Aging, intelligence, and anatomical segregation in the frontal lobes

AGING, INTELLIGENCE, AND ANATOMICAL SEGREGATION

IN THE FRONTAL LOBES

LOUISE H.PHlLLlPS AND SERGIO DELLASALA

ABERDEEN UNIVERSITY

ABSTRACT: In this paper we propose a specific neuroanatomical theory of cognitive aging. We review evidence supporting the growing consensus that normal adult age changes reflect differential deterioration of the frontal lobes of the brain. Important differences in the pattern of spared and impaired abilities classically linked to aging or frontal lesions are highlighted. Capitalizing on neuropsychological and neuroimaging findings, the notion of functional and anatomical segregation within the frontal lobes is introduced, suggesting that the frontal cortex is not equipotential. In particular, the dorsolateral and orbitoventral prefrontal regions are called upon by distinct cognitive and behavioral functions. A detailed analysis of the literature suggests that only functions associated with dorsolateral regions are impaired with age, while orbitoventral functions are spared. The hypothesis is advanced that cognitive aging could be better interpreted in terms of changes in dorsolateral prefrontal cortex rather than an all-encompassing “frontal” deterioration. Finally, the role of modularity in cognitive aging and frontal lobe function is discussed.

Adult age-related differences in intelligence have been well documented since early this century, yet there is still considerable disagreement as to the best explanation for such differences. One question that has been the focus of much interest is whether age changes are general across all cognitive domains, or specific to only limited types of function. For example, Hess and Blanchard-Fields (1996) argue that possibly the most important issue in studying age differences in cognition is whether “change is better conceptualized as an unidimensional process characterised primarily by decline or a multidimensional process in which different processes change in different ways”(p. 12). In the 198Os, the most influential

Direct alt correspondence to: Louise H. Phillips. Psychology Department, Aberdeen University Aberdeen, AB24 2tJB, Scotland, UK

Learning and Individual Differences, Volume IO, Number $1998, pages 217-243. Copyright 0 1999 by Elsevier Science Inc. All rights of reproduction in any form reserved. ISSN: 1041-6080

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theory of cognitive changes with age was that of “general slowing” in which a single speed factor was proposed to explain all of the age variance in cognitive tasks (Cerella, 1985; Myerson et al., 1990; Salthouse, 1985). In the 199Os, emphasis has moved to cognitive neuropsychological models of aging, which propose a differential rate of deterioration in various brain regions, and their associated cognitive functions. In particular, it is proposed that healthy adult aging results in greater decline in the frontal lobes compared to other areas of the brain (e.g., Dempster, 1992; Moscovitch & Winocur, 1995; West, 1996). There is now substantial agreement that the frontal lobes are involved in executive processes of cognition (e.g., Baddeley & Della Sala, 1996; Grafman, 1994; Shalice, 1988); therefore, age-related changes should be most evident in cognitive tasks demanding supervisory control. The following quotes indicate the influence of the frontal lobe theory of cognitive aging at present:

Our review of neuropsychological investigations suggests that cognitive processes mediated by the frontal lobes are particularly susceptible to normal aging. (Rapp & Heindel, 1994, p. 295)

Normal aging results in a pattern of cognitive decline that particularly reflects loss of functions associated with the frontal cortex. (Parkin, 1997, p. 184)

These findings have led a growing number of researchers and theorists to suggest that the cognitive processes supported by the frontal lobes are among the first to decline with increasing age. (West, 1996, p. 272)

Many of the age-related deficits in cognition can be interpreted to occur as a consequence of the observed deficits in the older frontal lobe. (Woodruff-Pak, 1997, p. 92)

Other reviews detail the frontal lobe theory of aging in relation to memory (Mayes & Daum, 1997; Moscovitch & Winocur, 1995; Chao & Knight, 1997). How- ever, it is curious that relatively few papers consider the frontal lobe theory of aging in relation to intelligence and problem-solving, being that (1) age changes in fluid intelligence are among the most reliable and best-replicated of any age effects (Phillips & Forshaw, 1998; Salthouse, 1991), and (2) frontal lobe patients are often described as having poor problem-solving skills (Della Sala & Logie, 1998; McCarthy & Warrington, 1990; Shallice & Burgess, 1991). The current review will evaluate the hypothesis that age changes in intelligence and reasoning can be explained in terms of localized changes in the frontal lobes of the brain.

A LOCALIZATION THEORY: AGE CHANGES IN THE FRONTAL LOBES

A growing consensus has developed in recent neuropsychological and aging literature that cognitive changes in the course of adult aging reflect localized deterioration of the frontal lobes of the brain (Daigneault & Braun, 1993; Mittenberg et al., 1989; Moscovitch & Winocur, 1995; Parkin, 1997; Raz, 1996; Shimamura, 1994;

Whelihan & Lesher, 1985). This “frontal theory of aging” has been very influential on recent models of cognitive and neuropsychological change with age. The theory proposes that age-related changes are attributable in neurological terms to deterioration of the frontal lobes,1 and in psychological terms to decline in executive function. Two main strands of evidence support the frontal theory of aging: neu- rophysiological findings that brain changes with age are most prominent in the frontal lobes, and claims that age changes in cognition parallel those found in patients with focal frontal lobe damage.

NEUROBiOLOGlCAL CHANGES W1TH AGE

The aging brain shows greater structural changes in the human frontal lobes compared to other brain regions. Age decrements in the size and number of neurons and cortical thickness (Albert, 1984; Haug & Eggers, 1991; Terry et al., 1987),2 as well as density of presynaptic terminals (Masliah et al., 1993) and decline in normal tau protein (Muka~tova-Ladinska et al., 1995), are more prom~ent in the frontal lobes than other brain areas. Similarly, senile plaques, which reflect neuronal degeneration, are more numerous in the frontal lobes than elsewhere in the brain (Struble et al., 1985),

Moreover, neuroimaging studies show that the volume of the frontal lobes decreases more than that of other cerebral areas. For example, Coffey et al. (1992) report a frontal volume decrement equal to 0.55% per year with age, twice the rate of change in other areas of the brain. In a recent review of studies of magnetic resonance imaging, Raz (1996) found that the correlation between age and volume of cortical gray matter in the brain was more substantial for the frontal lobes than any other brain region. Studies that have examined age differences in the metabolic uptake of various regions of the brain using positron emission tomography (PET), indicate that blood flow to the frontal lobes is ove~helm~gly reduced with age (Gur et al., 1987; Shaw et al., 1984). Likewise, De Santi et al. (1995) found that older adults had lower glucose metabolism at rest in all brain areas except the cerebellum. Regression slopes indicated greatest metabolic slowing in the frontal lobes.

AGE-RELATED EXECUTIVE DEFICITS

There is growing evidence that older adults perform poorly on several cognitive tasks that are also sensitive to frontal lobe damage. Mittenberg et al. (1989) examined age differences on a range of neuropsychological tests purported specifically to tap the ~ction~g of right and left hemispheres of the brain in relation to temporal, parietal, and frontal lobes. There were no differences in age effects on right and left hemispheric functions. Frontal lobe measures showed stronger age-related declines than did measures of temporal or parietal lobe function. They conclude that “degenerative changes in frontal lobe efficiency are the most pronounced and relatively specific sequelae of the aging process“ (p. 926).

Some neuropsychological tests, such as fluency, Stroop, the Wisconsin Card Sort, and the Tower of London, are commonly used to assess frontal lobe function

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(Lezak, 1995). Age differences are usually found on these tests; for example, letter fluency (e.g., Whelihan & Lesher, 1985; Phillips, 1999), Tower of London, (Alla- manno et al., 1987; Phillips et al., 1996), the Stroop test (Boone et al., 1990; Daigneault et al., 1992), and the Wisconsin Card Sort test, (Axelrod & Henry, 1992; Libon et al., 1994; Daigneault et al., 1992). These “frontal tests” are proposed to be selectively sensitive to frontal lobe lesions. However, there are problems with both the sensitivity and specificity of these tests as indicators of frontal lobe dysfunction (Darling et al., 1998; Phillips, 1997; Reitan & Wolfson, 1994). These classic frontal tests may also be affected by lesions elsewhere in the brain (Anderson et al., 1991; Reitan & Wolfson, 1994; Teuber, 1964) and are often performed well by patients with extensive frontal lobe lesions (Anderson et al., 1991; Shallice & Bur- gess, 1991). Further, there are frequent reports of patients with extensive frontal lobe damage and clear problems in the management of their daily life who never- theless perform well on one or all of the frontal lobe tests (Anderson et al., 1991; Shallice & Burgess, 1991). Indeed, these tests correlate poorly with the behavioral problems presented by frontal patients (Baddeley et al., 1997; Alderman, 1996).

There are also age differences in a range of memory measures known to be sensitive to frontal lobe dysfunction, such as memory for temporal order (for review, see Moscovitch & Winocur, 1992), source memory (Parkin, 1997), and spatial working memory (Mayr et al., 1996). Various authors have attempted to link age differences in these memory tasks to changes in the frontal lobes of the brain (e.g., Moscovitch & Winocur, 1995; Parkin, 1997; Shimamura, 1994). However, it is less clear whether age differences in intelligence and reasoning are linked to frontal lobe decline.

THE PATTERN OF AGE CHANGES IN INTELLIGENCE AND PROBLEM-SOLVING

There is ample evidence of age-related deficits in the ability to carry out intelligence tests. The first large-scale empirical evidence of such deficits was reported by Yerkes (1921) in relation to the mass U.S. Army intelligence testing of World War I. Linear declines is reasoning ability appear to begin early: from about age 30 onwards (Salthouse, 1991). However, the effects of aging are not equivalent on all intelligent subscales. Older adults perform particularly poorly on tests of verbal analogies (Jones & Conrad, 1993), the Performance Scale of the Weschler Adult Intelligence Scales (WAIS) (Kaufman et al., 1989), and verbal and spatial abstract reasoning (Schaie, 1995). Age differences are small or nonexistent on other intelligence tests such as arithmetical reasoning and general knowledge (Jones & Conrad, 1993; Kaufman et al., 1989) and the Verbal Scale of the WAIS, including vocabulary (Kaufman et al., 1989).

Several theories have been proposed to explain why some intelligence tests are susceptible to age differences, whereas others are not (see Salthouse, 1991, for review). One such theory suggests that adult aging may differentially affect the functioning of the right hemisphere of the brain compared to the left (e.g., Schaie & Schaie, 1977; Goldstein & Shelly, 1981). This idea arose from findings of larger

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age differences in the nonverbal Performance as compared to Verbal scales of the WAIS. However, as outlined above, substantial age differences are found on some verbal reasoning tests.

A more appropriate way of explaining the pattern of age differences in intelligence tests is to consider the distinction between measures of fluid and crystallized intelligence (e.g., Cattell, 1987). Fluid abilities involve abstract, novel reasoning, and show relatively early and steep age-related declines. Crystallized abilities reflect acquired knowledge, and they usually remain stable late into old age. Age correlations with a test specifically designed to tap the essence of Spear- man’s general fluid intelligence, namely Raven’s Matrices (Raven, 1960), average -0.6 (Salthouse, 1993), among the highest of any replicable correlation between age and cognitive performance (Phillips & Forshaw, 1998). In contrast, growing older (and, therefore, more experienced) conveys benefits in tasks such as solving crossword puzzle clues given some previous experience (Forshaw, 1994), occupa- tional decision making (Perlmutter et al., 1990), or emotional and social problem- solving (Blanchard-Fields, 1996). Cornelius and Caspi (1987) report that effective everyday problem-solving increases with age, while performance on traditional measures of fluid intelligence declines. Hartley (1989) concludes that, in contrast to laboratory tasks, age differences in everyday problem-solving are domain-specific, with relative preservation of interpersonal problem-solving.

There is therefore a fairly clear pattern that older adults perform poorly on tests of abstract fluid intelligence, but relatively well on reasoning tasks that de- mand knowledge or interpersonal skills. As will be outlined in the next section, this is in direct contrast with the deficits seen in at least some patients with focal frontal lobe lesions.

ARE THERE DIFFERENT PATTERNS OF INTELLECTUAL DEFICIT IN FRONTAL LOBE PATIENTS AND IN NORMAL AGING?

Despite the apparent consensus on the involvement of the frontal lobes in age- associated cognitive decline, the supporting evidence is far from watertight (see, e.g., Phillips, 1999; Salthouse et al., 1996; Robbins et al., 1994). The typical clinical picture presented by patients with frontal lobe damage does not seem to overlap with the behavioral and cognitive deficits due to nonpathological aging, as outlined in the previous section. Consider the following description of the prototypi- cal frontal lobe patient, Phineas Gage, in relation to the known pattern of age changes in intelligence:

He is fitful, irreverent, indulging at times in the grossest profanity (which was not previously his custom), manifesting but little deference for his fellows, im- patient of restraint or advice when it conflicts with his desires, at times pertina- ciously obstinate, yet capricious and vacillating, devising many plans of future operation, which are no sooner arranged than they are abandoned in turn for others appearing more feasible. (Harlow, 1868, pp. 339-340)

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Phineas Gage’s behavioral changes were so profound that those who had known him before his brain injury were forced to conclude that “he was no longer Gage” (Harlow, 1868, p. 340). Indeed:

After the accident he showed no respect for social convention; ethics, in the broad sense of the term were violated . . . . Another important aspect of Gage’s story is the discrepancy between the degenerated character and the apparent intactness of the several instruments of mind - attention, perception, memory, language and intelligence. (Damasio, 1994, p. 11)

This description of the effects of frontal dysfunction-immoral character, with preserved cognition-appears precisely opposite to the usual understanding of aging as a process of decline in fluid intelligence, with preserved or increased social wisdom. Indeed, Harlow describes Gage as behaving like a child.

Other patients with substantial frontal lobe damage who show a similar dissociation between impaired social decision making and relatively spared intelligence have been described subsequently (Brazzelli et al., 1994; Damasio & Van Hoesen, 1983; Eslinger & Damasio, 1985; Rolls et al., 1994; Shallice & Burgess, 1991). Reviews often emphasize the intact performance of patients with frontal lobe damage on intelligence and laboratory tests along with impaired social behavior, poor judgment, and inappropriate decisions taken in real life (Benton, 1994; Damasio & Anderson, 1993; Milner, 1995; Parker & Crawford, 1992). This pattern suggests that precisely those abilities that may be spared following frontal lobe lesions (e.g., abstract reasoning abilities, fluid intelligence) are most affected by aging, whereas the abilities that are impaired after frontal lobe lesions (e.g., social decision making, using knowledge wisely) are Zeast a&ted by aging. This seems like a serious problem for a frontal lobe theory of cognitive changes with age.

Further evidence of a dissociation comes from a task of planning multiple shopping errands. Shallice & Burgess (1991) describe patients with frontal lobe damage who, despite good performance on standard frontal lobe and intelligence tests, perform poorly on a “Multiple Errands” task, where they attempt a list of errands in a pedestrian precinct. Patients failed to adequately plan an efficient route (e.g., they entered an individual shop more than once), were unable to work out suitable means of obtaining information (e.g., “What was the temperature in Edinburgh yesterday?“), and displayed inappropriate social behaviors such as leaving shops without paying for goods. Some recent evidence suggests that there are few age differences in a comparable task (Garden & Phillips, 1999); see Table 1. Older adults attempted fewer of the listed errands, but there were no age differences in the number of errands successfully completed. Also, no age differences existed in the priority given to errands, or the route used in the task. Where age differences did exist, they suggested better performance in the older adults, who were less likely to start an errand and then fail to complete it, and were less likely to break one of the task rules (do not enter a shop without buying something). Overall, there was no evidence that older adults showed similar deficits to frontal lobe patients on this task.

One way of reconciling these apparent anomalies between performance of older

AGING, INTELLIGENCE, ANATOMICALSEGREGATION 223

TABLE 1 Performance of Younger and Older Adults on a Multiple Errands Task

Adult Performance

Measure Younger: Older:

mean age = 38 (n = 20) mean age = 60 (n = 20)

Mean number of errands Attempted Completed

% of individuals who broke the “buy” rulea “map” ruleb

14.0 12.1 10.8 10.0

70 45 55 45

The buy rule was “Do not enter a shop unless you buy something from the shop.” It is interesting to note that of the 9 older adults who broke this rule, 3 did not recall the rule when memory for rules was tested. In contrast, none of the 14 younger adults who broke this rule forgot it.

bThe map rule was “Stay within the boundaries of the map”: Subjects had a copy of the map available to them at all times.

adults and patients with frontal lobe damage is to consider the architecture of the frontal lobes in more detail. The frontal lobes occupy more than a third of the human cortex, and to make sense of such a large and diverse area many investigators have proposed that the frontal lobes be subdivided. There has recently been much interest in the idea of localization of function within specific areas of the frontal lobes (see, e.g., the recent overview by Beardsley, 1997; and the review by Darling et al., 1998). Relatively few studies on the frontal lobe theory of aging have explic- itly considered possible subdivisions within the frontal lobes; indeed, most do not even distinguish the prefrontal cortex from the motor and premotor areas. For instance, patients with frontal lesions often present with the so-called premotor syndrome, characterized by the disturbance of skilled movements or sequences of ges- tures (defined “kinetic melodies” by Luria, 1969) in the absence of paresis. These deficits are seldom observed in normal aging. Neuroanatomical and functional differences are also apparent within the prefrontal (nor-motor) region proper. We will now outline in some detail the distinction between orbitoventral and dorsolateral regions of prefrontal cortex, and the effects of age on these two regions, before re- turning to the implications that this has for cognitive function.

ORBITOVENTRAL AN0 DORSOLATERAL REGIONS OF THE PREFRONTAL CORTEX

Frontal theories of aging generally assume parallel decline across the various regions of the prefrontal cortex. However, the frontal lobes are a heterogeneous formation, and differentiable architectural and functional areas can be identified within this region. There is still considerable debate as to the number and function of distinct anatomical areas in the frontal lobes. For instance, there is some converging evidence of lateralization of function, at least in terms of left-frontal encoding and right-hemisphere retrieval mechanisms (Tulving et al., 1994), al-

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though this distinction may not apply to older adults (Cabeza et al., 1997). The distinction that might be particularly relevant to aging is between dorsolateral (DL) regions (centered on Brodmann’s areas 9 and 46)3 and orbitoventral (OV) regions (areas 11,12,13, and 14)4, see Figure 1.

The difference between the deficits following lesions in these two areas was recognized by early investigators; in reviewing the topic, Luria (1969) was un- equivocal: “The syndrome arising in patients with . . . convexity and basal lesions of the frontal regions are different” (p. 749). Indeed, the fractionation between DL and OV areas is seen ontogenetically: The cytoarchitectonic development of the orbital areas precedes that of the dorsolateral areas both in nonhuman primates and in man (Orzhekhovskaia, 1975,1977). Raz (1996) puts forward the argument that those brain areas which are phylogenetically latest are also those that are most susceptible to the effects of aging. The more recent brain areas in terms of evolution include the neocerebellar vermis, neostriatal basal ganglia, and the dorsolateral prefrontal cortex. Raz argues: “The selectivity of brain aging may have evolutionary underpinnings. Age-sensitive association areas of the neocortex, such as dorsolateral prefrontal and inferior parietal areas, are, phylogenetically, the latest additions to the brain. . . Contrasting local responses of the brain to the process of aging may follow a pattern: the last to come (in evolution) is the first to go (in senium)” (p. 171).

The OV and DL regions also differ in their cortico-subcortical connections; indeed, some investigators clearly distinguish anatomical paths and functions of dorsolateral-subcortical and orbitofrontal-subcortical circuits (Masterman & Cummings, 1997). Both OV and DL regions are richly connected to other parts of the brain (and each other). The DL regions are intensely connected to primary sensory and motor regions, while OV regions are heavily networked with the lim- bit system (Adolphs et al., 1996; Rolls, 1996; Pandya & Yeterian, 1996). There is evidence from studies of focal lesions in humans and monkeys, and from neuroimaging in normal adults, that these regions may have separable functions, although there is still debate as to exactly what these functions might be (Bechara et al., 1998; Della Sala et al., 1998; Goldman-Rakic, 1996; Petrides, 1994; Rolls, 1996). However, there is some consensus that DL regions are involved in executive function and spatial working memory, whereas OV regions are involved in emotional processing and regulation of social behavior. Within the DL and OV areas there may be further differentiation (Goldman-Rakic, 1996; Petrides, 1994).

Most proponents of the frontal lobe theory of aging have not specified whether both DL and OV regions (and functions) deteriorate at the same or at differing rates. The suggestion of regional differences within the prefrontal cortex in the effects of aging has been made in passing by West (1996):

Within the prefrontal cortex, there also is some evidence suggestive of regional differences in the effects of increasing age, with the dorsolateral prefrontal region demonstrating a linear decline throughout adulthood, and the orbital prefrontal region showing evidence of a decline only during the late 7th decade and beyond. (p. 276)


Lateral view

Medial (internal) view

C Ventral view (from underneath)

FIGURE 1 Lateral (A), medial (B), and ventral (0 views of the brain specifying the location of the dorsolateral

(dark gray) and orbitoventral (light gray) prefrontal regions.

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The majority of published studies on changes in brain neuroanatomy with age do not clearly distinguish between different regions within the frontal lobes. A number of studies do report the effects of age on neuronal density and size in one specific region of the frontal lobes, but differences in the methodology and sam- pling used make it somewhat difficult to compare across studies. The next section reviews the few pieces of relevant evidence that we could cull from the literature.

AGE EFFECTS Otd DORSOLATERAL AblD ORBITOVE~TRAL PREFRONTAL REGLOWS

Haug and co-workers have intensively studied age-related neuronal changes in area 11 (orbitoventral prefrontal cortex) in comparison to other areas of the brain, Their findings show that, in area 11, large neurons do tend to shrink with age, but that this process occurs later (after age 65), less massively and less rapidly than in other areas, including prefrontal area 6 (Haug, 1985; Haug et al., 1983; Haug & Eggers, 1991). Terry et al. (1987) report the effects of age on neurons in area 46 (dorsolateral prefrontal cortex). There was a substantial decrease in the number of counted large neurons (correlation between age and number of large neurons = -.63), and a corresponding increase in the number of small neurons and glia (correlations with age = .33 for small neurons and .51 for glia). Terry et al. (1987) conclude that increasing age causes substantial shrinkage in the neurons of area 46. This decline appears to be linear from age 30 to 100, in contrast to the later and slower decline in area 11 (Haug & Eggers, 1991).

A recent well-controlled MRi study examined age differences in brain volume in relation to specific areas of the frontal lobes (Raz et al., 1998). Raz and colleagues found very similar decrements in the volume of dorsolateral and orbital prefrontal regions from age 20 to age 80 (decrease = approximately 25%). How- ever, these areas do not correspond well to our delineation of DL and OV regions: The area described as dorsolateral by Raz et al. (1988) includes Brodmann’s areas 810, and 45, as well as areas 9 and 46. Further, the orbital prefrontal region defined by Raz et al. comprises areas 11 and 47, and not the more ventral and medial regions (12,13,14), which are critical in determining social behavior (Rolls, 1996).

There are a large number of in vivo studies of regional cerebral activity with, aging; however, few clearly distinguish between orbitoventral and dorsolateral areas (as defined in Figure 1). Some evidence can be gleaned from the literature of a differential decrement of glucose uptake within the different regions of the prefrontal cortex. For example, Duara et al. (1983) incidentally report (Table 3, p. 768) that age correlates negatively with weighted regional cerebral metabolic rates in the dorsolateral, but not in the orbitofrontal gyri. More recently, De Santi et al. (1995) concludes that “there is a stronger relationship between age and dorsal lateral frontal lobe metabolism than between age and orbital frontal lobe metabolism“ (p. 367) following a PET study of glucose metabolism in young and old adults. Correspondingly, Marchal et al, (1992)‘ exam~ing the changes in cerebral metabolic rate of oxygen in volunteers aged from 20 to 68 years, found age- related effects in nearly all the cortical gyri they analyzed, including DL prefrontal gyri, but did not find age-related changes in OV prefrontal regions.

Thus, there are at least some hints from studies of brain structure that aging

AGING, ~NTEiL/GfNC~ ANAT~~ICAL SEGREGATICN 227

may differentially affect the dorsolateral as opposed to orbitoventral prefrontal cortex.

FLUID INTELLIGENCE AND DDRSDLATERAL PREFRDNTAL CORTEX

Ever since the seminal work of Hebb (1939) and Hebb and Penfield (1940), it has been received wisdom that frontal lobe lesions do not impact performance on intelligence tests (Benton, 1994; Damasio & Anderson, 1993; Tranel et al., 1994; Teu- ber, 1964). However, Duncan, Burgess, and Emslie (1995) provide evidence that patients with frontal lobe lesions who perform well on the preferred intelligence test of neuropsychologists, the Weschler Adult Intelligence Scales (WAIS), perform poorly on a test that is a good measure of general intelligence, the Cattell Culture Fair (CCF). The reported patients had WAIS IQs ranging from 126 to 130, yet CCF IQs ranging from 88 to 108. Duncan et al. (1995) argue that WAIS scores are heavily influenced by knowledge (in psychometric terms, crystallized intelligence), whereas CCF scores are determined by the ability to carry out abstract problem-solv~g (i.e., fluid ~telligence). Duncan and colleagues (Duncan, 1994; Duncan et al., 1996) also provide evidence that members of the normal population who have low CCF scores show qualitatively similar instances of “goal neglect” as found in patients with focal prefrontal lesions. Duncan therefore argues that the frontal lobes are heavily involved in fluid intelligence, and that cognitive deficits following frontal lobe lesions are best described in terms of general intelligence.

However, there are a number of reports of patients with substantial frontal lobe damage who have unimpaired performance on an intelligence test, namely Raven’s Matrices (RM), which comes close to defining a general factor of fluid intelligence, (Snow et al., 1984). Bigler (1988) describes four patients, all with fairly severe frontal damage? who perform well on Ravens Coloured Matrices, and two of whom score almost 100%. While the Coloured Matrices are considerably easier than the Standard Matrices, they should still provide a valid measure of fluid intelligence within a nonelite population. Cockburn (1995) describes a patient who performs poorly on a number of tests of executive function and prospective memory, yet has a score at the 35th percentile on RM, which seems reasonable performance given that the patient had no academic qualifications and left school at age 15. Brazzelli et al. (1994) report a patient with massive bilateral damage to the frontal lobes who shows severe behavioral problems and overt utilization behavior (Lhermitte, 1983), yet adequate performance on a range of executive tests and scores of 25/48 on the Raven’s Standard Matrices, and 28/36 on the Coloured Matrices. These scores do not suggest particular impairment, given the patient’s level of education, and they do not offer adequate explanation of the severe behavioral deficits seen.

Do such patients contradict Duncan’s theory that the frontal lobes are inti- mately involved in fluid intelligence? Not necessarily, owing to the distribution of the damage within the frontal lobes in such patients. Duncan et al. (1996) argue

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that the dorsolateral prefrontal area may be particularly involved in intelligence and high-level cognition, as do Parker and Crawford (1992). The patient PG described by Brazzelli et al. (1994), with intact intelligence but impaired social behavior, had “damage to both medial frontal regions and the relative sparing of the dorsolateral cortex” (p. 29)-that is, severely damaged orbitoventral regions, but intact dorsolateral prefrontal regions. In addition, patient EVR, reported by Es- linger and Damasio (1985), who underwent the ablation of the orbitoventral cortex bilaterally (with relatively little damage to the dorsolateral regions) in the course of surgical treatment for a brain tumor displayed a similar pattern of deficits and preserved abilities. In fact, following surgery, EVR achieved WAIS-R verbal and performance IQ scores at the 98th percentile, yet he has been unable to hold down a job or manage his finances since his surgery (Damasio et al., 1991). In like manner, recent analyses of the skull of Phineas Gage, the textbook example of an individual with severe frontal lobe damage who “appeared to be as intelligent as before the accident” (Damasio et al., 1994, p. 1102) suggests that the lesion “fa- vored the ventromedial region of both frontal lobes while sparing the dorsolateral” (Damasio et al., 1994, p. 1104).

Further evidence comes from the questionable practice of frontal leukotomy, the technique pioneered by Moniz (see Valenstein, 1973, for a comprehensive review). This practice was based on the discovery that removal (or disconnection) of the frontal cortex in monkeys could result in behavioral changes believed to be for the better (Jacobson et al., 1935), coupled with a reassuring apparent absence of effect on intelligence of patients who underwent frontal surgery. Meyer and McLardy (1948) provide evidence that surgery to the orbitoventral regions, while causing behavioral difficulties, did not cause overt deficits in performing intelligence tests. Lewin (1961) reviewed the results of selective orbital leukotomies in more than a hundred patients without finding evidence of reduction of intellectual function following this operation. He concluded that “the more the supero- lateral surface of the frontal lobe is involved the greater the chance of intellectual deficit” (p. 44).

Also, recent neuroimaging studies support the role of DL regions in performing fluid intelligence tests. Prabhakaran et al. (1997) found bilateral activation of areas 9,10,44,45, and 46 when comparing performance on analytic Raven’s Ma- trices items with a baseline perceptual matching task. In contrast to the activation in DL prefrontal cortex, there was no reported activation in OV areas 11,12,13, or 14. This evidence seems consistent with a pattern such that DL regions of the prefrontal cortex are involved in fluid intelligence, as assessed by tests such as the CCF and RM, which fall close to defining a general factor of intelligence.

AGE, THE FRONTAL LOBES, AND INTELLIGENCE

As outlined above, age changes are apparent in DL prefrontal neuronal functioning, and in performance on fluid intelligence tests such as Raven’s Matrices. We therefore argue that age-related deterioration in DL cortex may (at least partially) underlie the relationship between adult age and abstract reasoning ability. Rela- tively little evidence is available to directly assess this claim. Raz et al. (1993) ex-

AGING, INTELLIGENCE ANATOMICAL SEGREGATION 229

amined the correlation among age, brain size (as measured by magnetic resonance imaging), and performance on the CCF intelligence test. Area of dorsolateral prefrontal cortex correlated with CCF scores, unlike the other neuroanatomical measures taken (primary somatosensory cortex, inferior parietal lobule, prefrontal white matter, hippocampal formation; note that orbitoventral prefrontal regions were not measured). Also, DL prefrontal and prefrontal white matter were the only structures that significantly shrank with age. This suggests that the strong age decline in CCF may be linked to the age-related shrinkage in DL cortex.

Further evidence to support the role of DL regions in age-related cognitive decline can be found by looking at other tests for which there is good evidence of localization to the DL prefrontal area. For example DL regions are activated during performance of a visual self-ordered retrieval task (Petrides et al., 1993) on which older adults perform poorly (Daigneault & Braun, 1993). The DL regions are involved in judgment about the temporal order of stimuli as shown by functional magnetic resonance imaging (Zorilla et al., 1996) and lesion studies (for a review, see Stuss et al., 1994). Likewise, older adults are poor at making temporal-order judgments (for a review, see Moscovitch & Winocur, 1995). In a study that directly compares the effects of frontal lobe lesions and age on memory, Levine, Stuss, and Milberg (1997) describe a conditional associative learning paradigm. In this task fixed (but arbitrary) associations among four different stimuli and some visual patterns are acquired through trial-and-error learning. Levine et al. (1997) provide a rich analysis of the errors made on the task, and it is clear that frontal lobe patients perform worse than do healthy adults on most error measures, and healthy older adults do worse than young ones. Also, the frontal lobe patients were divided into those who had primarily DL or OV lesions. Patients with OV damage made considerably fewer errors than did those with DL damage. Levine et al. (1997) argue that the age-related impairment in conditional associative learning reflects strategic deficits of contextual processing dependent on the DL prefrontal cortex.

REAL-LIFE PROBLEM-SOLVING AND DRBITOVENTRAL PREFRONTAL CORTEX

Although psychometric intelligence sometimes remains intact following frontal lobe lesions, the ability to deal with the trials of real life intelligently is often markedly impaired (Damasio & Anderson, 1993; Shallice & Burgess, 1991). Again, the distinction between functions of OV and DL regions of the prefrontal cortex may be critical in this regard. Evidence shows that tasks of decision making, which are dependent on real-life knowledge or emotional contingencies, are mediated by OV regions, and OV patient deficits in problem-solving are often only detectable in a realistic ecological niche5 (Damasio, 1995). The growing interest in the effect of age on ecologically valid tasks of problem-solving allows some comparison with frontal patients. Age differences in practical problem-solving are not


as pervasive as the age deficits in very novel reasoning tests. Although considerable variation exists in the effects of age on practical problem-solving, in a recent review of this literature Berg and Klaczynski (1996) conclude that

Taken as a whole, the literature seems to suggest that practical problem-solving performance does not show the marked declines which are seen on some traditional measures of intelligence (e.g., fluid intelligence) although excep- tions to this general conclusion do exist. (pp. 327-328)

Some measures of practical problem-solving do appear to decline with age, such as map reading (Marsiske & Willis, 1995), but it has been argued that such age-affected measures typically do not require socioemotional processing (Blan- chard-Fields et al., 1997). We will now compare the effects of OV lesions and adult aging on emotionally salient measures such as social behavior and personality, emotional problem-solving, and investment decisions.

SOCIALBEHAVIORANDPERSONALITY

The specific association between personality disorders and lesions in the OV regions of the frontal lobes was observed at the turn of the twentieth century by German neurologists (Welt, 1888; Jastrowitz, 1888; Oppenheim, 1890) and subsequently put to the test with large group studies (Kleist, 1934; Zangwill, 1966). Rolls et al. (1994) report a group of patients with OV lesions who show impaired social behavior yet intact cognitive performance (as measured by tasks such as Tower of London). In contrast, they report two patients with DL damage who show the opposite pattern of results: impaired cognitive performance but accept- able social behavior. The problem behaviors shown by OV patients included dis- inhibition, sexually inappropriate advances, boastfulness, misinterpretation of others’ mood states, impulsivity, and aggressive behavior.

Further evidence for the effects of OV ablations on personality comes from patients unfortunate enough to undergo frontal leukotomy. Capitalizing on previous observations (e.g., Ziegler & Osgood, 1945; Reitman, 1946, cited by Meyer & McLardy) Meyer and McLardy (1948) argue that cuts involving the posterior orbital frontal region, in particular area 13, “are often followed by an unfavorable post-operative course distinguished by particularly severe personality change” (p. 555). There was evidence that 13 out of 22 patients whose surgery involved the orbital region presented with moderate or severe personality changes, but only 4 of the 18 patients who suffered surgery to more dorsolateral regions presented with some signs of personality changes.

Duffy and Campbell (1994) review the effects of lesions in specific regions of the frontal lobes and conclude that OV lesions result in impulsivity, aggressiveness, lewdness, and lack of empathy. Behavior and personality changes such as those described in OV patients are rarely associated with normal adult aging. There are no age changes in traits such as impulsivity and aggressiveness (Renaud & Murray, 1996); indeed, age does not relate to either experimental or questionnaire measures of impulsivity (Phillips & Rabbitt, 1995). Further, the inci-


dence of personality disorders decreases in the course of normal aging (Ames & Molinari, 1994).

THE ROLE OF EMOTION IN PROBLEM-SOLVING

Patients with OV damage show lower affective responses to emotionally loaded stimuli, have less control over their emotions, and poorer ability to interpret and empathize with the emotional states of others. Hornak et al. (1996) examined the effects of OV lesions on emotions. Patients with OV lesions were impaired at rec- ognizing the emotion expressed by voices and/or faces and were poor at interpreting the feelings and moods of others. Patients with DL damage showed little change in the recognition of emotional expressions and relatively spared ability to interpret others’ feelings. Also, OV patients show a lack of skin conductance response to emotionally charged pictures that evoke strong skin conductance changes in normal subjects (Bechara et al., 1996). PET studies have shown that reading emotionally loaded words (as compared to nonemotional words) acti- vates the orbital, but not dorsolateral, prefrontal cortex (Beauregard et al., 1997). Thus, there is converging evidence for the role of orbitoventral (but not dorsolateral) prefrontal cortex in interpreting and regulating emotion.

Relatively little research has been done on changes in emotion with age (Schaie & Willis, 1996; Weiner & Graham, 1989). Available evidence suggests that, if any- thing, increasing age may be associated with better ability to interpret and regulate emotion (Blanchard-Fields, 1996). Blanchard-Fields, Jahnke, and Camp (1995) report that older adults adapt their problem-solving strategies appropriately to cope with the emotional demands of social situations, and in particular they use more emotion-regulation strategies than do young adults. Gross et al. (1997) found that older adults across a range of ethnic and cultural groups experience greater emotional control than do young adults.

Further, Gross et al. (1997) found that, in a large sample of Catholic nuns of different ages, older nuns experienced fewer episodes of anger, sadness and fear, but more episodes of happiness, and enhanced control of inner experience and outer expression of negative and positive emotions. They argue that older adults have greater ability to regulate emotion (although perhaps this could instead be interpreted as resignation). Weiner and Graham (1989) compared different age groups in terms of self-rated pity and anger toward protagonists in vignettes designed to provoke these emotions. Older adults reported less anger, but more pity, suggesting that older adults have high empathy and social tolerance. Hartley (1989) found that older adults gave more appropriate advice in interpersonal problems than did young or middle-aged individuals.

Wharton and Grafman (1998) propose that reasoning which has personally relevant content, in terms of beliefs, values, goals or plans, is mediated by the orbitoventral regions of the frontal lobes. In support of this, Adolphs et al. (1996) found that patients with OV damage did not vary task strategy in a deductive- reasoning task in response to different familiarity of the materials presented. In contrast, patients with nonfrontal or DL prefrontal lesion showed the usual pattern of enhanced performance when the material presented was familiar. They

232 LEARNlNGANDlNDlVlDUAL DFFfRENCfS VOLUME 10. NUMBER 3,1998

conclude that OV patients do not have a somatic feeling (or instinct) that a state- ment is correct in corroboration with previous experience, unlike patients with lesions elsewhere in the brain. Older adults do not show this absence of reaction to meaning~l, familiar materials.

In relation to age differences in syllogistic reasoning, Gilinsky and Judd (1994) found “robust support for the hypothesis that age-related declines in syllogistic reasoning are mediated by tendencies that increase with age to accept believable but invalid arguments and to reject unbelievable but valid arguments” (p. 369). In other words, older adults are more likely to concur with their “gut feeling” in decision making (a strategy that is probably beneficial in most everyday situations), unlike OV prefrontal patients, who may have an absence of such feelings (Dama- sio, 1994; Adolphs et al., 1996).

lNVEST~ENT AND FINANCIAL DECISION MAKING

Patients with OV lesions often make disastrous financial decisions. For example, patient EVR, described by Eslinger and Damasio (1985), became bankrupt because of poor investment decisions after suffering substantial OV damage. Bechara et al. (1998) compared patients with orbitoventral and dorsolateral prefrontal damage on a monetary decision-weighting task: the gambling paradigm. In the gambling task, subjects must bet fake money on a choice of card decks, which are equal in appearance and size, but vary in terms of reward and unexpected penal- ties, and contingencies on winning or losing. Performance on the task is assessed in terms of the pattern of choices made: Bechara et al. (1998) argue that people who perform the task well have a “hunch” that some decks of cards are riskier, and therefore choose these decks less as the task progresses. All of the OV patients made poor decisions as to how to gamble the money provided, and they showed a lack of behavior modification contingent on punishment and reward.

In contrast, none of the patients with DL damage showed poor decision making in the gambling task, despite deficits in working memory. We are not aware of any studies examining age differences in a directly comparable task; indeed, there is very little literature on age effects on decision making (Hartley, 1989). However, there is some evidence that older adults are as astute as young adults in terms of monetary decision making. For example, there are no age differences in efficacy of decisions on investing money (Walsh & Hershey, 1993). Further, Hart- ley (1989) reported no age differences in decision making in a task involving choice about which insurance policy to select.

SUMMARY OF AGE EFFECTS ON DORSOLATERAL AND ORBITOVENTRAL FUNCTIONS

Tasks dependent on dorsolateral prefrontal cortex include traditional tests of fluid intelligence such as Raven’s Matrices, as well as tasks with high working- memory demands. Such tests are also very sensitive to normal adult aging. In contrast, tasks with high orbitoventral prefrontal involvement include investment

AGING, INTELLIGENCE, ANATOMlCALSEGflEGATlON 233

decision making and emotionally salient problem-solving, which are little affected by age. We therefore propose that cognitive changes with age are better described in terms of deterioration of dorsolateral prefrontal cortex than in terms of general frontal lobe decline. The extent to which this can be described as a modular theory of aging is now considered.

IS COGNITIVE AGING MODULAR?

There is agreement that in neuroanatomical terms the process of aging is modular: “Every part of the brain has its own time history with aging” (Haug et al., 1983, p. 9). In reviewing studies of age-related change in brain structures, Raz noted that “These findings contradict the notion of global age-related degeneration . . . ; brain regions apparently age at an uneven pace” (Raz, 1996, p. 168). Some areas of the brain age faster than do others; in particular, the dorsolateral prefrontal cortex is susceptible to the early effects of age.

However, this does not necessarily mean that cognitive changes with age are neatly modular, because the notion of cognitive modularity breaks down somewhat when applied to more recently evolved cortical areas such as the dorsolat- era1 prefrontal cortex. Fodor (1983) proposed that modules are computational de- vices that are domain-specific (process only specific types of ~fo~ation), associated with a fixed neural architecture, very rapid at processing information, and resistant to top-down processes (such as knowledge and control functions). These are contrasted with central systems, which integrate information across different domains, are global and distributed in relation to brain architecture, process information slowly, and operate under executive control. Anderson (1992) proposes that intelligence can be identified as a central system, whereas processes such as phonological encoding can be classified as modular.

There have been a number of attacks on the strict Fodorian definitions of modular and central systems (e.g., Goldberg, 1995; Moscovitch & Umilta, 1990). Gold- berg (1995) argues that, while evolutionarily early parts of the brain such as the thalamus may be modular, the neocortex has evolved so that at anatomical and functional levels it is characterized by rich pathways and an absence of internal boundaries. Goldberg proposes that the cortex has evolved precisely to be flexible and nonmodular. This might be particularly important for dorsolateral prefrontal areas, which have evolved relatively recently, and are involved in the coordina- tion of many other functions. Moscovitch and Umilta (1990) argue that many of the properties that Fodor attaches to modules can also apply to “central systems.” For example, central systems sometimes act relatively quickly and can be located in a discrete anatomical location.

Considerable advances in knowledge about the frontal lobes have occurred since Fodor outlined the differences between modular and central systems in 1983. Moscovitch and Umilta (1990) argue that when the neuronal architecture of such areas is known “the distinction between modules and central systems be- comes very fuzzy” (p. 20). In particular, they argue that the frontal lobes may

234 LDlRNlNGANL?iNDlV/lXJAL DlFFERENiXS V0LlJME10,NUMBER3.1998

sometimes behave as a central system, and sometimes as a collection of modules: “Thus, at a global level the prefrontal cortex behaves as a central system, but at the local level the prefrontal cortex (and other cortical areas) may resemble modules” (Moscovitch & Umilta, 1990, p. 21).

Recent models of frontal lobe function often appear to have a tension between the general integrated properties of high-level cognition and more modular-specific aspects of executive functioning such as goal setting, solution checking, knowledge units (e.g., Shallice & Burgess, 1996; Grafman, 3994; Goldman-Rakic, 1996). Cognitive models of “executive function“ or “frontal lobe function” need to include both general and specific components. Perhaps the dichotomy between “intelligence” and “modularity” outlined by Anderson (1992) is better described as a continuum between the evolutionarily recent, flexible, very weakly modular frontal lobes (subserving intelligence and problem-solving) and more ancient, dedicated, strongly modular subcortical areas.

There is also a question as to whether functional subdivisions within the frontal lobes can be considered modular. We have presented a case for anatomical segregation of fluid intelligence from emotional problem-solving, and we have suggested that this distinction may be important in relation to adult aging. The proposal that both abstract reasoning and emotional reasoning are separable may appear at odds with literature suggesting that both social and emotional intelli- gences are not independent of fluid ability (e.g., Hartley, 1989). It is likely that few tasks purely assess either fluid abilities linked to dorsolateral regions or emotional aspects linked to orbitoventral regions. Most problem-solving tasks involve integration of the executive control afforded by the dorsolateral regions, and the motivational and emotional role of the orbitoven~al regions. Both the DL and OV regions of the frontal cortex are richly interlinked, and cross-talk between these areas is likely to be important in solving a range of tasks. Duncan et al. (1996) suggest that fluid intelligence may arise from cooperative activity in a variety of distinct frontal systems.

Aging does not affect all brain areas equally, and in that sense the effects of age could be classified as modular. However, because the areas most affected by age include dorsolateral prefrontal cortex, which has been shown by neuroimaging to be involved in a wide range of complex tasks (see, e.g., Duncan et al., 1996; Pet- rides, 1994), the effects of aging will impact a broad range of cognitive tasks.

Age changes in cognition are often explained in terms of deterioration of the frontal lobes of the brain. However, the pattern of age changes-decline in fluid intelligence test performance yet intact emotional problem-solving-does not match the deficits presented by well-documented patients with frontal lobe lesions. We propose that this anomaly can be explained in terms of age-related deterioration in dorsolateral, as opposed to orbitoventral, prefrontal cortex. At an anatomical level, age-related changes in the brain are best described in terms of modularity, with one of the regions most affected being the dorsolateral prefrontal cortex. At a cognitive level, age-related declines are more general, as befits the


role of the dorsolateral prefrontal cortex in a wide range of intelligence and working-memory tasks.

ACKNOWLEDGMENTS: The multiple-errands study described in this article was designed and run by Sharin Garden, Psychology Department, University of Aberdeen.

NOTES

1. Obviously, age also affects a number of other brain regions that impact cognition, such as the hippocampus.

2. It should be mentioned that earlier studies erroneously equated neuron density with neuron number, therefore biasing the degree of age-related changes (Coleman & Flood, 1987; Morrison & Hof, 1997).

3. The cerebral cortex does not have a homogeneous cellular structure and organization. Several different codes have been proposed to designate the various cortical areas (Crosby et al., 1962). The most generally recognized terminology applied to the different areas of the cortex is that of Brodmann (1909), who used numbers to indicate distinct regions, simply following the order in which he studied them.

4. In Brodmann’s original map of the cerebral cortex the numbers 12,13, and 14 are not mentioned (Braak, 1980; Gorman & Uniietzer, 1993). Influenced by the work of his contem- porary Vogt (1910), he later (Brodmann, 1910) inserted area 12 between area 10 and area 11 (Markowitsch, 1993). The locations of areas 13 and 14, as currently agreed in the posterior orbital surface of the human brain (see Figure l), are due to the work of Beck (1949), who mapped onto the human brain these two “new” areas described by Walker (1940) in the orbital gyrus and gyrus rectus of the macaque brain.

5. It is perhaps worth commenting on the difference between crystallized intelligence (having knowledge) and real-life problem-solving (the effective application of knowledge). Patients with orbitoventral prefrontal lesions often display a curious dissociation between possessing knowledge yet failing to act upon it: For example, patients may fail to carry out a requested action, despite being able to report exactly what they are supposed to be doing (e.g., goal neglect, Duncan et al., 1995), or that may perform relatively well on paper-and- pencil measures of ethical and social reasoning despite being unable to deal with parallel situations in real life (Saver & Damasio, 1991). The knowledge of what should be done is main- tained, but not called upon to guide behavior.

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Aging, intelligence, and anatomical segregation in the frontal lobes

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