Techniques for chronic monitoring of brain activity in freely moving sheep using wireless EEG recording

Large-scale cranial window for in vivo mouse brain imaging utilizing fluoropolymer nanosheet and light-curable resin

Two-photon microscopy enables in vivo imaging of neuronal activity in mammalian brains at high resolution. However, two-photon imaging tools for stable, long-term, and simultaneous study of multiple brain regions in same mice are lacking. Here, we propose a method to create large cranial windows covering such as the whole parietal cortex and cerebellum in mice using fluoropolymer nanosheets covered with light-curable resin (termed the 'Nanosheet Incorporated into light-curable REsin' or NIRE method). NIRE method can produce cranial windows conforming the curved cortical and cerebellar surfaces, without motion artifacts in awake mice, and maintain transparency for >5 months. In addition, we demonstrate that NIRE method can be used for in vivo two-photon imaging of neuronal ensembles, individual neurons and subcellular structures such as dendritic spines. The NIRE method can facilitate in vivo large-scale analysis of heretofore inaccessible neural processes, such as the neuroplastic changes associated with maturation, learning and neural pathogenesis.

Application of Electroencephalography in Preslaughter Management: A Review

Electroencephalography (EEG) can be reliable for assessing the brain’s electrical activity of preslaughter stress and pain. The duration between the ventral neck cut and induction of a state of unconsciousness/insensibility is crucial in the slaughtering of animals, reducing pain, fear, and distress. Various EEG variables, such as median frequency (F50), the total power of EEG spectrum (Ptot), waves patterns (amplitude and frequencies), epileptiform EEG, index of consciousness, and isoelectric EEG, are used to identify a valid indicator of the state of unconsciousness. Association among various behavioral, physiological, and hematological parameters with EEG variables could provide an overall assessment and deep insights into the animal stress levels or welfare status during various managemental and preslaughter operations, such as transport, stunning, and slaughtering operations. The application of EEG could help in further refining the stunning technologies and slaughter protocols in livestock, poultry, and fish. The present review analyzed the application of EEG as a neurophysiological tool for assessing animal welfare during the critical state of preslaughter handling and slaughter, thus ensuring proper compliance with animal welfare principles.

Deep brain electrophysiology in freely moving sheep

Although rodents are arguably the easiest animals to use for studying brain function, relying on them as model species for translational research comes with its own set of limitations. Here, we propose sheep as a practical large animal species to use for in vivo brain function studies performed in naturalistic settings. We conducted proof-of-principle deep brain electrophysiological recording experiments using unrestrained sheep during behavioral testing. Recordings were made from cortex and hippocampus, both while sheep performed goal-directed behaviors (two-choice discrimination tasks) and across states of vigilance, including sleep. Hippocampal and cortical oscillatory rhythms were consistent with those seen in rodents and non-human primates, and included cortical alpha oscillations and hippocampal sharp wave ripple oscillations (∼150 Hz) during immobility and hippocampal theta oscillations (5-6 Hz) during locomotion. Recordings were conducted over a period of many months during which time the animals participated willingly in the experiments. Over 3,000 putative neurons were identified, including examples whose activity was modulated by task, speed of locomotion, spatial position, reward and vigilance states, and one whose firing rate was potentially modulated by the sight of the investigator. Together, these experiments demonstrate that sheep are excellent experimental animals to use for longitudinal studies requiring a large-brained mammal and/or large-scale recordings across distributed neuronal networks. Sheep could be used safely for studying not only neural encoding of decision-making and spatial-mapping in naturalistic environments outside the confines of the traditional laboratory but also the neural basis of both intra- and inter-species social interactions.

Future trends in measuring physiology in free-living animals

Thus far, ecophysiology research has predominantly been conducted within controlled laboratory-based environments, owing to a mismatch between the recording technologies available for physiological monitoring in wild animals and the suite of behaviours and environments they need to withstand, without unduly affecting subjects. While it is possible to record some physiological variables for free-living animals using animal-attached logging devices, including inertial-measurement, heart-rate and temperature loggers, the field is still in its infancy. In this opinion piece, we review the most important future research directions for advancing the field of 'physiologging' in wild animals, including the technological development that we anticipate will be required, and the fiscal and ethical challenges that must be overcome. Non-invasive, multi-sensor miniature devices are ubiquitous in the world of human health and fitness monitoring, creating invaluable opportunities for animal and human physiologging to drive synergistic advances. We argue that by capitalizing on the research efforts and advancements made in the development of human wearables, it will be possible to design the non-invasive loggers needed by ecophysiologists to collect accurate physiological data from free-ranging animals ethically and with an absolute minimum of impact. In turn, findings have the capacity to foster transformative advances in human health monitoring. Thus, we invite biomedical engineers and researchers to collaborate with the animal-tagging community to drive forward the advancements necessary to realize the full potential of both fields. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

Abnormally abrupt transitions from sleep-to-wake in Huntington's disease sheep (Ovis aries) are revealed by automated analysis of sleep/wake transition dynamics

Sleep disturbance is a common and disruptive symptom of neurodegenerative diseases such as Alzheimer’s and Huntington’s disease (HD). In HD patients, sleep fragmentation appears at an early stage of disease, although features of the earliest sleep abnormalities in presymptomatic HD are not fully established. Here we used novel automated analysis of quantitative electroencephalography to study transitions between wake and non-rapid eye movement sleep in a sheep model of presymptomatic HD. We found that while the number of transitions between sleep and wake were similar in normal and HD sheep, the dynamics of transitions from sleep-to-wake differed markedly between genotypes. Rather than the gradual changes in EEG power that occurs during transitioning from sleep-to-wake in normal sheep, transition into wake was abrupt in HD sheep. Furthermore, transitions to wake in normal sheep were preceded by a significant reduction in slow wave power, whereas in HD sheep this prior reduction in slow wave power was far less pronounced. This suggests an impaired ability to prepare for waking in HD sheep. The abruptness of awakenings may also have potential to disrupt sleep-dependent processes if they are interrupted in an untimely and disjointed manner. We propose that not only could these abnormal dynamics of sleep transitions be useful as an early biomarker of HD, but also that our novel methodology would be useful for studying transition dynamics in other sleep disorders.

Development and in vivo assessment of a novel MRI-compatible headframe system for the ovine animal model

BACKGROUND

The brain of sheep has primarily been used in neuroscience as an animal model because of its similarity to the human brain, in particular if compared to other models such as the lissencephalic rodent brain. Their brain size also makes sheep an ideal model for the development of neurosurgical techniques using conventional clinical CT/MRI scanners and stereotactic systems for neurosurgery.

METHODS

In this study, we present the design and validation of a new CT/MRI compatible head frame for the ovine model and software, with its assessment under two real clinical scenarios.

RESULTS

Ex-vivo and in vivo trial results report an average linear displacement of the ovine head frame during conventional surgical procedures of 0.81 mm for ex-vivo trials and 0.68 mm for in vivo tests, respectively.

CONCLUSIONS

These trial results demonstrate the robustness of the head frame system and its suitability to be employed within a real clinical setting.

Analgesia for Sheep in Commercial Production: Where to Next?

Simple Summary

Increasing societal and customer pressure to provide animals with ‘a life worth living’ continues to apply pressure on industry to alleviate pain associated with husbandry practices, injury and illness. Although a number of analgesic solutions are now available for sheep, providing some amelioration of the acute pain responses, this review has highlighted a number of potential areas for further research.

Abstract

Increasing societal and customer pressure to provide animals with ‘a life worth living’ continues to apply pressure on livestock production industries to alleviate pain associated with husbandry practices, injury and illness. Over the past 15–20 years, there has been considerable research effort to understand and develop mitigation strategies for painful husbandry procedures in sheep, leading to the successful launch of analgesic approaches specific to sheep in a number of countries. However, even with multi-modal approaches to analgesia, using both local anaesthetic and non-steroidal anti-inflammatory drugs (NSAID), pain is not obliterated, and the challenge of pain mitigation and phasing out of painful husbandry practices remains. It is timely to review and reflect on progress to date in order to strategically focus on the most important challenges, and the avenues which offer the greatest potential to be incorporated into industry practice in a process of continuous improvement. A structured, systematic literature search was carried out, incorporating peer-reviewed scientific literature in the period 2000–2019. An enormous volume of research is underway, testament to the fact that we have not solved the pain and analgesia challenge for any species, including our own. This review has highlighted a number of potential areas for further research.

Abnormal patterns of sleep and EEG power distribution during non-rapid eye movement sleep in the sheep model of Huntington's disease

Sleep disruption is a common invisible symptom of neurological dysfunction in Huntington's disease (HD) that takes an insidious toll on well-being of patients. Here we used electroencephalography (EEG) to examine sleep in 6 year old OVT73 transgenic sheep (Ovis aries) that we used as a presymptomatic model of HD. We hypothesized that despite the lack of overt symptoms of HD at this age, early alterations of the sleep-wake pattern and EEG powers may already be present. We recorded EEG from female transgenic and normal sheep (5/group) during two undisturbed 'baseline' nights with different lighting conditions. We then recorded continuously through a night of sleep disruption and the following 24 h (recovery day and night). On baseline nights, regardless of whether the lights were on or off, transgenic sheep spent more time awake than normal sheep particularly at the beginning of the night. Furthermore, there were significant differences between transgenic and normal sheep in both EEG power and its pattern of distribution during non-rapid eye movement (NREM) sleep. In particular, there was a significant decrease in delta (0.5-4 Hz) power across the night in transgenic compared to normal sheep, and the distributions of delta, theta and alpha oscillations that typically dominate the EEG in the first half of the night of normal sheep were skewed so they were predominant in the second, rather than the first half of the night in transgenic sheep. Interestingly, the effect of sleep disruption on normal sheep was also to skew the pattern of distribution of EEG powers so they looked more like that of transgenic sheep under baseline conditions. Thus it is possible that transgenic sheep exist in a state that resemble a chronic state of physiological sleep deprivation. During the sleep recovery period, normal sheep showed a significant 'rebound' increase in delta power with frontal dominance. A similar rebound was not seen in transgenic sheep, suggesting that their homeostatic response to sleep deprivation is abnormal. Although sleep abnormalities in early stage HD patients are subtle, with patients often unaware of their existence, they may contribute to impairment of neurological function that herald the onset of disease. A better understanding of the mechanisms underlying EEG abnormalities in early stage HD would give insight into how, and when, they progress into the sleep disorder. The transgenic sheep model is ideally positioned for studies of the earliest phase of disease when sleep abnormalities first emerge.

Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals

Human activity recognition and neural activity analysis are the basis for human computational neureoethology research dealing with the simultaneous analysis of behavioral ethogram descriptions and neural activity measurements. Wireless electroencephalography (EEG) and wireless inertial measurement units (IMU) allow the realization of experimental data recording with improved ecological validity where the subjects can be carrying out natural activities while data recording is minimally invasive. Specifically, we aim to show that EEG and IMU data fusion allows improved human activity recognition in a natural setting. We have defined an experimental protocol composed of natural sitting, standing and walking activities, and we have recruited subjects in two sites: in-house ([Formula: see text]) and out-house ([Formula: see text]) populations with different demographics. Experimental protocol data capture was carried out with validated commercial systems. Classifier model training and validation were carried out with scikit-learn open source machine learning python package. EEG features consist of the amplitude of the standard EEG frequency bands. Inertial features were the instantaneous position of the body tracked points after a moving average smoothing to remove noise. We carry out three validation processes: a 10-fold cross-validation process per experimental protocol repetition, (b) the inference of the ethograms, and (c) the transfer learning from each experimental protocol repetition to the remaining repetitions. The in-house accuracy results were lower and much more variable than the out-house sessions results. In general, random forest was the best performing classifier model. Best cross-validation results, ethogram accuracy, and transfer learning were achieved from the fusion of EEG and IMUs data. Transfer learning behaved poorly compared to classification on the same protocol repetition, but it has accuracy still greater than 0.75 on average for the out-house data sessions. Transfer leaning accuracy among repetitions of the same subject was above 0.88 on average. Ethogram prediction accuracy was above 0.96 on average. Therefore, we conclude that wireless EEG and IMUs allow for the definition of natural experimental designs with high ecological validity toward human computational neuroethology research. The fusion of both EEG and IMUs signals improves activity and ethogram recognition.

Characteristic patterns of EEG oscillations in sheep (Ovis aries) induced by ketamine may explain the psychotropic effects seen in humans

Ketamine is a valuable anaesthetic and analgesic that in recent years has gained notoriety as a recreational drug. Recently, ketamine has also been proposed as a novel treatment for depression and post-traumatic stress disorder. Beyond its anaesthetic actions, however, the effects of ketamine on brain activity have rarely been probed. Here we examined the cortical electroencephalography (EEG) response to ketamine of 12 sheep. Following ketamine administration, EEG changes were immediate and widespread, affecting the full extent of the EEG frequency spectrum measured (0–125 Hz). After recovery from sedation during which low frequency activity dominated, the EEG was characterised by short periods (2–3 s) of alternating low (<14 Hz) and high (>35 Hz) frequency oscillation. This alternating EEG rhythm phase is likely to underlie the dissociative actions of ketamine, since it is during this phase that ketamine users report hallucinations. At the highest intravenous dose used (24 mg/kg), in 5/6 sheep we observed a novel effect of ketamine, namely the complete cessation of cortical EEG activity. This persisted for up to several minutes, after which cortical activity resumed. This phenomenon is likely to explain the ‘k-hole’, a state of oblivion likened to a near death experience that is keenly sought by ketamine abusers.

Characterizing Sleep Spindles in Sheep

Sleep spindles are distinctive transient patterns of brain activity that typically occur during non-rapid eye movement (NREM) sleep in humans and other mammals. Thought to be important for the consolidation of learning, they may also be useful for indicating the progression of aging and neurodegenerative diseases. The aim of this study was to characterize sleep spindles in sheep (Ovis aries). We recorded electroencephalographs wirelessly from six sheep over a continuous period containing 2 nights and a day. We detected and characterized spindles using an automated algorithm. We found that sheep sleep spindles fell within the classical range seen in humans (10–16 Hz), but we did not see a further separation into fast and slow bands. Spindles were detected predominantly during NREM sleep. Spindle characteristics (frequency, duration, density, topography) varied between individuals, but were similar within individuals between nights. Spindles that occurred during NREM sleep in daytime were indistinguishable from those found during NREM sleep at night. Surprisingly, we also detected numerous spindle-like events during unequivocal periods of wake during the day. These events were mainly local (detected at single sites), and their characteristics differed from spindles detected during sleep. These “wake spindles” are likely to be events that are commonly categorized as “spontaneous alpha activity” during wake. We speculate that wake and sleep spindles are generated via different mechanisms, and that wake spindles play a role in cognitive processes that occur during the daytime.

A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy

The aim of this study was to develop an integrated system of non-contact sleep stage detection and sleep disorder treatment for health monitoring. Hence, a method of brain activity detection based on microwave scattering technology instead of scalp electroencephalogram was developed to evaluate the sleep stage. First, microwaves at a specific frequency were used to penetrate the functional sites of the brain in patients with sleep disorders to change the firing frequency of the activated areas of the brain and analyze and evaluate statistically the effects on sleep improvement. Then, a wavelet packet algorithm was used to decompose the microwave transmission signal, the refined composite multiscale sample entropy, the refined composite multiscale fluctuation-based dispersion entropy and multivariate multiscale weighted permutation entropy were obtained as features from the wavelet packet coefficient. Finally, the mutual information-principal component analysis feature selection method was used to optimize the feature set and random forest was used to classify and evaluate the sleep stage. The results show that after four times of microwave modulation treatment, sleep efficiency improved continuously, the overall maintenance was above 80%, and the insomnia rate was reduced gradually. The overall classification accuracy of the four sleep stages was 86.4%. The results indicate that the microwaves with a certain frequency can treat sleep disorders and detect abnormal brain activity. Therefore, the microwave scattering method is of great significance in the development of a new brain disease treatment, diagnosis and clinical application system.

In vivo Diffusion Tensor Magnetic Resonance Tractography of the Sheep Brain: An Atlas of the Ovine White Matter Fiber Bundles

Diffusion Tensor Magnetic Resonance Imaging (DTI) allows to decode the mobility of water molecules in cerebral tissue, which is highly directional along myelinated fibers. By integrating the direction of highest water diffusion through the tissue, DTI Tractography enables a non-invasive dissection of brain fiber bundles. As such, this technique is a unique probe for in vivo characterization of white matter architecture. Unraveling the principal brain texture features of preclinical models that are advantageously exploited in experimental neuroscience is crucial to correctly evaluate investigational findings and to correlate them with real clinical scenarios. Although structurally similar to the human brain, the gyrencephalic ovine model has not yet been characterized by a systematic DTI study. Here we present the first in vivo sheep (ovis aries) tractography atlas, where the course of the main white matter fiber bundles of the ovine brain has been reconstructed. In the context of the EU's Horizon EDEN2020 project, in vivo brain MRI protocol for ovine animal models was optimized on a 1.5T scanner. High resolution conventional MRI scans and DTI sequences (b-value = 1,000 s/mm², 15 directions) were acquired on ten anesthetized sheep o. aries, in order to define the diffusion features of normal adult ovine brain tissue. Topography of the ovine cortex was studied and DTI maps were derived, to perform DTI tractography reconstruction of the corticospinal tract, corpus callosum, fornix, visual pathway, and occipitofrontal fascicle, bilaterally for all the animals. Binary masks of the tracts were then coregistered and reported in the space of a standard stereotaxic ovine reference system, to demonstrate the consistency of the fiber bundles and the minimal inter-subject variability in a unique tractography atlas. Our results determine the feasibility of a protocol to perform in vivo DTI tractography of the sheep, providing a reliable reconstruction and 3D rendering of major ovine fiber tracts underlying different neurological functions. Estimation of fiber directions and interactions would lead to a more comprehensive understanding of the sheep's brain anatomy, potentially exploitable in preclinical experiments, thus representing a precious tool for veterinaries and researchers.

Imaging local brain activity of multiple freely moving mice sharing the same environment

Electrophysiological field potential dynamics have been widely used to investigate brain functions and related psychiatric disorders. Considering recent demand for its applicability to freely moving subjects, especially for animals in a group and socially interacting with each other, here we propose a new method based on a bioluminescent voltage indicator LOTUS-V. Using our fiber-free recording method based on the LOTUS-V, we succeeded in capturing dynamic change of brain activity in freely moving mice. Because LOTUS-V is the ratiometric indicator, motion and head-angle artifacts were not significantly detected. Taking advantage of our method as a fiber-free system, we further succeeded in simultaneously recording from multiple independently-locomotive mice that were freely interacting with one another. Importantly, this enabled us to find that the primary visual cortex, a center of visual processing, was activated during the interaction of mice. This methodology may further facilitate a wide range of studies in neurobiology and psychiatry.

Sleep-Aids Derived from Natural Products

Although drugs such as barbiturates and benzodiazepines are often used for the treatment of insomnia, they are associated with various side effects such as habituations, tolerance and addiction. Alternatively, natural products with minimal unwanted effects have been preferred for the treatment of acute and/or mild insomnia, with additional benefits of overall health-promotion. Basic and clinical researches on the mechanisms of action of natural products have been carried out so far in insomnia treatments. Recent studies have been focusing on diverse chemical components available in natural products, with an interest of developing drugs that can improve sleep duration and quality. In the last 15 years, our co-workers have been actively looking for candidate substances from natural products that can relieve insomnia. This review is, therefore, intended to bring pharmacological data regarding to the effects of natural products on sleep duration and quality, mainly through the activation of GABA_A receptors. It is imperative that phytochemicals will provide useful information during electroencephalography (EEG) analysis and serve as an alternative medications for insomnia patients who are reluctant to use conventional drugs.

Large-Brained Animal Models of Huntington's Disease: Sheep

The limitations of using small-brained rodents to model diseases that affect large-brain humans are becoming increasingly obvious as novel therapies emerge. Huntington's disease (HD) is one such disease. In recent years, the desirability of a large-brained, long-lived animal model of HD for preclinical testing has changed into a necessity. Treatment involving gene therapy in particular presents delivery challenges that are currently unsolved. Models using long-lived, large-brained animals would be useful, not only for refining methods of delivery (particularly for gene and other therapies that do not involve small molecules) but also for measuring long-term "off-target" effects, and assessing the efficacy of therapies. With their large brains and convoluted cortices, sheep are emerging as feasible experimental subjects that can be used to bridge the gap between rodents and humans in preclinical drug development. Sheep are readily available, economical to use, and easy to care for in naturalistic settings. With brains of a similar size to a large rhesus macaque, they have much to offer. The only thing that was missing until recently was the means of testing their neurological function and behavior using approaches and methods that are relevant to HD. In this chapter, I will outline the present and future possibilities of using sheep and testing as large animal models of HD.

The brain during free movement - What can we learn from the animal model

Animals, just like humans, can freely move. They do so for various important reasons, such as finding food and escaping predators. Observing these behaviors can inform us about the underlying cognitive processes. In addition, while humans can convey complicated information easily through speaking, animals need to move their bodies to communicate. This has prompted many creative solutions by animal neuroscientists to enable studying the brain during movement. In this review, we first summarize how animal researchers record from the brain while an animal is moving, by describing the most common neural recording techniques in animals and how they were adapted to record during movement. We further discuss the challenge of controlling or monitoring sensory input during free movement. However, not only is free movement a necessity to reflect the outcome of certain internal cognitive processes in animals, it is also a fascinating field of research since certain crucial behavioral patterns can only be observed and studied during free movement. Therefore, in a second part of the review, we focus on some key findings in animal research that specifically address the interaction between free movement and brain activity. First, focusing on walking as a fundamental form of free movement, we discuss how important such intentional movements are for understanding processes as diverse as spatial navigation, active sensing, and complex motor planning. Second, we propose the idea of regarding free movement as the expression of a behavioral state. This view can help to understand the general influence of movement on brain function. Together, the technological advancements towards recording from the brain during movement, and the scientific questions asked about the brain engaged in movement, make animal research highly valuable to research into the human "moving brain".

Neurophysiological assessment of animal welfare

Livestock industries such as the pork industry are striving to continuously improve the welfare of animals. Inherent to the success of this is the ability to rigorously assess the welfare of animals in the field. While much progress has been made towards the development of methodology to assess the welfare of animals, there have been major challenges to establishing practical and definitive procedures to assess the welfare of animals. These include, but are not limited to, establishing a universally accepted definition of animal welfare and the choice of measures that are taken from the animal to assess its welfare. Measures of biological functioning and affective (emotional) state of the animal have been common, but there have been many limitations in terms of practical application. Some of the reasons for this include the choice of physiological measures, which are often restrictive in providing information about welfare, affective measures being restricted to specific behavioural measures and the biological-functioning and affective-states approaches being undertaken in isolation. Biological and affective functioning are integrated and controlled by the brain. Many of the regions of the brain involved in the regulation of biological and emotional functioning have been identified. Furthermore, there is considerable knowledge about the roles and interactions among the neurophysiological systems in these brain regions. We propose a strategy to use this knowledge to develop procedures to assess animal welfare. The initial phase is to identify the neural pathways that regulate the physiological and emotional processes that allow animals to adapt and cope. The next phase is to determine the activity of these pathways in conscious animals in the field. This requires the identification of biomarkers of specific neuronal activity that can be measured in the conscious animal in the field. Emerging technologies are offering promise in the identification of such biomarkers and some of these are already applicable to the pig. There is now the opportunity to apply this strategy within the pork industry to assess the welfare of pigs throughout the value chain.