And if we measure across time rather than space, we also see fractal patterns in the moment-to-moment fluctuations in physiologic signals, including heart and breathing rates, blood pressure, brain waves, and hormonal secretions. Contrary to what you might expect, these fluctuations don’t follow regular, or periodic, patterns, but instead show a complex type of variability—what’s known as “deterministic chaos.” Although the oscillations are irregular, they appear self-similar when observed over seconds, minutes, hours, or days. Another common metric of complexity, known as “multiscale entropy,” typically applies to processes, such as the beat-to-beat variability of your heart rate or the moment-to-moment postural shifts your body makes when balancing in a standing position. Multiscale entropy calculates the likelihood that a measured pattern repeats over various scales of time. Patterns with very low likelihood of repetition, such as white noise or randomness, aren’t very complex. Neither are patterns with high likelihood of repetition over a single time scale, such as the sinusoidal tick of a metronome. Patterns likely to have similarities across many different time scales, however, are more fractal-like, and hence more complex. A large and growing body of research suggests that biological complexity diminishes with aging, as various tissues and organs, and their communication pathways, gradually break down. The fractal-like networks of tissue in our brains, bones, kidneys, and skin all lose structural complexity as we age. This loss impairs their capacity to adapt to stress, and may eventually lead to disease or disability. For example, when the microscopic struts in bone tissue thin and disconnect, as occurs with osteoporosis, bones become brittle and prone to fracturing. Likewise, the pruning of neural connections in the brain is associated with age-related neurodegenerative disorders, such as Alzheimer’s and Parkinson’s diseases.