Ecology and neurophysiology of sleep in two wild sloth species

Study Objectives: Interspecific variation in sleep measured in captivity correlates with various physiological and environmental factors, including estimates of predation risk in the wild. However, it remains unclear whether prior comparative studies have been confounded by the captive recording environment. Herein we examine the impact of predation pressure on sleep in sloths living in the wild. Design: Comparison of two closely related sloth species, one exposed to predation and one free from predation. Setting: Panamanian mainland rainforest (predators present) and island mangrove (predators absent). Participants: Mainland (Bradypus variegatus, 5 males and 4 females) and island (Bradypus pygmaeus, 6 males) sloths. Interventions: None. Measurements and Results: EEG and EMG activity were recorded using a miniature data logger. Although both species spent between 9 and 10 hours per day sleeping, the mainland sloths showed a preference for sleeping at night, whereas island sloths showed no preference for sleeping during the day or night. EEG activity during NREM sleep showed lower low-frequency power, and increased spindle and higher frequency power in island sloths when compared to mainland sloths. Conclusions: In sloths sleeping in the wild, predation pressure influenced the timing of sleep, but not the amount of time spent asleep. The preference for sleeping at night in mainland sloths may be a strategy to avoid detection by nocturnal cats. The pronounced differences in the NREM sleep EEG spectrum remain unexplained, but might be related to genetic or environmental factors.

Quantifying consistency of Event Related Potentials across subjects based on single-trial topographic analysis

Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.