Interindividual Variability of Functional Connectivity in Awake and Anesthetized Rhesus Macaque Monkeys

Cognitive network interactions through communication subspaces in large-scale models of the neocortex

Neocortex-wide neural activity is organized into distinct networks of areas engaged in different cognitive processes. To elucidate the underlying mechanism of flexible network reconfiguration, we developed connectivity-constrained macaque and human whole-cortex models. In our model, within-area connectivity consists of a mixture of symmetric, asymmetric, and random motifs that give rise to stable (attractor) or transient (sequential) heterogeneous dynamics. Assuming sparse low-rank plus random inter-areal connectivity constrained by cognitive networks' activation maps, we show that our model captures key aspects of the cognitive networks' dynamics and interactions observed experimentally. In particular, the anti-correlation between the default mode network and the dorsal attention network. Communication between networks is shaped by the alignment of long-range communication subspaces with local connectivity motifs and is switchable in a bottom-up salience-dependent routing mechanism. Furthermore, the frontoparietal multiple-demand network displays a coexistence of stable and dynamic coding, suitable for top-down cognitive control. Our work provides a theoretical framework for understanding the dynamic routing in the cortical networks during cognition.

Evolutionarily conserved fMRI network dynamics in the mouse, macaque, and human brain

Evolutionarily relevant networks have been previously described in several mammalian species using time-averaged analyses of fMRI time-series. However, fMRI network activity is highly dynamic and continually evolves over timescales of seconds. Whether the dynamic organization of resting-state fMRI network activity is conserved across mammalian species remains unclear. Using frame-wise clustering of fMRI time-series, we find that intrinsic fMRI network dynamics in awake male macaques and humans is characterized by recurrent transitions between a set of 4 dominant, neuroanatomically homologous fMRI coactivation modes (C-modes), three of which are also plausibly represented in the male rodent brain. Importantly, in all species C-modes exhibit species-invariant dynamic features, including preferred occurrence at specific phases of fMRI global signal fluctuations, and a state transition structure compatible with infraslow coupled oscillator dynamics. Moreover, dominant C-mode occurrence reconstitutes the static organization of the fMRI connectome in all species, and is predictive of ranking of corresponding fMRI connectivity gradients. These results reveal a set of species-invariant principles underlying the dynamic organization of fMRI networks in mammalian species, and offer novel opportunities to relate fMRI network findings across the phylogenetic tree.

Multimodal Connectivity-Based Individual Parcellation and Analysis for Humans and Rhesus Monkeys

Individual brains vary greatly in morphology, connectivity and organization. Individualized brain parcellation is capable of precisely localizing subject-specific functional regions. However, most individualization approaches have examined single modalities of data and have not generalized to nonhuman primates. The present study proposed a novel multimodal connectivity-based individual parcellation (MCIP) method, which optimizes within-region homogeneity, spatial continuity and similarity to a reference atlas with the fusion of personal functional and anatomical connectivity. Comprehensive evaluation demonstrated that MCIP outperformed state-of-the-art multimodal individualization methods in terms of functional and anatomical homogeneity, predictability of cognitive measures, heritability, reproducibility and generalizability across species. Comparative investigation showed a higher topographic variability in humans than that in macaques. Therefore, MCIP provides improved accurate and reliable mapping of brain functional regions over existing methods at an individual level across species, and could facilitate comparative and translational neuroscience research.

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks.

A measure of reliability convergence to select and optimize cognitive tasks for individual differences research

Surging interest in individual differences has faced setbacks in light of recent replication crises in psychology, for example in brain-wide association studies exploring brain-behavior correlations. A crucial component of replicability for individual differences studies, which is often assumed but not directly tested, is the reliability of the measures we use. Here, we evaluate the reliability of different cognitive tasks on a dataset with over 250 participants, who each completed a multi-day task battery. We show how reliability improves as a function of number of trials, and describe the convergence of the reliability curves for the different tasks, allowing us to score tasks according to their suitability for studies of individual differences. We further show the effect on reliability of measuring over multiple time points, with tasks assessing different cognitive domains being differentially affected. Data collected over more than one session may be required to achieve trait-like stability.

The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

Measures of fMRI resting-state functional connectivity (rs-FC) are an essential tool for basic and clinical investigations of fronto-limbic circuits. Understanding the relationship between rs-FC and the underlying patterns of neural activity in these circuits is therefore vital. Here we introduced inhibitory designer receptors exclusively activated by designer drugs (DREADDs) into the amygdala of two male macaques. We evaluated the causal effect of activating the DREADD receptors on rs-FC and neural activity within circuits connecting amygdala and frontal cortex. Activating the inhibitory DREADD increased rs-FC between amygdala and ventrolateral prefrontal cortex. Neurophysiological recordings revealed that the DREADD-induced increase in fMRI rs-FC was associated with increased local field potential coherency in the alpha band (6.5-14.5 Hz) between amygdala and ventrolateral prefrontal cortex. Thus, our multi-modal approach reveals the specific signature of neuronal activity that underlies rs-FC in fronto-limbic circuits.

Systematic cross-species comparison of prefrontal cortex functional networks targeted via Transcranial Magnetic Stimulation

Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation method that safely modulates neural activity in vivo. Its precision in targeting specific brain networks makes TMS invaluable in diverse clinical applications. For example, TMS is used to treat depression by targeting prefrontal brain networks and their connection to other brain regions. However, despite its widespread use, the underlying neural mechanisms of TMS are not completely understood. Non-human primates (NHPs) offer an ideal model to study TMS mechanisms through invasive electrophysiological recordings. As such, bridging the gap between NHP experiments and human applications is imperative to ensure translational relevance. Here, we systematically compare the TMS-targeted functional networks in the prefrontal cortex in humans and NHPs. To conduct this comparison, we combine TMS electric field modeling in humans and macaques with resting-state functional magnetic resonance imaging (fMRI) data to compare the functional networks targeted via TMS across species. We identified distinct stimulation zones in macaque and human models, each exhibiting variations in the impacted networks (macaque: Frontoparietal Network, Somatomotor Network; human: Frontoparietal Network, Default Network). We identified differences in brain gyrification and functional organization across species as the underlying cause of found network differences. The TMS-network profiles we identified will allow researchers to establish consistency in network activation across species, aiding in the translational efforts to develop improved TMS functional network targeting approaches.

Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain's computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapt across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in male mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.

Mapping and comparing fMRI connectivity networks across species

Technical advances in neuroimaging, notably in fMRI, have allowed distributed patterns of functional connectivity to be mapped in the human brain with increasing spatiotemporal resolution. Recent years have seen a growing interest in extending this approach to rodents and non-human primates to understand the mechanism of fMRI connectivity and complement human investigations of the functional connectome. Here, we discuss current challenges and opportunities of fMRI connectivity mapping across species. We underscore the critical importance of physiologically decoding neuroimaging measures of brain (dys)connectivity via multiscale mechanistic investigations in animals. We next highlight a set of general principles governing the organization of mammalian connectivity networks across species. These include the presence of evolutionarily conserved network systems, a dominant cortical axis of functional connectivity, and a common repertoire of topographically conserved fMRI spatiotemporal modes. We finally describe emerging approaches allowing comparisons and extrapolations of fMRI connectivity findings across species. As neuroscientists gain access to increasingly sophisticated perturbational, computational and recording tools, cross-species fMRI offers novel opportunities to investigate the large-scale organization of the mammalian brain in health and disease.

The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

Measures of fMRI resting-state functional connectivity (rs-FC) are an essential tool for basic and clinical investigations of fronto-limbic circuits. Understanding the relationship between rs-FC and neural activity in these circuits is therefore vital. Here we introduced inhibitory designer receptors exclusively activated by designer drugs (DREADDs) into the macaque amygdala and activated them with a highly selective and potent DREADD agonist, deschloroclozapine. We evaluated the causal effect of activating the DREADD receptors on rs-FC and neural activity within circuits connecting amygdala and frontal cortex. Interestingly, activating the inhibitory DREADD increased rs-FC between amygdala and ventrolateral prefrontal cortex. Neurophysiological recordings revealed that the DREADD-induced increase in fMRI rs-FC was associated with increased local field potential coherency in the alpha band (6.5-14.5Hz) between amygdala and ventrolateral prefrontal cortex. Thus, our multi-disciplinary approach reveals the specific signature of neuronal activity that underlies rs-FC in fronto-limbic circuits.

Variation in spatial dependencies across the cortical mantle discriminates the functional behaviour of primary and association cortex

Recent theories of cortical organisation suggest features of function emerge from the spatial arrangement of brain regions. For example, association cortex is located furthest from systems involved in action and perception. Association cortex is also 'interdigitated' with adjacent regions having different patterns of functional connectivity. It is assumed that topographic properties, such as distance between regions, constrains their functions, however, we lack a formal description of how this occurs. Here we use variograms, a quantification of spatial autocorrelation, to profile how function changes with the distance between cortical regions. We find function changes with distance more gradually within sensory-motor cortex than association cortex. Importantly, systems within the same type of cortex (e.g., fronto-parietal and default mode networks) have similar profiles. Primary and association cortex, therefore, are differentiated by how function changes over space, emphasising the value of topographical features of a region when estimating its contribution to cognition and behaviour.

Cytoarchitectonic, receptor distribution and functional connectivity analyses of the macaque frontal lobe

Based on quantitative cyto- and receptor architectonic analyses, we identified 35 prefrontal areas, including novel subdivisions of Walker's areas 10, 9, 8B, and 46. Statistical analysis of receptor densities revealed regional differences in lateral and ventrolateral prefrontal cortex. Indeed, structural and functional organization of subdivisions encompassing areas 46 and 12 demonstrated significant differences in the interareal levels of α2 receptors. Furthermore, multivariate analysis included receptor fingerprints of previously identified 16 motor areas in the same macaque brains and revealed 5 clusters encompassing frontal lobe areas. We used the MRI datasets from the non-human primate data sharing consortium PRIME-DE to perform functional connectivity analyses using the resulting frontal maps as seed regions. In general, rostrally located frontal areas were characterized by bigger fingerprints, that is, higher receptor densities, and stronger regional interconnections. Whereas more caudal areas had smaller fingerprints, but showed a widespread connectivity pattern with distant cortical regions. Taken together, this study provides a comprehensive insight into the molecular structure underlying the functional organization of the cortex and, thus, reconcile the discrepancies between the structural and functional hierarchical organization of the primate frontal lobe. Finally, our data are publicly available via the EBRAINS and BALSA repositories for the entire scientific community.

Behavioral assessment scale of consciousness for nonhuman primates: A Delphi study

OBJECTIVE

Nonhuman primates (NHPs) are suitable for being model animals in the study of consciousness and loss of consciousness (LoC) with a similar brain structure and function to humans. However, there is no effective consciousness assessment scale for them. This study aimed to develop a behavioral assessment scale of consciousness for NHPs.

METHODS

We constructed an initial indicator framework based on the clinical consciousness disorder assessment scales and the physiological characteristics, consciousness, and arousal behavior of NHPs. A two-round online Delphi method was conducted by a multidisciplinary expert panel to construct a behavioral assessment scale of consciousness for NHPs. The indicators and descriptions were revised according to the experts' feedback and then sent out for repeated consultations along with a summary of the results of the previous round of consultations. The accepted competencies of indicators were established with mean scores in two scoring criteria (importance and feasibility) ≥4.0, agreement rate with a rating of importance or essential ≥70.0%, and a coefficient of variation ≤0.25, as well as discussions of the research group.

RESULTS

Consensus was achieved after the second round of consultations, which was completed by 28 experts who specialized in rehabilitation, neuroscience, psychology, neurosurgery, and neurology. A new behavioral assessment scale of consciousness for NHPs, including 37 items organized hierarchically within seven dimensions including visual function, auditory function, motor function, orofacial movements, arousal, brainstem reflexes, and respiration, was developed in this study.

CONCLUSIONS

This study has successfully developed a behavioral assessment scale for measuring the conscious state of NHPs or NHP models with LoC. This tool is expected to facilitate future research into the underlying mechanisms of consciousness by providing a detailed and comprehensive means of measurement.

Omnipresence of the sensorimotor-association axis topography in the human connectome

Low-dimensional representations are increasingly used to study meaningful organizational principles within the human brain. Most notably, the sensorimotor-association axis consistently explains the most variance in the human connectome as its so-called principal gradient, suggesting that it represents a fundamental organizational principle. While recent work indicates these low dimensional representations are relatively robust, they are limited by modeling only certain aspects of the functional connectivity structure. To date, the majority of studies have restricted these approaches to the strongest connections in the brain, treating weaker or negative connections as noise despite evidence of meaningful structure among them. The present work examines connectivity gradients of the human connectome across a full range of connectivity strengths and explores the implications for outcomes of individual differences, identifying potential dependencies on thresholds and opportunities to improve prediction tasks. Interestingly, the sensorimotor-association axis emerged as the principal gradient of the human connectome across the entire range of connectivity levels. Moreover, the principal gradient of connections at intermediate strengths encoded individual differences, better followed individual-specific anatomical features, and was also more predictive of intelligence. Taken together, our results add to evidence of the sensorimotor-association axis as a fundamental principle of the brain's functional organization, since it is evident even in the connectivity structure of more lenient connectivity thresholds. These more loosely coupled connections further appear to contain valuable and potentially important information that could be used to improve our understanding of individual differences, diagnosis, and the prediction of treatment outcomes.

Cerebral Activity in Female Baboons (Papio anubis) During the Perception of Conspecific and Heterospecific Agonistic Vocalizations: a Functional Near Infrared Spectroscopy Study

The "voice areas" in the superior temporal cortex have been identified in both humans and non-human primates as selective to conspecific vocalizations only (i.e., expressed by members of our own species), suggesting its old evolutionary roots across the primate lineage. With respect to non-human primate species, it remains unclear whether the listening of vocal emotions from conspecifics leads to similar or different cerebral activations when compared to heterospecific calls (i.e., expressed by another primate species) triggered by the same emotion. Using a neuroimaging technique rarely employed in monkeys so far, functional Near Infrared Spectroscopy, the present study investigated in three lightly anesthetized female baboons (Papio anubis), temporal cortex activities during exposure to agonistic vocalizations from conspecifics and from other primates (chimpanzees-Pan troglodytes), and energy matched white noises in order to control for this low-level acoustic feature. Permutation test analyses on the extracted OxyHemoglobin signal revealed great inter-individual differences on how conspecific and heterospecific vocal stimuli were processed in baboon brains with a cortical response recorded either in the right or the left temporal cortex. No difference was found between emotional vocalizations and their energy-matched white noises. Despite the phylogenetic gap between Homo sapiens and African monkeys, modern humans and baboons both showed a highly heterogeneous brain process for the perception of vocal and emotional stimuli. The results of this study do not exclude that old evolutionary mechanisms for vocal emotional processing may be shared and inherited from our common ancestor.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s42761-022-00164-z.

The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure

Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV.

Geometric effects of volume-to-surface mapping of fMRI data

In this work, we identify a problem with the process of volume-to-surface mapping of functional Magnetic Resonance Imaging (fMRI) data that emerges in local connectivity analysis. We show that neighborhood correlations on the surface of the brain vary spatially with the gyral structure, even when the underlying volumetric data are uncorrelated noise. This could potentially have impacted studies focusing upon local neighborhood connectivity. We explore the effects of this anomaly across varying data resolutions and surface mesh densities, and propose several measures to mitigate these unwanted effects.

A Macaque Brain Extraction Model Based on U-Net Combined with Residual Structure

Accurately extracting brain tissue is a critical and primary step in brain neuroimaging research. Due to the differences in brain size and structure between humans and nonhuman primates, the performance of the existing tools for brain tissue extraction, working on macaque brain MRI, is constrained. A new transfer learning training strategy was utilized to address the limitations, such as insufficient training data and unsatisfactory model generalization ability, when deep neural networks processing the limited samples of macaque magnetic resonance imaging(MRI). First, the project combines two human brain MRI data modes to pre-train the neural network, in order to achieve faster training and more accurate brain extraction. Then, a residual network structure in the U-Net model was added, in order to propose a ResTLU-Net model that aims to improve the generalization ability of multiple research sites data. The results demonstrated that the ResTLU-Net, combined with the proposed transfer learning strategy, achieved comparable accuracy for the macaque brain MRI extraction tasks on different macaque brain MRI volumes that were produced by various medical centers. The mean Dice of the ResTLU-Net was 95.81% (no need for denoise and recorrect), and the method required only approximately 30–60 s for one extraction task on an NVIDIA 1660S GPU.

Unique spatiotemporal fMRI dynamics in the awake mouse brain

Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally conscious states. However, whether and how this phenomenon can be generalized to lower mammalian species remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping in non-anesthetized, head-fixed mice, we investigated functional network topography and dynamic structure of spontaneous brain activity in wakeful animals. We found that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the mouse axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation patterns encompassing a prominent participation of arousal-related forebrain nuclei and functional anti-coordination between visual-auditory and polymodal cortical areas. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation patterns are configured as network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems and document that its dynamic structure recapitulates distinctive, evolutionarily relevant principles that are predictive of conscious states in higher mammalian species.

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fMRI networks in awake mice depart from underlying anatomical structure

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fMRI dynamics in wakeful mice is critically shaped by arousal-related nuclei

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Occurrence and topography of rsfMRI coactivation patterns define conscious states

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fMRI coactivation dynamics defines a signature of consciousness in the mouse brain

Transcriptomic and macroscopic architectures of intersubject functional variability in human brain white-matter

Intersubject variability is a fundamental characteristic of brain organizations, and not just "noise". Although intrinsic functional connectivity (FC) is unique to each individual and varies across brain gray-matter, the underlying mechanisms of intersubject functional variability in white-matter (WM) remain unknown. This study identified WMFC variabilities and determined the genetic basis and macroscale imaging in 45 healthy subjects. The functional localization pattern of intersubject variability across WM is heterogeneous, with most variability observed in the heteromodal cortex. The variabilities of heteromodal regions in expression profiles of genes are related to neuronal cells, involved in synapse-related and glutamic pathways, and associated with psychiatric disorders. In contrast, genes overexpressed in unimodal regions are mostly expressed in glial cells and were related to neurological diseases. Macroscopic variability recapitulates the functional and structural specializations and behavioral phenotypes. Together, our results provide clues to intersubject variabilities of the WMFC with convergent transcriptomic and cellular signatures, which relate to macroscale brain specialization.

Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate

A wide homology between human and macaque striatum is often assumed as in both the striatum is involved in cognition, emotion and executive functions. However, differences in functional and structural organization between human and macaque striatum may reveal evolutionary divergence and shed light on human vulnerability to neuropsychiatric diseases. For instance, dopaminergic dysfunction of the human striatum is considered to be a pathophysiological underpinning of different disorders, such as Parkinson's disease (PD) and schizophrenia (SCZ). Previous investigations have found a wide similarity in structural connectivity of the striatum between human and macaque, leaving the cross-species comparison of its functional organization unknown. In this study, resting-state functional connectivity (RSFC) derived striatal parcels were compared based on their homologous cortico-striatal connectivity. The goal here was to identify striatal parcels whose connectivity is human-specific compared to macaque parcels. Functional parcellation revealed that the human striatum was split into dorsal, dorsomedial, and rostral caudate and ventral, central, and caudal putamen, while the macaque striatum was divided into dorsal, and rostral caudate and rostral, and caudal putamen. Cross-species comparison indicated dissimilar cortico-striatal RSFC of the topographically similar dorsal caudate. We probed clinical relevance of the striatal clusters by examining differences in their cortico-striatal RSFC and gray matter (GM) volume between patients (with PD and SCZ) and healthy controls. We found abnormal RSFC not only between dorsal caudate, but also between rostral caudate, ventral, central and caudal putamen and widespread cortical regions for both PD and SCZ patients. Also, we observed significant structural atrophy in rostral caudate, ventral and central putamen for both PD and SCZ while atrophy in the dorsal caudate was specific to PD. Taken together, our cross-species comparative results revealed shared and human-specific RSFC of different striatal clusters reinforcing the complex organization and function of the striatum. In addition, we provided a testable hypothesis that abnormalities in a region with human-specific connectivity, i.e., dorsal caudate, might be associated with neuropsychiatric disorders.

Maternal Interleukin-6 Is Associated With Macaque Offspring Amygdala Development and Behavior

Human and animal cross-sectional studies have shown that maternal levels of the inflammatory cytokine interleukin-6 (IL-6) may compromise brain phenotypes assessed at single time points. However, how maternal IL-6 associates with the trajectory of brain development remains unclear. We investigated whether maternal IL-6 levels during pregnancy relate to offspring amygdala volume development and anxiety-like behavior in Japanese macaques. Magnetic resonance imaging (MRI) was administered to 39 Japanese macaque offspring (Female: 18), providing at least one or more time points at 4, 11, 21, and 36 months of age with a behavioral assessment at 11 months of age. Increased maternal third trimester plasma IL-6 levels were associated with offspring's smaller left amygdala volume at 4 months, but with more rapid amygdala growth from 4 to 36 months. Maternal IL-6 predicted offspring anxiety-like behavior at 11 months, which was mediated by reduced amygdala volumes in the model's intercept (i.e., 4 months). The results increase our understanding of the role of maternal inflammation in the development of neurobehavioral disorders by detailing the associations of a commonly examined inflammatory indicator, IL-6, on amygdala volume growth over time, and anxiety-like behavior.

Understanding Vulnerability and Adaptation in Early Brain Development using Network Neuroscience

Early adversity influences brain development and emerging behavioral phenotypes relevant for psychiatric disorders. Understanding the effects of adversity before and after conception on brain development has implications for contextualizing current public health crises and pervasive health inequities. The use of functional magnetic resonance imaging (fMRI) to study the brain at rest has shifted understanding of brain functioning and organization in the earliest periods of life. Here we review applications of this technique to examine effects of early life stress (ELS) on neurodevelopment in infancy, and highlight targets for future research. Building on the foundation of existing work in this area will require tackling significant challenges, including greater inclusion of often marginalized segments of society, and conducting larger, properly powered studies.

The Subcortical Atlas of the Rhesus Macaque (SARM) for neuroimaging

Digitized neuroanatomical atlases that can be overlaid onto functional data are crucial for localizing brain structures and analyzing functional networks identified by neuroimaging techniques. To aid in functional and structural data analysis, we have created a comprehensive parcellation of the rhesus macaque subcortex using a high-resolution ex vivo structural imaging scan. This anatomical scan and its parcellation were warped to the updated NIMH Macaque Template (NMT v2), an in vivo population template, where the parcellation was refined to produce the Subcortical Atlas of the Rhesus Macaque (SARM) with 210 primary regions-of-interest (ROIs). The subcortical parcellation and nomenclature reflect those of the 4^th edition of the Rhesus Monkey Brain in Stereotaxic Coordinates (Paxinos et al., in preparation), rather than proposing yet another novel atlas. The primary ROIs are organized across six spatial hierarchical scales from small, fine-grained ROIs to broader composites of multiple ROIs, making the SARM suitable for analysis at different resolutions and allowing broader labeling of functional signals when more accurate localization is not possible. As an example application of this atlas, we have included a functional localizer for the dorsal lateral geniculate (DLG) nucleus in three macaques using a visual flickering checkerboard stimulus, identifying and quantifying significant fMRI activation in this atlas region. The SARM has been made openly available to the neuroimaging community and can easily be used with common MRI data processing software, such as AFNI, where the atlas has been embedded into the software alongside cortical macaque atlases.

A comprehensive macaque fMRI pipeline and hierarchical atlas

Functional neuroimaging research in the non-human primate (NHP) has been advancing at a remarkable rate. The increase in available data establishes a need for robust analysis pipelines designed for NHP neuroimaging and accompanying template spaces to standardize the localization of neuroimaging results. Our group recently developed the NIMH Macaque Template (NMT), a high-resolution population average anatomical template and associated neuroimaging resources, providing researchers with a standard space for macaque neuroimaging . Here, we release NMT v2, which includes both symmetric and asymmetric templates in stereotaxic orientation, with improvements in spatial contrast, processing efficiency, and segmentation. We also introduce the Cortical Hierarchy Atlas of the Rhesus Macaque (CHARM), a hierarchical parcellation of the macaque cerebral cortex with varying degrees of detail. These tools have been integrated into the neuroimaging analysis software AFNI to provide a comprehensive and robust pipeline for fMRI processing, visualization and analysis of NHP data. AFNI's new @animal_warper program can be used to efficiently align anatomical scans to the NMT v2 space, and afni_proc.py integrates these results with full fMRI processing using macaque-specific parameters: from motion correction through regression modeling. Taken together, the NMT v2 and AFNI represent an all-in-one package for macaque functional neuroimaging analysis, as demonstrated with available demos for both task and resting state fMRI.

Muting, not fragmentation, of functional brain networks under general anesthesia

Changes in resting-state functional connectivity (rs-FC) under general anesthesia have been widely studied with the goal of identifying neural signatures of consciousness. This work has commonly revealed an apparent fragmentation of whole-brain network structure during unconsciousness, which has been interpreted as reflecting a break-down in connectivity and a disruption of the brain's ability to integrate information. Here we show, by studying rs-FC under varying depths of isoflurane-induced anesthesia in nonhuman primates, that this apparent fragmentation, rather than reflecting an actual change in network structure, can be simply explained as the result of a global reduction in FC. Specifically, by comparing the actual FC data to surrogate data sets that we derived to test competing hypotheses of how FC changes as a function of dose, we found that increases in whole-brain modularity and the number of network communities - considered hallmarks of fragmentation - are artifacts of constructing FC networks by thresholding based on correlation magnitude. Taken together, our findings suggest that deepening levels of unconsciousness are instead associated with the increasingly muted expression of functional networks, an observation that constrains current interpretations as to how anesthesia-induced FC changes map onto existing neurobiological theories of consciousness.

Multimodal 3D atlas of the macaque monkey motor and premotor cortex

In the present study we reevaluated the parcellation scheme of the macaque frontal agranular cortex by implementing quantitative cytoarchitectonic and multireceptor analyses, with the purpose to integrate and reconcile the discrepancies between previously published maps of this region. We applied an observer-independent and statistically testable approach to determine the position of cytoarchitectonic borders. Analysis of the regional and laminar distribution patterns of 13 different transmitter receptors confirmed the position of cytoarchitectonically identified borders. Receptor densities were extracted from each area and visualized as its "receptor fingerprint". Hierarchical and principal components analyses were conducted to detect clusters of areas according to the degree of (dis)similarity of their fingerprints. Finally, functional connectivity pattern of each identified area was analyzed with areas of prefrontal, cingulate, somatosensory and lateral parietal cortex and the results were depicted as "connectivity fingerprints" and seed-to-vertex connectivity maps. We identified 16 cyto- and receptor architectonically distinct areas, including novel subdivisions of the primary motor area 4 (i.e. 4a, 4p, 4m) and of premotor areas F4 (i.e. F4s, F4d, F4v), F5 (i.e. F5s, F5d, F5v) and F7 (i.e. F7d, F7i, F7s). Multivariate analyses of receptor fingerprints revealed three clusters, which first segregated the subdivisions of area 4 with F4d and F4s from the remaining premotor areas, then separated ventrolateral from dorsolateral and medial premotor areas. The functional connectivity analysis revealed that medial and dorsolateral premotor and motor areas show stronger functional connectivity with areas involved in visual processing, whereas 4p and ventrolateral premotor areas presented a stronger functional connectivity with areas involved in somatomotor responses. For the first time, we provide a 3D atlas integrating cyto- and multi-receptor architectonic features of the macaque motor and premotor cortex. This atlas constitutes a valuable resource for the analysis of functional experiments carried out with non-human primates, for modeling approaches with realistic synaptic dynamics, as well as to provide insights into how brain functions have developed by changes in the underlying microstructure and encoding strategies during evolution.

Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P < 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies.

Self-Injurious behavior in rhesus macaques: Issues and challenges

Some monkeys housed in research facilities develop abnormal behavior ranging from stereotypic to the more serious condition of self-injurious behavior (SIB). We initially sought to understand how and why monkeys engaged in SIB and more importantly why only a small percentage of laboratory monkeys, with seemingly similar housing and background, developed this disorder. Of particular importance was the recognition that different pathways might lead to SIB and that strong individual differences would affect the manifestation of this disorder and the response to treatment. We developed a comprehensive plan to identify effective treatment and prevention strategies. We started with characterizing the disorder in terms of prevalence and types of environments in which it was found. We then conducted observations on a cohort of SIB and control monkeys to identify conditions associated with SIB (e.g., disordered sleep) as well as clinical disease states and congenital defects that could be precipitating factors. We examined the environmental events that triggered episodes of SIB in monkeys with the disorder and evaluated three models that might explain the reinforcement contingencies associated with SIB, including tension reduction, self-stimulation, and social communication. Possible treatments for SIB such as environmental enrichment, social housing, and pharmacotherapy were tested by our group and others. To date, no single treatment has been found to abolish SIB, and each of these treatments is impacted by individual differences. To develop possible prevention strategies, we examined colony management and health records to find risk factors for SIB. These risk factors generalized to other facilities, and considerable effort was expended by all behavioral managers at these facilities to reduce early life stress exposure, to minimize the length of individual cage housing by emphasizing pair housing, and to reduce the possible stressfulness of various veterinary/medical procedures by implementing positive reinforcement training.

Individual Variability in Functional Organization of the Human and Monkey Auditory Cortex

Accumulating evidence shows that auditory cortex (AC) of humans, and other primates, is involved in more complex cognitive processes than feature segregation only, which are shaped by experience-dependent plasticity and thus likely show substantial individual variability. However, thus far, individual variability of ACs has been considered a methodological impediment rather than a phenomenon of theoretical importance. Here, we examined the variability of ACs using intrinsic functional connectivity patterns in humans and macaques. Our results demonstrate that in humans, interindividual variability is greater near the nonprimary than primary ACs, indicating that variability dramatically increases across the processing hierarchy. ACs are also more variable than comparable visual areas and show higher variability in the left than in the right hemisphere, which may be related to the left lateralization of auditory-related functions such as language. Intriguingly, remarkably similar modality differences and lateralization of variability were also observed in macaques. These connectivity-based findings are consistent with a confirmatory task-based functional magnetic resonance imaging analysis. The quantification of variability in auditory function, and the similar findings in both humans and macaques, will have strong implications for understanding the evolution of advanced auditory functions in humans.

Ultra-high field (10.5 T) resting state fMRI in the macaque

Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for contrast agents limiting translatability, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, imaging at magnetic fields above 7T has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed single-subject resting state analysis at high resolutions using a 10.5 Tesla scanner. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI 'macaque connectome' will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics.

Cross-species functional alignment reveals evolutionary hierarchy within the connectome

Evolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we develop a function-based method for cross-species alignment that enables the quantification of homologous regions between humans and rhesus macaques, even when their location is decoupled from anatomical landmarks. Critically, we find cross-species similarity in functional organization reflects a gradient of evolutionary change that decreases from unimodal systems and culminates with the most pronounced changes in posterior regions of the default mode network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default mode network, as the apex of a cognitive hierarchy, has changed in a complex manner during human evolution - even within subnetworks.

Reproducing macaque lateral grasping and oculomotor networks using resting state functional connectivity and diffusion tractography

Cortico-cortical networks involved in motor control have been well defined in the macaque using a range of invasive techniques. The advent of neuroimaging has enabled non-invasive study of these large-scale functionally specialized networks in the human brain; however, assessing its accuracy in reproducing genuine anatomy is more challenging. We set out to assess the similarities and differences between connections of macaque motor control networks defined using axonal tracing and those reproduced using structural and functional connectivity techniques. We processed a cohort of macaques scanned in vivo that were made available by the open access PRIME-DE resource, to evaluate connectivity using diffusion imaging tractography and resting state functional connectivity (rs-FC). Sectors of the lateral grasping and exploratory oculomotor networks were defined anatomically on structural images, and connections were reproduced using different structural and functional approaches (probabilistic and deterministic whole-brain and seed-based tractography; group template and native space functional connectivity analysis). The results showed that parieto-frontal connections were best reproduced using both structural and functional connectivity techniques. Tractography showed lower sensitivity but better specificity in reproducing connections identified by tracer data. Functional connectivity analysis performed in native space had higher sensitivity but lower specificity and was better at identifying connections between intrasulcal ROIs than group-level analysis. Connections of AIP were most consistently reproduced, although those connected with prefrontal sectors were not identified. We finally compared diffusion MR modelling with histology based on an injection in AIP and speculate on anatomical bases for the observed false negatives. Our results highlight the utility of precise ex vivo techniques to support the accuracy of neuroimaging in reproducing connections, which is relevant also for human studies.

Preserved extrastriate visual network in a monkey with substantial, naturally occurring damage to primary visual cortex

Lesions of primary visual cortex (V1) lead to loss of conscious visual perception with significant impact on human patients. Understanding the neural consequences of such damage may aid the development of rehabilitation methods. In this rare case of a Rhesus macaque (monkey S), likely born without V1, the animal's in-group behaviour was unremarkable, but visual task training was impaired. With multi-modal magnetic resonance imaging, visual structures outside of the lesion appeared normal. Visual stimulation under anaesthesia with checkerboards activated lateral geniculate nucleus of monkey S, while full-field moving dots activated pulvinar. Visual cortical activation was sparse but included face patches. Consistently across lesion and control monkeys, functional connectivity analysis revealed an intact network of bilateral dorsal visual areas temporally correlated with V5/MT activation, even without V1. Despite robust subcortical responses to visual stimulation, we found little evidence for strengthened subcortical input to V5/MT supporting residual visual function or blindsight-like phenomena.