Modified Wavelet Analyses Permit Quantification of Dynamic Interactions Between Ultradian and Circadian Rhythms

Area of Science:

• Chronobiology
• Signal Processing
• Animal Behavior

Background:

• Ultradian rhythms, biological cycles shorter than 24 hours, are ubiquitous but challenging to quantify due to their complex properties.
• Existing methods for analyzing ultradian rhythms are often idiographic, limiting group-level comparisons and experimental analysis.

Purpose of the Study:

• To develop and validate novel wavelet-based analytical approaches for precise and accurate quantification of ultradian rhythms.
• To enable group-level analyses of ultradian rhythms, facilitating the study of their modulation by various factors.

Main Methods:

• Application of discrete and continuous wavelet transforms for quantifying ultradian power distribution and identifying periods.
• Aggregation of normalized wavelet matrices for group-level analyses.
• Validation using in silico and in vivo models, including locomotor activity in mice.

Main Results:

• The novel wavelet methods accurately and precisely quantified ultradian period and power in mouse locomotor activity.
• Ultradian rhythms were modulated by sex, gonadal hormones, and circadian entrainment, with sex differences more pronounced at night.
• Seasonal changes in day length influenced ultradian rhythms, with opposing effects in light and dark phases.

Conclusions:

• Modified wavelet procedures provide accurate, repeatable, and group-analyzable measures of ultradian rhythms.
• These tools enhance the understanding of ultradian rhythm generation and responses to internal and external cues.
• The findings highlight the importance of considering circadian phase when studying ultradian rhythms.