Pribram Stages of Brain and Cognitive Maturation D-115

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Joumal or EduC2ltionDl PsycholOllY1990 Vol 82. No.4 881-884

1 \ \5Copyriaht 1990 the American Psyc:holOllicaJ Association. Inc.

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Stages ofBrain and Cognitive MaturationWilliam J. Hudspeth and Karl H. PribramCenter for Brain Research and Informational Sciences and Department of Psychology, Radford University

Epstein (1974a, 1986) and McCall (1988; McCall, Meyers, Hartman, Roche, 1983) presenteddiscrepant findings regarding the presence of stages in brain arid. ognitivematuration, as describedin Piagetian theory. This article questions whether their variables (e.g., skull circumference andglobal mental test scores) are appropriate indices from which to make such conclusions. Evidencefrom direct brain measurements (e.g., the quantitative eleetroencephalC?gram QEEG and otherneurobiological indices provides stronger support for the conclusion that regional brain maturation exhibits growth spurts and plateaus. The specific neuropsychological functions representedby regional QEEG maturation data give a composite picture of brain growth that is consistentwith Piagetian theory.

Epstein (1974a, 1986) and McCall (1988; McCall. Meyers,Hartman, Roche, 1983) reviewed studies on skull circumference and mental test performance to estimate the probablerelationships between brain and cognitive maturation. Epsteinreported that skull circumference and mental test performance (in independent, cross-sectional samples) were correlatedover the first 17 years of postnatal development. Furthermore,he reported that brain and cognitive maturation proceededby incremental spurts and plateaus, with three growth cyclesstarting at I, 6, and 10 years of age, respectively. McCallfound that he could not replicate these correlations in alongitudinal sample (same variables, within subjects). Consequently, he questioned the validity and usefulness of brainmeasurements (i.e., inferred from skull circumference) andtheir application in the design of educational programs.Epstein (l974a, 1986) and McCall (1988; McCall et aI.,1983) opened important discussions concerning the applicability of modern neuroscience data in the design of educational programs. It is clear that both identified critical issuesthat make the relationships between brain and mental growthdifficult to interpret. Because most investigators in this areaare reevaluating previously published data, there is little hopethat many desirable or critical variables were used in a singleresearch rePort. Given this limitation, the variables used byEpstein and McCall may not provide essential distinctions forrelating brain and cognitive growth. .There is evidence that skull circumference may be a weakindex for cerebral maturation (Thatcher. 1990). Furthermore,skull circumference cannot reveal the status of regional brainfunctions that underlie cognitive skills. Global mental testscores reflect averages of many specific cognitive skills thatcould, more appropriately. be attributed to functions of regional brain systems. Correlations between skull and mental

We want to express our gratitidue to Robert W Thatcher for hissupport and collaboration in comparing data sets and his efforts tobring understanding to this r of research. Similarly, we are deeplyindebted to ou r colleague Joseph King for his interest and help inclarifying the ideas presented in this article.Correspondence concerning this article should be addressed toWilliam J. Hudspeth. Center for Brain Research, Department ofPsychology, Radford University. Radford, Virginia 24124.

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test measurements do not provide sufficiently detailed information concerning brain or cognitive growth to warrant prospective decisions. Resolution of the issues raised by Epstein(1974, 1986) and McCall (1988; McCall et aI., 1983) mightwell be found in direct measurementsof regional brain growthand specific cognitive skills that emphasize the neuropsychological dependencies we assume in brain-cognition correlations.

Brain Systems and MaturationThe brain processes involved in mental function are composed of large anatomical regions that are organized hierarchically into executive, cross-modal, perceptual, and imagingfunctions. A working model for these functions can be foundin systematic discussions by Pribram (in press). A number ofrecent studies have suggested that cerebral and cognitivematuration are intimately correlated. Rates of cerebral maturation have been estimated from crosS-sectional studies ofskull size, the electroencephalogram, cortical thickness, cortical volume, and nerve cell densities (Epstein, 1974a, 1974b.1980, 1986; Hudspeth, 1985; Hudspeth, Pribram 1990;Hudspeth Thatcher, 1987; Thatcher, 1990; Thatcher,Giudice, Walker, 1987). This diverse set of measurements provides consistent evidence that cerebral maturation proceedsin a discontinuous manner, characterized by spurts and plateaus.

The Regional EEGThe human electroencephalogram (EEG) is a record ofbrain electrical activities that can routinely be obtained fromsubjects of any age Computer quantification of changes inthe EEG frequency spectrum (QEEG) has allowed investigators to establish statistical relationships between regional brainstates and maturity (Hudspeth, 1985; Hudspeth Pribram,1990; Hudspeth Thatcher, 1987; Matousek Petersen.1973; Thatcher, 1990; Thatcher et aI., 1987). QEEG measureshave been shown to have high reliability and validity as indicesfor both normal and abnormal brain functions.


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882 COMMENTSW e Hudspeth, 1985; Hudspeth Pribr am, 1990; Hud

speth Thatcher, 1987) described a ~ e t a i l e d pattern of neuropsychological maturation that would be expected on thebasis of incremental QEEG maturation curves obtained fromdifferent regions of the human brain. Our analysis showedt ha t b ra in m at ur at io n e xh ib its five cycles i.e., s pu rt s a ndplateaus)over the frrst 21 years of postnatal development andthat the temporal sequence of maturation in specific regionsof t he b rain is consistent with cognitive de vel op me nt asoutlined in thework of Piaget and Inhelder[Inhelder Piaget,1958; Piaget. 1950, 1971]. In the remainder of this article, wesurvey these findings.

Method

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Matousek and Petersen 1973) published in the first set of QEEGnonnative data, based on four bandsof the EEG frequency spectrum.All details concerning the methods, nature and selection of subjects,recording, and data analysis may be found in their original work.EEG records were obtained from 561 normal children aged I to 21years, using four bilateral locations of the cortex e.g., F7-T3 , F ST4, T3-T5, T4-T6, Cz-C3, Cz-C4, P3-01, P4-02 . We Hudspeth,1985; Hudspeth Pribram, 1990) calculated first


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COMMENTS 883observed shows that the temporal sequence of Piaget andInhelder s outline is consistent with stages of cerebral maturation, including neo-Piagetian concepts of postformal, ordialectic, functions (Kramer, 1983; Riegel, 1973, 1975). Thecorrelations between cognitive and cerebral maturation arepresented in Figure 2. Figure 2a of Figure 2 presents asummary of the Piagetian outline; and Figure 2b presents thechanges in rates of the QEEG plotted against age for variousrecording locations. As can be seen, Piaget s outline of cognitive maturat ion corresponds to changes in the rates ofQEEG recorded from different brain regions. Because theQEEG data were recorded from a limited number of cortical


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884 COMMENTSSecond, the limited number of QEEG electrodes presentedhere are not sufficient. The solution to this problem is mthereasily obtained by increasing the number of electrodes. Inlight of the geneml needs of education, we suggest that somereliable and valid approaches to the problem are possible.QEEG indices exhibit pammetric covariation with age R99 in our work). Similarly, the developmental tmjectoriesderived from the QEEG are consistent with increments incognitive m ~ u m t i o n These indices need to be coupled withpammetric measuresofmental growth, such as those obtainedfrom standardized intelligence test batteries. There is everyreason to believe that the correspondencesbetween the indiceswould be excellent. Perhaps other tests need to be developed,at least, the protocol outlined here can be used as a beginning.In summary, a caveat: Bmin and cognitive matumtion havea reciprocal influence on one another. Not only biologicalvariables produce accelemtions and decelemtions in bminmatumtionas it is reflected in the QEEG, cognitive experiencecan also produce bmin growth and, perhaps, alter the timecourse of cognitive development further. Nonetheless, theevidence reviewed here indicates that some very basic biological processes are codependent with experience in determiningbmin.,.cognition matumtional states.

eferencesEpstein, H T. (l974a). Phrenoblysis: Special brain and mind growthperiods. I Human brain and skull development. DevelopmentalPsychobiology 7,207-216.Epstein, H. T. 974b). Phrenoblysis: Special brain and mind growthperiods. II Human mental development. Developmental Psycho-biology 7.217-224.Epstein, H. T. (1980). EEG developmental stages. DevelopmentalPsychobiology. 13 629-631Epstein, H. T. (1986). Stages in human development. DevelopmentalBrain Research. 30 114-119.Hudspeth,W J. (1985). Developmental neuropsychology: Functionalimplications of quantitative EEG maturation [Summary]. Journalo/Clinical and ExperimentalNeuropsychology 7.606.

Hudspeth,W J., Pribram, K H (1990). Stages ofneuropsycholog.icalmaturation. Manuscript submitted for publication.Hudspeth, W J., Thatcher, R. W (1987, April) Functional Neuroscience: Neurophysiological Correlates Piagetian Maturation.Symposium conducted at the Western Psychological Association,Long Beach.Inhelder, B Piaget, J. (1958). The growth logical thinking.. London: Routledge Kegsn Paul.Kramer, D. A (1983). Postformal operations? A need for furtherconceptualization. Human Development 26 91-105.Matousek, M., Petersen, I (1973). Frequency analysis of the EEGbackground activity by means of age dependent age quotients. InP Kellaway I Petersen (Eds.), Automation clinical electroen-cephalography pp. 75-102). New York: Raven Press.McCall, R B (1988). Growth periodization in mental test performance. Journal Educational Ps} chology 80. 217-233.McCall, R B Meyers, E D., Jr., Hartman,J.,Roche, A F (1983).Development changes in head circumference and mental perform.ance growth rates: A test of Epstein's phrenoblysis hypothesis.. Developmental Psychobiology 16.457-468.Piaget, J. (1950). The psychology intelligence. M Piercy, D. EBerlyne, Trans.). London: Kegsn Paul, Trench, Trubner.Piaget, J. (1971). Biology knowledge. Chicago, IL: University ofChicago.Pribram, K H. (in press) Brain and perception: Holonomomy andstructure in figural processing. Hillsdale, NJ: Erlbaum.Riegel, K F (1973). Dialectic operations: The final period ofcognitive development. Human Development 16 346-370.Riegel, K F (1975). Toward a dialectic theory of development.Human Developmenl. 18 50-64.Thatcher, R. W (1990, June). Nonlineardynamics human cerebraldevelopment. Paper presented at the International Conference onMachinery of the Mind, Havana, Cuba. .Thatcher, R W Giudice, S. Walker, R. A (1987). Humancerebral hemispheres develop at different rates and ages. Science.236. 1110-1113.

Received February 16, 1990Revision received une IS, 1990AcCt:pted une21, 1990 0

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Pribram Stages of Brain and Cognitive Maturation D-115