Intrinsic connectional architecture of the brain is a crucial element in understanding the governing principle of brain organization. To date, enormous effort has been focused on addressing this issue in humans by combining resting-state functional magnetic resonance imaging (rsfMRI) with other techniques. However, this research area is significantly underexplored in animals, perhaps due to confounding effects of anesthetic agents used in most animal experiments on functional connectivity. To bridge this gap, we have systematically investigated the intrinsic connectional architecture in the rodent brain by using a previously established awake animal imaging model. First, group independent component analysis was applied to the rsfMRI data to extract elementary functional clusters of the brain. The connectional relationships between these clusters evaluated by partial correlation analysis were then used to construct a graph of whole-brain neural network. This network exhibited typical features of small-worldness and strong community structures as shown in the human brain. Finally, the whole-brain network was segregated into community structures using a graph-based analysis. The results of this work provided a functional ‘atlas’ of intrinsic connectional architecture of the rat brain at both intra- and inter-region levels. More importantly, the current work revealed that functional networks in rats are organized in a non-trivial manner and conserved fundamental topological properties as the human brain. Given the high psychopathological relevance of network organization of the brain, this study demonstrated the feasibility to study mechanisms and therapies of multiple neurological and psychiatric diseases through translational research.

The neural mechanism of unconsciousness has been a major unsolved question in neuroscience despite its vital role in brain states like coma and anesthesia. The existing literature suggests that neural connections, information integration and conscious states are closely related. Indeed, alterations in several important neural circuitries and networks during unconscious conditions have been reported. However, how the whole-brain network is topologically reorganized to support different patterns of information transfer at unconscious states remains unknown. Here we directly compared whole-brain neural networks in an awake and an anesthetized state in rodents. Consistent with our previous report, the awake rat brain was organized in a non-trivial manner and conserved fundamental topological properties as the human brain. Strikingly, these topological features were well maintained in the anesthetized brain. Meanwhile, local neural networks were reorganized with altered local network properties. The connectional strength between brain regions was also considerably different between the awake and anesthetized conditions. Interestingly, we found that long-distance connections were not preferentially reduced in the anesthetized condition, arguing against the hypothesis that loss of long-distance connections is characteristic to unconsciousness. These findings collectively show that the integrity of the whole-brain network can be conserved between widely dissimilar physiologic states while local neural networks can flexibly adapt to new conditions. They also illustrate that the governing principles of intrinsic brain organization might represent fundamental characteristics of the healthy brain. With the unique spatial and temporal scales of rsfMRI, this study has opened a new avenue for understanding the neural mechanism of (un)consciousness.

Functional magnetic resonance imaging (fMRI) has allowed the noninvasive study of task-based and resting-state brain dynamics in humans by inferring neural activity from blood-oxygenation-level dependent (BOLD) signal changes. An accurate interpretation of the hemodynamic changes that underlie fMRI signals depends on the understanding of the quantitative relationship between changes in neural activity and changes in cerebral blood flow, oxygenation and volume. While there has been extensive study of neurovascular coupling in anesthetized animal models, anesthesia causes large disruptions of brain metabolism, neural responsiveness and cardiovascular function. Here, we review work showing that neurovascular coupling and brain circuit function in the awake animal are profoundly different from those in the anesthetized state. We argue that the time is right to study neurovascular coupling and brain circuit function in the awake animal to bridge the physiological mechanisms that underlie animal and human neuroimaging signals, and to interpret them in light of underlying neural mechanisms. Lastly, we discuss recent experimental innovations that have enabled the study of neurovascular coupling and brain-wide circuit function in un-anesthetized and behaving animal models.

In the present study we mapped brain functional connectivity in the conscious rat at the “resting state” based on intrinsic blood-oxygenation-level dependent (BOLD) fluctuations. The conscious condition eliminated potential confounding effects of anesthetic agents on the connectivity between brain regions. Indeed, using correlational analysis we identified multiple cortical and subcortical regions that demonstrated temporally synchronous variation with anatomically well-defined regions that are crucial to cognitive and emotional information processing including the prefrontal cortex (PFC), thalamus and retrosplenial cortex. The functional connectivity maps created were stringently validated by controlling for false positive detection of correlation, the physiologic basis of the signal source, as well as quantitatively evaluating the reproducibility of maps. Taken together, the present study has demonstrated the feasibility of assessing functional connectivity in conscious animals using fMRI and thus provided a convenient and non-invasive tool to systematically investigate the connectional architecture of selected brain networks in multiple animal models.

Resting-state functional connectivity (RSFC) measured by functional magnetic resonance imaging has played an essential role in understanding neural circuitry and brain diseases. The vast majority of RSFC studies have been focused on positive RSFC, whereas our understanding about its conceptual counterpart—negative RSFC (i.e. anticorrelation)—remains elusive. To date, anticorrelated RSFC has yet been observed without the commonly used preprocessing step of global signal correction. However, this step can induce artifactual anticorrelation (Murphy et al., 2009), making it difficult to determine whether the observed anticorrelation in humans is a processing artifact (Fox et al., 2005). In this report we demonstrated robust anticorrelated RSFC in a well characterized frontolimbic circuit between the infralimbic cortex (IL) and amygdala in the awake rat. This anticorrelation was anatomically specific, highly reproducible and independent of preprocessing methods. Interestingly, this anticorrelated relationship was absent in anesthetized rats even with global signal regression, further supporting its functional significance. Establishing negative RSFC independent of data preprocessing methods will significantly enhance the applicability of RSFC in better understanding neural circuitries and brain networks. In addition, combining the neurobiological data of the IL-amygdala circuit in rodents, the finding of the present study will enable further investigation of the neurobiological basis underlying anticorrelation.

Since its introduction, resting-state functional magnetic resonance imaging (rsfMRI) has been a powerful tool for investigating functional neural networks in both normal and pathological conditions. When measuring resting-state functional connectivity (RSFC), most rsfMRI approaches do not consider its temporal variations and thus only provide the averaged RSFC over the scan time. Recently, there has been a surge of interest to investigate the dynamic characteristics of RSFC in humans, and promising results have been yielded. However, our knowledge regarding the dynamic RSFC in animals remains sparse. In the present study we utilized the single-volume coactivation method to systematically study the dynamic properties of RSFC within the networks of infralimbic cortex (IL) and primary somatosensory cortex (S1) in both awake and anesthetized rats. Our data showed that both IL and S1 networks could be decomposed into several spatially reproducible but temporally changing co-activation patterns (CAPs), suggesting that dynamic RSFC was indeed a characteristic feature in rodents. In addition, we demonstrated that anesthesia profoundly impacted the dynamic RSFC of neural circuits subserving cognitive and emotional functions but had less effects on sensorimotor systems. Finally, we examined the temporal characteristics of each CAP, and found that individual CAPs exhibited consistent temporal evolution patterns. Together, these results suggest that dynamic RSFC might be a general phenomenon in vertebrate animals. In addition, this study has paved the way for further understanding the alterations of dynamic RSFC in animal models of brain disorders.

Simultaneous deep brain stimulation (DBS) and functional magnetic resonance imaging (fMRI) constitutes a powerful tool for elucidating brain functional connectivity, and exploring neuromodulatory mechanisms of DBS therapies. Previous DBS-fMRI studies could not provide full activation pattern maps due to poor MRI compatibility of the DBS electrodes, which caused obstruction of large brain areas on MRI scans. Here, we fabricate graphene fiber (GF) electrodes with high charge-injection-capacity and little-to-no MRI artifact at 9.4T. DBS-fMRI with GF electrodes at the subthalamic nucleus (STN) in Parkinsonian rats reveal robust blood-oxygenation-level-dependent responses along the basal ganglia-thalamocortical network in a frequency-dependent manner, with responses from some regions not previously detectable. This full map indicates that STN-DBS modulates both motor and non-motor pathways, possibly through orthodromic and antidromic signal propagation. With the capability for full, unbiased activation pattern mapping, DBS-fMRI using GF electrodes can provide important insights into DBS therapeutic mechanisms in various neurological disorders.

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