Sleep spindles are phasic bursts of thalamo-cortical activity, visible in the cortex as transient oscillations in the sigma range (usually defined in humans as 12–14 or 9–16 Hz). They have been associated with sleep-dependent memory consolidation and sleep stability in humans and rodents. Occurrence, frequency, amplitude and duration of sleep spindles co-vary with age, sex and psychiatric conditions. Spindle analogue activity in dogs has been qualitatively described, but never quantified and related to function. In the present study we used an adjusted version of a detection method previously validated in children to test whether detections in the dogs show equivalent functional correlates as described in the human literature. We found that the density of EEG transients in the 9–16 Hz range during non-REM sleep relates to memory and is characterized by sexual dimorphism similarly as in humans. The number of transients/minute was larger in the learning condition and for female dogs, and correlated with the increase of performance during recall. It can be concluded that in dogs, automatic detections in the 9–16 Hz range, in particular the slow variant (<13 Hz), are functional analogues of human spindles.

Non-REM bursts of activity in the sigma range (9–16 Hz) typical of sleep spindles predict learning in dogs, similar to humans and rats. Little is known, however, about the age-related changes in amplitude, density (spindles/minute) and frequency (waves/second) of canine spindles. We investigated a large sample (N = 155) of intact and neutered pet dogs of both sexes, varying in breed and age, searching for spindles in segments of non-REM sleep. We recorded EEG from both a frontal midline electrode (Fz) and a central midline electrode (Cz) in 55.5% of the dogs, in the remaining animals only the Fz electrode was active (bipolar derivation). A similar topography was observed for fast (≥13 Hz) spindle occurrence as in humans (fast spindle number, density on Cz > Fz). For fast spindles, density was higher in females, and increased with age. These effects were more pronounced among intact animals and on Fz. Slow spindle density declined and fast spindle frequency increased with age on Cz, while on Fz age-related amplitude decline was observed. The frequency of fast spindles on Fz and slow spindles on Cz was linked to both sex and neutering, suggesting modulation by sexual hormones. Intact females displayed higher frequencies than males and neutered females. Our findings support the argument that sigma bursts in the canine non-REM sleep are analogous to human sleep spindles, and suggest that slow and fast spindles display different trajectories related to age, of which an increase in frontal fast spindles is unique to dogs.

The gaze of other dogs and humans is informative for dogs, but it has not been explored which factors predict face-directed attention. We used image presentations of unfamiliar human and dog heads, facing the observer (portrait) or facing away (profile), and measured looking time responses. We expected dog portraits to be aversive, human portraits to attract interest, and tested dogs of different sex, skull length and breed function, which in previous work had predicted human-directed attention. Dog portraits attracted longer looking times than human profiles. Mesocephalic dogs looked at portraits longer than at profiles, independent of the species in the image. Overall, brachycephalic dogs and dogs of unspecified breed function (such as mixed breeds) displayed the longest looking times. Among the latter, females observed the images for longer than males, which is in line with human findings on sex differences in processing faces. In a subsequent experiment, we tested whether dog portraits functioned as threatening stimuli. We hypothesized that dogs will avoid food rewards or approach them more slowly in the presence of a dog portrait, but found no effect of image type. In general, older dogs took longer to approach food placed in front of the images and mesocephalic dogs were faster than dogs of other skull length types. The results suggest that short-headed dogs are more attentive to faces, while sex and breed function predict looking times through complex interactions.

Over the last few years, several efforts have been undertaken to characterize the aging process in dogs. In the present study, we evaluate a short protocol measuring dogs’ cognitive, social, and physical capacities. Our aim was to develop a feasible test battery, with minimal pre-training requirements, no complex devices, and which is set outdoors (i.e., a specific testing room is not needed). As ageing in dogs is usually associated with a decrease in activity, we also assessed the personality trait activity/excitability with a dog personality questionnaire. Four subtests proved sensitive to the dogs’ age. In particular, old dogs displayed less approaching and following behaviors toward an unknown but friendly human, showed both less avoidance and interest toward a novel object, looked less at the owner when faced with an unsolvable problem, and performed worse on the short-term memory task. Previous test procedures for investigating age-related changes involve expensive and/or complicated devices and extensive pre-training. The main advantage of the proposed battery is to reduce costs and efforts in veterinary assessments. Further tests in same-breed, large samples and between dogs with mild and severe cognitive impairments will be needed in order to further validate the battery.

In both humans and dogs sleep spindle occurrence between acquisition and recall of a specific memory correlate with learning performance. However, it is not known whether sleep spindle characteristics are also linked to performance beyond the span of a day, except in regard to general mental ability in humans. Such a relationship is likely, as both memory and spindle expression decline with age in both species (in dogs specifically the density and amplitude of slow spindles). We investigated if spindle amplitude, density (spindles/minute) and/or frequency (waves/second) correlate with performance on a short-term memory and a reversal-learning task in old dogs (> 7 years), when measurements of behavior and eeG were on average a month apart. Higher frequencies of fast (≥ 13 Hz) spindles on the frontal and central midline electrodes, and of slow spindles (≤ 13 Hz) on the central midline electrode were linked to worse performance on a reversal-learning task. The present findings suggest a role for spindle frequency as a biomarker of cognitive aging across species: changes in spindle frequency are associated with dementia risk and onset in humans and declining learning performance in the dog.Sleep spindles are brief trains of rhythmic activity, at least half a second in duration 1 and maximally 6 seconds long 2 , which appear in the EEG signal of humans 3,4 and other mammals 5 during non-REM sleep, in particular stage 2 of non-REM sleep in humans. They are commonly distinguished in a slow (predominantly frontal, ≤ 13 Hz) and fast (≥ 13 Hz, predominantly central and posterior) subtype 6 .One promising model animal in comparative sleep spindle research is the dog (Canis familiaris). A shared anthropogenic environment and evolutionary adaptation to its dynamics 7 characterize dogs as an animal model for human conditions in general 8 , and they have specifically been argued a favorable model in comparative neuroscience as well 9 . Moreover, there is recent evidence 10,11 that, in dogs, transients oscillating in the 9-16 Hz frequency range, corresponding to the broad definition of the sigma band or spindling frequency in humans 12,13 , are analogous to human sleep spindles (See Table 1 for an overview of these analogies and the associated literature).As a note of caution, regarding spindle-cognition associations in general, detection methods for sleep spindles tend to correlate poorly with each other 14,15 which is challenging to the comparability between studies. In addition, sleep spindles also appear to display a link to memory consolidation and learning only under specific circumstances. The distance of the to-be-learned material to prior knowledge 16,17 , the exact stage of non-REM sleep in which spindles are measured 18 and the timing relative to cortical up-states and ripples 17-19 all seem to have an influence. In light of this it is not surprising that associations between sleep spindles and learning are not always replicated 20 . Considering the controversy about the comparability of different spindle detection m...

Non-invasive polysomnography recording on dogs has been claimed to produce data comparable to those for humans regarding sleep macrostructure, EEG spectra and sleep spindles. While functional parallels have been described relating to both affective (e.g., emotion processing) and cognitive (e.g., memory consolidation) domains, methodologically relevant questions about the reliability of sleep stage scoring still need to be addressed. In Study 1, we analyzed the effects of different coders and different numbers of visible EEG channels on the visual scoring of the same polysomnography recordings. The lowest agreement was found between independent coders with different scoring experience using full (3 h-long) recordings of the whole dataset, and the highest agreement within-coder, using only a fraction of the original dataset (randomly selected 100 epochs (i.e., 100 × 20 s long segments)). The identification of drowsiness was found to be the least reliable, while that of non-REM (rapid eye movement, NREM) was the most reliable. Disagreements resulted in no or only moderate differences in macrostructural and spectral variables. Study 2 targeted the task of automated sleep EEG time series classification. Supervised machine learning (ML) models were used to help the manual annotation process by reliably predicting if the dog was sleeping or awake. Logistic regression models (LogREG), gradient boosted trees (GBT) and convolutional neural networks (CNN) were set up and trained for sleep state prediction from already collected and manually annotated EEG data. The evaluation of the individual models suggests that their combination results in the best performance: ~0.9 AUC test scores.

Sleep spindles are phasic events observed in mammalian non-rapid eye movement sleep. They are relevant today in the study of memory consolidation, sleep quality, mental health and ageing. We argue that our advanced understanding of their mechanisms has not exhausted the utility and need for animal model work. This is both because some topics, like cognitive ageing, have not yet been addressed sufficiently in comparative efforts and because the evolutionary history of this oscillation is still poorly understood. Comparisons across species often are either limited to referencing the classical cat and rodent models, or are over-inclusive, uncritically including reports of sleep spindles in rarely studied animals. In this review, we discuss the emergence of new (dog and sheep) models for sleep spindles and compare the strengths and shortcomings of new and old models based on the three validation criteria for animal modelsface, predictive, and construct validity. We conclude that an emphasis on cognitive ageing might dictate the future of comparative sleep spindle studies, a development that is already becoming visible in studies on dogs. Moreover, reconstructing the evolutionary history of sleep spindles will require more stringent criteria for their identification, across more species. In particular, a stronger emphasis on construct and predictive validity can help verify if spindle-like events in other species are actual sleep spindles. Work in accordance with such stricter validation suggests that sleep spindles display more universally shared features, like defining frequency, than previously thought.

Although a positive link between sleep spindle occurrence and measures of post-sleep recall (learning success) is often reported for humans and replicated across species, the test–retest reliability of the effect is sometimes questioned. The largest to date study could not confirm the association, however methods for automatic spindle detection diverge in their estimates and vary between studies. Here we report that in dogs using the same detection method across different learning tasks is associated with observing a positive association between sleep spindle density (spindles/minute) and learning success. Our results suggest that reducing measurement error by averaging across measurements of density and learning can increase the visibility of this effect, implying that trait density (estimated through averaged occurrence) is a more reliable predictor of cognitive performance than estimates based on single measures.