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Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.

Objective: Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales. Approach: In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted. Main results: The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images. Significance: This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.

Studies of resting-state functional connectivity (rsFC) have provided rich insights into the structures and functions of the human brain. However, most rsFC studies have focused on large-scale brain connectivity. To explore rsFC at a finer scale, we used intrinsic signal optical imaging to image the ongoing activity of the anesthetized macaque visual cortex. Differential signals from functional domains were used to quantify network-specific fluctuations. In 30–60 min resting-state imaging, a series of coherent activation patterns were observed in all three visual areas we examined (V1, V2, and V4). These patterns matched the known functional maps (ocular dominance, orientation, color) obtained in visual stimulation conditions. These functional connectivity (FC) networks fluctuated independently over time and exhibited similar temporal characteristics. Coherent fluctuations, however, were observed from orientation FC networks in different areas and even across two hemispheres. Thus, FC in the macaque visual cortex was fully mapped both on a fine scale and over a long range. Hemodynamic signals can be used to explore mesoscale rsFC in a submillimeter resolution.

Non-human primate (NHP) neuroimaging can provide essential insights into the neural basis of human cognitive functions. While functional magnetic resonance imaging (fMRI) localizers can play an essential role in reaching this objective (Russ et al., 2021), they often differ substantially across species in terms of paradigms, measured signals, and data analysis, biasing the comparisons. Here we introduce a functional frequency-tagging face localizer for NHP imaging, successfully developed in humans and outperforming standard face localizers (Gao et al., 2018). FMRI recordings were performed in two awake macaques. Within a rapid 6 Hz stream of natural non-face objects images, human or monkey face stimuli were presented in bursts every 9 s. We also included control conditions with phase-scrambled versions of all images. As in humans, face-selective activity was objectively identified and quantified at the peak of the face-stimulation frequency (0.111 Hz) and its second harmonic (0.222 Hz) in the Fourier domain. Focal activations with a high signal-to-noise ratio were observed in regions previously described as face-selective, mainly in the STS (clusters PL, ML, MF; also, AL, AF), both for human and monkey faces. Robust face-selective activations were also found in the prefrontal cortex of one monkey (PVL and PO clusters). Face-selective neural activity was highly reliable and excluded all contributions from low-level visual cues contained in the amplitude spectrum of the stimuli. These observations indicate that fMRI frequency-tagging provides a highly valuable approach to objectively compare human and monkey visual recognition systems within the same framework.

Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter-scale subcortical brain structures in humans. However, the simultaneous visualization of cortical, subcortical, and white matter structure remains challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortex and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first applied QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analysis methods allowed a similar accurate delineation of subcortical structures in humans. However, the QSM contrast of white and cortical gray matter was not sufficient for appropriate segmentation. Applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of subcortical brain structures as compared to the single T1 contrast by maintaining an excellent white to cortical gray matter contrast. Furthermore, we validated our dual-contrast fusion approach in humans and similarly demonstrated improvements in automated segmentation of the cortex and subcortical structures. We believe the proposed contrast will facilitate translational studies in nonhuman primates to investigate the pathophysiology of neurodegenerative diseases that affect subcortical structures such as the basal ganglia in humans.

Event-related potentials (ERP) are among the most widely measured indices for studying human cognition. While their timing and magnitude provide valuable insights, their usefulness is limited by our understanding of their neural generators at the circuit level. Inverse source localization offers insights into such generators, but their solutions are not unique. To address this problem, scientists have assumed the source space generating such signals comprises a set of discrete equivalent current dipoles, representing the activity of small cortical regions. Based on this notion, theoretical studies have employed forward modeling of scalp potentials to understand how changes in circuit-level dynamics translate into macroscopic ERPs. However, experimental validation is lacking because it requires in vivo measurements of intracranial brain sources. Laminar local field potentials (LFP) offer a mechanism for estimating intracranial current sources. Yet, a theoretical link between LFPs and intracranial brain sources is missing. Here, we present a forward modeling approach for estimating mesoscopic intracranial brain sources from LFPs and predict their contribution to macroscopic ERPs. We evaluate the accuracy of this LFP-based representation of brain sources utilizing synthetic laminar neurophysiological measurements and then demonstrate the power of the approach in vivo to clarify the source of a representative cognitive ERP component. To that end, LFP was measured across the cortical layers of visual area V4 in macaque monkeys performing an attention demanding task. We show that area V4 generates dipoles through layer-specific transsynaptic currents that biophysically recapitulate the ERP component through the detailed forward modeling. The constraints imposed on EEG production by this method also revealed an important dissociation between computational and biophysical contributors. As such, this approach represents an important bridge between laminar microcircuitry, through the mesoscopic activity of cortical columns to the patterns of EEG we measure at the scalp.

Tool understanding and use are supported by a dedicated left-lateralized, intrinsically connected network in the human adult brain. To examine this network's phylogenetic and ontogenetic origins, we compared resting-state functional connectivity (rsFC) among regions subserving tool processing in human adults to rsFC among homologous regions in human neonates and macaque monkeys (adolescent and mature). These homologous regions formed an intrinsic network in human neonates, but not in macaques. Network topological patterns were highly similar between human adults and neonates, and significantly less so between humans and macaques. The premotor-parietal rsFC had most significant contribution to the formation of the neonatal tool network. These results suggest that an intrinsic brain network potentially supporting tool processing exists in the human brain prior to individual tool use experiences, and that the premotor-parietal functional connection in particular offers a brain basis for complex tool behaviors specific to humans.

Activity observed in biological neural networks is determined by anatomical connectivity between cortical areas. The monkey frontoparietal network facilitates cognitive functions, but the organization of its connectivity is unknown. Here, a new connectivity matrix is proposed which shows that the network utilizes a small-world architecture and the 3-node M9 motif. Its areas exhibit relatively homogeneous connectivity with no suggestion of the hubs seen in scale-free networks. Crucially, its M9 dynamical relay motif is optimally arranged for near-zero and non-zero phase synchrony to arise in support of cognition, serving as a candidate topological mechanism for previously reported findings. These results can serve as a benchmark to be used in the treatment of neurological disorders where the types of cognition the frontoparietal network supports are impaired.

While mirror neurons have been found in several monkey brain regions, their existence in the human brain is still largely inferred from indirect non-invasive measurements like functional MRI. It has been proposed that, beyond showing overlapping brain responses during action observation and execution tasks, candidate mirror neuron regions should demonstrate cross-modal action specificity, in line with a defining physiological characteristic of these neurons in the monkey brain. Although cross-modal fMRI adaptation has been put forward as a suited method to test this key feature of cross-modal action specificity in the human brain, so far, the overall usefulness of this technique to demonstrate mirror neuron activity remains unclear. To date, it has never been tested to what extent monkey brain regions known to house mirror neurons, would yield uni- and/or cross-modal fMRI adaptation effects. We therefore performed an fMRI adaptation experiment while male rhesus macaques either performed or observed two different goal-directed hand actions. Executing grasp/lift or touch/press actions in the dark, as well as observing videos of these monkey hand actions, yielded robust responses throughout the brain, including overlapping fMRI responses in parietal and premotor mirror neuron regions. Uni-modal adaptation effects were mostly restricted to the visual modality and the early visual cortices. Both frequentist and Bayesian statistical analyses however suggested no evidence for cross-modal fMRI adaptation effects in monkey parietal and premotor mirror neuron regions. Overall, these findings suggest monkey mirror neuron activity does not readily translate into cross-modal repetition suppression effects that can be detected by fMRI.

Macaques are the most common nonhuman primate (NHP) species used in neuroscience research. With the advancement of many neuroimaging techniques, new studies are beginning to apply multiple types of in vivo magnetic resonance imaging (MRI), such as structural imaging (sMRI) with T1 and T2 weighted contrasts alongside diffusion weighed (DW) imaging. In studies involving rhesus macaques, this approach can be used to better understand micro-structural changes that occur during development, in various disease states or with normative aging. However, many of the available rhesus brain atlases have been designed for only one imaging modality, making it difficult to consistently define the same brain regions across multiple imaging modalities in the same subject. To address this, we created a brain atlas from 18 adult rhesus macaques that includes co-registered templates constructed from images frequently used to characterize macroscopic brain structure (T2/SPACE and T1/MP-RAGE), and a diffusion tensor imaging (DTI) template. The DTI template was up-sampled from 1 mm isotropic resolution to resolution match to the T1 and T2-weighted images (0.5 mm isotropic), and the parameter maps were derived for FA, AD, RD and MD.The labelmap volumes delineate 57 gray matter regions of interest (ROIs; 36 cortical regions and 21 subcortical structures), as well as 74 white matter tracts. Importantly, the labelmap overlays both the structural and diffusion templates, enabling the same regions to be consistently identified across imaging modalities. A specialized condensed version of the labelmap ROIs are also included to further extend the usefulness of this tool for imaging data with lower spatial resolution, such as functional MRI (fMRI) or positron emission tomography (PET).

Magnetic resonance imaging is playing a significant role in applying the 3Rs to neuroscience studies using non-human primates. MRI scans are contributing to refinement by enhancing the selection and assignment of animals, guiding the manufacture of custom-fitted recording and head fixation devices, and assisting with the diagnosis of health issues and their treatment. MRI is also being used to better understand the impact of neuroscience procedures on the welfare of NHPs. MRI has helped to optimise NHP use and make greater scientific progress than would otherwise be made using larger numbers of animals. Whilst human fMRI studies have replaced some NHP studies, their potential to directly replace NHP electrophysiology is limited at present. Given the considerable advantages of MRI for electrophysiology experiments, including improved welfare of NHPs, consideration should be given to focusing NHP electrophysiology laboratories around MRI facilities. Greater sharing of MRI data sets, and improvements in MRI contrast and resolution, are expected to further advance the 3Rs in the future.

Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain.

Non-human primate functional MRI (fMRI) is a growing field in neuroscience. However, there is no standardized method for monkey fMRI data analysis, specifically for data preprocessing. The preprocessing of monkey fMRI data is challenged by several technical and experimental specificities of the monkey research such as artifacts related to body movements or to intracranial leads. Here we propose to address these challenges by developing a new versatile pipeline for macaque fMRI preprocessing. We developed a Python module, Pypreclin, to process raw images using state of the art algorithms embedded in a fully automatic pipeline. To evaluate its robustness, we applied Pypreclin to fMRI data acquired at 3T in both awake and anesthetized macaques, with or without iron oxide contrast agent, using single loop or multichannel phased-array coils, combined or not with intracranial implanted electrodes. We performed both resting-state and auditory evoked fMRI and compared the results of Pypreclin to a previously employed preprocessing pipeline. Pypreclin successfully achieved the registration of the fMRI data to the macaque brain template in all the experimental conditions. Moreover, Pypreclin enables more accurate locations of auditory evoked activations in relation to the gray matter at corrected level in the awake fMRI condition. Finally, using the Primate neuroimaging Data-Exchange open access platform, we could further validate Pypreclin for monkey fMRI images that were acquired at ultra-high fields, from other institutions and using different protocols. Pypreclin is a validated preprocessing tool that adapts to diverse experimental and technical situations of monkey fMRI. Pypreclin code is available on open source data sharing platform.

The precuneus (PCun) is one of the most expanded areas of the association cortex and plays an important role in integrating information from different modalities. However, whether the functional architecture of PCun is shared by humans and macaques is an open question. We used both anatomical connectivity and task-dependent coactivation patterns to parcellate the human PCun and consistently identified three subregions in the human PCun using two independent datasets. Two subregions were located in the dorsal PCun and one subregion was located in the ventral PCun. This parcellation scheme for the PCun was supported by identifying the subregion-specific networks and by functional characterization. Then, the absolute and relative gray matter volume of precuneus in human and macaque was calculated and significantly smaller absolute and relative gray matter volume in macaque was identified. Next, three macaque PCun subregions were defined based on our tractographic atlas. Finally, the whole brain anatomical connectivity patterns and connectivity fingerprints with 17 predefined homologous target brain areas were mapped for each PCun subregion and revealed that the PCun shares similar anatomical connectivity patterns in humans and macaques. The similar anatomical connectivity patterns of PCun were validated by an independent in-house dataset. Our findings demonstrated that anatomical connectivity patterns can reflect the functional architecture of the PCun in humans and that the functional architecture of the PCun is similar in humans and macaques. • Corresponding anatomical and coactivation atlas of precuneus was mapped. • Anatomical, resting, and coactivation patters for precuneus were calculated. • Absolute and relative gray matter volume of precuneus between human and macaque was compared. • Similar anatomical connectivity pattern of precuneus subregions in human and macaque was identified. [ABSTRACT FROM AUTHOR]

Abstract Based on architectonic, tract-tracing or functional criteria, the rostral portion of ventral premotor cortex in the macaque monkey, also termed area F5, has been divided into several subfields. Cytoarchitectonical investigations suggest the existence of three subfields, F5c (convexity), F5p (posterior) and F5a (anterior). Electrophysiological investigations have suggested a gradual dorso-ventral transition from hand- to mouth-dominated motor fields, with F5p and ventral F5c strictly related to hand movements and mouth movements, respectively. The involvement of F5a in this respect, however, has received much less attention. Recently, data-driven resting-state fMRI approaches have also been used to examine the presence of distinct functional fields in macaque ventral premotor cortex. Although these studies have suggested several functional clusters in/near macaque F5, so far the parcellation schemes derived from these clustering methods do not completely retrieve the same level of F5 specialization as suggested by aforementioned invasive techniques. Here, using seed-based resting-state fMRI analyses, we examined the functional connectivity of different F5 seeds with key regions of the hand and face/mouth parieto-frontal-insular motor networks. In addition, we trained monkeys to perform either hand grasping or ingestive mouth movements in the scanner in order to compare resting-state with task-derived functional hand and mouth motor networks. In line with previous single-cell investigations, task-fMRI suggests involvement of F5p, dorsal F5c and F5a in the execution of hand grasping movements, while non-communicative mouth movements yielded particularly pronounced responses in ventral F5c. Corroborating with anatomical tracing data of macaque F5 subfields, seed-based resting-state fMRI suggests a transition from predominant functional correlations with the hand-motor network in F5p to mostly mouth-motor network functional correlations in ventral F5c. Dorsal F5c yielded robust functional correlations with both hand- and mouth-motor networks. In addition, the deepest part of the fundus of the inferior arcuate, corresponding to area 44, displayed a strikingly different functional connectivity profile compared to neighboring F5a, suggesting a different functional specialization for these two neighboring regions. Highlights • Functional specialization of macaque F5 was studied using resting-state and task fMRI. • Task fMRI suggests involvement of F5p, dorsal F5c and F5a in hand grasping execution. • Ventral F5c yielded particularly pronounced functional responses to mouth movements. • Resting-state fMRI showed similar functional specialization for different F5 sectors. • Premotor F5a and neighboring area 44 showed distinct functional connectivity. [ABSTRACT FROM AUTHOR]

Abstract Our ability to act flexibly, according to goals and context, is known as cognitive control. Hierarchical levels of control, reflecting different levels of abstraction, are represented across prefrontal cortex (PFC). Although the mediodorsal thalamic nucleus (MD) is extensively interconnected with PFC, the role of MD in cognitive control is unclear. Tract tracer studies in macaques, involving subsets of PFC areas, have converged on coarse MD-PFC connectivity principles; but proposed finer-grained topographic schemes, which constrain interactions between MD and PFC, disagree in many respects. To investigate a unifying topographic scheme, we performed probabilistic tractography on diffusion MRI data from eight macaque monkeys, and estimated the probable paths connecting MD with each of all 19 architectonic areas of PFC. We found a connectional topography where the orderly progression from ventromedial to anterior to posterolateral PFC was represented from anteromedial to posterolateral MD. The projection zones of posterolateral PFC areas in MD showed substantial overlap, and those of ventral and anteromedial PFC areas in MD overlapped. The exception was cingulate area 24: its projection zone overlapped with projections zones of all other PFC areas. Overall, our data suggest that nearby, functionally related, directly connected PFC areas have partially overlapping projection zones in MD, consistent with a role for MD in coordinating communication across PFC. Indeed, the organizing principle for PFC projection zones in MD appears to reflect the flow of information across the hierarchical, multi-level PFC architecture. In addition, cingulate area 24 may have privileged access to influence thalamocortical interactions involving all other PFC areas. Highlights • PFC connections topographically organized along anteromedial-posterolateral MD axis. • Ventromedial to posterolateral PFC mapped across this axis in MD. • Nearby, functionally-related PFC areas have overlapping projection zones in MD. • Projection zone overlap allows MD to integrate information from multiple PFC areas. • MD can contribute to cognitive control by influencing cortico-cortical communication. [ABSTRACT FROM AUTHOR]

• We model selective visual attention in macaques using Dynamic Causal Modeling. • Intrinsic V1 modulation can explain attention effects in V1-V4 communication. • Modulation of superficial and granular inhibition is key to induce the effects. • Those modulations increase V1-V4 communication in a feedforward manner. Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing. [Display omitted] [ABSTRACT FROM AUTHOR]

Mirror neurons are generally described as a neural substrate hosting shared representations of actions, by simulating or ‘mirroring’ the actions of others onto the observer's own motor system. Since single neuron recordings are rarely feasible in humans, it has been argued that cross-modal multi-variate pattern analysis (MVPA) of non-invasive fMRI data is a suitable technique to investigate common coding of observed and executed actions, allowing researchers to infer the presence of mirror neurons in the human brain. In an effort to close the gap between monkey electrophysiology and human fMRI data with respect to the mirror neuron system, here we tested this proposal for the first time in the monkey. Rhesus monkeys either performed reach-and-grasp or reach-and-touch motor acts with their right hand in the dark or observed videos of human actors performing similar motor acts. Unimodal decoding showed that both executed or observed motor acts could be decoded from numerous brain regions. Specific portions of rostral parietal, premotor and motor cortices, previously shown to house mirror neurons, in addition to somatosensory regions, yielded significant asymmetric action-specific cross-modal decoding. These results validate the use of cross-modal multi-variate fMRI analyses to probe the representations of own and others' actions in the primate brain and support the proposed mapping of others' actions onto the observer's own motor cortices. [ABSTRACT FROM AUTHOR]

The use of standard anatomical templates is common in human neuroimaging, as it facilitates data analysis and comparison across subjects and studies. For non-human primates, previous in vivo templates have lacked sufficient contrast to reliably validate known anatomical brain regions and have not provided tools for automated single-subject processing. Here we present the “ National Institute of Mental Health Macaque Template” , or NMT for short. The NMT is a high-resolution in vivo MRI template of the average macaque brain generated from 31 subjects, as well as a neuroimaging tool for improved data analysis and visualization. From the NMT volume, we generated maps of tissue segmentation and cortical thickness. Surface reconstructions and transformations to previously published digital brain atlases are also provided. We further provide an analysis pipeline using the NMT that automates and standardizes the time-consuming processes of brain extraction, tissue segmentation, and morphometric feature estimation for anatomical scans of individual subjects. The NMT and associated tools thus provide a common platform for precise single-subject data analysis and for characterizations of neuroimaging results across subjects and studies. [ABSTRACT FROM AUTHOR]

The cortical network processing three-dimensional (3D) object structure defined by binocular disparity spans both the ventral and dorsal visual streams. However, very little is known about the neural representation of 3D structure at intermediate levels of the visual hierarchy. Here, we investigated the neural selectivity for 3D surfaces in the macaque Posterior Intraparietal area (PIP) in the medial bank of the caudal intraparietal sulcus (IPS). We first identified a region sensitive to depth-structure information in the medial bank of the caudal IPS using functional Magnetic Resonance Imaging (fMRI), and then recorded single-cell activity within this fMRI activation in the same animals. Most PIP neurons were selective for the 3D orientation of planar surfaces (first-order disparity) at very short latencies, whereas a very small fraction of PIP neurons were selective for curved surfaces (second-order disparity). A linear support vector machine classifier could reliably identify the direction of the disparity gradient in planar and curved surfaces based on the responses of a population of disparity-selective PIP neurons. These results provide the first detailed account of the neuronal properties in area PIP, which occupies an intermediate position in the hierarchy of visual areas involved in processing depth structure from disparity. [ABSTRACT FROM AUTHOR]

• A tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed to accommodate multimodal neuroimaging and neurostimulation devices. • The coil provides satisfactory transmit efficiency / homogeneity, signal coverage and SNR over the macaque brain. • Promising results obtained by combining fMRI with infrared neural stimulation, focused ultrasound stimulation, or transcranial direct current stimulation. • This pilot study reveals the opportunity for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks. Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales. In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted. The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images. This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks. [ABSTRACT FROM AUTHOR]

Because they bridge the genetic gap between rodents and humans, non-human primates (NHPs) play a major role in therapy development and evaluation for neurological disorders. However, translational research success from NHPs to patients requires an accurate phenotyping of the models. In patients, magnetic resonance imaging (MRI) combined with automated segmentation methods has offered the unique opportunity to assess in vivo brain morphological changes. Meanwhile, specific challenges caused by brain size and high field contrasts make existing algorithms hard to use routinely in NHPs. To tackle this issue, we propose a complete pipeline, Primatologist, for multi-region segmentation. Tissue segmentation is based on a modular statistical model that includes random field regularization, bias correction and denoising and is optimized by expectation-maximization. To deal with the broad variety of structures with different relaxing times at 7 T, images are segmented into 17 anatomical classes, including subcortical regions. Pre-processing steps insure a good initialization of the parameters and thus the robustness of the pipeline. It is validated on 10 T2-weighted MRIs of healthy macaque brains. Classification scores are compared with those of a non-linear atlas registration, and the impact of each module on classification scores is thoroughly evaluated. [ABSTRACT FROM AUTHOR]

• ISOI was employed to study mesoscale rsFC in the macaque visual cortex. • Multiplexed FC maps resembling functional maps coexist in spontaneous fluctuations. • Coherent network activity was observed across visual areas and hemispheres. • Hemodynamic rsFC has high spatial resolution over long distances. Studies of resting-state functional connectivity (rsFC) have provided rich insights into the structures and functions of the human brain. However, most rsFC studies have focused on large-scale brain connectivity. To explore rsFC at a finer scale, we used intrinsic signal optical imaging to image the ongoing activity of the anesthetized macaque visual cortex. Differential signals from functional domains were used to quantify network-specific fluctuations. In 30–60 min resting-state imaging, a series of coherent activation patterns were observed in all three visual areas we examined (V1, V2, and V4). These patterns matched the known functional maps (ocular dominance, orientation, color) obtained in visual stimulation conditions. These functional connectivity (FC) networks fluctuated independently over time and exhibited similar temporal characteristics. Coherent fluctuations, however, were observed from orientation FC networks in different areas and even across two hemispheres. Thus, FC in the macaque visual cortex was fully mapped both on a fine scale and over a long range. Hemodynamic signals can be used to explore mesoscale rsFC in a submillimeter resolution. [ABSTRACT FROM AUTHOR]

• Validation of a new face localizer for non-human primate (NHP) imaging. • Typical face-selective clusters in monkey STS with frequency-tagging. • Highest sensitivity and test-retest reliability of face-selective activations. • No face-selective activation in ventral occipito-temporal regions. • Face-selective activation significantly larger to monkey faces in middle STS. Non-human primate (NHP) neuroimaging can provide essential insights into the neural basis of human cognitive functions. While functional magnetic resonance imaging (fMRI) localizers can play an essential role in reaching this objective (Russ et al., 2021), they often differ substantially across species in terms of paradigms, measured signals, and data analysis, biasing the comparisons. Here we introduce a functional frequency-tagging face localizer for NHP imaging, successfully developed in humans and outperforming standard face localizers (Gao et al., 2018). FMRI recordings were performed in two awake macaques. Within a rapid 6 Hz stream of natural non-face objects images, human or monkey face stimuli were presented in bursts every 9 s. We also included control conditions with phase-scrambled versions of all images. As in humans, face-selective activity was objectively identified and quantified at the peak of the face-stimulation frequency (0.111 Hz) and its second harmonic (0.222 Hz) in the Fourier domain. Focal activations with a high signal-to-noise ratio were observed in regions previously described as face-selective, mainly in the STS (clusters PL, ML, MF; also, AL, AF), both for human and monkey faces. Robust face-selective activations were also found in the prefrontal cortex of one monkey (PVL and PO clusters). Face-selective neural activity was highly reliable and excluded all contributions from low-level visual cues contained in the amplitude spectrum of the stimuli. These observations indicate that fMRI frequency-tagging provides a highly valuable approach to objectively compare human and monkey visual recognition systems within the same framework. [ABSTRACT FROM AUTHOR]

• The subcortical gray matter areas of macaque monkeys are reliably mapped by QSM, much as they are in humans. • Combining T1w and QSM images improves the visualization and segmentation of white matter, cortex, and subcortical structures in the macaque monkey. • The proposed dual contrast TQ-SILiCON provides a similar image quality also in humans. • TQ-SILiCON facilitates comparative and translational neuroscience studies investigating subcortical structures. Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter-scale subcortical brain structures in humans. However, the simultaneous visualization of cortical, subcortical, and white matter structure remains challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortex and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first applied QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analysis methods allowed a similar accurate delineation of subcortical structures in humans. However, the QSM contrast of white and cortical gray matter was not sufficient for appropriate segmentation. Applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of subcortical brain structures as compared to the single T1 contrast by maintaining an excellent white to cortical gray matter contrast. Furthermore, we validated our dual-contrast fusion approach in humans and similarly demonstrated improvements in automated segmentation of the cortex and subcortical structures. We believe the proposed contrast will facilitate translational studies in nonhuman primates to investigate the pathophysiology of neurodegenerative diseases that affect subcortical structures such as the basal ganglia in humans. [Display omitted] [ABSTRACT FROM AUTHOR]

• Cognitive EEG production was accurately modeled from empirically measured cortical activity in macaques. • V4 laminar activity can generate a well-known attention-related EEG signal. • Models demonstrate the importance of biophysical geometry in cognitive EEG production. • Biophysical and computational contributions are dissociable. Event-related potentials (ERP) are among the most widely measured indices for studying human cognition. While their timing and magnitude provide valuable insights, their usefulness is limited by our understanding of their neural generators at the circuit level. Inverse source localization offers insights into such generators, but their solutions are not unique. To address this problem, scientists have assumed the source space generating such signals comprises a set of discrete equivalent current dipoles, representing the activity of small cortical regions. Based on this notion, theoretical studies have employed forward modeling of scalp potentials to understand how changes in circuit-level dynamics translate into macroscopic ERPs. However, experimental validation is lacking because it requires in vivo measurements of intracranial brain sources. Laminar local field potentials (LFP) offer a mechanism for estimating intracranial current sources. Yet, a theoretical link between LFPs and intracranial brain sources is missing. Here, we present a forward modeling approach for estimating mesoscopic intracranial brain sources from LFPs and predict their contribution to macroscopic ERPs. We evaluate the accuracy of this LFP-based representation of brain sources utilizing synthetic laminar neurophysiological measurements and then demonstrate the power of the approach in vivo to clarify the source of a representative cognitive ERP component. To that end, LFP was measured across the cortical layers of visual area V4 in macaque monkeys performing an attention demanding task. We show that area V4 generates dipoles through layer-specific transsynaptic currents that biophysically recapitulate the ERP component through the detailed forward modeling. The constraints imposed on EEG production by this method also revealed an important dissociation between computational and biophysical contributors. As such, this approach represents an important bridge between laminar microcircuitry, through the mesoscopic activity of cortical columns to the patterns of EEG we measure at the scalp. [ABSTRACT FROM AUTHOR]

• The phylogenetic and ontogenetic origins of the tool network were examined. • The intrinsic tool processing network is present in human neonates and not macaques. • The premotor-parietal path contributes significantly to the neonatal tool network. • The premotor-parietal path is a candidate substrate for causal understanding. Tool understanding and use are supported by a dedicated left-lateralized, intrinsically connected network in the human adult brain. To examine this network's phylogenetic and ontogenetic origins, we compared resting-state functional connectivity (rsFC) among regions subserving tool processing in human adults to rsFC among homologous regions in human neonates and macaque monkeys (adolescent and mature). These homologous regions formed an intrinsic network in human neonates, but not in macaques. Network topological patterns were highly similar between human adults and neonates, and significantly less so between humans and macaques. The premotor-parietal rsFC had most significant contribution to the formation of the neonatal tool network. These results suggest that an intrinsic brain network potentially supporting tool processing exists in the human brain prior to individual tool use experiences, and that the premotor-parietal functional connection in particular offers a brain basis for complex tool behaviors specific to humans. [ABSTRACT FROM AUTHOR]

The proposal that sensory processing is achieved in segregated anatomical pathways has been profoundly revisited following the description of cross-modal anatomical connections both at higher and at lower processing levels. However, an understanding of the cortical extent of these long range cross-modal functional influences has been missing. Here, we use functional magnetic resonance imaging (fMRI) to map, in the non-human primate brain, the cortical regions which are activated by both visual and tactile stimulations. We describe an unprecedented pattern of functional visuo-tactile convergence, encompassing both low-level visual and somatosensory areas and multiple higher-order associative areas. We also show that the profile of this convergence depends on the physical properties of the mapping stimuli, indicating that visuo-tactile convergence is most probably even more prevailing than what we actually describe. Overall, these observations substantiate the view that the brain is massively multisensory. [ABSTRACT FROM AUTHOR]

Based on its diverse and wide-spread patterns of connectivity, primate posteromedial cortex (PMC) is well positioned to support roles in several aspects of sensory-, cognitive- and motor-related processing. Previous work in both humans and non-human primates (NHPs) using resting-state functional MRI (rs-fMRI) suggests that a subregion of PMC, the medial parieto-occipital cortex (mPOC), by virtue of its intrinsic functional connectivity (FC) with visual cortex, may only play a role in higher-order visual processing. Recent neuroanatomical tracer studies in NHPs, however, demonstrate that mPOC also has prominent cortico-cortical connections with several frontoparietal structures involved in movement planning and control, a finding consistent with increasing observations of reach- and grasp-related activity in the mPOC of both NHPs and humans. To reconcile these observations, here we used rs-fMRI data collected from both awake humans and anesthetized macaque monkeys to more closely examine and compare parcellations of mPOC across species and explore the FC patterns associated with these subdivisions. Seed-based and voxel-wise hierarchical cluster analyses revealed four broad spatially separated functional boundaries that correspond with graded differences in whole-brain FC patterns in each species. The patterns of FC observed are consistent with mPOC forming a critical hub of networks involved in action planning and control, spatial navigation, and working memory. In addition, our comparison between species indicates that while there are several similarities, there may be some species-specific differences in functional neural organization. These findings and the associated theoretical implications are discussed. [ABSTRACT FROM AUTHOR]

Reach and grasp kinematics are known to be encoded in the spiking activity of neuronal ensembles and in local field potentials (LFPs) recorded from primate motor cortex during movement planning and execution. However, little is known, especially in LFPs, about the encoding of kinetic parameters, such as forces exerted on the object during the same actions. We implanted two monkeys with microelectrode arrays in the motor cortical areas MI and PMd to investigate encoding of grasp-related parameters in motor cortical LFPs during planning and execution of reach-and-grasp movements. We identified three components of the LFP that modulated during grasps corresponding to low (0.3–7 Hz), intermediate (~ 10–~ 40 Hz) and high (~ 80–250 Hz) frequency bands. We show that all three components can be used to classify not only grip types but also object loads during planning and execution of a grasping movement. In addition, we demonstrate that all three components recorded during planning or execution can be used to continuously decode finger pressure forces and hand position related to the grasping movement. Low and high frequency components provide similar classification and decoding accuracies, which were substantially higher than those obtained from the intermediate frequency component. Our results demonstrate that intended reach and grasp kinetic parameters are encoded in multiple LFP bands during both movement planning and execution. These findings also suggest that the LFP is a reliable signal for the control of parameters related to object load and applied pressure forces in brain–machine interfaces. [ABSTRACT FROM AUTHOR]

Spontaneous brain activity is ubiquitous across brain structures and states. Determining the role of these metabolically costly intrinsic events may be critical for understanding the brain's fundamental physiological principles that govern cognition and behavior. To date, most investigations of large-scale fluctuations and their coupling have been conducted using electro- or magneto-encephalography, modalities that are limited in their ability to spatially resolve the origin of the signals. Invasive, electrophysiological local field potential (LFP) recordings are limited in their spatial range and studies combining the approach with functional imaging have been primarily relegated to sensory/motor areas with little basis in which to extrapolate findings to evolutionarily newer prefrontal cortical regions. Here, we acquired spontaneous fMRI data in two anesthetized macaque monkeys ( Macaca fascicularis ) at 7 T together with simultaneous recordings of intracortical LFPs recorded bilaterally from the prefrontal cortex (area 9/46d). High (beta–low gamma) and low (delta–theta) band-limited power (BLP) ranges of the LFP frequencies were anticorrelated in the absence of any explicit stimuli. Beyond the high LFP–BLP signal being correlated with BOLD activity at the recording site, the high and low LFP–BLP envelopes were shown to be significantly correlated with spontaneous BOLD activity recorded from positively and negatively connected prefrontal network regions, respectively. The results suggest that complementary changes in low and high frequency bands may be an intrinsic property of LFPs, that local prefrontal cortical activity is related to spontaneous BOLD fluctuations, and further, that LFP–BLPs may be correlated at a network level. [ABSTRACT FROM AUTHOR]

The ventral visual pathway of the primate brain is specialized to respond to stimuli in certain categories, such as the well-studied face selective patches in the macaque inferotemporal cortex. To what extent does response selectivity determined using brief presentations of isolated stimuli predict activity during the free viewing of a natural, dynamic scene, where features are superimposed in space and time? To approach this question, we obtained fMRI activity from the brains of three macaques viewing extended video clips containing a range of social and nonsocial content and compared the fMRI time courses to a family of feature models derived from the movie content. Starting with more than two dozen feature models extracted from each movie, we created functional maps based on features whose time courses were nearly orthogonal, focusing primarily on faces, motion content, and contrast level. Activity mapping using the face feature model readily yielded functional regions closely resembling face patches obtained using a block design in the same animals. Overall, the motion feature model dominated responses in nearly all visually driven areas, including the face patches as well as ventral visual areas V4, TEO, and TE. Control experiments presenting dynamic movies, whose content was free of animals, demonstrated that biological movement critically contributed to the predominance of motion in fMRI responses. These results highlight the value of natural viewing paradigms for studying the brain's functional organization and also underscore the paramount contribution of magnocellular input to the ventral visual pathway during natural vision. [ABSTRACT FROM AUTHOR]

Abstract: Based upon cytoarchitectonic properties, the primate prefrontal cortex has been partitioned into different subregions that show unique structural connectivity patterns, with ongoing efforts to provide more fine-grained divisions. While meaningful divisions may be found within the sub-millimeter range, the subdivisions exist within an overall hierarchical architecture and at higher levels likely share similar activity patterns and functionality. Here, we used resting-state fMRI in lightly anesthetized macaque monkeys to measure the intrinsic functional connectivity of the prefrontal cortex. At a gross anatomical level, the data driven approach revealed five broad clusters that showed distinct brain-wide functional connectivity. Although each cluster encompasses several cytoarchitectonic subregions, the clusters overlap with the intrinsic structural connectivity of the prefrontal cortex and each cluster may subserve common functions. [Copyright &y& Elsevier]