possibilities? Furthermore, there may be other reasons for the slower cortical
metabolic rate in people who score higher on the intelligence tests. Perhaps
people who are able to remain calm while taking intelligence tests have lower
cortical metabolic rates as a result, and thus do better on the tests. Both intelli-
gence test performance and metabolic rate may be affected by control over
anxiety. Haier et al. (1988) dismiss this possibility because their subjects did not
appear to be anxious, and because other research suggests that anxiety in-
creases metabolic rates primarily in the frontal lobes. The authors found that
metabolic rate changes related to learning occurred primarily in the posterior
regions. However, it is possible that anxiety responses interacting with the
responses necessary to do cognitive tasks may produce a different pattern of
cortical metabolic rate than observed in other situations.
Neural Conduction Rate and Smart Brains Some recent research suggests that
the rate at which neurons conduct electrical activity may be faster for people
who score higher on intelligence tests. Reed and Jensen (1992) presented sub-
jects with visual stimuli and measured the latency with which an evoked po-
tential was detected in primary visual cortex. Shorter latencies imply faster
neural conduction. They found a .37 correlation between scores on the Raven’s
Matrices test and conduction rates. Similar findings have been reported by
Vernon and Mori (1992).
Again, though, the conduction latency results are not easy to interpret. What
is different about the neural structure between people whose neurons conduct
impulses faster and people whose neurons conduct impulses more slowly?
Does the variation in conduction latency reflect intellectual efficiency, motiva-
tion, consistency of performance, or what?
Let me make one final comment on the studies of the physiological basis of
individual intellectual differences. It is possible that certain physiological fea-
tures on which people differ and which determine intelligence permeate much
of the brain. There may be something about the development of neurons such
that virtually all of them are more efficient in some people. In such a case, in-
telligence would have a unitary character, as much of the research on the neu-
rophysiology of intelligence implicitly assumes. On the other hand, it is also
possible that the relative efficiency of neurons varies across neural domains
within any given brain. Such variability in efficiency within a single brain could
be due to environmental experiences, genetic ‘‘programming,’’ or some interac-
tion between the two. At any rate, neural domain variability would give rise to
a multifaceted form of intelligence. And it is to a multifaceted view of intelli-
gence that I will now direct my discussion.
36.3 Building the Case for a Multifaceted Approach to Intelligence
Interpreting the Evidence for Unitary Models of Intelligence
There have been a number of reactions to the unitary intelligence interpretation
of the positive correlations observed among various measures of intelligence
and information processing. One reaction is that the g factor has many possible
interpretations besides the interpretation that it reflects the intrinsic efficiency
of the cognitive system (Gould, 1981; Richardson, 1991). One possibility is that
788 R. Kim Guenther