Gamma distribution model describes maturational curves for delta wave amplitude, cortical metabolic rate and synaptic density*

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We analyzed the available ontogenetic data (birth to 30 years of age) for: amplitude of delta EEG (DA) waves during sleep; cortical metabolic rate (CMR) measured with positron emission tomography; and synaptic density (SD) in frontal cortex. Each is at the adult level at birth, increases to about twice this level by 3 years of age, and then gradually falls back to the adult level over the next two decades. Statistical analyses revealed that individual gamma distribution models fit each data set as well as did the best ad hoc polynomial. A test of whether a single gamma distribution model could describe all three data sets gave good results for DA and CMR but the fit was unsatisfactory for SD. However, because so few data were available for SD, this test was not conclusive.

We proposed the following model to account for these changes. First, cortical neurons are stimulted by birth to enter a proliferative state (PS) that creates many connections. Next, as a result of interactions in the PS, neurons are triggered into a transient organizational state (OS) in which they make enduring connections. The OS has a finite duration (minutes to years), and is characterized by high rates of information-processing and metabolism. Levels of CMR, SD and DA, therefore, are proportional to the number of neurons in the OS at any time. Thus, the cortex after birth duplicates, over a vastly greater time scale, the overproduction and regression of neural elements that occurs repeatedly in embryonic development.

Finally, we discussed the implications of post-natal brain changes for normal and abnormal brain function. Mental disorders that have their onset after puberty (notably schizophrenia and manic-depressive psychoses) might be caused by errors in these late maturational processes. In addition to age of onset, this neurodevelopmental hypothesis might explain several other puzzling features of these subtle disorders.

References (27)

  • FeinbergI. et al.

    Sleep variables as a function of age in man

    Arch. gen. Psychiat.

    (1968)
  • FeinbergI. et al.

    Changes in EEG amplitude during sleep with age

  • FeinbergI. et al.

    Late maturational decline in delta (0–3 Hz) EEG amplitude during sleep: a reflection of synaptic elimination?

    Soc. Neurosci. Abs.

    (1989)
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    *

    This research was supported by Veterans Administration research funds and by National Institutes of Health (Bethesda, MD) grant 5RO1 AG07224 (to 1F) and by MHSB 2 R44 MH43066 (to JDM).

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