A comparison of techniques for identifying recurrent patterns of behavioral state in neonates

While a variety of researchers have identified periodic recurrences in infant behavioral state with various time-series techniques, the appropriateness of techniques which identify periodic recurrences in all infants at all ages have been questioned. The purpose of this study was to compare the utility of four time-series techniques used in the analysis of periodic recurrences in the behavioral state of 21 newborns during a 2 hour observation period. For quiet sleep, active sleep and awake states the period length of the major rhythm was estimated by 1) binary spectrum analysis, 2) binary autocorrelation, 3) renewal time analysis, and 4) kappa analysis. Repeated measures analysis of variance showed that the period lengths identified by renewal time analysis were significantly shorter than those identified by the other three techniques for quiet and active sleep. Further, the kappa analysis and binary autocorrelation showed that awake states were significantly shorter than both active sleep and quiet sleep. Pearson product-moment correlations showed that the relation between the periods for a given state identified by each analysis ranged from .01 to .83. The results indicate that 1) renewal time analysis is more sensitive to state interruptions than the other techniques, 2) awake states may have a different period length than either quiet sleep or active sleep, and 3) although the four techniques identified state recurrences in almost all of the neonates, only a smaller subgroup of neonates displayed a pattern of technique agreement that would indicate a clearly rhythmic pattern of states.