Resting state network topology of the ferret brain

Ferret as a model system for studying the anatomy and function of the prefrontal cortex: A systematic review

There is a lack of consensus on anatomical nomenclature, standards of documentation, and functional equivalence of the frontal cortex between species. There remains a major gap between human prefrontal function and interpretation of findings in the mouse brain that appears to lack several key prefrontal areas involved in cognition and psychiatric illnesses. The ferret is an emerging model organism that has gained traction as an intermediate model species for the study of top-down cognitive control and other higher-order brain functions. However, this research has yet to benefit from synthesis. Here, we provide a summary of all published research pertaining to the frontal and/or prefrontal cortex of the ferret across research scales. The targeted location within the ferret brain is summarized visually for each experiment, and the anatomical terminology used at time of publishing is compared to what would be the appropriate term to use presently. By doing so, we hope to improve clarity in the interpretation of both previous and future publications on the comparative study of frontal cortex.

Sheep (Ovis aries) training protocol for voluntary awake and unrestrained structural brain MRI acquisitions

Magnetic resonance imaging (MRI) is a non-invasive technique that requires the participant to be completely motionless. To date, MRI in awake and unrestrained animals has only been achieved with humans and dogs. For other species, alternative techniques such as anesthesia, restraint and/or sedation have been necessary. Anatomical and functional MRI studies with sheep have only been conducted under general anesthesia. This ensures the absence of movement and allows relatively long MRI experiments but it removes the non-invasive nature of the MRI technique (i.e., IV injections, intubation). Anesthesia can also be detrimental to health, disrupt neurovascular coupling, and does not permit the study of higher-level cognition. Here, we present a proof-of-concept that sheep can be trained to perform a series of tasks, enabling them to voluntarily participate in MRI sessions without anesthesia or restraint. We describe a step-by-step training protocol based on positive reinforcement (food and praise) that could be used as a basis for future neuroimaging research in sheep. This protocol details the two successive phases required for sheep to successfully achieve MRI acquisitions of their brain. By providing structural brain MRI images from six out of ten sheep, we demonstrate the feasibility of our training protocol. This innovative training protocol paves the way for the possibility of conducting animal welfare-friendly functional MRI studies with sheep to investigate ovine cognition.

Cholinergic modulation supports dynamic switching of resting state networks through selective DMN suppression

Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.

Resting state networks of awake adolescent and adult squirrel monkeys using ultra-high field (9.4T) functional magnetic resonance imaging

Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys (n=12 adolescents [6 male/6 female] ∼2.5 years and n=15 adults [7 male/8 female] ∼9.5 years) were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Group level independent component (ICA) analysis (30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared to adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.Significance Statement Functional magnetic resonance imaging procedures have revealed important information about how the brain is modified by experimental manipulations, disease states, and aging throughout the lifespan. Preclinical neuroimaging, especially in nonhuman primates, has become a frequently used means to answer targeted questions related to brain resting-state functional connectivity. The present study characterized resting state networks (RSNs) in adult and adolescent squirrel monkeys; twenty RSNs corresponding to networks representing a range of neural functions were identified. The RSNs identified here can be utilized in future studies examining the effects of experimental manipulations on brain connectivity in squirrel monkeys. These data also may be useful for comparative analysis with other primate species to provide an evolutionary perspective for understanding brain function and organization.

Central nodes of canine functional brain networks are concentrated in the cingulate gyrus

Compared to the field of human fMRI, knowledge about functional networks in dogs is scarce. In this paper, we present the first anatomically-defined ROI (region of interest) based functional network map of the companion dog brain. We scanned 33 awake dogs in a "task-free condition". Our trained subjects, similarly to humans, remain willingly motionless during scanning. Our goal is to provide a reference map with a current best estimate for the organisation of the cerebral cortex as measured by functional connectivity. The findings extend a previous spatial ICA (independent component analysis) study (Szabo et al. in Sci Rep 9(1):1.25. https://doi.org/10.1038/s41598-019-51752-2 , 2019), with the current study including (1) more subjects and (2) improved scanning protocol to avoid asymmetric lateral distortions. In dogs, similarly to humans (Sacca et al. in J Neurosci Methods. https://doi.org/10.1016/j.jneumeth.2021.109084 , 2021), ageing resulted in increasing framewise displacement (i.e. head motion) in the scanner. Despite the inherently different approaches between model-free ICA and model-based ROI, the resulting functional networks show a remarkable similarity. However, in the present study, we did not detect a designated auditory network. Instead, we identified two highly connected, lateralised multi-region networks extending to non-homotropic regions (Sylvian L, Sylvian R), including the respective auditory regions, together with the associative and sensorimotor cortices and the insular cortex. The attention and control networks were not split into two fully separated, dedicated networks. Overall, in dogs, fronto-parietal networks and hubs were less dominant than in humans, with the cingulate gyrus playing a central role. The current manuscript provides the first attempt to map whole-brain functional networks in dogs via a model-based approach.

Resting state networks of awake adolescent and adult squirrel monkeys using ultra-high field (9.4T) functional magnetic resonance imaging

Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys ( n =12 adolescents [6 male/6 female] ∼2.5 years and n =15 adults [7 male/8 female] ∼9.5 years) were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Group level independent component (IC) analysis (30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward (e.g., basal ganglia), and cognitive processes were identified in both adolescent and adult monkeys. Significant age-related differences between the adult and adolescent subjects (adult > adolescent) were found in two networks of interest: (1) the right upper occipital region with an OFC IC and (2) the left temporal cortex, bilateral visual areas, and cerebellum with the cingulate IC. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.

Significance Statement

Functional magnetic resonance imaging procedures have revealed important information about how the brain is modified by experimental manipulations, disease states, and aging throughout the lifespan. Preclinical neuroimaging, especially in nonhuman primates, has become a frequently used means to answer targeted questions related to brain resting-state functional connectivity. The present study characterized resting state networks (RSNs) in adult and adolescent squirrel monkeys; twenty RSNs corresponding to networks representing a range of neural functions were identified. The RSNs identified here can be utilized in future studies examining the effects of experimental manipulations on brain connectivity in squirrel monkeys. These data also may be useful for comparative analysis with other primate species to provide an evolutionary perspective for understanding brain function and organization.

Assessment of Attentional Processes in Patients with Anxiety-Depressive Disorders Using Virtual Reality

To characterize the attention deficits in one-hundred-fifteen participants, comprising two types of clinical profiles (affective and anxiety disorder), through a test of continuous VR execution. Method: Three tests (i.e., Nesplora Aquarium, BDI, and STAI) were used to obtain a standardized measure of attention, as well as the existence and severity of depression and anxiety, respectively. Results: Significant differences (CI = 95%) were found between the control group and the group with depression, in variables related to the speed of visual processing (p = 0.008) in the absence of distractors (p = 0.041) and during the first dual execution task (p = 0.011). For scores related to sustained attention, patients with depression and those with anxiety did not differ from controls. Our results suggest attentional deficits in both clinical populations when performing a continuous performance test that involved the participation of the central executive system of working memory.

The Ferret as a Model System for Neocortex Development and Evolution

The neocortex is the largest part of the cerebral cortex and a key structure involved in human behavior and cognition. Comparison of neocortex development across mammals reveals that the proliferative capacity of neural stem and progenitor cells and the length of the neurogenic period are essential for regulating neocortex size and complexity, which in turn are thought to be instrumental for the increased cognitive abilities in humans. The domesticated ferret, Mustela putorius furo, is an important animal model in neurodevelopment for its complex postnatal cortical folding, its long period of forebrain development and its accessibility to genetic manipulation in vivo. Here, we discuss the molecular, cellular, and histological features that make this small gyrencephalic carnivore a suitable animal model to study the physiological and pathological mechanisms for the development of an expanded neocortex. We particularly focus on the mechanisms of neural stem cell proliferation, neuronal differentiation, cortical folding, visual system development, and neurodevelopmental pathologies. We further discuss the technological advances that have enabled the genetic manipulation of the ferret in vivo. Finally, we compare the features of neocortex development in the ferret with those of other model organisms.

Noise-driven multistability vs deterministic chaos in phenomenological semi-empirical models of whole-brain activity

An outstanding open problem in neuroscience is to understand how neural systems are capable of producing and sustaining complex spatiotemporal dynamics. Computational models that combine local dynamics with in vivo measurements of anatomical and functional connectivity can be used to test potential mechanisms underlying this complexity. We compared two conceptually different mechanisms: noise-driven switching between equilibrium solutions (modeled by coupled Stuart-Landau oscillators) and deterministic chaos (modeled by coupled Rossler oscillators). We found that both models struggled to simultaneously reproduce multiple observables computed from the empirical data. This issue was especially manifested in the case of noise-driven dynamics close to a bifurcation, which imposed overly strong constraints on the optimal model parameters. In contrast, the chaotic model could produce complex behavior over a range of parameters, thus being capable of capturing multiple observables at the same time with good performance. Our observations support the view of the brain as a non-equilibrium system able to produce endogenous variability. We presented a simple model capable of jointly reproducing functional connectivity computed at different temporal scales. Besides adding to our conceptual understanding of brain complexity, our results inform and constrain the future development of biophysically realistic large-scale models.

Suppressing Anterior Cingulate Cortex Modulates Default Mode Network and Behavior in Awake Rats

The default mode network (DMN) is a principal brain network in the mammalian brain. Although the DMN in humans has been extensively studied with respect to network structure, function, and clinical implications, our knowledge of DMN in animals remains limited. In particular, the functional role of DMN nodes, and how DMN organization relates to DMN-relevant behavior are still elusive. Here we investigated the causal relationship of inactivating a pivotal node of DMN (i.e., dorsal anterior cingulate cortex [dACC]) on DMN function, network organization, and behavior by combining chemogenetics, resting-state functional magnetic resonance imaging (rsfMRI) and behavioral tests in awake rodents. We found that suppressing dACC activity profoundly changed the activity and connectivity of DMN, and these changes were associated with altered DMN-related behavior in animals. The chemo-rsfMRI-behavior approach opens an avenue to mechanistically dissecting the relationships between a specific node, brain network function, and behavior. Our data suggest that, like in humans, DMN in rodents is a functional network with coordinated activity that mediates behavior.

Resting-State functional networks of different topographic representations in the somatosensory cortex of macaque monkeys and humans

Information processing in the brain is mediated through a complex functional network architecture whose comprising nodes integrate and segregate themselves on different timescales. To gain an understanding of the network function it is imperative to identify and understand the network structure with respect to the underlying anatomical connectivity and the topographic organization. Here we show that the previously described resting-state network for the somatosensory area 3b comprises of distinct networks that are characteristic for different topographic representations. Seed-based resting-state functional connectivity analysis in macaque monkeys and humans using BOLD-fMRI signals from the face, the hand and rest of the medial somatosensory representations of area 3b revealed different correlation patterns. Both monkeys and humans have many similarities in the connectivity networks, although the networks are more complex in humans with many more nodes. In both the species face area network has the highest ipsilateral and contralateral connectivity, which included areas 3b and 4, and ventral premotor area. The area 3b hand network included ipsilateral hand representation in area 4. The emergent functional network structures largely reflect the known anatomical connectivity. Our results show that different body part representations in area 3b have independent functional networks perhaps reflecting differences in the behavioral use of different body parts. The results also show that large cortical areas if considered together, do not give a complete and accurate picture of the network architecture.

Putative modulation of the gut microbiome by probiotics enhances preference for novelty in a preliminary double-blind placebo-controlled study in ferrets

Background

Increasing evidence suggests a causal relationship between the gut microbiome and psychiatric illnesses. In particular, autism spectrum disorder is associated with gastrointestinal symptoms and alterations in the gut microbiome. Administration of probiotics is a commonly used strategy by caregivers of people with neurodevelopmental illness. However, evidence for successful improvement in gut microbiome and (behavioral) symptoms has been lacking.

Results

Here, we use a novel ferret model of maternal immune activation to show that high-dose probiotic administration in a placebo-controlled study design causes changes in the gut microbiome in the form of a transient increase in the administered bacterial species. In contrast, we found no differences in baseline microbiome composition or changes induced by probiotic administration between animals exposed in utero to maternal immune activation and control animals. However, the relative presence of several bacterial species correlated with an increased preference for novelty (object and conspecific). Intriguingly, several of the hits in this screen are species that have previously emerged in the literature as being associated with autism and anxiety.

Conclusions

Together, our results suggest that high-dose probiotic interventions may be beneficial for the adjunct treatment of psychiatric illnesses. Placebo-controlled clinical trials in humans are urgently needed.

Resting state networks of the canine brain under sevoflurane anaesthesia

Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has become an established technique in humans and reliably determines several resting state networks (RSNs) simultaneously. Limited data exist about RSN in dogs. The aim of this study was to investigate the RSNs in 10 healthy beagle dogs using a 3 tesla MRI scanner and subsequently perform group-level independent component analysis (ICA) to identify functionally connected brain networks. Rs-fMRI sequences were performed under steady state sevoflurane inhalation anaesthesia. Anaesthetic depth was titrated to the minimum level needed for immobilisation and mechanical ventilation of the patient. This required a sevoflurane MAC between 0.8 to 1.2. Group-level ICA dimensionality of 20 components revealed distributed sensory, motor and higher-order networks in the dogs’ brain. We identified in total 7 RSNs (default mode, primary and higher order visual, auditory, two putative motor-somatosensory and one putative somatosensory), which are common to other mammals including humans. Identified RSN are remarkably similar to those identified in awake dogs. This study proves the feasibility of rs-fMRI in anesthetized dogs and describes several RSNs, which may set the basis for investigating pathophysiological characteristics of various canine brain diseases.

What is a multisensory cortex? A laminar, connectional, and functional study of a ferret temporal cortical multisensory area

Now that examples of multisensory neurons have been observed across the neocortex, this has led to some confusion about the features that actually designate a region as "multisensory." While the documentation of multisensory effects within many different cortical areas is clear, often little information is available about their proportions or net functional effects. To assess the compositional and functional features that contribute to the multisensory nature of a region, the present investigation used multichannel neuronal recording and tract tracing methods to examine the ferret temporal region: the lateral rostral suprasylvian sulcal area. Here, auditory-tactile multisensory neurons were predominant and constituted the majority of neurons across all cortical layers whose responses dominated the net spiking activity of the area. These results were then compared with a literature review of cortical multisensory data and were found to closely resemble multisensory features of other, higher-order sensory areas. Collectively, these observations argue that multisensory processing presents itself in hierarchical and area-specific ways, from regions that exhibit few multisensory features to those whose composition and processes are dominated by multisensory activity. It seems logical that the former exhibit some multisensory features (among many others), while the latter are legitimately designated as "multisensory."

Animal Functional Magnetic Resonance Imaging: Trends and Path Toward Standardization

Animal whole-brain functional magnetic resonance imaging (fMRI) provides a non-invasive window into brain activity. A collection of associated methods aims to replicate observations made in humans and to identify the mechanisms underlying the distributed neuronal activity in the healthy and disordered brain. Animal fMRI studies have developed rapidly over the past years, fueled by the development of resting-state fMRI connectivity and genetically encoded neuromodulatory tools. Yet, comparisons between sites remain hampered by lack of standardization. Recently, we highlighted that mouse resting-state functional connectivity converges across centers, although large discrepancies in sensitivity and specificity remained. Here, we explore past and present trends within the animal fMRI community and highlight critical aspects in study design, data acquisition, and post-processing operations, that may affect the results and influence the comparability between studies. We also suggest practices aimed to promote the adoption of standards within the community and improve between-lab reproducibility. The implementation of standardized animal neuroimaging protocols will facilitate animal population imaging efforts as well as meta-analysis and replication studies, the gold standards in evidence-based science.

Resting-state fMRI data of awake dogs (Canis familiaris) via group-level independent component analysis reveal multiple, spatially distributed resting-state networks

Resting-state networks are spatially distributed, functionally connected brain regions. Studying these networks gives us information about the large-scale functional organization of the brain and alternations in these networks are considered to play a role in a wide range of neurological conditions and aging. To describe resting-state networks in dogs, we measured 22 awake, unrestrained individuals of both sexes and carried out group-level spatial independent component analysis to explore whole-brain connectivity patterns. In this exploratory study, using resting-state functional magnetic resonance imaging (rs-fMRI), we found several such networks: a network involving prefrontal, anterior cingulate, posterior cingulate and hippocampal regions; sensorimotor (SMN), auditory (AUD), frontal (FRO), cerebellar (CER) and striatal networks. The network containing posterior cingulate regions, similarly to Primates, but unlike previous studies in dogs, showed antero-posterior connectedness with involvement of hippocampal and lateral temporal regions. The results give insight into the resting-state networks of awake animals from a taxon beyond rodents through a non-invasive method.

Differential distributions of parvalbumin-positive interneurons in the sulci and gyri of the adult ferret cerebral cortex

Although accumulating evidence suggests that there are significant anatomical and histological differences between the sulci and gyri of the cerebral cortex, whether there is a difference in the distribution of interneurons between the two cortical regions remains largely unknown. In this study, we systematically compared the distributions of parvalbumin-positive interneurons among three neighboring gyrus and sulcus pairs-coronal gyrus and cruciate sulcus, anterior ectosylvian gyrus and rostral suprasylvian sulcus, and posterior ectosylvian gyrus and pseudosylvian sulcus-in the adult ferret cerebral cortex. We proposed a method to partition sulci and gyri into several specific subregions through the deepest points of the sulci and the highest points of gyri in the inner and outer cortical contours of coronal sections. We found that the density of parvalbumin-positive interneurons in the gyri was significantly higher than that in the sulci. Further study revealed that the density of PV interneurons in superficial cortical layers (layers 2/3 and layer 4) was comparable among the three pairs of sulci and gyri. However, the density of parvalbumin-positive interneurons in cortical layers 5/6 was significantly higher in gyri than in sulci. These results indicate that parvalbumin-positive interneurons are differently distributed in infragranular layers of cortical sulci and gyri.

Voxelwise-based Brain Function Network using Multi-Graph Model

In the research of the fMRI based brain functional network, the pairwise correlation between vertices usually means the similarity between BOLD signals. Our analysis found that the low (0:01–0:06 Hz), intermediate (0:06–0:15 Hz), and high (0:15–0:2 Hz) bands of the BOLD signal are not synchronous. Therefore, this paper presents a voxelwise based multi-frequency band brain functional network model, called Multi-graph brain functional network. First, our analysis found the low-frequency information on the BOLD signal of the brain functional network obscures the other information because of its high intensity. Then, a low-, intermediate-, and high-band brain functional networks were constructed by dividing the BOLD signals. After that, using complex network analysis, we found that different frequency bands have different properties; the modulation in low-frequency is higher than that of the intermediate and high frequency. The power distributions of different frequency bands were also significantly different, and the ‘hub’ vertices under all frequency bands are evenly distributed. Compared to a full-frequency network, the multi-graph model enhances the accuracy of the classification of Alzheimer’s disease.

Mapping multiple principles of parietal-frontal cortical organization using functional connectivity

Resting state functional connectivity has been promoted as a promising tool for creating cortical maps that show remarkable similarity to those established by invasive histological methods. While this tool has been largely used to identify and map cortical areas, its true potential in the context of studying connectional architecture and in conducting comparative neuroscience has remained unexplored. Here, we employ widely used resting state connectivity and data-driven clustering methods to extend this approach for the study of the organizational principles of the macaque parietal–frontal system. We show multiple, overlapping principles of organization, including a dissociation between dorsomedial and dorsolateral pathways and separate parietal–premotor and parietal–frontal pathways. These results demonstrate the suitability of this approach for understanding the complex organizational principles of the brain and for large-scale comparative neuroscience.

Theta Oscillations Organize Spiking Activity in Higher-Order Visual Thalamus during Sustained Attention

Higher-order visual thalamus plays a fundamental but poorly understood role in attention-demanding tasks. To investigate how neuronal dynamics in higher-order visual thalamus are modulated by sustained attention, we performed multichannel electrophysiological recordings in the lateral posterior-pulvinar complex (LP/pulvinar) in the ferret (Mustela putorius furo). We recorded single unit activity and local field potential (LFP) during the performance of the five-choice serial reaction time task (5-CSRTT), which is used in both humans and animals as an assay of sustained attention. We found that half of the units exhibited an increasing firing rate during the delay period before stimulus onset (attention-modulated units). In contrast, the non-attention-modulated units responded to the stimulus, but not during the delay period. Spike-field coherence (SFC) of only the attention-modulated neurons significantly increased from the start of the delay period until screen touch, predominantly in the θ frequency band. In addition, θ power and θ/γ phase amplitude coupling (PAC) were elevated throughout the delay period. Our findings suggest that the θ oscillation plays a central role in orchestrating thalamic signaling during sustained attention.

Basal forebrain contributes to default mode network regulation

The default mode network (DMN) is a collection of cortical brain regions that is active during states of rest or quiet wakefulness in humans and other mammalian species. A pertinent characteristic of the DMN is a suppression of local field potential gamma activity during cognitive task performance as well as during engagement with external sensory stimuli. Conversely, gamma activity is elevated in the DMN during rest. Here, we document that the rat basal forebrain (BF) exhibits the same pattern of responses, namely pronounced gamma oscillations during quiet wakefulness in the home cage and suppression of this activity during active exploration of an unfamiliar environment. We show that gamma oscillations are localized to the BF and that gamma-band activity in the BF has a directional influence on a hub of the rat DMN, the anterior cingulate cortex, during DMN-dominated brain states. The BF is well known as an ascending, activating, neuromodulatory system involved in wake-sleep regulation, memory formation, and regulation of sensory information processing. Our findings suggest a hitherto undocumented role of the BF as a subcortical node of the DMN, which we speculate may be important for switching between internally and externally directed brain states. We discuss potential BF projection circuits that could underlie its role in DMN regulation and highlight that certain BF nuclei may provide potential target regions for up- or down-regulation of DMN activity that might prove useful for treatment of DMN dysfunction in conditions such as epilepsy or major depressive disorder.

Resting state brain networks in the prairie vole

Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

Effects of neonatal deafness on resting-state functional network connectivity

Normal brain development depends on early sensory experience. Behavioral consequences of brain maturation in the absence of sensory input early in life are well documented. For example, experiments with mature, neonatally deaf human or animal subjects have revealed improved peripheral visual motion detection and spatial localization abilities. Such supranormal behavioral abilities in the nondeprived sensory modality are evidence of compensatory plasticity occurring in deprived brain regions at some point or throughout development. Sensory deprived brain regions may simply become unused neural real-estate resulting in a loss of function. Compensatory plasticity and loss of function are likely reflected in the differences in correlations between brain networks in deaf compared with hearing subjects. To address this, we used resting-state functional magnetic resonance imaging (fMRI) in lightly anesthetized hearing and neonatally deafened cats. Group independent component analysis (ICA) was used to identify 20 spatially distinct brain networks across all animals including auditory, visual, somatosensory, cingulate, insular, cerebellar, and subcortical networks. The resulting group ICA components were back-reconstructed to individual animal brains. The maximum correlations between the time-courses associated with each spatial component were computed using functional network connectivity (FNC). While no significant differences in the delay to peak correlations were identified between hearing and deaf cats, we observed 10 (of 190) significant differences in the amplitudes of between-network correlations. Six of the significant differences involved auditory-related networks and four involved visual, cingulate, or somatosensory networks. The results are discussed in context of known behavioral, electrophysiological, and anatomical differences following neonatal deafness. Furthermore, these results identify novel targets for future investigations at the neuronal level.

Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity

The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.