School Readiness Considered
From a Neuro-Cognitive Perspective

Throughout the history of our nation, many Americans have worked to better the human condition. Nowhere is this more evident than in the history of schooling in America. Just one century ago leaders in our nation demanded that all Americans should be provided with a free public education. In the late 1800s this mandate meant that for the first time children of non-English speaking immigrants would go to school, and in the early 1900s that handicapped children would be given the opportunity for a separate but free education. Today as the twentieth century approaches its end, we aspire to better the human condition by setting a new national priority: that all of America's children should come to school "ready to learn." This national priority of the late 1900s reminds us that some of the nation's children consistently have seemed less ready for school than others, and upon entering school, some children have been less successful than others in reaping the benefits of a free public education that their states provide.

But what constitutes a child's readiness for school or for learning? An important question to ask as the public demands higher standards of school performance in the face of diminishing school budgets, increasing numbers of non-English speaking children, and increasing costs for the integration of all special needs students in regular classrooms. And how feasible is it to identify children who are "not ready" for school, or to create programs that will help less-than-ready children become ready? This volume considers such questions by having enlisted the views of an interdisciplinary group of scholars who have been asked to describe the current state of knowledge about school readiness from their various disciplinary points of view.

As an educator with strong roots in the biological foundations of human development, attention, learning, and memory, I have framed my discussion around a central question: What can the neural and cognitive sciences contribute to our understanding of the readiness of children and adolescents for the challenges they will encounter in school?

In this discussion of school readiness, I will first describe research which points to the importance of knowing about the natural or biological timetables for mind and brain development during childhood and adolescence, that is, to neurodevelopmental timetables which allow us to approximate the normal readiness of children and adolescents for the academic demands of schools. To consider the subject of neurodevelopmental timetables more deeply, I next take into account what is known about forces that can threaten normal mind-brain development during critical periods as well as sensitive periods of neuro-cognitive development of the mind and brain in which individuals are acutely in need of specific stimuli or at least are optimally ready to benefit from other kinds of environmental stimulation in order for normal neurological development to proceed. To more fully understand the limitations of critical or sensitive periods, I next discuss research concerned with the human brain's plasticity, that is, the species' capacity to adapt to its environment and to recover from deprivations, illnesses, and injuries to the brain, and I consider how schools might take advantage of a new approach to research about the brain's plasticity. Within this discussion which focuses on natural neurodevelopmental timetables, critical and sensitive periods in development, and the brain's natural plasticity to overcome deprivations or injuries during critical or sensitive periods, I finally focus on the importance of knowledge derived from the study of special populations--exceptions to the norm--as a mechanism for understanding the full range of neurodevelopmental variation that exists among age-cohort groups of school children and adolescents in relation to natural timetables. I will conclude this paper by considering the most pressing needs for new knowledge from the neuro-cognitive sciences, from the standpoint of that knowledge which is most needed to transform educational practice.

Throughout the literature of Western civilization one finds a dominant paradigm for describing the development of the human mind; it is the idea that human beings acquire knowledge of the world gradually from birth to adulthood and that experience modifies one's perception of the world at the same time that it refines one's thought processes. This Western paradigm of gradual development has received

close scrutiny during the twentieth century, and resulted in a refined notion of "gradual" in the development of the intellect from childhood to adulthood.

Among the twentieth century's giants, Piaget (1950, 1952, 1958), was among the first to describe and popularize the behavioral evidence of several distinctly different stages of cognitive development from childhood through adolescence. I will not elaborate on these stages here because their details are well known to readers. But underlying Piaget's formulation of cognitive development was the assumption that distinct stages of cognitive development paralleled the physical development of the human brain. Piaget's publications of his discoveries stimulated four decades of research with a mixture of results some of which corroborated, others challenged, and still others revised Piaget's model (as examples, see Baillargeon, 1991; Bauer, 1991; Brainerd, 1978; Case, 1978; Gardner, 1983; Gelman, 1978; Kraft, et al., 1980; Nelson, 1991; Pascual-Leone, 1970; and Spelke, 1991, to name just a few). In general, one sees in the past four decades a revised paradigm of gradual cognitive development characterized by several more or less distinct and qualitatively different stages of intellectual development with increasing capacities for attention, memory, and complex reasoning.

At the same time, computerized technology for brain monitoring and brain imaging was becoming widely available and more sophisticated. By the 1970s scientists began to look for and to find evidence of associations between measures of cognitive development and brain activity, a relationship that previously had been assumed by Piaget (Matousek and Peterson, 1973; Kraft, 1980; Thatcher, et al., 1987). The work of Thatcher, Walker, and Guidice illustrates a large scale attempt to refine the paradigm of gradual development by incorporating measures of brain activity with measures of cognitive development.

Thatcher's group searched for evidence of brain growth spurts which coincided with Piagetian stages that were assumed to represent the development of logical thought from childhood to adolescence. Their search for this coincidence was only one aspect of an extensive study of the relationship between nutrition and child development (Science, 29 May 1987). Thatcher's group obtained a variety of measures from each of 577 normal subjects, including a neurological and developmental history, a full-scale intelligence test (IQ), measures of school achievement, motor development, handedness, and EEG data. Their sample included individuals ranging in age from 2 months to early adulthood. The sample also included 58% males and 42% females, as well as 28% black and 72% white children and adults from rural and urban areas of the state of Maryland. Thatcher, Walker, and Guidice found confirming evidence of the coincidence of brain growth spurts with the emergence of new stages of cognitive development as indicated by standard Piagetian tasks which have been used for four decades.

One view of Thatcher's group study is the view that the findings were not surprising. Major investigators in applied and theoretical neuroscience believe that the development of the brain is orchestrated in an exceedingly regular fashion and that bursts of maturation in the brain's physical structure and in its higher cognitive functions are the outcome of closely knit and well-synchronized neurophysiological processes.

However, from the standpoint of interests in school readiness an even more important finding of Thatcher's group was the discovery that different regions within the right-left hemispheres and within the anterior-posterior regions of the brain developed at different times and rates throughout childhood and adolescence. Their finding that growth spurts were asymmetrical and highly localized in different regions of the brain, and that growth spurts were associated with stages of cognitive development, as indicated by Piagetian tasks, is significant to anyone interested in the relationship of child development to education because of the amply validated positive relationship between Piagetian stages of cognitive development and students' capacities to meet the academic demands of school, particularly as indicated on measures of school achievement in subjects like science. Thus, the findings of Thatcher's group suggest physiological evidence of natural timetables for school readiness, at least for certain kinds of academic challenges in subjects that require logical or abstract reasoning during early and late adolescence. As findings such as those by Thatcher's group are replicated by others, it may be helpful for researchers to begin looking for ways in which asymmetrical brain growth spurts might be related to other benchmarks of school readiness as seen in the academic demands at various grade levels.

Two additional implications can be drawn from the research by Thatcher, et al., and others (cited in this section and at the end of this paper) concerned with natural timetables for intellectual or cognitive development and brain development throughout childhood and adolescence. One obvious implication is that readiness should not be viewed as a single point in time when children are considered ready for school; a much larger audience than 5- and 6-year-old children must be considered in terms of discussions and questions about school readiness. Based on the very substantial amount of evidence available, one sees a prolonged neurodevelopmental timetable throughout childhood and adolescence in which the mind and brain exhibit a gradual, yet stage-like development characterized by qualitatively distinct stages and asymmetrical patterns of growth.

I do not need to convince my colleagues of this point, but the general public may be less aware of its significance. It is common knowledge that children are continuously challenged as they proceed from elementary school to middle school or junior high school, and finally to high school; but the general public is less aware of the fact that each new segment of school places new neuro-cognitive demands on the child--challenges for which the child or adolescent may or may not be ready, in a neurodevelopmental sense. Decades of studies have shown that children and adolescents are not very successful when the curriculum or instructional demands are not matched to their cognitive development. From a neurobiological perspective, readiness falls along a continuum throughout the school segments rather than as any single point in time when children might be viewed as "coming to school ready to learn."

A second major implication to be drawn from the research cited here concerns future research on natural timetables. Our current understanding of mind-brain development during childhood and adolescence has been broadened from studies by epistemologists, neuropsychologists, and cognitive scientists. The work in two areas, for example--cognitive development and QEEG methodology--has been brought together in an informative and persuasive review by Hudspeth and Pribram (1991) to further understanding of the evolution of early cognitive development, systematically related to brain indices. But presently we still lack neurodevelopmental timetables which provide enough information about brain development in relation to the emergence of cognitive functions throughout the span of school years. Without such information, decisions about the readiness of groups of children for the instructional demands of schooling at various levels are, at best, inadequately informed estimates which may in fact contribute to school failure and self-doubt for some groups of students. Evidence to support this latter assertion will be discussed later within the context of the need to study special populations (Levine, 1992) and the need for information about the normal range of variability as it relates to neurodevelopmental variation within and between age groups.

Hopefully, the importance of launching a major effort to chart such neurodevelopmental timetables will be recognized at this meeting and assigned a high priority for research. If we are to formulate a neurological-cognitive-pedagogical framework from which a better understanding of readiness can emerge, collaboration will be required between neuroscientists interested in brain development during childhood and adolescence, cognitive scientists interested in the development of cognitive functioning and the emergence of thought processes during childhood and adolescence, and educators with a special interest in the development of children's mental capacities in relation to the academic demands of school.

To more fully consider natural timetables for mind-brain development in relation to the subject of readiness for school and learning, it is important to include a discussion of processes that have been known to threaten, delay or otherwise interrupt natural timetables for children's normal brain-mind development. I refer to the related phenomena of critical periods and sensitive periods. A number of scientists have suggested the exclusive use of the latter term; but I find both terms essential to the full understanding of processes that influence natural timetables for human neurocognitive development, and I will attempt to convince readers of this view.

For several decades, scientists studying animal behavior documented the existence of critical periods during normal development when newly-born/hatched or young animals of various species were most responsive to specific kinds of stimulation from the environment. Central to the concept of critical periods was and is the notion that the brain and behavior of specific species of animals can be adversely affected when individuals are deprived of environmental stimulation that is essential for their normal brain-behavioral development during early, often brief, critical periods of life. For example, the absence of a biological mother, the absence of proximity to another member of one's own species, the absence of hearing one's species' language, or deprivation of a primary sense (such as vision or hearing) during critical periods as brief as a few days or weeks can profoundly affect the normal development of affected individuals within the species and radically alter their chance for a "normal" life (Hess, 1966; Lorenze, 1971; Blakemore, 1982).

An example of the influence of critical periods is seen in Goldman-Rakic's work with rhesus monkeys (1981). Brain damage to the prefrontal cortex of rhesus monkeys was introduced during their prenatal development. After full-term gestation and birth, the young experimental rhesus monkeys were presented with easy tasks early in their lives. Their brain injuries led to no significant difference in their performance compared with their non-brain-injured peers of the same age. However, a delayed effect of brain impairment was observed as the experimental monkeys reached an age when advanced cognitive functions were required to solve complex tasks. In this example, Goldman-Rakic's research provides evidence that prenatal brain injuries can have delayed effects.

Research on critical periods with animals such as chicks, goslings, kittens, and monkeys led scientists to search for evidence of critical periods in the lives of the human species. Goldman-Rakic, in her study of events that are thought to shape the development of the human nervous system, describes an analysis of the effects of the atom bomb on human survivors of Hiroshima. The analysis revealed a large number of cases of mental retardation in (only) those individuals who were the offspring of pregnant women exposed to the blast between their 8th and 16th weeks of pregnancy at the time of the atomic explosion.

"This observation (by Otake & Schull, 1984) can now be explained by our understanding that this period corresponds to that of the second and larger wave of neuron proliferation and migration to specific layers of primate neocortex and to knowledge that dividing cells are selectively vulnerable to radiation.... Although the effects of nuclear irradiation is an example of a gross distortion of brain development, of which mental retardation is a devastating outcome, it is not at all difficult to imagine how less-dramatic insults and errors of development could account for more subtle differences in brain structure that could provide for a wide variety of talents and skills among human beings.... It must be obvious that with so many complex mechanisms requiring an orchestrated plan of evolution, alteration of any one of these processes could set in motion a whole chain of events, the ultimate consequence of which could be an altered nervous system, functioning more or less optimally, depending on the perturbations that have resulted" (Goldman-Rakic, "Setting the stage: Neural development before birth," p. 253, in The Brain, Cognition, and Education, Friedman, Klivington, & Peterson, Eds., Academic Press Inc., 1986).

A second example further illustrates the potential impact that a single prenatal event can have on normal brain-mind development. A few years ago, an outbreak of measles (Rubella) occurred in Southern California. Many pregnant mothers were among those in the population that became infected. Some but not all of the infants later born to mothers who had contracted Rubella during their pregnancy suffered the devastating consequences of blindness or deafness, or both. According to Shephard (1992), the first trimester is the most critical period during prenatal development when the presence of Rubella carries with it the greatest risk for damage to the unborn child: 50% during the first month, 30% during the second month, 10% during the third month, and 5% during the fourth month. Many of these Rubella-affected children are now in Special Education programs in Southern California's public schools.

In these few example, one sees the traumatic and irreversible consequences of critical periods wherein external factors profoundly influenced the development and later lives of individuals with mental retardation, blindness, and deafness. How do critical periods in prenatal development differ from what have been described by other scientists as sensitive periods? Rauschecker and Marler (1987) describe "sensitive periods for experiential modifiability" in a manner that distinguishes not only the variability of onset and duration of sensitive periods within species but also the degree of influence factors have on individuals during sensitive periods, as well as the mutability of such outcomes. "[During sensitive periods] many kinds of stimulation ... have the potential to engender neural and behavioral reorganization in the right circumstances..." according to Rauschecker and Marler. These sensitive periods can be related to development within a single sensory system, like the visual system, or even a single process within that system such as ocular dominance or the development of binocular vision. Yet, Rauschecker and Marler observe that the occurrence and duration of sensitive periods varies greatly within species. Marler, in describing various bird species, notes that some individuals within the species have sensitive periods which are restricted to a few weeks while in others the sensitive period extends over a period of nine months. Even closely related individuals within the species vary greatly with regard to these sensitive periods (Chap. 15).

One early objection to the notion of critical periods was the implication of immutability (Rauschecker and Marler, 1987). To demonstrate the plasticity of sensitive periods for the development of language in song bird species, Marler offers the example involving young birds that had been deprived of the opportunity to hear the language of their species during the sensitive period for language development. Following the sensitive period, adult males were engaged to act as tutors for the young birds. The adult males were socially interactive and highly aroused themselves, "presumably constituting a strong form of stimulation" which increased the arousal state of the young birds. The result was as expected; the young birds learned the song. "It is intuitively reasonable that one means for instating a readiness to learn ... is to induce a strong state of arousal" (pp. 357-358).

All of the examples above were chosen to illustrate and to clarify differences between two conceptual models, critical periods and sensitive periods, and to demonstrate the value of both for furthering our understanding of processes which have the potential to influence natural neurodevelopmental timetables. Certainly in discussions of the subject of school readiness in relation to child development, we must be concerned about both the devastating and immutable effects that can occur during critical periods, as well as the depriving and/or damaging events that occur during sensitive periods in the lives of children and adolescents.

Clearly research is now needed to investigate the possible existence of still-unrecognized critical periods during prenatal development when deprivation or damaging events, varying in degrees of magnitude, have led to irreversible neuro-cognitive losses, impacting normal brain-mind development among school-aged children in yet-to-be-understood ways. Moreover, research must clarify the nature and range of sensitive periods during postnatal development, early childhood, and adolescence when individuals are optimally ready to take advantage of experiences that advance neuro-cognitive development and learning, and to experimentally test ways to overcome the effects of deprivations or other influences during such sensitive periods. We have only to recall the eleven million children who are better off today because of a program called Head Start to validate the importance of recognizing and intervening during sensitive periods (Zigler & Muenchow, 1992), but are we confident that such sensitive periods are limited to early childhood? And ought we not be at least as concerned about unsuspected critical periods?

In this paper I have not discussed the potential impact of psychologically traumatic events during childhood and adolescence, a topic which I believe will receive serious attention in discussions about readiness for school or learning in this volume, but there is growing evidence regarding the influence of emotional states on the neurobiology of learning and memory (Gazzaniga, 1988; Klivington, 1989; McGaugh, 1992).

To further understand the various ways that neurodevelopmental timetables during childhood and adolescence are related to school readiness, and including the devastating or disruptive effects of critical and sensitive periods on natural timetables, it is important to consider research on the brain’s plasticity. When neuroscientists discuss brain plasticity, typically they refer to a fundamental adaptive feature of organisms that serves as a working definition of learning and memory:

"Organisms inherit in the structure of their nervous systems many adaptations developed as a result of variation and natural selection operating during previous generations. Yet they also inherit the potential to adapt or change as the result of events occurring during their own lifetime. Because of this [capacity for] adaptation, the experiences of an organism can modify the nervous system and the organism can later behave differently because of these experiences.

This ability to change gives the organism the capacity for learning and memory." (Squire, "Memory and the Brain," p.171 in The Brain, Cognition, and Education, Friedman, Klivington, & Peterson, Eds., Academic Press, Inc., 1986).

Schooling, of course, represents a continuous example of the brain's plasticity. But what can be learned from the current or recent neuro-cognitive research on brain plasticity?

Many individuals have looked to studies of the human brain's capacity to recover from injury, disease, or illness, for clues that might benefit human learning. The work of Bach-y-Rita (1982), Picton (1986), and Squire (1990, 1991) are examples of research which has provided evidence of the brain's plasticity and limitations in its plasticity among brain-impaired adults. However, studies of adults appear to have limited application to school-aged children. Bernstein (1990) and Goldman-Rakic (1986) point out that brain injuries among adults typically result in relatively well-defined deficits in cognition. In contrast, prenatal brain injuries appear to have telescopic effects upon the development of cognition during childhood and adolescence, making it difficult to draw inferences about the nature of prenatal brain injuries in humans. Generally it has been deemed inappropriate to conduct brain imaging studies among healthy children for purposes of understanding possible reasons for difficulties in school, let alone for purposes of establishing school readiness. Thus, to consider readiness for school or learning, I was led to look elsewhere for studies of the brain's plasticity.

The first example, the work of Tsunoda who studies auditory disorders at the Medical Research Institute in Tokyo, illustrates an instance of a limitation of the brain's plasticity in normal children. Studying automatic switching between the right and left hemispheres for coding or responding to sounds among normal Japanese and non-Japanese, he found:

"...the tests revealed that the switching function is determined up to the age of nine by the exposure to speech sounds in a certain language. For most non-Japanese (except for Polynesians) the sounds perceived by the left hemisphere (the side for speech) are actually limited to syllables containing consonants, while vowels, the noises of our environment, and the sounds that express an emotion ("Oh!" "Ah") are perceived by the right hemisphere. More generally, emotion is perceived by the right hemisphere for non-Japanese, who use many more consonants in their speech, and by the left hemisphere for Japanese who employ many vowels.....these differences are caused by the environment and not any racial difference. The structure of the brain, determined by exposure to the language, remains unchanged after the age of nine .... a Japanese child raised as an American until the age of nine will henceforth perceive his emotions like a non-Japanese, predominantly in the right hemisphere, after his return to Japan" (T. Tsunoda, 1989, pp. 54-55).

Tsunoda's research is not immediately connected to the subject of school readiness, but it does provide an example of an age-related limitation of the brain's plasticity for normal children's organization of the kind of auditory information studied, and Tsunoda's study further serves as an example of the manner in which the neurobiology of learning and memory is influenced by the environment.

My second example illustrates the brain's plasticity at a later stage of life: the transition between adolescence and young adulthood. At the Brain-Behavior Lab at Ohio State University, Languis developed a procedure which allows him to correlate students' performance on scholastic tasks with maps of their brain activity (1986, 1988, 1989). Using technology which converts the brain's electrical energy into 4-color maps, Languis is able to show patterns of brain activity during students' performance on cognitive/academic tasks. Of particular relevance to discussions of the brain's plasticity, Languis has demonstrated before-and-after changes in the brain maps of individuals who have received intensive training in areas of cognitive deficits. To illustrate the magnitude of such changes, Languis reports selecting two groups of university students for special training: one group of students demonstrated strong verbal knowledge and skills (i.e., high scores on the Verbal portion of their SAT) but weak mathematical knowledge and skills (i.e., low scores on the Math portion of the SAT) while students in the second group exhibited the reverse SAT performance patterns. Data were gathered before and after intensive training in the areas of students' greatest weaknesses. Like other researchers (e.g., Gordon, 1988, 1989), Languis found on the "before" maps significant differences in the brain activity of students who were strong vs. weak in verbal skills, and similarly, significant differences in brain activity between students with strong vs. weak mathematical skills. Following intensive training in their areas of weakness, Languis was able to provide students with graphic evidence of their brains' responsiveness to training using before-and-after brain maps to illustrate their improvement (Languis, 1988, 1989).

Just how long these changes observed by Languis survive from the newly-acquired academic and metacognitive skills that are reflected in students' brain maps is unclear at this time. Nor is it clear whether the training effects will require "booster shots" from time to time. Yet this area of research by Languis offers considerable promise as an approach for exploring the brain plasticity of children and adolescents because the approach provides a nonthreatening, non-invasive neuro-cognitive means of tracking the effects of instruction. Presently sixteen researchers throughout the United States are reported to be using Languis' procedure to gather normative data on the performance of students engaged in a range of school-related tasks in conjunction with recordings of their brain maps. Such a database may ultimately allow us to explore some of the limits which may be associated with hypothesized critical periods in prenatal development or sensitive periods in the development of the brain and mind during childhood and adolescence.

A final area of neuro-cognitive research which holds promise for advancing our understanding of readiness for school and for learning is that which focuses on the characteristics of children who are grouped at the upper end of the academic performance spectrum (i.e., gifted and talented) as well as those at the other end of the spectrum who find they cannot meet the academic demands of the regular classroom without special help. In this regard it is useful to consider the research of a small number of cognitive psychologists, neuropsychologists and pediatricians who study the range of variation in neurological and cognitive functioning and disorders that are associated with school success and failure among children and adolescents (Levine, 1989, 1990a, 1990b, 1993; Bernstein and Waber, 1990; Bernstein, 1990, 1991; Gardner, 1993).

The work of Levine (1990b) illustrates the relationship of studying special populations to our understanding of school readiness. Based on his study of the learning disorders found among early adolescents who were failing in middle school, Levine has described a neurodevelopmental framework which characterizes the degree to which some school failures experienced by early adolescents appear to be attributed to weaknesses in one or more of the following neurodevelopmental functions: 1) attention, 2) memory, 3) visual-spatial ordering, 4) temporal-sequential ordering, 5) language, 6) neuromotor function, 7) higher-order cognition, and 8) social cognition. Working with groups of middle school teachers, Levine has now developed materials for teachers which allow them to recognize many students' neurodevelopmental weaknesses and which guide teachers in making accommodations in instructional settings and academic demands placed on students who appear to have weaknesses in one or more of these neurodevelopmental functions. These materials are designed for children whose neurodevelopmental variations do not qualify them for Special Education support services under present guidelines.

Levine's work has focused on the early adolescent as a student failing in middle school, but as of this writing, Levine has broadened his focus to include younger children of elementary school age (1993). Clearly, a need also exists to understand the role that learning disorders of low severity play in the lack of readiness for learning among older adolescents of high school age who may have similar weaknesses in attention, memory, language, visual-spatial or temporal-sequential ordering, neuromotor functioning, and so forth, -- disorders that may contribute to their lack of readiness for the academic demands their teachers present.

While the causes of many learning disabilities are not fully understood, scientists think such disorders are frequently related to differences in the ways brains work. The next example illustrates the importance of a biological perspective for understanding school readiness. Chall and Peterson (1986) provide the following description of neurological damage associated with a serious reading disability:

"A young man died in an accident in the mid-1970s, and his death brought neuroscience and education one step closer together. As a child, the young man had suffered from a severe reading disability, and had achieved only a fourth-grade reading level after considerable schooling and special tutoring. An autopsy revealed abnormalities in his brain, particularly in those areas dealing with language.... In the years since Galaburda and Kemper (1979) reported this accidental death and the results of the autopsy, advances in the field of neuroscience have... increased the likelihood of collaboration between these two [neuroscience and education] fields." (Chall and Peterson, p. 287 in chapter, 'The Influence of Neuroscience upon Educational Practice' in The Brain, Cognition, & Education, Friedman, Klivington, & Peterson, Eds., 1986, Academic Press Inc. London Ltd.)

This second example is not intended to suggest that most children or adolescents who seem unready for school or learning--or who fail in school--may be learning impaired or brain damaged; it simply illustrates the value that studies of special populations contribute to our understanding of the entire population as well as our understanding of school readiness, by characterizing the nature of the neurodevelopmental functions which are essential for all children's success in school.

Through the process of developing instructional accommodations for students who have reaming disorders of low or moderate severity, we may then find that such accommodations also benefit a wider population of children or adolescents. The work of Montessori demonstrated this phenomenon nearly a century ago when she developed strategies and materials which improved learning for "special students." Today her programs benefit the general population and are considered by many to be the preferred enrichment program for preschoolers.

A third example which sheds light on the degree of natural variation in neurocognitive functioning is seen in the work of Gardner and his theory of multiple intelligences (1983, 1993). Gardner's theory is framed in a biological context of problem-solving skills that are alleged to be universal to the human species, and that are valued in one or more cultural settings. Seven "intelligences" are described: (a) musical, (b) bodily-kinesthetic, (c) logical-mathematical, often referred to as "scientific thinking", (d) linguistic, (e) spatial, (f) interpersonal, and (g) intrapersonal intelligences. Using documented historical biographies to illustrate exceptionalities in each of these intelligences, Gardner makes the case that all humans possess core abilities in each of the intelligences. Certain individuals are then recognized as "promising" because of their exceptional capacity in one or more of these intelligences while others are identified "at risk." Gardner argues that particular kinds of instruction can either be appropriate and nourish a child's exceptionality or undermine it.

"An exclusive focus on linguistic and logical skills in formal schooling can shortchange individuals with skills in other intelligences. It is evident from inspection of adult roles, even in language-dominated Western society, that spatial, interpersonal, or bodily-kinesthetic skills often play key roles. Yet linguistic and logical skills form the core of most diagnostic tests of 'intelligence' and are placed on a pedagogical pedestal in our schools." (Gardner, 1993, pp. 30-31)

The point of these three examples with regard to the relationship between school readiness and the study of special populations is the following: As one thinks about natural timetables for school readiness in general--or specifically considers the readiness of any individual child or adolescent for learning--it is crucial to have a clear understanding of the normal range of neurodevelopmental variations that exists among school-age children and adolescents, including those identified as gifted and talented in areas that are and are not assessed on popular "intelligence" tests, as well as students called "average" and those identified as unmotivated, failing, or having special needs.

Educators often take for granted the wide range of variations observed in children's physical development during early adolescence and yet fail to remember that a similarly wide range of variation characterizes their mind-brain or neuro-cognitive development. It is not uncommon in middle school classrooms for some children to have reached nearly adult height, weight and/or sexual maturity while other children still look more like fifth graders. Yet in spite of these observable physical differences, teachers sometimes think of early adolescents as being more or less equally capable in terms of cognitive demands, and suspect a lack of motivation when students differ in their capacities for academic skills on the "pedagogical pedestal" or when they have unrecognized neurodevelopmental weakness in functions such as attention or memory.

The study of special populations is essential to understanding of the full natural range of variations found in the population of children and adolescents, to an understanding of the neurodevelopmental timetables, and to an understanding of the degree to which combinations of neurodevelopmental strengths and weaknesses contribute to the heterogeneity or "bell-shaped curves" that characterize the populations of students found in schools and classrooms. This point will be explored further in the next and final sections of my paper.

The research discussed in this paper has been divided arbitrarily into four areas--natural timetables, critical and sensitive periods, brain plasticity, and the study of special populations--as a way of thinking about school readiness from a biological perspective; yet they are all part of one whole. I have tried to show how these four areas are related to one another, at least insofar as the topic of school readiness. If I were to draw one conclusion from the neuro-cognitive research described here, it would have to be stated as a working hypothesis:

The readiness of every child and adolescent for school or for learning is strongly influenced by two biological conditions over which the individual has no control. One biological condition is the maturational level of the individual's brain or neurological development itself, in terms of the range of normal or natural timetables for the development of various cognitive functions and in the sense that children's neurological development makes possible the emergence of cognitive functions which need to be "on-line and ready" to meet the academic demands posed by individual teachers. And the other biological condition over which the individual has no control is the degree to which his or her individual mind-brain architecture is attuned to the predominant mode of school instruction. Children who appear ready for school or ready to learn obviously possess capacities for attention and linguistic competence that match the attention requirements and predominantly linguistic modes of teaching that are characteristic of many school subjects. Similarly, children whose neurodevelopmental strengths lie in other less-linguistically skewed areas and/or who have less well-controlled attentional or memory mechanisms are in all likelihood perceived as less ready for school or learning, and as such are disadvantaged to varying degrees in most schools.

This working hypothesis is supported by the neuro-cognitive research cited here. First, with regard to natural neurodevelopmental timetables, it has been noted that different localized regions of the brain appear to manifest growth spurts at different times in an asymmetrical, yet complexly orchestrated manner. While we do not yet know how these differentially maturing areas of the brain are related to the range of specific cognitive processes that are required in school, we do know that they are related to academic success in some subjects which require logical and sequential reasoning. And while we do know how to adjust the curriculum to the neurodevelopmental variations that exist in some cases, we have a long way to go if we are to make better accommodations in most areas.

Presently, neurodevelopmental timetables which characterize the emergence of complex neurodevelopmental processes are largely uncharted, at least insofar as they are needed by educators to understand children's readiness for learning. With the availability of non-invasive technology such as that used by Languis for brain imaging, it is now possible to begin charting neurodevelopmental timetables and the range of neurodevelopmental variations found within age-groups, characterizing the emergence of various neuro-cognitive functions during childhood and adolescence in relation to the academic demands of school. Information about natural neurodevelopmental timetables would allow us to better approximate children's readiness for school or learning at various levels and to estimate their likelihood of success at each new segment (elementary, middle, and high school levels) of schooling.

In terms of research on critical periods and sensitive periods, it is known that critical periods exist in which normal human mind-brain development can be threatened by the presence of harmful substances or events (e.g., radiation, Rubella, alcohol and other drugs, lead, etc.) during prenatal and early postnatal development of the nervous system. Likewise, it has been known for decades that nutritional deficiencies can impair mental as well as physical development in childhood. Still we do not know the full extent to which undetected critical periods may exist which have the potential to threaten normal mind-brain development. We do not know what proportion of the range of learning disorders seen in school children might be related to events that occurred during undetected critical or sensitive periods in the early stages of development; but from the few examples of research on critical and sensitive periods which were cited, we can conclude that this area of research deserves increased attention, especially in view of increased numbers of substance-exposed children entering school each year.

In terms of research on the brain's plasticity, we have seen in the work of Languis that brain images of students can be changed over time following intensive training programs. Likewise, we have seen in the work of Tsunoda an example of the limits of the brain's plasticity at age nine for organizing specific information in the right and left hemispheres.

Finally, with regard to the study of special populations, we know from Levine's work that learning disorders of low severity account for some students' failures in middle school. However, we do not know if, or how, variations in brain-mind functioning might account for the range of individual differences that are observed in the "normal distribution" of grades or students' performance seen in most classrooms. Gardner's model of multiple intelligences helps to explain variations among individuals in the human neurodevelopmental talent pool; and we know that some individual children and adolescents adopt compensatory strategies to overcome their neurodevelopmental weaknesses while other students fail to recognize or compensate for identical weaknesses.

From the research reviewed here, one can conclude a need exists for more information about the range of neurodevelopmental variations in students' capacities for attention, perception, verbal and spatial sequencing, short-term and long-term memory, and other aspects of cognitive functioning before educators can provide instructional alternatives that will better accommodate students' needs. Before one can revise curricula, programs, and the perceptions of those who view failing students as bored, lazy, indifferent, or lacking motivation, educators need to know how to recognize instances when the neurodevelopmental demands of school programs are poorly matched to students' neurodevelopmental strengths and weaknesses.

It is seductive to suppose that a lack of school readiness or readiness for learning is an outcome--an artifact or epiphenomenon--which shows up because various teachers and curriculum developers along the way between preschool and high school have not known how to address the richly diverse learning needs of students who represent some part of the natural neurodevelopmental variation that exists in the normal population. But that view places the educators' cart before the neuro-cognitive scientists' horse. Nearly 200 years of teachers' good intentions combined with trial and error have produced a rough approximation of natural timetables for school readiness and readiness for learning various content at certain ages; but society cannot afford to have 10% to 40% of its population fail at school. Trial and error is no longer an acceptable process.

The neuro-cognitive sciences have the potential to provide a much needed conceptual framework for viewing school readiness and school success during childhood and adolescence by mapping natural timetables for neuro-cognitive-pedagogical development from childhood to adolescence, and by characterizing the normal range of neurodevelopmental variations within populations of children and adolescents.

As one reflects broadly on the evolution of free public education in the United States, it becomes apparent that our knowledge about human development and human capacities for learning often lags far behind our desire for social action and responsibility with regard to education. In the late 1800s when a free public education for "all Americans" was extended to include children of poverty and children of immigrants who previously had been excluded, teachers found themselves overwhelmed by the consequent increased range of their students' readiness for learning. With the current second major wave of immigration in our nation's history, schools again are struggling to accommodate the increased range of children's readiness levels for school and for learning in American classrooms.

Similarly, during the twentieth century as society has expanded educational opportunities to children with a range of handicapping conditions, and especially as one traces legislation through the 1970s, 1980s and 1990s regarding learning disabled or otherwise handicapped students, one also finds schools struggling to meet the needs of a wider range of readiness indicators for learning.

Social needs frequently have outstripped the production of knowledge required to act responsibly, and that is the case in both of the examples above. Yet, there is reason for optimism: it is argued that the nation can improve the readiness of its children and adolescents for success in school. A first step would be to advance knowledge about the biological basis for readiness to meet various kinds of academic demands.

Variation in the biological world represents the natural distribution of strengths and vigor that are needed to ensure a species' survival. If the natural range of neurodevelopmental variation that one might expect to find in a typical school-aged population represents a valuable range of survival skills for the population, then educators perhaps should be expected to help students and society find ways to accommodate, encourage and develop students' varied strengths in schools rather than to focus on their weaknesses. The unique contribution that the neuro-cognitive sciences can offer toward further understanding of school readiness is to characterize natural timetables for neuro-cognitive-pedagogical development for school-aged children and adolescents, and to describe the normal range of neurodevelopmental variations within populations of children and adolescents.

Back-y-Rita, P. (1982). Human brain plasticity: Mechanisms for alteration of neural functions. Paper presented at the annual meeting of the American Association for the Advancement of Science, Washington, D.C.

Baddeley, A. (1992). Working memory. Science, 255, 556-559.

Baillargeon, R. (1991). Pioneering research challenges accepted notions concerning the cognitive abilities of infants. In Raymond, C.: The chronicle of higher education, Jan. 23.

Barinaga, M. (1990). Neuroscience models the brain. Science, 247, 524-526.

Barnes, D.M. (1987). Neural models yield data on learning. Science, 236, 1628-1629.

Bauer, P J. (1991). Pioneering research challenges accepted notions concerning the cognitive abilities of infants. In Raymond, C. The chronicle of higher education, Jan. 23.

Bellugi, U. (1987). Language research: new views of how the brain works. The Salk Institute for Biological Studies: Research Report (summer), San Diego CA.

Bellugi, U., Poizner, H., Klima, E. S. (1989). Language, modularity and the brain. Trends in Neurosciences, 12 (10), 380-388.

Bernstein, J. H. (1990). The learning dis-labelled child: new perspectives of assessment and management. Conference, Costa Mesa, CA.

Bernstein, J. H. and Waber, D.P. (1990). Developmental neuropsychological assessment: the systemic approach. In Boulton, A,A.; Baker, G.B.; Hisscock, M., Eds. Neuromethods: 17, Neuropsychology. Clifton, N.J., Humana Press.

Bernstein, J. H. (1991) Personal communication.

Blakemore, C. (1982). Developmental plasticity in the brain: A parable for education. Paper presented at symposium on The Brain Sciences and Education, Organized by R. W Peterson. Annual meeting of the American Association for the Advancement of Science, Washington, D.C. and personal communication.

Denkla, M. (1991). The brain and learning--knowledge of differences: the value and caution. "The art and science of learning conference" sponsored by the U. S. Office of Educational Research and Improvement, Washington, D.C., January.

Friedman, SL.; Klivington, K. A.; Peterson, R. W. (I 986). The brain, cognition, and education. Orlando, FL., Academic Press, Incorporated.

Gardner, H. (I 993). Multiple intelligences: The theory in practice. New York, Basic Books, Incorporated, Publishers.

Gardner, H. (1983). Frames of mind. The theory of multiple intelligences. New York, Basic Books, Incorporated, Publishers.

Gazzaniga, M. S. (1988). Mind matters: How the mind and brain interact to create our conscious lives. Boston, Houghton Mifflin Company.

Goldman-Rakic, P. S.(1989). Comparison of human infants and rhesus monkeys on Piaget's AB task: evidence for dependence on dorsolateral prefrontal cortex. Experimental Brain Research, 74(l), 24-40.

Goldman-Rakic, P. S.(1981). Conversation at conference on the brain, cognition, and education, sponsored by the National Institute of Education, the National Science Foundation, and the Alfred P. Sloan Foundation, Washington, D.C.

Goldman-Rakic, P. (1986). Setting the stage: Neural Development before birth. In Friedman, S.L., Klivington, K. A, Peterson, R. W, The brain, cognition, and education. Orlando, Fl., Academic Press, Incorporated.

Gordon, H. W. (1988a). Specialized cognitive function and school achievement. Developmental Neuropsychology, 4(3), 239-257.

Gordon, H. W. (1988b). The effect of right brain/left brain cognitive profiles on school achievement. In Molfese, D.L.; Segalowitz, S.J., Eds. Brain lateralization in children. New York, The Guilford Press.

Gordon, H. W (I 9 8 9). Hemisphericity and its validity for education, vocation, and cognitive style. International Journal of Neuroscience, 47, 47-55.

Hamilton, D.P. (1992). NASA brainstorms a neuroscience shuttle. Science, 257, 603.

Harness, B. Z.; Epstein, R.; Gordon, H. W (1984). Cognitive profile of children referred to a clinic for reading disabilities. Journal of Learning Disabilities, 17 (6).

Hess, E. H. (1 966). In Marler, P., Hamilton, W J., Mechanisms of animal behavior. New York, John Wiley & Sons, Inc., 632-637.

Janowsky, J. S.; Shimamura, A. P; Squire, L. R. (1989). Source memory impairment in patients with frontal lobe lesions. Neuropsychologia, 27 (8) 1043-1056.

Kandel, E. R. (1990) Molecular and structural approaches to long-term memory. Fourth conference to the neurobiology of learning and memory, Memory: organization and locus of change, Irvine, CA.

Klein, J. T (1990). Interdisciplinarity: history, theory, and practice. Wayne State University Press, Detroit.

Klivington, K. A. (1992). What do we know about natural timetables for school readiness? Emerging evidence from the neural and cognitive sciences. Conference for school readiness sponsored by the U.S. Department of Health and Human Services, Washington, D.C.

Klivington, K. A. (1989). The science of mind. Cambridge, MA, The MIT Press.

Knolle, L.; Gordon, H. W; Gwany, D. (1987). Relationship between performance and preference measures of cognitive laterality. Psychological Reports, 61, 215-223.

Kosslyn, S.M. (1988). Aspects of a cognitive neuroscience of mental imagery. Science, 240, 1621-1626.

Kraft, R. H.; Mitchell, R. O.; Languis, M. L.; Wheatly, G. H. (1 980). Hemispheric asymmetries during 6- to eight-year-olds' performance of Piagetian conservation and reading tasks. Neuropsychologia, 18, 637-643.

Lamm, O.; Gordon, H. W. (1984). Right hemisphere superiority in processing new symbols for arithmetic operators. Acta Psychologia, 57, 29-45.

Languis, M. L.; Wittrock, M. C (1986). Integrating neuropsychology and cognitive research: a perspective for bridging brain-behavior relationships. In Obrzut, J. E.; Hynd, G. E., Eds. Child neuropsychology (1) theory and research. Academic Press.

Languis, M. L. (1988-1990). Personal communication.

Levine, M.D. (1993). All kinds of minds: A young student’s book about learning abilities and learning disorders. Cambridge, MA: Educators Publishing Service.

Levine, M.D. (1992a). Developmental demands over time: some evolving and cumulative school-related expectations. Cambridge, MA: Educators Publishing Service.

Levine, M.D. (1992b). Readiness as an ongoing process: what have we learned from "unready" older children? Conference on school readiness sponsored by the U.S. Department of Health and Human Services, Washington, D.C.

Levine, M.D. (1990a). Keeping a head in school: a students’ book about learning abilities and learning disorders. Cambridge, MA: Educators Publishing Service.

Levine, M.D. (1990b). The learning dis-labelled child. Conference, Costa Mesa, CA.

Lorenz, K. (1931-1942). Studies in animal and human behavior, Vol. I. Translated by R. Martin, Cambridge, MA Harvard University Press, 1970.

MacKinnon, D. F.; Squire, L. R. (1989). Autobiographical memory and amnesia. Psychobiology, 17(3), 247-256.

Matousek, M.; Petersen, I. (1973). In Kellaway, R; Petersen, I, Eds. Automation of Clinical Electroencephalography. New York: Raven, 75-102.

McGaugh, J. (1990). Fourth conference on the neurobiology of learning and memory, University of California, Irvine, CA; personal communication.

Nelson, C. A. (I 99 1). Pioneering research challenges accepted notions concerning the cognitive abilities of infants. In Raymond, C. The chronicle of higher education, Jan. 23.

Neville, H. (1990). Personal communication at The Salk Institute for Biological Studies, San Diego, CA.

Petitto, L. A.; Marentette, P F. (1 99 1). Babbling in the manual mode: Evidence for the ontogeny of language. Science, 251, 1493-1496.

Peterson, R. W. (1993). The search for neuro-cognitive models to guide research in science education. Paper presented at the annual meeting of the National Association for Research in Science Teaching, Atlanta.

Peterson, R. W and Chall, J. S. (1986). The influence of neuroscience upon educational practice. In Friedman, S.L.; Klivington, K. A.; and Peterson, R. W., Eds. The brain, cognition, and education. Academic Press, Incorporated.

Piaget, J. (1950). The psychology of intelligence. Translated by M. Piercy and D. Berlyne. London: Routledge & Kegan.

Piaget, J. and Inhelder, B. (1958). The growth of logical thinking from childhood to adolescence. Translated by A. Parsons and S. Milgram. New York: Basic Books.

Piaget, J. (1971). Biology and knowledge: An essay on the relations between organic regulations and the cognitive processes. Chicago, IL., The University of Chicago Press.

Piaget, J. (1972). Judgment and reasoning in the child. Totowa, N.J., Littlefield, Adams, and Company.

Piaget, J. (1974). The language and thought of the child. New York, N.Y, The New American Library, Incorporated.

Raichle, M. E. (1990). Modular organization of information processing in the normal human brain: Studies with positron emission tomography. Fourth conference on the neurobiology of learning and memory, Memory: organization and locus of change, Irvine CA.

Rauschecker, J. P. and Marler, P. (1987). Cortical Plasticity and Imprinting, (especially Chapter 15: Behavioral and Physiological contrasts and Parallels), Wiley Series in Neuroscience, John Wiley & Sons, New York.

Roberts, L, (1991). A call to action on a human brain project. Science, 252, 1794.

Roland, P. (1990). Structures in the human brain participating in visual learning, motor learning, and tactile learning. Fourth conference on the neurobiology of learning and memory, Memory organization and locus of change, Irvine, CA

Shephard, T. H. (1992). Catalog of Teratogenic Agents, Seventh Edition. Johns Hopkins Press.

Sochurek, H. (I 987) Medicine's new vision. National Geographic, 1771(l) 2-41.

Sokolov, E. N.(1990). Local plasticity in neuronal learning. Fourth conference on the neurobiology of learning and memory, Memory: organization and locus of change, Irvine, CA.

Spelke, E. S. (1991). Pioneering research challenges accepted notions concerning the cognitive abilities of infants. In Raymond, C., The chronicle of higher education, Jan. 23.

Sperry, R. W, Gassiniga, M. S. (1966) Language following disconnection of the hemispheres. In W L. Darley (Ed.), Brain mechanisms underlying speech and language. New York: Grune & Stratton.

Squire, L. R. (1990). Personal communication at University of California, San Diego, CA.

Squire, L. R.; Press, G.A.; Amaral, D. G. (1989). Hippocampal abnormalities in amnesic patients revealed by high-resolution magnetic resonance imaging. Mature, 341 (6237) 54-57.

Squire, L.R. (1987). Memory and brain. New York: Oxford University Press.

Thatcher, R. W; Walker, R. A.; Guidice, S., (1987). Human cerebral hemispheres develop at different rates and ages. Science, 236, 1110-1113.

Tsunoda, T. (1989). Hemispheric dominance in Japan and the West, The science of mind, K. Klivington, Ed. Cambridge, MA, The MIT Press.

Tulving, E. (1990). Concepts of human memory. Fourth conference on the neurobiology of learning and memory: Memory: organization and locus of change, Irvine, CA.

Tulving, E.; Schacter, D.L. (1990). Priming and human memory systems. Science, 247, 301-306.

Vaid, J.; Bellugi, U.; Poizner, H. (1989). Hand dominance for signing: Clues to brain lateralization of language. Neuropsychologia, 27, 949-960.

Winget, (1993). Personal communication.

Wittrock, M. C. (1980). The Brain and Psychology. New York: Academic Press.

Zigler, E. and Muenchow, S. (1992). Head Start: The Inside Story of America’s Most Successful Educational Experiment. New York: Basic Books.

This article was originally published in Early Education and Development, volume 5 number 2, April 1994, pp. 120-40. The article is reproduced with the permission of Wide Range, Inc., the publisher of Early Education and Development.