature

22 pages of text 3 tables 5 figures

DO NOT CITE IN ANY CONTEXT WITHOUT PERMISSION OF THE AUTHORS

*Address all correspondence to: J. Wagner, Department of Anthropology, University of New Mexico. Albuquerque, New

Mexico 87131. phone: 505 277-1628 email: wagner@unm.edu webpage: http://www.unm.edu/~wagner

2

ABSTRACT

Objectively assessing cognitive parameters among non-Western populations would

provide an important tool for human ecology researchers. However, applying western-

derived psychometrics in traditional societies is complicated by variable exposure to

testing materials and tasks, which affects performance. To explore these issues we

collected three types of cognitive measures among the Aché (ah-CHAY), a forager-

farming population of eastern Paraguay. Raven's Colored Progressive Matrices (CPM),

forward spatial span (SS), and visual evoked potentials (VEP) provide measures of fluid

intelligence (Gf), short-term memory (STM) and visual system integrity, respectively.

VEP reflects the latency between a visual stimulus and processing in the occipital cortex;

dividing head length by this latency provides an estimate of nerve speed in the brain, or

central nerve conduction velocity (CNCV). After controlling for age, correlations were

found between STM and Gf, and between Gf and CNCV. These findings are consistent

with an emerging picture of the organization of mental abilities and are notable given the

unique nature of the sample. Further, age-specific (cross-sectional) trends in

psychometric scores show rapid decline over adulthood in comparison to westernized

populations. We interpret this pattern in light of variable cultural exposure and changing

health conditions since the Aché made first contact and settlement in the mid-1970s. A

potential method for evaluating the cross-cultural validity of psychometrics is described.

3

INTRODUCTION

There exists limited knowledge of cognition among traditional and small-scale

populations. Given the broad range and variability of factors that intimately interact with

cognitive function across the lifespan it is desirable to develop objective measurements

that can be applied across cultures. Reliable instruments for assessing cognition could

provide answers to a number of evolutionary questions that are best studied in non-

industrial or traditional populations, which are frequently isolated and experience unique

environmental conditions.

Efforts to develop "culture-free" intelligence tests have been made for nearly a

century (Jensen 1980) and interest in cross-cultural comparisons has increased in recent

years with attention paid to standardizing certain biases (Van de Vijver and Hambleton

1996). However, applying standard psychometrics in traditional populations is more

difficult because the euro-centric biases of these tests (Nessier et al. 1996) can become

acute in societies with limited exposure to test taking materials and tasks. A lack of

relevancy clearly contributes to poor performance on some western-derived psychometric

tasks among traditional populations (e.g., Ardilo and Moreno 2001).

A frequent component of cultural exposure is schooling and its effect on test taking

performance. Schooling is a potent variable for predicting performance on psychometric

tasks because it contributes to systematic problem-solving, abstract thinking,

categorization, sustained attention to material of little intrinsic interest, and repeated

manipulation of basic symbols and operations (Nessier et al. 1996). Studies support that

even a minimal amount of schooling is an extremely important source of variance on IQ

tests and the development of intelligence (see Ceci 1991 for review).

4

A further complication arises where previously isolated populations come into contact

with outside influences such that cohorts emerge between an older generation with less

exposure to (in this case) Western culture and a more acculturated younger generation.

However, these types of situations also provide an opportunity to investigate the

influence of cultural exposure on particular psychometrics and other cognitive issues of

interest.

Here we present the results from three types of tests that provide distinct but related

information concerning cognitive ontogeny and performance collected among the Aché,

an indigenous South American population who experienced first contact and settlement

in the mid-1970s. Before describing the population and tests in detail, we briefly review

intelligence and cognitive concepts where applicable.

Intelligence and Cognitive Correlates

The concept of general intellectual ability or g arose from early findings that an

individual�s performance at one test tended to correlate with their performance on other

tests (Spearman 1904). This general ability or factor was later refined into two distinct

abilities: fluid and crystallized intelligence (Horn and Cattell 1966). Fluid intelligence

(Gf) is characterized as a general problem solving or reasoning ability that has the �fluid�

quality of being applied in virtually any situation. Gf handles abstract thought, is not

dependent on prior knowledge and tends to decrease with age. In contrast, crystallized

intelligence (Gc) consists of specific, acquired and stored knowledge such as vocabulary

and tends to increase over the lifetime. It is generally held that Gf is more amenable to

cross-cultural analysis because it is involved in dealing with novel situations that require

learning and adaptation; whereas Gc is language or culture-specific. The general factor

5

(g) and its subcomponents Gf and Gc sit at the top of most hierarchical models of

intelligence with various arrays of subsystems that support these abilities (e.g., Carroll

1993).

In cognitive psychology, the construct of working memory capacity (WMC) is held to

be closely related if not isomorphic to the psychometrician�s Gf given that performance

on measures of WMC correlate highly with a variety of Gf tasks (Engle 2002; Kyllolen

1996). There is also good evidence that the cognitive or brain systems that underpin Gf

and WMC are mediated in the prefrontal cortex (PFC) and more specifically in the

dorsolateral PFC (Kane and Engle 2002). An influential model of working memory

consists of a three-component system with an attentional controller, or central executive,

aided by two subsystems that handle auditory and visuospatial information, respectively

(Baddeley and Hitch 1974). The phonological loop and visuospatial sketchpad, as they

have come to be known, are short-term memory stores that probably use a mechanism for

reading into and refreshing information in the store. These slave systems subserve the

central executive, which regulate from their active memory portions what is elevated to

active or �working� thought processes. A fourth component, the episodic buffer, was later

proposed to account for empirical findings concerning the integration of short and long-

term memory processes by the central executive (Baddeley 2000).

The WMC system is responsible for the maintenance of information in a highly active

and easily accessible state with the central executive responsible for allocating attentional

resources such as focusing attention, preventing distraction, or dividing attention during

multi-tasking � abilities that lie at the core of fluid intelligence (Kane and Engle 2002). A

conceptual separation between the central executive and short-term memory (STM)

6

processes of WMC has now been demonstrated (Cowan 1995). Strong correlations arise

between STM and WMC due their being closely intertwined and initially led to the

conclusion that both were involved with Gf. However, latent variable analyses have since

revealed that it is primarily the central executive that accounts for the correlation between

WMC tasks and measures of Gf (Conway et al. 2002; Engle et al. 1999) with

performance on STM tasks tending to be domain-specific and WMC being more domain-

general (Kane et al. 2004). However, few tasks can actually be considered ��pure��

measures of STM or WMC and some amount of overlap is expected on any given task

whether it is considered simple or complex (Conway et al. 2002).

Another approach to cognitive assessment investigates biological substrates that

underpin mental abilities such as measuring brain volume or using brain-imaging

techniques to measure the rate of cortical glucose uptake during cognitive tasks (Haier et

al. 1988). Processing speed, or the ability to execute basic cognitive processes, has been

suggested as a primary factor underlying cognitive performance (Jensen 1998) typically

measured through reaction time or inspection time tasks. Overall, a consistent but

moderate correlation is found between speed tasks and measures of Gf with variability in

performance at repeated trials�probably reflecting the integrity and fidelity of signal

processing�also likely involved (see Geary 2005 for review). However, performing

processing speed tasks also requires attentional focus such that performance will be a

product of basic processing mechanisms and how much the task draws upon the central

executive (Conway et al. 2002).

Conduction velocity in brain nerve axons is a likely component of overall processing

speed and has been suggested as a factor underpinning g (Reed 1984; Jensen 1998). Only

7

two studies have investigated the relationship between nerve speed in the visual system

(hereafter central nerve conduction velocity or CNCV) and intelligence measures with

both finding significant correlations (Reed and Jensen 1992; Reed et al. 2004a). To

compute CNCV, head length is divided by the latency of a visual evoked potential

(VEP)�a standard clinical tool for assessing the integrity of the visual system. We

describe VEP in some detail as this measure may be unfamiliar for some and is key to

understanding the CNCV measure.

Pattern-reversal VEP is the most common method for collecting VEP and uses a

reversing black-white, checkerboard pattern as the stimulus. Each stimulus reversal elicits

a corresponding response in the occipital cortex occurring approximately 100ms after the

stimulus, Electrodes placed over the occipital cortex record the electrical activity of the

processing response which is observable as a characteristic peak waveform, or P100.

Pattern-reversal VEP only requires subjects to focus their gaze on the surface of display

screen and is appropriate for all subjects except the very young or disabled where a

flashing light is preferred (flash VEP). The latency of P100 follows a U-shaped curve

over the lifespan with early rapid decreases in P100 latency (faster processing) associated

with myelination of the optic nerve, followed by gradual maturation through early

adulthood coincident with continual maturation of the visual cortex (Brecelj 2003). P100

increases slightly across adulthood (slower processing) and is reflective of changes in

optic nerve conduction velocity (Fotiou et al. 2003) although unspecific decline in retinal

structures and luminance response may also be involved (Fiorentini et al. 1996). Decay in

visual cortex structure is probably not involved because, in contrast to some other brain

8

regions, the visual cortex shows minimal if any degradation with increasing age (Raz et

al. 1997).

Optic nerve conduction velocity depends on the fiber diameter of the axons, the

number and form of ion channels in the axon membrane, and the quality (thickness and

stability) of the myelin sheath generated by the oligodendrocytes (Kandel et al. 1991).

However, estimates of this velocity using VEP must consider test parameters known to

affect P100 latency � particularly the size of individual checks in the checkerboard

pattern and luminance. Check size has been shown to reliably affect P100 latency with

larger checks (fewer checks within the same viewing area) being associated with shorter

P100 latencies relative to smaller checks (Moskowitz and Sokol 1983). Luminance also

affects P100 with brighter screen displays associated with shorter latencies (Tobimatsu et

al. 1993). The general pattern of visual ontogeny is that the ability to discriminate larger

checks presented on bright screens is achieved earlier than the ability to discriminate

small check sizes presented on dimly lit screens. P100 latency is an indicator of visual

system ontogeny and P100 values will appear more adult-like at younger ages if the

checks are larger and brighter. Conversely, the use of smaller and dimmer checks will

produce a picture of visual ontogeny characterized by an extended period of continual

development before reaching adult levels. A similar pattern obtains for aging adulthood

where senescence is more prominent for checks that are small and dim versus large and

bright (Mitchell et al. 1987; Porciatti et al. 1992).

In addition to the VEP parameters just discussed, there are a number of anatomical

and conceptual issues involved in how to interpret CNCV (head length/ P100) � either as

a reliable indicator of nerve conduction velocity or in its functional relation to Gf. These

9

issues are beyond the scope of this paper but we refer interested readers to relevant

discussions (Burns 1999 and related; Jensen 1999; Reed and Jensen 1992; Reed et al.

2004b) and agree with Jensen that, given the few studies and positive correlations

between CNCV and Gf reported thus far, replication is in order (Jensen 1999).

Here we evaluate two psychometrics believed to be minimally influenced by cultural

exposure: forward spatial span (SS) and Raven�s Colored Progressive Matrices (CPM)

(Raven et al. 1998). Our version of SS test is very similar to the Corsi Blocks tapping

task and is considered an excellent measure of short-term memory (STM). Raven�s

Progressive Matrices is the most widely used psychometric in the world and is widely

considered to be the most reliable indicator of Gf.

Short-latency potentials like P100 are only indicative of early sensory processing and

should not be confused with later evoked potentials that occur with subsequent or higher

cortical processing steps in response to a cognitive task, which have been variously but

not consistently correlated to psychometric intelligence (e.g., Caryl 1994). No prior

significant correlations between P100 and Gf have been reported save for the previously

mentioned studies that use P100 to calculate CNCV. We also use P100 values from

pattern-reversal VEP to compute CNCV and test for age-controlled correlations among

all variables.

MATERIALS AND METHODS

Study group

The Northern Ache were nomadic hunter-gatherers without horticulture before first

peaceful contact in the 1970s (Hill and Hurtado 1996; Clastres 1998). There is no

evidence of friendly relations between the Aché and any other ethnic population in

10

Paraguay until the 1960s and 1970s, when various groups made contact with outsiders.

The Aché currently live in five major mission/ reservation settlements with a total

population of about 1,000 individuals. Data for this study were collected in the

communities of Arroyo Bandera and Kuetuvy, cultural groups that lived in isolation until

the mid to late 1970s (Hill and Hurtado 1996). The Aché now have a mixed economy

with some communities heavily dependent on cultigens, farm animals, and wage labor,

while others are still partially dependent on hunting and gathering in the nearby

Mbaracayu Natural Reserve. Game animals comprise up to 80% of the Ache diet in the

forest (Kaplan et al. 2000) but the settlement diet is based on a staple of sweet manioc

planted in slash-and-burn fields.

The Aché continue to suffer considerable mortality and morbidity as a result of

disease exposure and particularly tuberculosis (Hurtado et al. 2003). Health conditions

have likely improved after settlement�evidenced by improved growth patterns in the

younger generation�with increased access to medicine and doctors.

Because of the acculturation process, the sample includes an older generation who

lived most of their lives as hunter-gatherers and a younger generation who have grown up

on reservation settlements. Following contact, the Aché have undertaken formal

classroom instruction with school days lasting about 3-4 hours and punctuated by long

seasonal vacations. All individuals under age 25 have attended some school but no one

over age 40 has ever been to school. A genealogical approach with interview-generated

age ranks was used to age all individuals in the population born before fieldwork

commenced in the late 1970s (see Hill and Hurtado 1996), while ages for individuals

born during the fieldwork period are exact to the day.

11

Visual evoked potentials (VEP) and Central Nerve Conduction Velocity (CNCV)

Most people residing in the two communities were recruited to participate in

February-March 2005 by J.W. and R.W. Results from 161 individuals are included in

these analyses (86 males, age range 5-75, mean = 28.71, std. = 18.62; 75 females, age

range 3-73, mean = 26.76, std. = 17.477). Participants had basic anthropometrics

collected including head length measured with calipers to the nearest millimeter from the

nasion to the inion. Subjects were then fitted with an electrode cap (Electro-Cap

International, Eaton, OH) made of an elastic spandex-type material with pure tin recessed

electrodes attached to the fabric and arrayed in the international 10-20 system. Recessed

electrodes place a conductive layer between the scalp and the metal conductor and have

the advantage of reducing movement artifacts (Cooper et al. 1980). Electrodes were filled

with conductive gel using a blunted needle syringe at locations F3, F4, C3, C4, P3, P4,

O1, O2, T4, T5, FZ with an average reference and a ground electrode positioned slightly

below FZ. Impedances were always held below 10 kilo-ohms and typically below 5 kilo-

ohms. Following collection of resting electroencephalography (EEG) pattern and flash

VEP were collected. However, for our purposes here we only report the P100 latency of

the pattern-reversal VEP to conform to prior studies that calculate CNCV. Of the various

measurable components of VEP, P100 is the most informative due to its stability and low

variability (Chiappa 1990).

Electrophysiological signals were amplified with Neuron-spectrum-3 and analyzed

with software Version 1.4.5.28 (Neurosoft Corporation, Ivanovo, Russia). Bandwidth

was set from 0.5 to 35 Hz with a quantization frequency of 200 Hz. EEG signals for the

VEP test were collected using the registration montage described above. The software

12

allows for post-test reconfiguration of the montage such that a VEP montage was created

with active electrodes at O1 (left occipital) and O2 (right occipital) with a reference

electrode at Fz (frontal sagittal) to better isolate occipital cortex recordings (Chiappa

1990). The pattern-reversal checkerboard was presented on a 15-inch flat-screen monitor

(LiquidVideo E15LCD1). Viewing distance was 1 m and luminance remained constant at

30 cd/m2. Field size was 18° x 13.5° with individual checks subtending an arc of 60�.

Participants were directed to focus on a red dot at the center of the checkerboard pattern,

which reversed at a rate of 1 Hz (two reversals per second) for 100 reversals. Trials were

run in duplicate and P100 was taken as the average of O1 and O2 for both trials although

these values rarely differed by more than a few milliseconds. The analysis epoch was 400

ms.

Data were inspected offline and artifacts from eye blinks, which were clearly visible

as muscle artifacts in the F3 and F4 electrodes, were excluded from the analyses as were

any other obvious signs of major electrical interference. A mean of about 80 pattern

reversals were used for averaging. It was discovered that even removing over half of the

trials had little effect on the VEP waveform and P100 latency such that we are confident

that the P100 values are robust. Nine subjects were removed from the analyses due to

uncertainty in identifying P100 waveforms. For example, one older subject (75) had

obviously occluded vision and no discernable P100 peak. Two others had obvious

indications of mental or physical disability. For the remainder of subjects, VEP

waveforms were identified for the characteristic P100 peak and marked to the nearest

millisecond as shown in Figure 1.

13

Figure 1. Representative VEP waveforms recorded from left and right occipital (O1 and O2) and referenced to Fz. By moving the line cursor to the apex of the major peak (P100) latency is recorded to the nearest millisecond. The earlier peak (N75) occurs about 75ms before the P100. X-axis is measured in milliseconds and vertical axis in microvolts.

Psychometrics: Raven's Colored Progressive Matrices and Forward Spatial Span

All testing sessions began with casual conversation and joking for several minutes.

Participants understood that they were being tested for mental ability and were typically a

bit nervous and competitive. The Raven's Colored Progressive Matrices (CPM) were

administered by K.H. alone with a subject in a small room. CPM consists of a set of 36

schematic colored figures in which one is asked to find a rule connecting a set of figures

and to complete the set according to the rule. Each figure has a piece missing and

respondents are prompted to choose one of six choices below each figure to complete the

pattern (Raven et al 1998). It was clearly explained by Hill, who has over 30 years

experience working with this populations and speaks the native language fluently, that

the subject should look at the pattern and figure out which piece fits into the missing

space correctly. The first two items on the test are extremely easy such that if a subject

missed these items it was assumed they did not understand the task correctly. If there

were errors on either of these two items, the above procedure was repeated until the

10uV

14

subjects picked answered correctly. Respondents were prodded by asking such questions

as, �do you think that piece really fits the pattern? Look, can you see how it is different

and doesn�t make the pattern look right? Pick another one that fits the pattern.,� and so

on. The patterns and rules become increasingly complex throughout the 36-item test and

no time limit was given. Prepubescent subjects � or younger than about 12 years of age �

were not included.

Short-term memory (STM) was assessed with a simple forward spatial span (SS) task,

which asks participants to replicate, following the experimenter, an increasingly long

sequence of spatial locations. Locations were 9 circles (4cm diameter) drawn randomly

on a cardboard plate (30cm diameter). Figure 2 provides an approximate pictorial

representation of the task. A semi-random (non-consecutive) sequence was committed to

memory by J.W. who began the test by pointing at the first circle and then prompted the

participant to mimic his motion. J.W. then repeated pointing to the first location and then

added another location and prompted the subject to again mimic this motion. Subjects

typically caught on very fast as to what was expected both very young and old. It was

assumed that any subject who could not replicate the first 3 locations did not understand

the task and instructions were repeated until it was clear they comprehended the task. The

spatial sequence was then lengthened by one location per trial until the subject failed to

correctly repeat a sequence. At this point, the same sequence was repeated and if subjects

were able to correctly repeat the sequence on this attempt the trial would continue with

another location added. However, if they incorrectly repeated the sequence the second

time their score was recorded as the last number of correctly repeated spatial locations.

15

Figure 2. The forward Spatial Span (SS) task. The experimenter points to the first location (1) and prompts the subject to mimic this motion before again pointing to the first location followed by a second location (2). The sequence is lengthened according to this fashion one location per trial until the participant fails to mimic two consecutive sequences.

Analytical methods and strategy

We rely on non-parametric curve fitting (i.e., least ordinary weighted sum of squares

or LOWESS) plots of performance by age to display subtle changes with age that may

not be captured in a parametric model. Individual scores that control for age are taken as

the residual off of the LOWESS fit for that particular age. We present data together and

by sex given evidence for sex differences in P100 latency and CNCV (Reed et al. 2004b)

that arises from anatomical size differences and hormonal influences (Celesia et al.

1987). Sex differences in SS and CPM are believed to be minimal (Court 1983; Hester et

al. 2004) with a slight male advantage sometimes reported (Lynn and Irwing 2004). We

also compare and contrast trends in psychometrics from other populations across

adulthood ages because this age range encompasses the potential acculturation effect on

psychometric performance previously mentioned. Given previous findings of significant

correlations between short-term memory tasks and Gf, and between Gf and CNCV, one-

tailed significance tests are justified.

16

RESULTS

Descriptive statistics for the sample are provided in Table 1. P100 and head length,

and hence CNCV, all share the same age ranges, means and standard deviations. The

mean age of respondents for the SS task is lower than for CPM because subjects under

the age of 12 were not administered the CPM.

Table 1. Descriptive statistics of the sample and tests. Significance indicators in the left mean column test for sex differences (Independent samples t-test, 2-tailed), * p < 0.05, ** p < 0.01

Test Age N Min Max Mean S.D Range (yr) Mean S.D. P100 (ms) 161 99 149 116.4 7.18 3-75 28.2 17.72

Male 86 108 142 117.5 7.51 5-75 29.0 18.02Female 75 99 149 115.0* 6.57 3-73 27.3 17.44

Head Length (mm) 161 152 199 177.8 7.57 � � � Male 86 159 199 180.1 7.50 � � � Female 75 152 191 175.1** 6.74 � � �

CNCV (m/s) 161 1.17 1.84 1.533 0.1110 � � � Male 86 1.18 1.84 1.538 0.1145 � � � Female 75 1.17 1.80 1.527 n.s. 0.1072 � � �

Spatial Span 164 4 15 8.0 2.24 5-75 28.0 17.87Male 92 4 15 8.1 2.46 5-75 28.9 18.58Female 72 4 14 7.9 n.s. 1.94 6-60 26.7 16.95

Raven's CPM 129 2 32 16.0 6.86 12-70 35.5 16.11Male 76 3 32 16.3 7.05 12-70 38.6 16.03Female 53 2 29 15.5 n.s. 6.62 13-66 31.1 15.28

Visual Evoked Potentials (VEP) and Central Nerve Conduction Velocity (CNCV)

Figure 2 indicates that P100 latency and CNCV show developmental changes up until

late adolescence or early adulthood (~18 years of age) and then senesce slightly across

middle adulthood before rapidly senescing after age 60. While the over 60 years old

17

sample is very small (n=4), the marked senescence pattern is a likely accurate for several

reasons. First, the few subjects in this age range with identifiable P100 values exhibited

slow latencies. Second, a 75-year old subject was excluded due to an undecipherable

P100 peak�attributable to obvious visual deterioration. And lastly, the number of

individuals over age 60 is limited, suggesting that strong senescence is operating in this

population at older adult ages.

(a) (b) Figure 3. a) P100 (in ms) across the lifespan for males and females. Note that the Y-axis is inverted to give a more intuitive feel for ontogenetic patterns. b) Central Nerve Conduction Velocity (CNCV), computed as head length divided by P100 latency across the lifespan for males and females. Data are fit with a LOWESS in both figures.

Psychometrics

Figure 4a presents cross-sectional age trends spatial span (SS) and has the same

general shape as P100 latency and CNCV although SS scores appear to decline rapidly

across adulthood and particularly in comparison to a westernized population (Figure 3b).

A significant sex difference also exists in SS between ages 15 and 25 with males

outperforming females (independent samples T-test, p = 0.006, t = -2.937).

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(a) (b) Figure 4. a) Forward spatial span scores across the lifespan with LOWESS fit curves for each sex. b) Forward spatial span scores across the lifespan for Ache and Australian samples (data adapted from Hester et al. 2004, reproduced with permission).

Figure 4a presents cross-sectional age trends in CPM and the expected pattern of

general developmental and aging trends is observed. However, a highly significant sex

difference emerges between ages 15 and 30 with males again outperforming females

(independent samples T-test, p = 0.000, t = -4.054) and scores again decline rapidly

across adulthood. The rate of this decline appears to be somewhat faster than observed in

an industrial society (Figure 4b).

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19

Figure 5. a) Raven's Colored Progressive Matrices (CPM) scores across the lifespan with LOWESS fit curves for each sex. b) CPM scores across the lifespan for Ache and Italian sample (data adapted from Measso et al. 1993).

Table 3 presents Pearson correlations for test variables taken as residuals off of the

LOWESS best fit line thereby controlling for age. The extremely high correlations

between P100 and CNCV result from P100 being in the denominator for the calculation

of CNVC. CPM correlates with SS (stronger in males) and with CNCV (stronger in

females). Correcting P100 for head length, or dividing head length by P100, strengthens

the correlation of SS and CPM with CNCV except for male SS where there is virtually no

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Age

70656055504540353025201510

CPM

35

30

25

20

15

10

5

0

male

female

20

Table 3. Pearson correlation matrices. Lower left halves control for age by using the residuals off the LOWESS fit by age. Upper right halves indicate the number of valid (listwise) cases for a given correlation. * Correlation significant at the 0.05 level, ** correlation significant at the 0.01 level (1-tailed). Significance values provided if correlation was stronger than 0.2 or p-value less than 0.2. TOTAL P100 CNCV Spatial Span CPMP100 161 156 80 CNCV -0.756** 156 79 Spatial Span -0.064 0.076 77 CPM -0.024 0.199* 0.190* p = 0.040 p = 0.049 FEMALES P100 CNCV Spatial Span CPMP100 75 70 33 CNCV -0.827** 70 32 Spatial Span 0.005 -0.061 29 CPM -0.076 0.239 0.099 p = 0.094 p = .304 MALES P100 CNCV Spatial Span CPMP100 86 86 47 CNCV -0.769** 86 47 Spatial Span -0.141 0.139 48 p = 0.097 p = 0.101 CPM -0.072 0.157 0.218 p = 0.146 p = 0.068

DISCUSSION

Assessing cognition within a traditional or non-Western population presents a unique

set of challenges. We found correlations between measures of STM and Gf, and between

Gf and CNCV, collected among a group of traditional living forager-farmers. These

findings are consistent with previous studies (Conway et al. 2002; Engle et al. 1999; Reed

21

et al. 2004a) and are perhaps more impressive considering the nature of the sample, that

is, a traditional population, relatively small N distributed across much of the lifespan, and

controlling for age indirectly through residual analyses. Considered in this light, these

findings lend powerful support to the conceptual and empirical bases for the

interrelationships among STM, Gf and nerve speed.

Accounting for the pattern of Aché psychometric scores across the lifespan is open to

interpretation but requires consideration of the effects of variable cultural exposure in

combination perhaps with changing nutritional and disease patterns. Ache scores on both

tests decline much more rapidly across middle adulthood in comparison to trends from

other industrialized populations; SS scores are comparable at young ages before declining

rapidly and CPM scores are significantly lower at all ages.

The effects of schooling on psychometric test performance should not be

underestimated given the clear evidence, although the effect appears to be stronger for

verbal versus nonverbal tasks (Cahan and Cohen 1987). The abilities encouraged by

schooling relate directly to the functional conceptions of executive function, WMC and

Gf. In general, performance on Gf tasks depends on controlling attention, inhibiting

irrelevant information, and the speed and fidelity of information processing (Engle 2002;

Jensen 1998). To this list we would add that performance on Gf tasks also depends on

prior experience with testing materials and tasks. A cultural exposure or experience effect

is bound to be stronger when it encompasses pre-pubertal periods of higher neural

plasticity but probably operates over the entire lifecourse in terms of continual learning

and cognitive approaches to problem solving. Given that the Ache were nomadic hunter-

gatherers until the mid 1970s, it is perhaps not surprising that subsequent exposure to

22

western culture and moderate schooling could produce significantly improved

performance on psychometric tasks within the more recent generation.

At the same time, some of the cohort difference in test scores could be attributable to

steadily improving living conditions following settlement in the 1970s including

increased access to medicine, healthcare, and more consistent and higher caloric intake

(Hill and Hurtado 1996). Enduring worse living conditions throughout pre-contact life

would now be realized as more severe senescence in the older generation.

Future Directions and Conclusion

Our interest in pursuing this research was not solely guided by a desire to delineate

individual differences in intelligence per se and, based on previous studies, we expected

to encounter some degree of cultural dissonance with respect to psychometric test

dynamics. However, we also endeavored to collect objective physiological measures of

cognitive integrity with which to evaluate overall developmental and aging trends in the

population as a whole. Consider that all of the measures used here (P100/CNCV, SS,

CPM) exhibit expected age-related changes across the lifespan coincident with

development and senescence. However, the psychometric trends for the Aché are

noticeably different from that found in other populations. Combining the above

approaches could potentially offer a method for evaluating the validity of various

psychometrics within any given population.

Consider for example that aging trends in Gf tasks closely approximate those for

information processing speed in a large German sample (Li et al. 2004). Whether a

common underlying source of variation � perhaps attentional focus or neuronal speed

transmission � accounts for this pattern would not be particularly important. All that

23

would be required is for a predictable relationship to exist between the tests of interest,

and that the information be collected in a population where acculturation and schooling

differences are not a factor. If we assume that psychometrics are more prone to cultural

modification than physiological variables, it might then be possible to apply these tests in

a traditional population to compare the expected with the observed trend and evaluate the

age-specific validity of the psychometric task. We note that by recording short-latency

potentials (<200ms) while passively viewing a monitor, VEP demands minimal effort

and cooperation from participants, and thereby avoids most of the confounding effects of

acculturation, motivation and familiarity with test materials. Unfortunately, VEP results

cannot be formally compared across studies due to poorly understood variation arising

among laboratories, requiring the establishment of within-laboratory reference values

(Odom et al. 2004). Developing VEP or CNCV norms in association with Gf measures in

a population where acculturation or schooling differences are not a concern (or even

controlling for IQ) seems to be a reasonable approach for evaluating the differential and

age-specific validity of psychometrics within a given population.

The inability to formally compare VEP across studies limits our ability to characterize

the senescent VEP/CNCV pattern in the Aché. On the one hand, the large check sizes

used in this study (60�) and clear age decline in P100 across adulthood suggest marked

senescence. On the other hand, the relatively low luminance (30 cd/m2) of the

checkerboard stimulus � also presented on a flat screen monitor which has not to our

knowledge been performed before � would mitigate in the opposite direction by

exaggerating senescent trends and is likely contributing to the relatively longer P100

latencies recorded here.

24

There are limitations to this data and particularly its cross-sectional nature. Although

words such as �development", "senescence" and �change� are used, these should be

interpreted with caution. Also, forms of dementia, such as Alzheimer�s disease (AD),

were not gauged in this study and could possibly be contributing to the rapid deterioration

of cognitive skills as evidenced by psychometrics. Mean P100 latencies are normal in AD

patients indicating that optical pathways are spared (Martinelli et al. 1996). However,

from ethnographic experience we doubt dementia is highly prevalent among the Ache

and point out that age-specific mortality acting against cognitively impaired individuals

(Deary and Der 2005) could be particularly strong in relatively high senescence, high

mortality populations such as the Aché.

In conclusion, we found modest but compelling correlations among measures of

STM, Gf and brain nerve speed that accord with an emerging picture of the organization

of mental abilities (Geary 2005). Effects of task relevance, cultural exposure, and

schooling should be considered when applying western-derived psychometric in non-

western populations. The application of psychophysiological techniques such as VEP

appears useful for estimating neural integrity and may assist in evaluating the cross-

cultural efficacy of psychometric tasks. We encourage further investigations of this topic.

25

ACKNOWLEDGMENTS

A Leakey Foundation General Research Grant to JW funded this research.

Comments from several reviewers were instrumental for improving the focus of this

paper.

26

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