Correction: Sleep architecture and lying behavior in horses across age groups and two housing systems: an overnight non-invasive EEG study.

Sleep patterns and lying behavior in horses were studied across different age groups and housing conditions using a non-invasive overnight EEG method to better understand how these factors influence equine sleep architecture.

Introduction and Purpose

• The study aims to investigate sleep architecture and lying behavior in horses across various age groups and two different housing systems.
• Sleep architecture refers to the structure and pattern of sleep stages, typically analyzed using EEG (electroencephalogram) recordings.
• Non-invasive overnight EEG technology was utilized to monitor horses’ brain activity during sleep without causing stress or discomfort.
• The study aims to establish how age and housing environment affect the quality and characteristics of sleep in horses.

Methodology

• Participants: Horses from multiple age groups to evaluate developmental and aging-related differences in sleep behavior and physiology.
• Housing Systems: Two distinct types of housing environments were selected to see how different living conditions impact sleep.
• Data Collection: Non-invasive EEG devices were implemented overnight to continuously record brain activity during natural sleep cycles.
• Additional measurements of lying behavior (time spent lying down, posture, sleep position) were recorded and correlated with EEG data.
• All procedures were designed to minimize disturbance and comply with welfare standards.

Findings

• Age-related differences were observed in sleep architecture parameters, indicating that younger and older horses have distinct sleep patterns.
• Housing system influenced the amount and quality of sleep, with certain environments promoting more restorative sleep stages.
• Lying behavior varied according to both age and housing, showing that physical and environmental factors interplay to affect comfort and sleep quality.
• The use of non-invasive EEG proved effective in capturing detailed sleep data without negatively affecting the horses’ natural behaviors.

Significance and Implications

• The study provides new insights into the natural sleep behaviors of horses, an area previously less understood due to technical and ethical challenges.
• Sleep quality and architecture are important indicators of welfare; understanding these helps improve equine management practices.
• Results highlight the impact of environmental enrichment and housing design on animal health, particularly for aging horses.
• The methodology can be applied in further studies to assess interventions aimed at enhancing equine sleep and overall wellbeing.

Correction Note

• This explanation pertains to a correction of a previously published article identified by DOI 10.3389/fvets.2026.1898580.
• The correction ensures accuracy in reporting the study’s data or methodology, but the core findings and conclusions remain relevant.