Abstract
Age related differences in quantified electrophysiological measures of interhemispheric EEG coherence were studied in 371 subjects (171 males and 200 females), ages 20-80, all of whom were judged to be optimally healthy. Principal components analysis (PCA) was performed on interhemispheric coherence of Laplacian referenced data from eight homologous left-right electrode pairs, from 0.5 to 32 Hz. Regression procedures, using signals from artifact monitoring channels, were used to minimize effects of eye movement and muscle artifact. Forty-six factors described 80% of the total variance, with electrode location the primary source of communality in factor formation. Within 350 right-handed subjects, results indicated a broad trend for decreased interhemispheric coherence with advancing age. Using canonical correlation, the coherence-based factors also successfully predicted spectral variables, previously found to maximally illsutrate age- related EEG desynchronization. We speculate that age-related reduction of interhemispheric coherence may in part explain age-related EEG desynchrony and stems from age-related reduction of cortical connectivity. Gender differences in interhemispheric coherence were also evident. Females demonstrated higher interhemispheric coherence than males. Within a smaller subpopulation of 63 subjects (21 left and 42 right handed), there was a gender-by-handedness interaction, with higher interhemispheric coherence in right-handed females than right-handed males and the reverse in left-handed male and female subjects.
Original language | English (US) |
---|---|
Pages (from-to) | 587-599 |
Number of pages | 13 |
Journal | Neurobiology of aging |
Volume | 17 |
Issue number | 4 |
DOIs | |
State | Published - 1996 |
Externally published | Yes |
Keywords
- Age
- Analysis of variance
- Canonical correlation
- Corpus callosum
- Gender
- Handedness
- Healthy adults
- Interhemispheric coherence
- Principal components analysis
- Quantitative EEG
ASJC Scopus subject areas
- Neuroscience(all)
- Aging
- Clinical Neurology
- Developmental Biology
- Geriatrics and Gerontology