Effects of heartbeat and respiration on macaque fMRI: implications for functional connectivity

Subdural CMOS optical probe (SCOPe) for bidirectional neural interfacing

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical extents. While there has been significant progress in miniaturizing microscope for head-mounted configurations, these existing devices are still very bulky and could never be fully implanted. Any viable translation of these technologies to human use will require a much more noninvasive, fully implantable form factor. Here, we leverage advances in microelectronics and heterogeneous optoelectronic packaging to develop a transformative, ultrathin, miniaturized device for bidirectional optical stimulation and recording: the subdural CMOS Optical Probe (SCOPe). By being thin enough to lie entirely within the subdural space of the primate brain, SCOPe defines a path for the eventual human translation of a new generation of brain-machine interfaces based on light.

Contribution of animal models toward understanding resting state functional connectivity

Functional connectivity, which reflects the spatial and temporal organization of intrinsic activity throughout the brain, is one of the most studied measures in human neuroimaging research. The noninvasive acquisition of resting state functional magnetic resonance imaging (rs-fMRI) allows the characterization of features designated as functional networks, functional connectivity gradients, and time-varying activity patterns that provide insight into the intrinsic functional organization of the brain and potential alterations related to brain dysfunction. Functional connectivity, hence, captures dimensions of the brain's activity that have enormous potential for both clinical and preclinical research. However, the mechanisms underlying functional connectivity have yet to be fully characterized, hindering interpretation of rs-fMRI studies. As in other branches of neuroscience, the identification of the neurophysiological processes that contribute to functional connectivity largely depends on research conducted on laboratory animals, which provide a platform where specific, multi-dimensional investigations that involve invasive measurements can be carried out. These highly controlled experiments facilitate the interpretation of the temporal correlations observed across the brain. Indeed, information obtained from animal experimentation to date is the basis for our current understanding of the underlying basis for functional brain connectivity. This review presents a compendium of some of the most critical advances in the field based on the efforts made by the animal neuroimaging community.

Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection

Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.

Functional hyperemia drives fluid exchange in the paravascular space

The brain lacks a conventional lymphatic system to remove metabolic waste. It has been proposed that directional fluid movement through the arteriolar paravascular space (PVS) promotes metabolite clearance. We performed simulations to examine if arteriolar pulsations and dilations can drive directional CSF flow in the PVS and found that arteriolar wall movements do not drive directional CSF flow. We propose an alternative method of metabolite clearance from the PVS, namely fluid exchange between the PVS and the subarachnoid space (SAS). In simulations with compliant brain tissue, arteriolar pulsations did not drive appreciable fluid exchange between the PVS and the SAS. However, when the arteriole dilated, as seen during functional hyperemia, there was a marked exchange of fluid. Simulations suggest that functional hyperemia may serve to increase metabolite clearance from the PVS. We measured blood vessels and brain tissue displacement simultaneously in awake, head-fixed mice using two-photon microscopy. These measurements showed that brain deforms in response to pressure changes in PVS, consistent with our simulations. Our results show that the deformability of the brain tissue needs to be accounted for when studying fluid flow and metabolite transport.

Intersubject consistent dynamic connectivity during natural vision revealed by functional MRI

The functional communications between brain regions are thought to be dynamic. However, it is usually difficult to elucidate whether the observed dynamic connectivity is functionally meaningful or simply due to noise during unconstrained task conditions such as resting-state. During naturalistic conditions, such as watching a movie, it has been shown that local brain activities, e.g. in the visual cortex, are consistent across subjects. Following similar logic, we propose to study intersubject correlations of the time courses of dynamic connectivity during naturalistic conditions to extract functionally meaningful dynamic connectivity patterns. We analyzed a functional MRI (fMRI) dataset when the subjects watched a short animated movie. We calculated dynamic connectivity by using sliding window technique, and quantified the intersubject correlations of the time courses of dynamic connectivity. Although the time courses of dynamic connectivity are thought to be noisier than the original signals, we found similar level of intersubject correlations of dynamic connectivity to those of regional activity. Most importantly, highly consistent dynamic connectivity could occur between regions that did not show high intersubject correlations of regional activity, and between regions with little stable functional connectivity. The analysis highlighted higher order brain regions such as the default mode network that dynamically interacted with posterior visual regions during the movie watching, which may be associated with the understanding of the movie.

A 16-channel AC/DC array coil for anesthetized monkey whole-brain imaging at 7T

Functional magnetic resonance imaging (fMRI) in monkeys is important for bridging the gap between invasive animal brain studies and non-invasive human brain studies. To resolve the finer functional structure of the monkey brain, ultra-high-field (UHF) MR is essential, and high-performance, close-fitting RF receive coils are typically desired to fully leverage the intrinsic gains provided by UHF MRI. Moreover, static field (B0) inhomogeneity arising from the tissue susceptibility interface is more severe at UHF, presenting an obstacle to achieving high-resolution fMRI. B0 shim of the monkey head is challenging due to its smaller size and more complex sources of B0 offsets in multi-modal imaging tasks. In the present work, we have customized an array coil for lightly-anesthetized monkey fMRI in the 7T human scanner that combines RF and multi-coil (MC) B0 shim functionality (also referred to as AC/DC coils) to provide high imaging SNR and high-spatial-order, rapidly switchable B0-shim capability. Additional space was retained on the coil to render it compatible with monkey multi-modal imaging studies. Both MC global (whole-volume) and dynamic (slice-optimized) shim methods were tested and evaluated, and the benefits of MC shim for fMRI experiments was also studied. A minor reduction in RF coil performance was found after introducing additional B0 shim circuitry. However, the proposed RF coil provided higher image SNR and more uniform contrast compared to a commercially available coil for human knee imaging. Compared with static 2nd-order shim, the B0 inhomogeneity was reduced by 56.8%, and 95-percentile B0 offset was reduced to within 28.2 Hz through MC shim, versus 68.7 Hz with 2nd-order static shim. As a result, functional image quality could be improved, and brain activation can be better detected using the proposed AC/DC monkey coil.

Isoflurane-Induced Burst Suppression Increases Intrinsic Functional Connectivity of the Monkey Brain

Animal functional magnetic resonance imaging (fMRI) has provided key insights into the physiological mechanisms underlying healthy and diseased brain states. In non-human primates, resting-state fMRI studies are commonly conducted under isoflurane anesthesia, where anesthetic concentration is used to roughly infer anesthesia depth. However, within the recommended isoflurane concentration range (1.00–1.50%), the brain state can switch from moderate anesthesia characterized by stable slow wave (SW) electroencephalogram (EEG) signals to deep anesthesia characterized by burst suppression (BS), which is electrophysiologically distinct from the resting state. To confirm the occurrence rate of BS activity in common setting of animal fMRI study, we conducted simultaneous resting-state EEG and fMRI experiments on 16 monkeys anesthetized using 0.80–1.30% isoflurane, and detected BS activity in two of them. Datasets either featured with BS or SW activity from these two monkeys were analyzed to investigate the intrinsic functional connectivity (FC) patterns during BS. In datasets with BS activity, we observed robust coupling between the BS pattern (the binary alternation between burst and suppression activity in EEG signal) and filtered BOLD signals in most brain areas, which was associated with a non-specific enhancement in whole brain connectivity. After eliminating the BS coupling effect by regressing out the BS pattern, we detected an overall increase in FC with a few decreased connectivity compared to datasets with SW activity. These affected connections were preferentially distributed within orbitofrontal cortex, between orbitofrontal and prefrontal/cingulate/occipital cortex, and between temporal and parietal cortex. Persistence of the default mode network and recovery of thalamocortical connections were also detected under deep anesthesia with BS activity. Taken together, the observed spatially specific alterations in BS activity induced by isoflurane not only highlight the necessity of EEG monitoring and careful data preprocessing in fMRI studies on anesthetized animals, but also advance our understanding of the underlying multi-phased mechanisms of anesthesia.

The evolution of the temporoparietal junction and posterior superior temporal sulcus

The scale at which humans can handle complex social situations is massively increased compared to other animals. However, the neural substrates of this scaling remain poorly understood. In this review, we discuss how the expansion and rearrangement of the temporoparietal junction and posterior superior temporal sulcus (TPJ-pSTS) may have played a key role in the growth of human social abilities. Comparing the function and anatomy of the TPJ-pSTS in humans and macaques, which are thought to be separated by 25 million years of evolution, we find that the expansion of this region in humans has shifted the architecture of the dorsal and ventral processing streams. The TPJ-pSTS contains areas related to face-emotion processing, attention, theory of mind operations, and memory; its expansion has allowed for the elaboration and rearrangement of the cortical areas contained within, and potentially the introduction of new cortical areas. Based on the arrangement and the function of these areas in the human, we propose that the TPJ-pSTS is the basis of a third frontoparietal processing stream that underlies the increased social abilities in humans. We then describe a model of how the TPJ-pSTS areas interact as a hub that coordinates the activities of multiple brain networks in the exploration of the complex dynamic social scenes typical of the human social experience.

Attention Shifts Recruit the Monkey Default Mode Network

A unifying function associated with the default mode network (DMN), which is more active during rest than under active task conditions, has been difficult to define. The DMN is activated during monitoring the external world for unexpected events, as a sentinel, and when humans are engaged in high-level internally focused tasks. The existence of DMN correlates in other species, such as mice, challenge the idea that internally focused, high-level cognitive operations, such as introspection, autobiographical memory retrieval, planning the future, and predicting someone else's thoughts, are evolutionarily preserved defining properties of the DMN. A recent human study demonstrated that demanding cognitive shifts could recruit the DMN, yet it is unknown whether this holds for nonhuman species. Therefore, we tested whether large changes in cognitive context would recruit DMN regions in female and male nonhuman primates. Such changes were measured as displacements of spatial attentional weights based on internal rules of relevance (spatial shifts) compared with maintaining attentional weights at the same location (stay events). Using fMRI in macaques, we detected that a cortical network, activated during shifts, largely overlapped with the DMN. Moreover, fMRI time courses sampled from independently defined DMN foci showed significant shift selectivity during the demanding attention task. Finally, functional clustering based on independent resting state data revealed that DMN and shift regions clustered conjointly, whereas regions activated during the stay events clustered apart. We therefore propose that cognitive shifting in primates generally recruits DMN regions. This might explain a breakdown of the DMN in many neurological diseases characterized by declined cognitive flexibility.SIGNIFICANCE STATEMENT Activation of the human default mode network (DMN) can be measured with fMRI when subjects shift thoughts between high-level internally directed cognitive states, when thinking about the self, the perspective of others, when imagining future and past events, and during mind wandering. Furthermore, the DMN is activated as a sentinel, monitoring the environment for unexpected events. Arguably, these cognitive processes have in common fast and substantial changes in cognitive context. As DMN activity has also been reported in nonhuman species, we tested whether shifts in spatial attention activated the monkey DMN. Core monkey DMN and shift-selective regions shared several functional properties, indicating that cognitive shifting, in general, might constitute one of the evolutionarily preserved functions of the DMN.

Connectome-scale functional intrinsic connectivity networks in macaques

There have been extensive studies of intrinsic connectivity networks (ICNs) in the human brains using resting-state functional magnetic resonance imaging (fMRI) in the literature. However, the functional organization of ICNs in macaque brains has been less explored so far, despite growing interests in the field. In this work, we propose a computational framework to identify connectome-scale group-wise consistent ICNs in macaques via sparse representation of whole-brain resting-state fMRI data. Experimental results demonstrate that 70 group-wise consistent ICNs are successfully identified in macaque brains via the proposed framework. These 70 ICNs are interpreted based on two publicly available parcellation maps of macaque brains and our work significantly expand currently known macaque ICNs already reported in the literature. In general, this set of connectome-scale group-wise consistent ICNs can potentially benefit a variety of studies in the neuroscience and brain-mapping fields, and they provide a foundation to better understand brain evolution in the future.

Mapping complementary features of cross-species structural connectivity to construct realistic "Virtual Brains"

Modern systems neuroscience increasingly leans on large-scale multi-lab neuroinformatics initiatives to provide necessary capacity for biologically realistic modeling of primate whole-brain activity. Here, we present a framework to assemble primate brain's biologically plausible anatomical backbone for such modeling initiatives. In this framework, structural connectivity is determined by adding complementary information from invasive macaque axonal tract tracing and non-invasive human diffusion tensor imaging. Both modalities are combined by means of available interspecies registration tools and a newly developed Bayesian probabilistic modeling approach to extract common connectivity evidence. We demonstrate how this novel framework is embedded in the whole-brain simulation platform called The Virtual Brain (TVB). Hum Brain Mapp 38:2080-2093, 2017. © 2017 Wiley Periodicals, Inc.

Face Patch Resting State Networks Link Face Processing to Social Cognition

Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills.

An analysis of the functional connectivity of regions of the monkey brain involved in face recognition suggests substrates for the cognitive, mnemonic, emotive, and motoric impact of faces, revealing striking similarities to the human brain, and implying a deep evolutionary heritage of even the most high-level sociocognitive functions.

Primates have evolved to transmit social information through their faces. Where and how the brain processes facial information received by the eyes we now understand quite well. Yet we do not know how this information is made available to other brain areas so that a face can evoke an emotion, activate the memory of a person, or draw attention. Here, to identify brain regions interacting with face areas, we performed whole-brain imaging in macaque monkeys, whose face-processing system we know best. We find that the core face-processing areas are connected to several other brain areas supporting socially, emotionally, and cognitively relevant functions. Together, they form an extended face-processing network, similar to what has been proposed for humans. This extended face-processing network intersects with a second large-scale network, the so-called “default mode network”, in a pattern stunningly similar to that in the human brain. This intersection identifies selectively those brain regions that implement the most high-level forms of social cognition, such as understanding others’ thoughts and feelings. Thus, the results of this novel approach to understanding the functional organization of the social brain point to a deep evolutionary heritage of human abilities for social cognition.

Network structure shapes spontaneous functional connectivity dynamics

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture.

Functional connectivity arises from a slow rhythmic mechanism

The mechanism underlying temporal correlations among blood oxygen level-dependent signals is unclear. We used oxygen polarography to better characterize oxygen fluctuations and their correlation and to gain insight into the driving mechanism. The power spectrum of local oxygen fluctuations is inversely proportional to frequency raised to a power (1/f) raised to the beta, with an additional positive band-limited component centered at 0.06 Hz. In contrast, the power of the correlated oxygen signal is band limited from ∼ 0.01 Hz to 0.4 Hz with a peak at 0.06 Hz. These results suggest that there is a band-limited mechanism (or mechanisms) driving interregional oxygen correlation that is distinct from the mechanism(s) driving local (1/f) oxygen fluctuations. Candidates for driving interregional oxygen correlation include rhythmic or pseudo-oscillatory mechanisms.

Isoflurane induces dose-dependent alterations in the cortical connectivity profiles and dynamic properties of the brain's functional architecture

Despite their widespread use, the effect of anesthetic agents on the brain's functional architecture remains poorly understood. This is particularly true of alterations that occur beyond the point of induced unconsciousness. Here, we examined the distributed intrinsic connectivity of macaques across six isoflurane levels using resting-state functional MRI (fMRI) following the loss of consciousness. The results from multiple analysis strategies showed stable functional connectivity (FC) patterns between 1.00% and 1.50% suggesting this as a suitable range for anesthetized nonhuman primate resting-state investigations. Dose-dependent effects were evident at moderate to high dosages showing substantial alteration of the functional topology and a decrease or complete loss of interhemispheric cortical FC strength including that of contralateral homologues. The assessment of dynamic FC patterns revealed that the functional repertoire of brain states is related to anesthesia depth and most strikingly, that the number of state transitions linearly decreases with increased isoflurane dosage. Taken together, the results indicate dose-specific spatial and temporal alterations of FC that occur beyond the typically defined endpoint of consciousness. Future work will be necessary to determine how these findings generalize across anesthetic types and extend to the transition between consciousness and unconsciousness.

The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI

Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. In the current study, the robustness of this standard approach to physiological variations in a placebo controlled, repeated measures pharmacological RSfMRI study of morphine and alcohol in 12 healthy young men is tested. The impact of physiology-related variations on statistical inferences has been studied by: 1) modeling average physiological rates in higher level group analysis; 2) Regressing out the instantaneous respiration variation (RV); 3) applying retrospective image correction (RETROICOR) in the preprocessing stage; and 4) performing combined RV and heart rate correction (RVHRCOR) by regressing out physiological pulses convolved with canonical respiratory and cardiac hemodynamic response functions. Results indicate regional sensitivity of the BOLD signal to physiological variations, especially in the vicinity of large vessels, plus certain brain structures that are reported to be involved in physiological regulation, such as posterior cingulate, precuneus, medial prefrontal and insular cortices, as well as the thalamus, cerebellum and the brainstem. The largest impact of "correction" on final statistical test outcomes resulted from including the average respiration frequency and heart rate in the higher-level group analysis. Overall, the template-based dual regression method seems robust against physical noise that is corrected by RV regression or RETROICOR. However, convolving the RV and HR with canonical hemodynamic response functions caused a notable change in the BOLD signal variance, and in resting state connectivity estimates. The impact of RVHRCOR on statistical tests was limited to elimination of both morphine and alcohol effects related to the somatosensory network that consists of insula and cingulate cortex-important structures for autonomic regulation. Although our data do not warrant speculations about neuronal or vascular origins of these effects, these observations raise caution about the implications of physiological 'noise' and the risks of introducing false positives (e.g. increased white matter connectivity) by using generalized physiological correction methods in pharmacological studies. The obvious sensitivity of the posterior part of the default mode network to different correction schemes, underlines the importance of controlling for physiological fluctuations in seed-based functional connectivity analyses.

Monkey in the middle: why non-human primates are needed to bridge the gap in resting-state investigations

Resting-state investigations based on the evaluation of intrinsic low-frequency fluctuations of the BOLD fMRI signal have been extensively utilized to map the structure and dynamics of large-scale functional network organization in humans. In addition to increasing our knowledge of normal brain connectivity, disruptions of the spontaneous hemodynamic fluctuations have been suggested as possible diagnostic indicators of neurological and psychiatric disease states. Though the non-invasive technique has been received with much acclamation, open questions remain regarding the origin, organization, phylogenesis, as well as the basis of disease-related alterations underlying the signal patterns. Experimental work utilizing animal models, including the use of neurophysiological recordings and pharmacological manipulations, therefore, represents a critical component in the understanding and successful application of resting-state analysis, as it affords a range of experimental manipulations not possible in human subjects. In this article, we review recent rodent and non-human primate studies and based on the examination of the homologous brain architecture propose the latter to be the best-suited model for exploring these unresolved resting-state concerns. Ongoing work examining the correspondence of functional and structural connectivity, state-dependency and the neuronal correlates of the hemodynamic oscillations are discussed. We then consider the potential experiments that will allow insight into different brain states and disease-related network disruptions that can extend the clinical applications of resting-state fMRI (RS-fMRI).

Anatomical and functional assemblies of brain BOLD oscillations

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD) signal. Resting-state BOLD signal was transformed into frequency space (Welch's method) and averaged across subjects, and its spatial distribution was studied as a function of four frequency bands, spanning the full BOLD bandwidth. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), versus complex properties (transmodal), are dominated by low-frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher-frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking BOLD frequency properties to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency-dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxelwise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs.

Functional connectivity fMRI of the rodent brain: comparison of functional connectivity networks in rat and mouse

At present, resting state functional MRI (rsfMRI) is increasingly used in human neuropathological research. The present study aims at implementing rsfMRI in mice, a species that holds the widest variety of neurological disease models. Moreover, by acquiring rsfMRI data with a comparable protocol for anesthesia, scanning and analysis, in both rats and mice we were able to compare findings obtained in both species. The outcome of rsfMRI is different for rats and mice and depends strongly on the applied number of components in the Independent Component Analysis (ICA). The most important difference was the appearance of unilateral cortical components for the mouse resting state data compared to bilateral rat cortical networks. Furthermore, a higher number of components was needed for the ICA analysis to separate different cortical regions in mice as compared to rats.