Zinc Nanoparticles Enhance Brain Connectivity in the Canine Olfactory Network: Evidence From an fMRI Study in Unrestrained Awake Dogs

Domestic dogs as a comparative model for social neuroscience: Advances and challenges

Dogs and humans have lived together for thousands of years and share many analogous socio-cognitive skills. Dog neuroimaging now provides insight into the neural bases of these shared social abilities. Here, we summarize key findings from dog fMRI identifying neocortical brain areas implicated in visual social cognition, such as face, body, and emotion perception, as well as action observation in dogs. These findings provide converging evidence that the temporal cortex plays a significant role in visual social cognition in dogs. We further briefly review investigations into the neural base of the dog-human relationship, mainly involving limbic brain regions. We then discuss current challenges in the field, such as statistical power and lack of common template spaces, and how to overcome them. Finally, we argue that the foundation has now been built to investigate and compare the neural bases of more complex socio-cognitive phenomena shared by dogs and humans. This will strengthen and expand the role of the domestic dog as a powerful comparative model species and provide novel insights into the evolutionary roots of social cognition.

Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs

Functional brain connectivity based on resting-state functional magnetic resonance imaging (fMRI) has been shown to be correlated with human personality and behavior. In this study, we sought to know whether capabilities and traits in dogs can be predicted from their resting-state connectivity, as in humans. We trained awake dogs to keep their head still inside a 3T MRI scanner while resting-state fMRI data was acquired. Canine behavior was characterized by an integrated behavioral score capturing their hunting, retrieving, and environmental soundness. Functional scans and behavioral measures were acquired at three different time points across detector dog training. The first time point (TP1) was prior to the dogs entering formal working detector dog training. The second time point (TP2) was soon after formal detector dog training. The third time point (TP3) was three months' post detector dog training while the dogs were engaged in a program of maintenance training for detection work. We hypothesized that the correlation between resting-state FC in the dog brain and behavior measures would significantly change during their detection training process (from TP1 to TP2) and would maintain for the subsequent several months of detection work (from TP2 to TP3). To further study the resting-state FC features that can predict the success of training, dogs at TP1 were divided into a successful group and a non-successful group. We observed a core brain network which showed relatively stable (with respect to time) patterns of interaction that were significantly stronger in successful detector dogs compared to failures and whose connectivity strength at the first time point predicted whether a given dog was eventually successful in becoming a detector dog. A second ontologically based flexible peripheral network was observed whose changes in connectivity strength with detection training tracked corresponding changes in behavior over the training program. Comparing dog and human brains, the functional connectivity between the brain stem and the frontal cortex in dogs corresponded to that between the locus coeruleus and left middle frontal gyrus in humans, suggestive of a shared mechanism for learning and retrieval of odors. Overall, the findings point toward the influence of phylogeny and ontogeny in dogs producing two dissociable functional neural networks.

The Role of Endogenous Metal Nanoparticles in Biological Systems

The blood and tissues of vertebrate animals and mammals contain small endogenous metal nanoparticles. These nanoparticles were observed to be composed of individual atoms of iron, copper, zinc, silver, gold, platinum, and other metals. Metal nanoparticles can bind proteins and produce proteinaceous particles called proteons. A small fraction of the entire pool of nanoparticles is usually linked with proteins to form proteons. These endogenous metal nanoparticles, along with engineered zinc and copper nanoparticles at subnanomolar levels, were shown to be lethal to cultured cancer cells. These nanoparticles appear to be elemental crystalline metal nanoparticles. It was discovered that zinc nanoparticles produce no odor response but increase the odor reaction if mixed with an odorant. Some other metal nanoparticles, including copper, silver, gold, and platinum nanoparticles, do not affect the responses to odorants. The sources of metal nanoparticles in animal blood and tissues may include dietary plants and gut microorganisms. The solid physiological and biochemical properties of metal nanoparticles reflect their importance in cell homeostasis and disease.

Canine Olfaction: Physiology, Behavior, and Possibilities for Practical Applications

Simple Summary

Dogs have an extraordinary olfactory capability, which far exceeds that of humans. Dogs’ sense of smell seems to be the main sense, allowing them to not only gather both current and historical information about their surrounding environment, but also to find the source of the smell, which is crucial for locating food, danger, or partners for reproduction. Dogs can be trained by humans to use their olfactory abilities in a variety of fields, with a detection limit often much lower than that of sophisticated laboratory instruments. The specific anatomical and physiological features of dog olfaction allow humans to achieve outstanding results in the detection of drugs, explosives, and different illnesses, such as cancer, diabetes, or infectious disease. This article provides an overview of the anatomical features and physiological mechanisms involved in the process of odor detection and identification, as well as behavioral aspects of canine olfaction and its use in the service of humans in many fields.

Abstract

Olfaction in dogs is crucial for gathering important information about the environment, recognizing individuals, making decisions, and learning. It is far more specialized and sensitive than humans’ sense of smell. Using the strength of dogs’ sense of smell, humans work with dogs for the recognition of different odors, with a precision far exceeding the analytical capabilities of most modern instruments. Due to their extremely sensitive sense of smell, dogs could be used as modern, super-sensitive mobile area scanners, detecting specific chemical signals in real time in various environments outside the laboratory, and then tracking the odor of dynamic targets to their source, also in crowded places. Recent studies show that dogs can detect not only specific scents of drugs or explosives, but also changes in emotions as well as in human cell metabolism during various illnesses, including COVID-19 infection. Here, we provide an overview of canine olfaction, discussing aspects connected with anatomy, physiology, behavioral aspects of sniffing, and factors influencing the olfactory abilities of the domestic dog (Canis familiaris).

Dog-human social relationship: representation of human face familiarity and emotions in the dog brain

This study investigated the behavioral and neural indices of detecting facial familiarity and facial emotions in human faces by dogs. Awake canine fMRI was used to evaluate dogs' neural response to pictures and videos of familiar and unfamiliar human faces, which contained positive, neutral, and negative emotional expressions. The dog-human relationship was behaviorally characterized out-of-scanner using an unsolvable task. The caudate, hippocampus, and amygdala, mainly implicated in reward, familiarity and emotion processing, respectively, were activated in dogs when viewing familiar and emotionally salient human faces. Further, the magnitude of activation in these regions correlated with the duration for which dogs showed human-oriented behavior towards a familiar (as opposed to unfamiliar) person in the unsolvable task. These findings provide a bio-behavioral basis for the underlying markers and functions of human-dog interaction as they relate to familiarity and emotion in human faces.

Human-dog relationships as a working framework for exploring human-robot attachment: a multidisciplinary review

Robotic agents will be life-long companions of humans in the foreseeable future. To achieve such successful relationships, people will likely attribute emotions and personality, assign social competencies, and develop a long-lasting attachment to robots. However, without a clear theoretical framework-building on biological, psychological, and technological knowledge-current societal demands for establishing successful human-robot attachment (HRA) as a new form of inter-species interactions might fail. The study of evolutionarily adaptive animal behavior (i.e., ethology) suggests that human-animal behaviors can be considered as a plausible solution in designing and building models of ethorobots-including modeling the inter-species bond between domesticated animals and humans. Evidence shows that people assign emotional feelings and personality characteristics to animal species leading to cooperation and communication-crucial for designing social robots such as companion robots. Because dogs have excellent social skills with humans, current research applies human-dog relationships as a template to understand HRA. Our goal of this article is twofold. First, we overview the research on how human-dog interactions are implemented as prototypes of non-human social companions in HRA. Second, we review research about attitudes that humans have for interacting with robotic dogs based on their appearance and behavior, the implications for forming attachments, and human-animal interactions in the rising sphere of robot-assisted therapy. The rationale for this review is to provide a new perspective to facilitate future research among biologists, psychologists, and engineers-contributing to the creation of innovative research practices for studying social behaviors and its implications for society addressing HRA.

Endogenous zinc nanoparticles in the rat olfactory epithelium are functionally significant

The role of zinc in neurobiology is rapidly expanding. Zinc is especially essential in olfactory neurobiology. Naturally occurring zinc nanoparticles were detected in olfactory and nasal respiratory epithelia and cilia in animals. The addition of these nanoparticles to a mixture of odorants, including ethyl butyrate, eugenol, and carvone, considerably increased the electrical responses of the olfactory sensory receptors. Studies of these nanoparticles by ransmission electron microscopy (TEM) and selected area electron diffraction revealed metal elemental crystalline zinc nanoparticles 2–4 nm in diameter. These particles did not contain oxidized zinc. The enhancement of the odorant responses induced by the endogenous zinc nanoparticles appears to be similar to the amplification produced by engineered zinc nanoparticles. Zinc nanoparticles produce no odor response but increase odor response if mixed with an odorant. These effects are dose-dependent and reversible. Some other metal nanoparticles, such as copper, silver, gold, and platinum, do not have the effects observed in the case of zinc nanoparticles. The olfactory enhancement was observed in young and mature mouse olfactory epithelium cultures, in the dissected olfactory epithelium of rodents, and in live conscious dogs. The physiological significance of the detected endogenous metal nanoparticles in an animal tissue has been demonstrated for the first time. Overall, our results may advance the understanding of the initial events in olfaction.

Multi-Level Clustering of Dynamic Directional Brain Network Patterns and Their Behavioral Relevance

Dynamic functional connectivity (DFC) obtained from resting state functional magnetic resonance imaging (fMRI) data has been shown to provide novel insights into brain function which may be obscured by static functional connectivity (SFC). Further, DFC, and by implication how different brain regions may engage or disengage with each other over time, has been shown to be behaviorally relevant and more predictive than SFC of behavioral performance and/or diagnostic status. DFC is not a directional entity and may capture neural synchronization. However, directional interactions between different brain regions is another putative mechanism by which neural populations communicate. Accordingly, static effective connectivity (SEC) has been explored as a means of characterizing such directional interactions. But investigation of its dynamic counterpart, i.e., dynamic effective connectivity (DEC), is still in its infancy. Of particular note are methodological insufficiencies in identifying DEC configurations that are reproducible across time and subjects as well as a lack of understanding of the behavioral relevance of DEC obtained from resting state fMRI. In order to address these issues, we employed a dynamic multivariate autoregressive (MVAR) model to estimate DEC. The method was first validated using simulations and then applied to resting state fMRI data obtained in-house (N = 21), wherein we performed dynamic clustering of DEC matrices across multiple levels [using adaptive evolutionary clustering (AEC)] – spatial location, time, and subjects. We observed a small number of directional brain network configurations alternating between each other over time in a quasi-stable manner akin to brain microstates. The dominant and consistent DEC network patterns involved several regions including inferior and mid temporal cortex, motor and parietal cortex, occipital cortex, as well as part of frontal cortex. The functional relevance of these DEC states were determined using meta-analyses and pertained mainly to memory and emotion, but also involved execution and language. Finally, a larger cohort of resting-state fMRI and behavioral data from the Human Connectome Project (HCP) (N = 232, Q1–Q3 release) was used to demonstrate that metrics derived from DEC can explain larger variance in 70 behaviors across different domains (alertness, cognition, emotion, and personality traits) compared to SEC in healthy individuals.

Separate brain areas for processing human and dog faces as revealed by awake fMRI in dogs (Canis familiaris)

Functional magnetic resonance imaging (fMRI) has emerged as a viable method to study the neural processing underlying cognition in awake dogs. Working dogs were presented with pictures of dog and human faces. The human faces varied in familiarity (familiar trainers and unfamiliar individuals) and emotional valence (negative, neutral, and positive). Dog faces were familiar (kennel mates) or unfamiliar. The findings revealed adjacent but separate brain areas in the left temporal cortex for processing human and dog faces in the dog brain. The human face area (HFA) and dog face area (DFA) were both parametrically modulated by valence indicating emotion was not the basis for the separation. The HFA and DFA were not influenced by familiarity. Using resting state fMRI data, functional connectivity networks (connectivity fingerprints) were compared and matched across dogs and humans. These network analyses found that the HFA mapped onto the human fusiform area and the DFA mapped onto the human superior temporal gyrus, both core areas in the human face processing system. The findings provide insight into the evolution of face processing.