Background Dysregulation of the hypothalamic‐pituitary‐adrenal (HPA) axis is associated with poor physical and mental health. Early‐life adversity may dysregulate cortisol response to subsequent stress. This study examines the association between patterns of maternal behavior and infant stress response to a challenge. Specifically, we test whether infant exposure to unpredictable maternal sensory signals is related to the cortisol response to a painful stressor. Method Participants were 102 mothers and their children enrolled in a longitudinal study. Patterns of maternal sensory signals were evaluated at 6 and 12 months during a 10‐min mother–infant play episode. Entropy rate was calculated as a quantitative measure of the degree of unpredictability of maternal sensory signals (visual, auditory, and tactile) exhibited during the play episode. Infant saliva samples were collected for cortisol analysis before and after inoculation at 12 months. Results Unpredictable patterns of maternal sensory signals were associated with a blunted infant cortisol response to a painful stressor. This relation persisted after evaluation of covariates including maternal sensitivity and maternal psychological distress. Conclusions This study provides evidence that unpredictable patterns of maternal sensory signals are one process through which caregiving affects the function of infant stress response systems.

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The Growing Point Language (GPL) is used to engineer the emergent behaviour of an amorphous computer. GPL patterns are topologically one-dimensional objects, regardless of the dimension of the space in which the system exists. A crude length measure in GPL means that GPL patterns also have a geometric character to them. One of the constructs defined in GPL (diatropisim), directs a growing point to propagate tangentially to the level curve of a spatial distribution called a pheromone. In 2-dimensions, tangent spaces are 1-dimensional and therefore diatropism is reasonably well defined. However, in 3-dimensions (and higher) diatropismis no longer confined to 1-dimension, which means that some programs whose behaviour was well understood in 2-dimensional systems, become less so in higher dimensions. We argue that the predictability of the geometric properties of a GPL program in 3-dimensions can be completely recovered. We support this argument with the presentation of a program that given a centre point, a direction, and a radius will generate a circular path in the plane containing the centre, that is normal to the given direction. We provide quantitative data from a single run to illustrate how well the geometric objectives can be achieved.