Combining brain perturbation and neuroimaging in non-human primates

Multimodal Correspondence between Optogenetic fMRI, Electrophysiology, and Anatomical Maps of the Secondary Somatosensory Cortex in Nonhuman Primates

Optogenetic neuromodulation combined with functional MRI (opto-fMRI) enables noninvasive monitoring of brain-wide activity and probes causal connections. In this study, we focused on the secondary somatosensory (S2) cortex, a hub for integrating tactile and nociceptive information. By selectively stimulating excitatory neurons in the S2 cortex of monkeys using optogenetics, we observed widespread opto-fMRI activity in regions beyond the somatosensory system, as well as a strong spatial correspondence between opto-fMRI activity map and anatomical connections of the S2 cortex. Locally, optogenetically evoked fMRI BOLD signals from putative excitatory neurons exhibited standard hemodynamic response function. At low laser power, graded opto-fMRI signal changes are closely correlated with increases in local field potential (LFP) signals, but not with spiking activity. This indicates that LFP changes in excitatory neurons more accurately reflect the opto-fMRI signals than spikes. In summary, our optogenetic fMRI and anatomical findings provide causal functional and anatomical evidence supporting the role of the S2 cortex as a critical hub connecting sensory regions to higher-order cortical and subcortical regions involved in cognition and emotion. The electrophysiological basis of the opto-fMRI signals uncovered in this study offers novel insights into interpreting opto-fMRI results. Nonhuman primates are an invaluable intermediate model for translating optogenetic preclinical findings to humans.

Whole-brain effective connectivity of the sensorimotor system using 7 T fMRI with electrical microstimulation in non-human primates

The sensorimotor system is a crucial interface between the brain and the environment, and it is endowed with multiple computational mechanisms that enable efficient behaviors. For example, predictive processing via an efference copy of a motor command has been proposed as one of the key computations used to compensate for the sensory consequence of movement. However, the neural pathways underlying this process remain unclear, particularly regarding whether the M1-to-S1 pathway plays a dominant role in predictive processing and how its influence compares to that of other pathways. In this study, we present a causally inferable input-output map of the sensorimotor effective connectivity that we made by combining ultrahigh-field functional MRI, electrical microstimulation of the S1/M1 cortex, and dynamic causal modeling for the whole sensorimotor network in anesthetized primates. We investigated how motor signals from M1 are transmitted to S1 at the circuit level, either via direct cortico-cortical projections or indirectly via subcortical structures such as the thalamus. Across different stimulation conditions, we observed a robust asymmetric connectivity from M1 to S1 that was also the most prominent output from M1. In the thalamus, we identified distinct activations: M1 stimulation showed connections to the anterior part of ventral thalamic nuclei, whereas S1 was linked to the more posterior regions of the ventral thalamic nuclei. These findings suggest that the cortico-cortical projection from M1 to S1, rather than the cortico-thalamic loop, plays a dominant role in transmitting movement-related information. Together, our detailed dissection of the sensorimotor circuitry underscores the importance of M1-to-S1 connectivity in sensorimotor coordination.

Neuromodulation with Ultrasound: Hypotheses on the Directionality of Effects and Community Resource

Low-intensity Transcranial Ultrasound Stimulation is a promising non-invasive technique for brain stimulation and focal neuromodulation. Research with humans and animal models has raised the possibility that TUS can be biased towards enhancing or suppressing neural function. Here, we first collate a set of hypotheses on the directionality of TUS effects and conduct an initial meta-analysis on the available healthy human participant TUS studies reporting stimulation parameters and outcomes (n = 47 studies, 52 experiments). In these initial exploratory analyses, we find that parameters such as the intensity and continuity of stimulation (duty cycle) with univariate tests show only statistical trends towards likely enhancement or suppressed of function with TUS. Multivariate machine learning analyses are currently limited by the small sample size. Given that human TUS sample sizes will continue to increase, predictability on the directionality of TUS effects could improve if this database can continue to grow as TUS studies more systematically explore the TUS stimulation parameter space and report outcomes. Therefore, we establish an inTUS database and resource for the systematic reporting of TUS parameters and outcomes to assist in greater precision in TUS use for brain stimulation and neuromodulation. The paper concludes with a selective review of human clinical TUS studies illustrating how hypotheses on the directionality of TUS effects could be developed for empirical testing in the intended clinical application, not limited to the examples provided.

Comparison of derivative-based and correlation-based methods to estimate effective connectivity in neural networks

Inferring and understanding the underlying connectivity structure of a system solely from the observed activity of its constituent components is a challenge in many areas of science. In neuroscience, techniques for estimating connectivity are paramount when attempting to understand the network structure of neural systems from their recorded activity patterns. To date, no universally accepted method exists for the inference of effective connectivity, which describes how the activity of a neural node mechanistically affects the activity of other nodes. Here, focussing on purely excitatory networks of small to intermediate size and continuous node dynamics, we provide a systematic comparison of different approaches for estimating effective connectivity. Starting with the Hopf neuron model in conjunction with known ground truth structural connectivity, we reconstruct the system's connectivity matrix using a variety of algorithms. We show that, in sparse non-linear networks with delays, combining a lagged-cross-correlation (LCC) approach with a recently published derivative-based covariance analysis method provides the most reliable estimation of the known ground truth connectivity matrix. We outline how the parameters of the Hopf model, including those controlling the bifurcation, noise, and delay distribution, affect this result. We also show that in linear networks, LCC has comparable performance to a method based on transfer entropy, at a drastically lower computational cost. We highlight that LCC works best for small sparse networks, and show how performance decreases in larger and less sparse networks. Applying the method to linear dynamics without time delays, we find that it does not outperform derivative-based methods. We comment on this finding in light of recent theoretical results for such systems. Employing the Hopf model, we then use the estimated structural connectivity matrix as the basis for a forward simulation of the system dynamics, in order to recreate the observed node activity patterns. We show that, under certain conditions, the best method, LCC, results in higher trace-to-trace correlations than derivative-based methods for sparse noise-driven systems. Finally, we apply the LCC method to empirical biological data. Choosing a suitable threshold for binarization, we reconstruct the structural connectivity of a subset of the nervous system of the nematode C. elegans. We show that the computationally simple LCC method performs better than another recently published, computationally more expensive reservoir computing-based method. We apply different methods to this dataset and find that they all lead to similar performances. Our results show that a comparatively simple method can be used to reliably estimate directed effective connectivity in sparse neural systems in the presence of spatio-temporal delays and noise. We provide concrete suggestions for the estimation of effective connectivity in a scenario common in biological research, where only neuronal activity of a small set of neurons, but not connectivity or single-neuron and synapse dynamics, are known.

Selective activation of mesoscale functional circuits via multichannel infrared stimulation of cortical columns in ultra-high-field 7T MRI

To restore vision in the blind, advances in visual cortical prosthetics (VCPs) have offered high-channel-count electrical interfaces. Here, we design a 100-fiber optical bundle interface apposed to known feature-specific (color, shape, motion, and depth) functional columns that populate the visual cortex in humans, primates, and cats. Based on a non-viral optical stimulation method (INS, infrared neural stimulation; 1,875 nm), it can deliver dynamic patterns of stimulation, is non-penetrating and non-damaging to tissue, and is movable and removable. In addition, its magnetic resonance (MR) compatibility (INS-fMRI) permits systematic mapping of brain-wide circuits. In the MRI, we illustrate (1) the single-point activation of functionally specific networks, (2) shifting cortical networks activated via shifting points of stimulation, and (3) "moving dot" stimulation-evoked activation of higher-order motion-selective areas. We suggest that, by mimicking patterns of columnar activation normally activated by visual stimuli, a columnar VCP opens doors for the planned activation of feature-specific circuits and their associated visual percepts.

Depth-electrode stimulation and concurrent functional MRI in humans: Factors influencing heating with body coil transmission

Electrical-stimulation fMRI (es-fMRI) combines direct stimulation of the brain via implanted electrodes with simultaneous rapid functional magnetic resonance imaging of the evoked response. Widely used to map effective functional connectivity in animal studies, its application to the human brain has been limited due to safety concerns. In particular, the method requires reliable prediction and minimization of local tissue heating close to the electrodes, which will vary with imaging parameters and hardware configurations. Electrode leads for such experiments typically remain connected to stimulators outside the magnet room and cannot therefore be treated as electrically short at the radio frequencies employed for 1.5 T and 3 T fMRI. The potential for significant absorption and scattering of radiofrequency energy from excitation pulses during imaging is therefore a major concern. We report a series of temperature measurements conducted in human brain phantoms at two independent imaging centers to characterize factors effecting RF heating of electrically long leads with body coil transmission at 3 Tesla for temporal RMS RF transmit fields ( [Formula: see text] ) up to 3.5 µT including multiband echo planar imaging and 3D T2w turbo spin echo imaging. Under all conditions tested, with one exception, the temperature rise measured immediately adjacent to electrode contacts in a head-torso phantom with body coil RF transmission was less than 0.75 °C. We provide detailed quantification across a range of configurations and conclude with specific recommendations for cable routing that will help ensure the safety of es-fMRI in humans and provide essential data to institutional review boards.

Role of the Medial Posterior Parietal Cortex in Orchestrating Attention and Reaching

The interplay between attention, alertness, and motor planning is crucial for our manual interactions. To investigate the neural bases of this interaction and challenge the views that attention cannot be disentangled from motor planning, we instructed human volunteers of both sexes to plan and execute reaching movements while attending to the target, while attending elsewhere, or without constraining attention. We recorded reaction times to reach initiation and pupil diameter and interfered with the functions of the medial posterior parietal cortex (mPPC) with online repetitive transcranial magnetic stimulation to test the causal role of this cortical region in the interplay between spatial attention and reaching. We found that mPPC plays a key role in the spatial association of reach planning and covert attention. Moreover, we have found that alertness, measured by pupil size, is a good predictor of the promptness of reach initiation only if we plan a reach to attended targets, and mPPC is causally involved in this coupling. Different from previous understanding, we suggest that mPPC is neither involved in reach planning per se, nor in sustained covert attention in the absence of a reach plan, but it is specifically involved in attention functional to reaching.

Brain-computer interfaces inspired spiking neural network model for depression stage identification

BACKGROUND

Depression is a global mental disorder, and traditional diagnostic methods mainly rely on scales and subjective evaluations by doctors, which cannot effectively identify symptoms and even carry the risk of misdiagnosis. Brain-Computer Interfaces inspired deep learning-assisted diagnosis based on physiological signals holds promise for improving traditional methods lacking physiological basis and leads next generation neuro-technologies. However, traditional deep learning methods rely on immense computational power and mostly involve end-to-end network learning. These learning methods also lack physiological interpretability, limiting their clinical application in assisted diagnosis.

METHODOLOGY

A brain-like learning model for diagnosing depression using electroencephalogram (EEG) is proposed. The study collects EEG data using 128-channel electrodes, producing a 128×128 brain adjacency matrix. Given the assumption of undirected connectivity, the upper half of the 128×128 matrix is chosen in order to minimise the input parameter size, producing 8,128-dimensional data. After eliminating 28 components derived from irrelevant or reference electrodes, a 90×90 matrix is produced, which can be used as an input for a single-channel brain-computer interface image.

RESULT

At the functional level, a spiking neural network is constructed to classify individuals with depression and healthy individuals, achieving an accuracy exceeding 97.5 %.

COMPARISON WITH EXISTING METHODS

Compared to deep convolutional methods, the spiking method reduces energy consumption.

CONCLUSION

At the structural level, complex networks are utilized to establish spatial topology of brain connections and analyse their graph features, identifying potential abnormal brain functional connections in individuals with depression.

Dorsal pulvinar inactivation leads to spatial selection bias without perceptual deficit

The dorsal pulvinar has been implicated in visuospatial attentional and perceptual confidence processing. Pulvinar lesions in humans and monkeys lead to spatial neglect symptoms, including an overt spatial saccade bias during free choices. However, it remains unclear whether disrupting the dorsal pulvinar during target selection that relies on a perceptual decision leads to a perceptual impairment or a more general spatial orienting and choice deficit. To address this question, we reversibly inactivated the unilateral dorsal pulvinar by injecting GABA-A agonist THIP while two macaque monkeys performed a color discrimination saccade task with varying perceptual difficulty. We used Signal Detection Theory and simulations to dissociate perceptual sensitivity (d-prime) and spatial selection bias (response criterion) effects. We expected a decrease in d-prime if dorsal pulvinar affects perceptual discrimination and a shift in response criterion if dorsal pulvinar is mainly involved in spatial orienting. After the inactivation, we observed response criterion shifts away from contralesional stimuli, especially when two competing stimuli in opposite hemifields were present. Notably, the d-prime and overall accuracy remained largely unaffected. Our results underline the critical contribution of the dorsal pulvinar to spatial orienting and action selection while showing it to be less important for visual perceptual discrimination.

Using camera-guided electrode microdrive navigation for precise 3D targeting of macaque brain sites

Spatial accuracy in electrophysiological investigations is paramount, as precise localization and reliable access to specific brain regions help the advancement of our understanding of the brain's complex neural activity. Here, we introduce a novel, multi camera-based, frameless neuronavigation technique for precise, 3-dimensional electrode positioning in awake monkeys. The investigation of neural functions in awake primates often requires stable access to the brain with thin and delicate recording electrodes. This is usually realized by implanting a chronic recording chamber onto the skull of the animal that allows direct access to the dura. Most recording and positioning techniques utilize this implanted recording chamber as a holder of the microdrive or to hold a grid. This in turn reduces the degrees of freedom in positioning. To solve this problem, we require innovative, flexible, but precise tools for neuronal recordings. We instead mount the electrode microdrive above the animal on an arch, equipped with a series of translational and rotational micromanipulators, allowing movements in all axes. Here, the positioning is controlled by infrared cameras tracking the location of the microdrive and the monkey, allowing precise and flexible trajectories. To verify the accuracy of this technique, we created iron deposits in the tissue that could be detected by MRI. Our results demonstrate a remarkable precision with the confirmed physical location of these deposits averaging less than 0.5 mm from their planned position. Pilot electrophysiological recordings additionally demonstrate the accuracy and flexibility of this method. Our innovative approach could significantly enhance the accuracy and flexibility of neural recordings, potentially catalyzing further advancements in neuroscientific research.

rTMS over the human medial parietal cortex impairs online reaching corrections

Indirect correlational evidence suggests that the posteromedial sector of the human parietal cortex (area hV6A) is involved in reaching corrections. We interfered with hV6A functions using repetitive transcranial magnetic stimulation (rTMS) while healthy participants performed reaching movements and in-flight adjustments of the hand trajectory in presence of unexpected target shifts. rTMS over hV6A specifically altered action reprogramming, causing deviations of the shifted trajectories, particularly along the vertical dimension (i.e., distance). This study provides evidence of the functional relevance of hV6A in action reprogramming while a sudden event requires a change in performance and shows that hV6A also plays a role in state estimation during reaching. These findings are in line with neurological data showing impairments in actions performed along the distance dimension when lesions occur in the dorsal posterior parietal cortex.

Grounding neuroscience in behavioral changes using artificial neural networks

Connecting neural activity to function is a common aim in neuroscience. How to define and conceptualize function, however, can vary. Here I focus on grounding this goal in the specific question of how a given change in behavior is produced by a change in neural circuits or activity. Artificial neural network models offer a particularly fruitful format for tackling such questions because they use neural mechanisms to perform complex transformations and produce appropriate behavior. Therefore, they can be a means of causally testing the extent to which a neural change can be responsible for an experimentally observed behavioral change. Furthermore, because the field of interpretability in artificial intelligence has similar aims, neuroscientists can look to interpretability methods for new ways of identifying neural features that drive performance and behaviors.

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.

Visual, delay, and oculomotor timing and tuning in macaque dorsal pulvinar during instructed and free choice memory saccades

Causal perturbations suggest that primate dorsal pulvinar plays a crucial role in target selection and saccade planning, though its basic neuronal properties remain unclear. Some functional aspects of dorsal pulvinar and interconnected frontoparietal areas-e.g. ipsilesional choice bias after inactivation-are similar. But it is unknown if dorsal pulvinar shares oculomotor properties of cortical circuitry, in particular delay and choice-related activity. We investigated such properties in macaque dorsal pulvinar during instructed and free-choice memory saccades. Most recorded units showed visual (12%), saccade-related (30%), or both types of responses (22%). Visual responses were primarily contralateral; diverse saccade-related responses were predominantly post-saccadic with a weak contralateral bias. Memory delay and pre-saccadic enhancement was infrequent (11-9%)-instead, activity was often suppressed during saccade planning (25%) and further during execution (15%). Surprisingly, only few units exhibited classical visuomotor patterns combining cue and continuous delay activity or pre-saccadic ramping; moreover, most spatially-selective neurons did not encode the upcoming decision during free-choice delay. Thus, in absence of a visible goal, the dorsal pulvinar has a limited role in prospective saccade planning, with patterns partially complementing its frontoparietal partners. Conversely, prevalent visual and post-saccadic responses imply its participation in integrating spatial goals with processing across saccades.

Adeno-associated viral vectors for functional intravenous gene transfer throughout the non-human primate brain

Crossing the blood-brain barrier in primates is a major obstacle for gene delivery to the brain. Adeno-associated viruses (AAVs) promise robust, non-invasive gene delivery from the bloodstream to the brain. However, unlike in rodents, few neurotropic AAVs efficiently cross the blood-brain barrier in non-human primates. Here we report on AAV.CAP-Mac, an engineered variant identified by screening in adult marmosets and newborn macaques, which has improved delivery efficiency in the brains of multiple non-human primate species: marmoset, rhesus macaque and green monkey. CAP-Mac is neuron biased in infant Old World primates, exhibits broad tropism in adult rhesus macaques and is vasculature biased in adult marmosets. We demonstrate applications of a single, intravenous dose of CAP-Mac to deliver functional GCaMP for ex vivo calcium imaging across multiple brain areas, or a cocktail of fluorescent reporters for Brainbow-like labelling throughout the macaque brain, circumventing the need for germline manipulations in Old World primates. As such, CAP-Mac is shown to have potential for non-invasive systemic gene transfer in the brains of non-human primates.

Ultra-High Field Imaging of Human Visual Cognition

Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.

Update on Nonhuman Primate Models of Brain Disease and Related Research Tools

The aging of the population is an increasingly serious issue, and many age-related illnesses are on the rise. These illnesses pose a serious threat to the health and safety of elderly individuals and create a serious economic and social burden. Despite substantial research into the pathogenesis of these diseases, their etiology and pathogenesis remain unclear. In recent decades, rodent models have been used in attempts to elucidate these disorders, but such models fail to simulate the full range of symptoms. Nonhuman primates (NHPs) are the most ideal neuroscientific models for studying the human brain and are more functionally similar to humans because of their high genetic similarities and phenotypic characteristics in comparison with humans. Here, we review the literature examining typical NHP brain disease models, focusing on NHP models of common diseases such as dementia, Parkinson's disease, and epilepsy. We also explore the application of electroencephalography (EEG), magnetic resonance imaging (MRI), and optogenetic study methods on NHPs and neural circuits associated with cognitive impairment.

Functional characterization of macaque insula using task-based and resting-state fMRI

Neurophysiological investigations over the past decades have demonstrated the involvement of the primate insula in a wide array of sensory, cognitive, affective and regulatory functions, yet the complex functional organization of the insula remains unclear. Here we examined to what extent non-invasive task-based and resting-state fMRI provides support for functional specialization and integration of sensory and motor information in the macaque insula. Task-based fMRI experiments suggested a functional specialization related to processing of ingestive/taste/distaste information in anterior insula, grasping-related sensorimotor responses in middle insula and vestibular information in posterior insula. Visual stimuli depicting social information involving conspecific`s lip-smacking gestures yielded responses in middle and anterior portions of dorsal and ventral insula, overlapping partially with the sensorimotor and ingestive/taste/distaste fields. Functional specialization/integration of the insula was further corroborated by seed-based whole brain resting-state analyses, showing distinct functional connectivity gradients across the anterio-posterior extent of both dorsal and ventral insula. Posterior insula showed functional correlations in particular with vestibular/optic flow network regions, mid-dorsal insula with vestibular/optic flow as well as parieto-frontal regions of the sensorimotor grasping network, mid-ventral insula with social/affiliative network regions in temporal, cingulate and prefrontal cortices and anterior insula with taste and mouth motor networks including premotor and frontal opercular regions.

Convolutional neural networks for vision neuroscience: significance, developments, and outstanding issues

Convolutional Neural Networks (CNN) are a class of machine learning models predominately used in computer vision tasks and can achieve human-like performance through learning from experience. Their striking similarities to the structural and functional principles of the primate visual system allow for comparisons between these artificial networks and their biological counterparts, enabling exploration of how visual functions and neural representations may emerge in the real brain from a limited set of computational principles. After considering the basic features of CNNs, we discuss the opportunities and challenges of endorsing CNNs as in silico models of the primate visual system. Specifically, we highlight several emerging notions about the anatomical and physiological properties of the visual system that still need to be systematically integrated into current CNN models. These tenets include the implementation of parallel processing pathways from the early stages of retinal input and the reconsideration of several assumptions concerning the serial progression of information flow. We suggest design choices and architectural constraints that could facilitate a closer alignment with biology provide causal evidence of the predictive link between the artificial and biological visual systems. Adopting this principled perspective could potentially lead to new research questions and applications of CNNs beyond modeling object recognition.

Co-variations of cerebral blood volume and single neurons discharge during resting state and visual cognitive tasks in non-human primates

To better understand how the brain allows primates to perform various sets of tasks, the ability to simultaneously record neural activity at multiple spatiotemporal scales is challenging but necessary. However, the contribution of single-unit activities (SUAs) to neurovascular activity remains to be fully understood. Here, we combine functional ultrasound imaging of cerebral blood volume (CBV) and SUA recordings in visual and fronto-medial cortices of behaving macaques. We show that SUA provides a significant estimate of the neurovascular response below the typical fMRI spatial resolution of 2mm3. Furthermore, our results also show that SUAs and CBV activities are statistically uncorrelated during the resting state but correlate during tasks. These results have important implications for interpreting functional imaging findings while one constructs inferences of SUA during resting state or tasks.

A framework and resource for global collaboration in non-human primate neuroscience

As science and technology evolve, there is an increasing need for promotion of international scientific exchange. Collaborations, while offering substantial opportunities for scientists and benefit to society, also present challenges for those working with animal models, such as non-human primates (NHPs). Diversity in regulation of animal research is sometimes mistaken for the absence of common international welfare standards. Here, the ethical and regulatory protocols for 13 countries that have guidelines in place for biomedical research involving NHPs were assessed with a focus on neuroscience. Review of the variability and similarity in trans-national NHP welfare regulations extended to countries in Asia, Europe and North America. A tabulated resource was established to advance solution-oriented discussions and scientific collaborations across borders. Our aim is to better inform the public and other stakeholders. Through cooperative efforts to identify and analyze information with reference to evidence-based discussion, the proposed key ingredients may help to shape and support a more informed, open framework. This framework and resource can be expanded further for biomedical research in other countries.

A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning

Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness - detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework's decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.

Visualizing advances in the future of primate neuroscience research

Future neuroscience and biomedical projects involving non-human primates (NHPs) remain essential in our endeavors to understand the complexities and functioning of the mammalian central nervous system. In so doing, the NHP neuroscience researcher must be allowed to incorporate state-of-the-art technologies, including the use of novel viral vectors, gene therapy and transgenic approaches to answer continuing and emerging research questions that can only be addressed in NHP research models. This perspective piece captures these emerging technologies and some specific research questions they can address. At the same time, we highlight some current caveats to global NHP research and collaborations including the lack of common ethical and regulatory frameworks for NHP research, the limitations involving animal transportation and exports, and the ongoing influence of activist groups opposed to NHP research.

Fusion of quantitative susceptibility maps and T1-weighted images improve brain tissue contrast in primates

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.

Bidirectional and parallel relationships in macaque face circuit revealed by fMRI and causal pharmacological inactivation

Although the presence of face patches in primate inferotemporal (IT) cortex is well established, the functional and causal relationships among these patches remain elusive. In two monkeys, muscimol was infused sequentially into each patch or pair of patches to assess their respective influence on the remaining IT face network and the amygdala, as determined using fMRI. The results revealed that anterior face patches required input from middle face patches for their responses to both faces and objects, while the face selectivity in middle face patches arose, in part, from top-down input from anterior face patches. Moreover, we uncovered a parallel fundal-lateral functional organization in the IT face network, supporting dual routes (dorsal-ventral) in face processing within IT cortex as well as between IT cortex and the amygdala. Our findings of the causal relationship among the face patches demonstrate that the IT face circuit is organized into multiple functional compartments.

Mapping effective connectivity of human amygdala subdivisions with intracranial stimulation

The primate amygdala is a complex consisting of over a dozen nuclei that have been implicated in a host of cognitive functions, individual differences, and psychiatric illnesses. These functions are implemented through distinct connectivity profiles, which have been documented in animals but remain largely unknown in humans. Here we present results from 25 neurosurgical patients who had concurrent electrical stimulation of the amygdala with intracranial electroencephalography (electrical stimulation tract-tracing; es-TT), or fMRI (electrical stimulation fMRI; es-fMRI), methods providing strong inferences about effective connectivity of amygdala subdivisions with the rest of the brain. We quantified functional connectivity with medial and lateral amygdala, the temporal order of these connections on the timescale of milliseconds, and also detail second-order effective connectivity among the key nodes. These findings provide a uniquely detailed characterization of human amygdala functional connectivity that will inform functional neuroimaging studies in healthy and clinical populations.

Graph theory analysis identified two hubs that connect sensorimotor and cognitive and cortical and subcortical nociceptive networks in the non-human primate

Pain perception involves multiple brain regions and networks. Understanding how these brain networks work together is fundamental for appreciating network-wise changes reported in patients with chronic pain disorders. Parcellating pain related networks and understanding their causal relationships is the first step to understand how painful information is processed, integrated, and modulated, and it requires direct manipulation of specific brain regions. Nonhuman primates (NHP) offer an ideal model system to achieve these goals because cortical and subcortical regions in the NHP brain are established based on a variety of different types of data collected in a way that is not feasible or, at least, extremely difficult in humans (i.e., histology data, tract-tracing, intracerebral recordings). In addition, different methodological techniques can also help characterize and further understand these brain cortical and subcortical regions over the course of development. Here we used a heat nociceptive stimulation that is proven to elicit activity of nociceptive neurons in the cortex to refine and parcellate the whole brain nociceptive functional networks, to identify key network hubs, and to characterize network-wise temporal dynamic signatures using high-resolution fMRI. We first functionally localized 24 cortical and subcortical regions that responded to heat nociceptive stimuli (somatosensory area 1/2, area 3a/3b, S2, posterior insula (pIns), anterior insula, area 7b, posterior parietal cortex, anterior cingulate cortex (ACC), prefrontal cortex, caudate, and mediodorsal (MD) and ventral posterior lateral (VPL) thalamic nuclei) and used them as seeds in resting state fMRI (rsfMRI) data analysis. We applied both hierarchical clustering and graph-theory analyses of the pairwise rsfMRI correlation metrics and identified five cortical and one subcortical sub-networks: strong resting state functional connectivity (rsFC) between ACC and prefrontal regions, parietal cortex and area 7b, S2 and posterior insula, areas 3a/3b and 1/2 within the S1 cortex, and thalamic MD and caudate nuclei. The rsFC strengths between cortical areas within each subnetwork were significantly stronger than those between subcortical regions. Regions within each sub-network also exhibited highly correlated temporal dynamics at rest, but the overall dynamic patterns varied drastically across sub-networks. Graph-theory analysis identified the MD nucleus as a hub that connects subcortical and cortical nociceptive sub-networks. The S2-pIns connection joins the sensory and affective/cognitive sub-networks.

Cerebro-cerebellar interactions in nonhuman primates examined by optogenetic functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is a promising approach for the simultaneous and extensive scanning of whole-brain activities. Optogenetics is free from electrical and magnetic artifacts and is an ideal stimulation method for combined use with fMRI. However, the application of optogenetics in nonhuman primates (NHPs) remains limited. Recently, we developed an efficient optogenetic intracortical microstimulation method of the primary motor cortex (M1), which successfully induced forelimb movements in macaque monkeys. Here, we aimed to investigate how optogenetic M1 stimulation causes neural modulation in the local and remote brain regions in anesthetized monkeys using 7-tesla fMRI. We demonstrated that optogenetic stimulation of the M1 forelimb and hindlimb regions successfully evoked robust direct and remote fMRI activities. Prominent remote activities were detected in the anterior and posterior lobes in the contralateral cerebellum, which receive projections polysynaptically from the M1. We further demonstrated that the cerebro-cerebellar projections from these M1 regions were topographically organized, which is concordant with the somatotopic map in the cerebellar cortex previously reported in macaques and humans. The present study significantly enhances optogenetic fMRI in NHPs, resulting in profound understanding of the brain network, thereby accelerating the translation of findings from animal models to humans.

Dissecting the Prefrontal Network With Pathway-Selective Manipulation in the Macaque Brain-A Review

Macaque monkeys are prime animal models for studying the neural mechanisms of decision-making because of their close kinship with humans. Manipulation of neural activity during decision-making tasks is essential for approaching the causal relationship between the brain and its functions. Conventional manipulation methods used in macaque studies are coarse-grained, and have worked indiscriminately on mutually intertwined neural pathways. To systematically dissect neural circuits responsible for a variety of functions, it is essential to analyze changes in behavior and neural activity through interventions in specific neural pathways. In recent years, an increasing number of studies have applied optogenetics and chemogenetics to achieve fine-grained pathway-selective manipulation in the macaque brain. Here, we review the developments in macaque studies involving pathway-selective operations, with a particular focus on applications to the prefrontal network. Pathway selectivity can be achieved using single viral vector transduction combined with local light stimulation or ligand administration directly into the brain or double-viral vector transduction combined with systemic drug administration. We discuss the advantages and disadvantages of these methods. We also highlight recent technological developments in viral vectors that can effectively infect the macaque brain, as well as the development of methods to deliver photostimulation or ligand drugs to a wide area to effectively manipulate behavior. The development and dissemination of such pathway-selective manipulations of macaque prefrontal networks will enable us to efficiently dissect the neural mechanisms of decision-making and innovate novel treatments for decision-related psychiatric disorders.

Functionally specific and sparse domain-based micro-networks in monkey V1 and V2

The cerebral cortices of human and nonhuman primate brains are characterized by submillimeter functional domains. However, little is known about the connections of single functional domains. Here, in macaque monkey visual cortex, we have developed a targeted focal electrical stimulation method, coupled with functional optical imaging, to map cortical networks with submillimeter precision in vivo. We find that single functional domains are a part of highly specific and sparse intra-areal and inter-areal micro-networks. Across color-related and orientation-related functionalities, these micro-networks exhibit parallel connection patterns, suggesting a common domain-based architecture. Moreover, these micro-networks shift topographically at a submillimeter scale, suggesting that they serve as a fundamental unit for cortical information processing. Our findings establish a domain-based connectional architecture in the primate brain and present new constraints for cortical map representation.

Two-monkey fMRI setup for investigating multifaceted aspects of social cognition and behavior involving a real-live conspecific

While brain research over the past decades has shed light on the neural correlates of social cognition and behavior in human and non-human primates, most of this research has been performed in virtual settings requiring subjects to observe pictures or recorded videos instead of observing or interacting with another real-live individual. Here we present a two-monkey fMRI setup, allowing examining whole brain responses in macaque monkeys while they observe or interact face-to-face with another real-live conspecific. We tested this setup by comparing overall brain responses during observation of conspecific hand actions in a virtual (observation of recorded videos of actions) or live context (observation of a real-live conspecific performing actions). This dyadic monkey fMRI setup allows examining brain-wide responses in macaque monkeys during different aspects of social behavior, including observation of real-live actions and sensations, social facilitation, joint-attention and social interactions.

Co-expressing fast channelrhodopsin with step-function opsin overcomes spike failure due to photocurrent desensitization in optogenetics: a theoretical study

Objective A fundamental challenge in optogenetics is to elicit long-term high-fidelity neuronal spiking with negligible heating. Fast channelrhodopsins (ChRs) require higher irradiances and cause spike failure due to photocurrent desensitization under sustained illumination, whereas, more light-sensitive step-function opsins (SFOs) exhibit prolonged depolarization with insufficient photocurrent and fast response for high-fidelity spiking. Approach We present a novel method to overcome this fundamental limitation by co-expressing fast ChRs with SFOs. A detailed theoretical analysis of ChETA co-expressed with different SFOs, namely ChR2(C128A), ChR2(C128S), SSFO and SOUL, expressing hippocampal neurons has been carried out by formulating their accurate theoretical models. Main results ChETA-SFO-expressing hippocampal neurons show a more stable photocurrent that overcomes spike failure. Spiking fidelity in these neurons can be sustained even at lower irradiances of subsequent pulses (77 % of initial pulse intensity in ChETA-ChR2(C128A)-expressing neurons) or by using red-shifted light pulses at appropriate intervals. High-fidelity spiking up to 60 Hz can be evoked in ChR2-C128S-ChETA-expressing neurons, which cannot be attained with only SFOs. Significance The present study provides important insights about photostimulation protocols for bi-stable switching of neurons. This new approach provides a means for sustained low-power, high-frequency, and high-fidelity optogenetic switching of neurons, necessary to study various neural functions and neurodegenerative disorders and enhance the utility of optogenetics for biomedical applications.

The Digital Brain Bank, an open access platform for post-mortem imaging datasets

Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

The cortical connectome of primate lateral prefrontal cortex

The lateral prefrontal cortex (LPFC) of primates plays an important role in executive control, but how it interacts with the rest of the cortex remains unclear. To address this, we densely mapped the cortical connectome of LPFC, using electrical microstimulation combined with functional MRI (EM-fMRI). We found isomorphic mappings between LPFC and five major processing domains composing most of the cerebral cortex except early sensory and motor areas. An LPFC grid of ∼200 stimulation sites topographically mapped to separate grids of activation sites in the five domains, coarsely resembling how the visual cortex maps the retina. The temporal and parietal maps largely overlapped in LPFC, suggesting topographically organized convergence of the ventral and dorsal streams, and the other maps overlapped at least partially. Thus, the LPFC contains overlapping, millimeter-scale maps that mirror the organization of major cortical processing domains, supporting LPFC's role in coordinating activity within and across these domains.

Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging

Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.

Comparative connectomics of the primate social brain

Social interaction is thought to provide a selection pressure for human intelligence, yet little is known about its neurobiological basis and evolution throughout the primate lineage. Recent advances in neuroimaging have enabled whole brain investigation of brain structure, function, and connectivity in humans and non-human primates (NHPs), leading to a nascent field of comparative connectomics. However, linking social behavior to brain organization across the primates remains challenging. Here, we review the current understanding of the macroscale neural mechanisms of social behaviors from the viewpoint of system neuroscience. We first demonstrate an association between the number of cortical neurons and the size of social groups across primates, suggesting a link between neural information-processing capacity and social capabilities. Moreover, by capitalizing on recent advances in species-harmonized functional MRI, we demonstrate that portions of the mirror neuron system and default-mode networks, which are thought to be important for representation of the other's actions and sense of self, respectively, exhibit similarities in functional organization in macaque monkeys and humans, suggesting possible homologies. With respect to these two networks, we describe recent developments in the neurobiology of social perception, joint attention, personality and social complexity. Together, the Human Connectome Project (HCP)-style comparative neuroimaging, hyperscanning, behavioral, and other multi-modal investigations are expected to yield important insights into the evolutionary foundations of human social behavior.

One object, two networks? Assessing the relationship between the face and body-selective regions in the primate visual system

Faces and bodies are often treated as distinct categories that are processed separately by face- and body-selective brain regions in the primate visual system. These regions occupy distinct regions of visual cortex and are often thought to constitute independent functional networks. Yet faces and bodies are part of the same object and their presence inevitably covary in naturalistic settings. Here, we re-evaluate both the evidence supporting the independent processing of faces and bodies and the organizational principles that have been invoked to explain this distinction. We outline four hypotheses ranging from completely separate networks to a single network supporting the perception of whole people or animals. The current evidence, especially in humans, is compatible with all of these hypotheses, making it presently unclear how the representation of faces and bodies is organized in the cortex.

Chemogenetic sensory fMRI reveals behaviorally relevant bidirectional changes in primate somatosensory network

Concurrent genetic neuromodulation and functional magnetic resonance imaging (fMRI) in primates has provided a valuable opportunity to assess the modified brain-wide operation in the resting state. However, its application to link the network operation with behavior still remains challenging. Here, we combined chemogenetic silencing of the primary somatosensory cortex (SI) with tactile fMRI and related behaviors in macaques. Focal chemogenetic silencing of functionally identified SI hand region impaired grasping behavior. The same silencing also attenuated hand stimulation-evoked fMRI signal at both the local silencing site and the anatomically and/or functionally connected downstream grasping network, suggesting altered network operation underlying the induced behavioral impairment. Furthermore, the hand region silencing unexpectedly disinhibited foot representation with accompanying behavioral hypersensitization. These results demonstrate that focal chemogenetic silencing with sensory fMRI in macaques unveils bidirectional network changes to generate multifaceted behavioral impairments, thereby opening a pivotal window toward elucidating the causal network operation underpinning higher brain functions in primates.

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

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.