A comprehensive macaque fMRI pipeline and hierarchical atlas

Temporal dynamics of offline transcranial ultrasound stimulation

Transcranial ultrasound stimulation (TUS) is a promising non-invasive neuromodulation modality, characterized by deep-brain accuracy and the capability to induce longer-lasting effects. However, most TUS datasets are underpowered, hampering efforts to identify TUS longevity and temporal dynamics. This primate case was studied awake with over 50 fMRI datasets, with and without left anterior hippocampus TUS. We therefore amassed the highest-powered TUS dataset to date required to reveal TUS longevity and dynamics. Most of the effects were found in the TUS region itself and alongside the default mode and sensorimotor networks. Seed-based functional connectivity exhibited a time-constrained alteration which dissipated ∼60 min post-TUS. Intrinsic activity measure and regional homogeneity displayed extended diffusivity and longer durations. This high-powered dataset allowed predicting TUS using pre-stimulation features that can now extend to modeling of individuals scanned less extensively. This case report reveals the diversity of TUS temporal dynamics to help to advance long-lasting human applications.

Shared and Unique Neural Codes for Biological Motion Perception in Humans and Macaque Monkeys

Throughout evolution, living organisms have honed the ability to swiftly recognize biological motion (BM) across species. However, how the brain processes within- and cross-species BM, and the evolutionary progression of these processes, remain unclear. To investigate these questions, the current study examined brain activity in the lateral temporal areas of humans and monkeys as they passively observed upright and inverted human and macaque BM stimuli. In humans, the middle temporal area (hMT+) responded to both human and macaque BM stimuli, while the right posterior superior temporal sulcus (hpSTS) exhibited selective responses to human BM stimuli. This selectivity is evidenced by an increased feedforward connection from hMT+ to hpSTS during the processing of human BM stimuli. In monkeys, the MT region processed BM stimuli from both species, but no subregion in the STS anterior to MT is specific to conspecific BM stimuli. A comparison of these findings suggests that upstream brain regions (i.e., MT) may retain homologous functions across species, while downstream brain regions (i.e., STS) may have undergone differentiation and specialization throughout evolution. These results provide insights into the commonalities and differences in the specialized visual pathway engaged in processing within- and cross-species BMs, as well as their functional divergence during evolution.

Contrastive machine learning reveals species -shared and -specific brain functional architecture

A deep comparative analysis of brain functional connectome across species in primates has the potential to yield valuable insights for both scientific and clinical applications. However, the interspecies commonality and differences are inherently entangled with each other and with other irrelevant factors. Here we develop a novel contrastive machine learning method, called shared-unique variation autoencoder (SU-VAE), to allow disentanglement of the species-shared and species-specific functional connectome variation between macaque and human brains on large-scale resting-state fMRI datasets. The method was validated by confirming that human-specific features are differentially related to cognitive scores, while features shared with macaque better capture sensorimotor ones. The projection of disentangled connectomes to the cortex revealed a gradient that reflected species divergence. In contrast to macaque, the introduction of human-specific connectomes to the shared ones enhanced network efficiency. We identified genes enriched on 'axon guidance' that could be related to the human-specific connectomes. The code contains the model and analysis can be found in https://github.com/BBBBrain/SU-VAE.

Age-related alterations in functional and structural networks in the brain in macaque monkeys

Resting-state networks (RSNs) have been used as biomarkers of brain diseases and cognitive performance. However, age-related changes in the RSNs of macaques, a representative animal model, are still not fully understood. In this study, we measured the RSNs in macaques aged 3-20 years and investigated the age-related changes from both functional and structural perspectives. The proportion of structural connectivity in the RSNs relative to the total fibers in the whole brain significantly decreased in aged macaques, whereas functional connectivity showed an increasing trend with age. Additionally, the amplitude of low-frequency fluctuations tended to increase with age, indicating that resting-state neural activity may be more active in the RSNs may increase with age. These results indicate that structural and functional alterations in typical RSNs are age-dependent and can be a marker of aging in the macaque's brain.

General anaesthesia decreases the uniqueness of brain functional connectivity across individuals and species

The human brain is characterized by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI scans acquired under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain, both with respect to the brains of other individuals and the brains of another species. Using functional connectivity, we report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organized: it co-localizes with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol and reversed upon recovery. Providing convergent evidence, we show that anaesthesia shifts the functional connectivity of the human brain closer to the functional connectivity of the macaque brain in a low-dimensional space. Finally, anaesthesia diminishes the match between spontaneous brain activity and cognitive brain patterns aggregated from the Neurosynth meta-analytic engine. Collectively, the present results reveal that anaesthetized human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.

PET Mapping of Receptor Occupancy Using Joint Direct Parametric Reconstruction

Receptor occupancy (RO) studies using PET neuroimaging play a critical role in the development of drugs targeting the central nervous system (CNS). The conventional approach to estimate drug receptor occupancy consists in estimation of binding potential changes between two PET scans (baseline and post-drug injection). This estimation is typically performed separately for each scan by first reconstructing dynamic PET scan data before fitting a kinetic model to time activity curves. This approach fails to properly model the noise in PET measurements, resulting in poor RO estimates, especially in low receptor density regions.

OBJECTIVE

In this work, we evaluate a novel joint direct parametric reconstruction framework to directly estimate distributions of RO and other kinetic parameters in the brain from a pair of baseline and post-drug injection dynamic PET scans.

METHODS

The proposed method combines the use of regularization on RO maps with alternating optimization to enable estimation of occupancy even in low binding regions.

RESULTS

Simulation results demonstrate the quantitative improvement of this method over conventional approaches in terms of accuracy and precision of occupancy. The proposed method is also evaluated in preclinical in-vivo experiments using 11C-MK-6884 and a muscarinic acetylcholine receptor 4 positive allosteric modulator drug, showing improved estimation of receptor occupancy as compared to traditional estimators.

CONCLUSION

The proposed joint direct estimation framework improves RO estimation compared to conventional methods, especially in intermediate to low-binding regions.

SIGNIFICANCE

This work could potentially facilitate the evaluation of new drug candidates targeting the CNS.

Basal forebrain activation improves working memory in senescent monkeys

Brain aging contributes to cognitive decline and risk of dementia. Degeneration of the basal forebrain cholinergic system parallels these changes in aging, Alzheimer's dementia, Parkinson's dementia, and Lewy body dementia, and thus is a common element linked to executive function across the lifespan and in disease states. Here, we tested the potential of one-hour daily intermittent basal forebrain stimulation to improve cognition in senescent Rhesus monkeys, and its mechanisms of action. Stimulation in five animals improved working memory duration in each animal over 8-12 weeks, with peak improvements observed in the first four weeks. In an ensuing three month period without stimulation, improvements were retained. With additional stimulation, performance remained above baseline throughout the 15 months of the study. Studies with a cholinesterase inhibitor in five animals produced inconsistent improvements in behavior. One of five animals improved significantly. Manipulating the stimulation pattern demonstrated selectivity for both stimulation and recovery period duration in two animals. Brain stimulation led to acute increases in cerebrospinal fluid levels of tissue plasminogen activator, which is an activating element for two brain neurotrophins, Nerve Growth Factor (NGF) and Brain-Derived Growth Factor (BDNF), in four animals. Stimulation also led to improved glucose utilization in stimulated hemispheres relative to contralateral in three animals. Glucose utilization also consistently declines with aging and some dementias. Together, these findings suggest that intermittent stimulation of the nucleus basalis of Meynert improves executive function and reverses some aspects of brain aging.

Modulating nociception networks: the impact of low-intensity focused ultrasound on thalamocortical connectivity

Pain engages multiple brain networks, with the thalamus serving as a critical subcortical hub. This study aims to explore the effects of low-intensity transcranial focused ultrasound-induced suppression on the organization of thalamocortical nociceptive networks. We employed MR-guided focused ultrasound, a potential non-invasive therapy, with real-time ultrasound beam localization feedback and fMRI monitoring. We first functionally identified the focused ultrasound target at the thalamic ventroposterior lateral nucleus by mapping the whole-brain blood oxygenation level-dependent responses to nociceptive heat stimulation of the hand using fMRI in each individual macaque monkey under light anaesthesia. The blood oxygenation level-dependent fMRI signals from the heat-responsive thalamic ventroposterior lateral nucleus were analysed to derive thalamocortical effective functional connectivity network using the psychophysical interaction method. Nineteen cortical regions across sensorimotor, cognitive, associative and limbic networks exhibited strong effective functional connectivity to the thalamic ventroposterior lateral during heat nociceptive processing. Focused ultrasound-induced suppression of heat activity in the thalamic ventroposterior lateral nucleus altered nociceptive responses in most of the 19 regions. Data-driven hierarchical clustering analyses of blood oxygenation level-dependent time courses across all thalamocortical region-of-interest pairs identified two effective functional connectivity subnetworks. The concurrent suppression of thalamic heat response with focused ultrasound reorganized these subnetworks and modified thalamocortical connection strength. Our findings suggest that the thalamic ventroposterior lateral nucleus has extensive and causal connections to a wide array of cortical areas during nociceptive processing. The combination of MR-guided focused ultrasound with fMRI enables precise dissection and modulation of nociceptive networks in the brain, a capability that no other device-based neuromodulation methods have achieved. This presents a promising non-invasive tool for modulating pain networks with profound clinical relevance. The robust modulation of nociceptive effective functional connectivity networks by focused ultrasound strongly supports the thalamic ventroposterior lateral as a viable target for pain management strategies.

Myelination across cortical hierarchies and depths in humans and macaques

Myelination is fundamental to brain function, enabling rapid neural communication and supporting neuroplasticity throughout the lifespan. While hierarchical patterns of myelin maturation across the cortical surface are well-documented in humans, it remains unclear which features reflect evolutionarily conserved developmental processes versus human-characteristic adaptations. Moreover, the laminar development of myelin across the primate cortical surface, which shapes hierarchies and supports functions ranging from sensory integration to network communication, has been largely unexplored. Using neuroimaging to measure the T1-weighted/T2-weighted ratio in tissue contrast as a proxy for myelin content, we systematically compared depth-dependent trajectories of myelination across the cortical surface in humans and macaques. We identified a conserved "inside-out" pattern, with deeper layers exhibiting steeper increases in myelination and earlier plateaus than superficial layers. This depth-dependent organization followed a hierarchical gradient across the cortical surface, progressing from early maturation in sensorimotor regions to prolonged development in association areas. Humans exhibited a markedly extended timeline of myelination across both cortical regions and depths compared to macaques, allowing for prolonged postnatal plasticity across the entire cortical hierarchy - from sensory and motor processing to higher-order association networks. This extended potential for plasticity may facilitate the shaping of cortical circuits through postnatal experience in ways that support human-characteristic perceptual and cognitive capabilities.

Pharmacological Modulation of Dopamine Receptors Reveals Distinct Brain-Wide Networks Associated with Learning and Motivation in Nonhuman Primates

The neurotransmitter dopamine (DA) has a multifaceted role in healthy and disordered brains through its action on multiple subtypes of dopaminergic receptors. How the modulation of these receptors influences learning and motivation by altering intrinsic brain-wide networks remains unclear. Here, we performed parallel behavioral and resting-state functional MRI experiments after administration of two different DA receptor antagonists in male and female macaque monkeys. Systemic administration of SCH-23390 (D1 antagonist) slowed probabilistic learning when subjects had to learn new stimulus-reward associations and diminished functional connectivity (FC) in corticocortical and frontostriatal connections. In contrast, haloperidol (D2 antagonist) improved learning and broadly enhanced FC in cortical connections. Further comparisons between the effect of SCH-23390/haloperidol on behavioral and resting-state FC revealed specific cortical and subcortical networks associated with the cognitive and motivational effects of DA manipulation, respectively. Thus, we reveal distinct brain-wide networks that are associated with the dopaminergic control of learning and motivation via DA receptors.

Ensemble reactivations during brief rest drive fast learning of sequences

During motor learning, breaks in practice are known to facilitate behavioural optimizations. Although this process has traditionally been studied over long breaks that last hours to days1-6, recent studies in humans have demonstrated that rapid performance gains during early motor sequence learning are most pronounced after very brief breaks lasting seconds to minutes7-10. However, the precise causal neural mechanisms that facilitate performance gains after brief breaks remain poorly understood. Here we recorded neural ensemble activity in the motor cortex of macaques while they performed a visuomotor sequence learning task interspersed with brief breaks. We found that task-related neural cofiring patterns were reactivated during brief breaks. The rate and content of reactivations predicted the magnitude and pattern of subsequent performance gains. Of note, we found that performance gains and reactivations were positively correlated with cortical ripples (80-120 Hz oscillations) but anti-correlated with β bursts (13-30 Hz oscillations), which ultimately dominated breaks after the fast learning phase plateaued. We then applied 20 Hz epidural alternating current stimulation (ACS) to motor cortex, which reduced reactivation rates in a phase-specific and dose-dependent manner. Notably, 20 Hz ACS also eliminated performance gains. Overall, our results indicate that the reactivations of task ensembles during brief breaks are causal drivers of subsequent performance gains. β bursts compete with this process, possibly to support stable performance.

Connectional differences between humans and macaques in the MT+ complex

MT+ is pivotal in the dorsal visual stream, encoding tool-use characteristics such as motion speed and direction. Despite its conservation between humans and monkeys, differences in MT+ spatial location and organization may lead to divergent, yet unexplored, connectivity patterns and functional characteristics. Using diffusion tensor imaging, we examined the structural connectivity of MT+ subregions in macaques and humans. We also employed graph-theoretical analyses on the constructed homologous tool-use network to assess their functional roles. Our results revealed location-dependent connectivity in macaques, with MST, MT, and FST predominantly connected to dorsal, middle, and ventral surfaces, respectively. Humans showed similar connectivity across all subregions. Differences in connectivity between MST and FST are more pronounced in macaques. In humans, the entire MT+ region, especially MST, exhibited stronger information transmission capabilities. Our findings suggest that the differences in tool use between humans and macaques may originate earlier than previously thought, particularly within the MT+ region.

A mathematical language for linking fine-scale structure in spikes from hundreds to thousands of neurons with behaviour

Recent advances in neural recording technology allow simultaneously recording action potentials from hundreds to thousands of neurons in awake, behaving animals. However, characterizing spike patterns in the resulting data, and linking these patterns to behaviour, remains a challenging task. The lack of a rigorous mathematical language for variable numbers of events (spikes) emitted by multiple agents (neurons) is an important limiting factor. We introduce a new mathematical operation to decompose complex spike patterns into a set of simple, structured elements. This creates a mathematical language that allows comparing spike patterns across trials, detecting sub-patterns, and making links to behaviour via a clear distance measure. We first demonstrate the method using Neuropixel recordings from macaque motor cortex. We then apply the method to dual Utah array recordings from macaque prefrontal cortex, where this technique reveals previously unseen structure that can predict both memory-guided decisions and errors in a virtual-reality working memory task. These results demonstrate that this technique provides a powerful new approach to understand structure in the spike times of neural populations, at a scale that will continue to grow more and more rapidly in upcoming years.

Color and Spatial Frequency Provide Functional Signatures of Retinotopic Visual Areas

Primate vision relies on retinotopically organized cortical parcels defined by representations of hemifield (upper vs lower visual field), eccentricity (fovea vs periphery), and area (V1, V2, V3, V4). Here we test for functional signatures of these organizing principles. We used functional magnetic resonance imaging to measure responses to gratings varying in spatial frequency, color, and saturation across retinotopically defined parcels in two macaque monkeys, and we developed a Sparse Supervised Embedding (SSE) analysis to identify stimulus features that best distinguish cortical parcels from each other. Constraining the SSE model to distinguish just eccentricity representations of the voxels revealed the expected variation of spatial frequency and S-cone modulation with eccentricity. Constraining the model according to the dorsal/ventral location and retinotopic area of each voxel provided unexpected functional signatures, which we investigated further with standard univariate analyses. Posterior parcels (V1) were distinguished from anterior parcels (V4) by differential responses to chromatic and luminance contrast, especially of low-spatial-frequency gratings. Meanwhile, ventral parcels were distinguished from dorsal parcels by differential responses to chromatic and luminance contrast, especially of colors that modulate all three cone types. The dorsal/ventral asymmetry not only resembled differences between candidate dorsal and ventral subdivisions of human V4 but also extended to include all retinotopic visual areas, starting in V1 and increasing from V1 to V4. The results provide insight into the functional roles of different retinotopic areas and demonstrate the utility of SSE as a data-driven tool for generating hypotheses about cortical function and behavior.

Development and early life stress sensitivity of the rat cortical microstructural similarity network

The rat offers a uniquely valuable animal model in neuroscience, but we currently lack an individual-level understanding of the in vivo rat brain network. Here, leveraging longitudinal measures of cortical magnetization transfer ratio (MTR) from in vivo neuroimaging between postnatal days 20 (weanling) and 290 (mid-adulthood), we design and implement a computational pipeline that captures the network of structural similarity (MIND, morphometric inverse divergence) between each of 53 distinct cortical areas. We first characterized the normative development of the network in a cohort of rats undergoing typical development (N=47), and then contrasted these findings with a cohort exposed to early life stress (ELS, N=40). MIND as a metric of cortical similarity and connectivity was validated by cortical cytoarchitectonics and axonal tract-tracing data. The normative rat MIND network had high between-study reliability and complex topological properties including a rich club. Similarity changed during post-natal and adolescent development, including a phase of fronto-hippocampal convergence, or increasing inter-areal similarity. An inverse process of increasing fronto-hippocampal dissimilarity was seen with post-adult aging. Exposure to ELS in the form of maternal separation appeared to accelerate the normative trajectory of brain development - highlighting embedding of stress in the dynamic rat brain network. Our work provides novel tools for systems-level study of the rat brain that can now be used to understand network-based underpinnings of complex lifespan behaviors and experimental manipulations that this model organism allows.

Monkeys engage in visual simulation to solve complex problems

Visual simulation-i.e., using internal reconstructions of the world to experience potential future versions of events that are not currently happening-is among the most sophisticated capacities of the human mind. But is this ability in fact uniquely human? To answer this question, we tested monkeys on a series of experiments involving the "Planko" game, which we have previously used to evoke visual simulation in human participants. We found that monkeys were able to successfully play the game using a simulation strategy, predicting the trajectory of a ball through a field of planks while demonstrating a level of accuracy and behavioral signatures comparable with those of humans. Computational analyses further revealed that the monkeys' strategy while playing Planko aligned with a recurrent neural network (RNN) that approached the task using a spontaneously learned simulation strategy. Finally, we carried out awake functional magnetic resonance imaging while monkeys played Planko. We found activity in motion-sensitive regions of the monkey brain during hypothesized simulation periods, even without any perceived visual motion cues. This neural result closely mirrors previous findings from human research, suggesting a shared mechanism of visual simulation across species. Taken together, these findings challenge traditional views of animal cognition, proposing that nonhuman primates possess a complex cognitive landscape, capable of invoking imaginative and predictive mental experiences to solve complex everyday problems.

Transcranial ultrasound stimulation effect in the redundant and synergistic networks consistent across macaques

Low-intensity transcranial ultrasound stimulation (TUS) is a noninvasive technique that safely alters neural activity, reaching deep brain areas with good spatial accuracy. We investigated the effects of TUS in macaques using a recent metric, the synergy minus redundancy rank gradient, which quantifies different kinds of neural information processing. We analyzed this high-order quantity on the fMRI data after TUS in two targets: the supplementary motor area (SMA-TUS) and the frontal polar cortex (FPC-TUS). The TUS produced specific changes at the limbic network at FPC-TUS and the motor network at SMA-TUS and altered the sensorimotor, temporal, and frontal networks in both targets, mostly consistent across macaques. Moreover, there was a reduction in the structural and functional coupling after both stimulations. Finally, the TUS changed the intrinsic high-order network topology, decreasing the modular organization of the redundancy at SMA-TUS and increasing the synergistic integration at FPC-TUS.

Involvement of Neurons in the Nonhuman Primate Anterior Striatum in Proactive Inhibition

Behaving as desired requires selecting the appropriate behavior and inhibiting the selection of inappropriate behavior. This inhibitory function involves multiple processes, such as reactive and proactive inhibition, instead of a single process. In this study, two male macaque monkeys were required to perform a task in which they had to sequentially select (accept) or refuse (reject) a choice. Neural activity was recorded from the anterior striatum, which is considered to be involved in behavioral inhibition, focusing on the distinction between proactive and reactive inhibitions. We identified neurons with significant activity changes during the rejection of bad objects. Cluster analysis revealed three distinct groups, of which only one showed increased activity during object rejection, suggesting its involvement in proactive inhibition. This activity pattern was consistent irrespective of the rejection method, indicating a role beyond saccadic suppression. Furthermore, minimal activity changes during the fixation task indicated that these neurons were not primarily involved in reactive inhibition. In conclusion, these findings suggest that the anterior striatum plays a crucial role in cognitive control and orchestrates goal-directed behavior through proactive inhibition, which may be critical in understanding the mechanisms of behavioral inhibition dysfunction that occur in patients with basal ganglia disease.

Real Face Value: The Processing of Naturalistic Facial Expressions in the Macaque Inferior Temporal Cortex

For primates, expressions of fear are thought to be powerful social signals. In laboratory settings, faces with fearful expressions have reliably evoked valence effects in inferior temporal cortex. However, because macaques use so called "fear grins" in a variety of different contexts, the deeper question is whether the macaque inferior temporal cortex is tuned to the prototypical fear grin, or to conspecifics signaling fear? In this study, we combined neuroimaging with the results of a behavioral task to investigate how macaques encode a wide variety of fearful facial expressions. In Experiment 1, we identified two sets of macaque face stimuli using different approaches; we selected faces based on the emotional context (i.e., calm vs. fearful), and we selected faces based on the engagement of action units (i.e., neutral vs. fear grins). We also included human faces in Experiment 1. Then, using fMRI, we found that the faces selected based on context elicited a larger valence effect in the inferior temporal cortex than faces selected based on visual appearance. Furthermore, human facial expressions only elicited weak valence effects. These observations were further supported by the results of a two-alternative, forced-choice task (Experiment 2), suggesting that fear grins vary in their perceived pleasantness. Collectively, these findings indicate that the macaque inferior temporal cortex is more involved in social intelligence than commonly assumed, encoding emergent properties in naturalistic face stimuli that transcend basic visual features. These results demand a rethinking of theories surrounding the function and operationalization of primate inferior temporal cortex.

Multi-scale hierarchical brain regions detect individual and interspecies variations of structural connectivity in macaque monkeys and humans

Macaques are representative animal models in translational research. However, the distinct shape and location of the brain regions between macaques and humans prevents us from comparing the brain structure directly. Here, we calculated structural connectivity (SC) with multi-scale hierarchical regions of interest (ROIs) to parcel out human and macaque brain into 8 (level 1 ROIs), 28 (level 2 ROIs), or 46 (level 3 ROIs) regions, which consist of anatomically and functionally defined level 4 ROIs (around 100 parcellation of the brain). The SC with the level 1 ROIs showed lower individual and interspecies variation in macaques and humans. SC with level 2 and 3 ROIs shows that the several regions in frontal, temporal and parietal lobe show distinct connectivity between macaques and humans. Lateral frontal cortex, motor cortex and auditory cortex were shown to be important areas for interspecies differences. These results provide insights to use macaques as animal models for translational study.

Pharmacological modulation of dopamine receptors reveals distinct brain-wide networks associated with learning and motivation in non-human primates

The neurotransmitter dopamine (DA) has a multifaceted role in healthy and disordered brains through its action on multiple subtypes of dopaminergic receptors. How modulation of these receptors influences learning and motivation by altering intrinsic brain-wide networks remains unclear. Here we performed parallel behavioral and resting-state functional MRI experiments after administration of two different DA receptor antagonists in macaque monkeys. Systemic administration of SCH-23390 (D1 antagonist) slowed probabilistic learning when subjects had to learn new stimulus-reward associations and diminished functional connectivity (FC) in cortico-cortical and fronto-striatal connections. By contrast, haloperidol (D2 antagonist) improved learning and broadly enhanced FC in cortical connections. Further comparisons between the effect of SCH-23390/haloperidol on behavioral and resting-state FC revealed specific cortical and subcortical networks associated with the cognitive and motivational effects of DA manipulation, respectively. Thus, we reveal distinct brain-wide networks that are associated with the dopaminergic control of learning and motivation via DA receptors.

Basal forebrain activation improves working memory in senescent monkeys

Brain aging contributes to cognitive decline and risk of dementia. Degeneration of the basal forebrain cholinergic system parallels these changes in aging, Alzheimer's dementia, Parkinson's dementia, and Lewy body dementia, and thus is a common element linked to executive function across the lifespan and in disease states. Here, we tested the potential of one-hour daily intermittent basal forebrain stimulation to improve cognition in senescent monkeys, and its mechanisms of action. Stimulation in five animals improved working memory duration in 8-12 weeks across all animals, with peak improvements observed in the first four weeks. In an ensuing three month period without stimulation, improvements were retained. With additional stimulation, performance remained above baseline throughout the 15 months of the study. Studies with a cholinesterase inhibitor produced inconsistent improvements in behavior. One of five animals improved significantly. Manipulating the stimulation pattern demonstrated selectivity for both stimulation and recovery period duration. Brain stimulation led to acute increases in cerebrospinal levels of tissue plasminogen activator, which is an activating element for two brain neurotrophins, Nerve Growth Factor (NGF) and Brain-Derived Growth Factor (BDNF). Stimulation also led to improved glucose utilization in stimulated hemispheres relative to contralateral. Glucose utilization also consistently declines with aging and some dementias. Together, these findings suggest that intermittent stimulation of the nucleus basalis of Meynert improves executive function and reverses some aspects of brain aging.

Fusing multi-scale functional connectivity patterns via Multi-Branch Vision Transformer (MB-ViT) for macaque brain age prediction

Brain age (BA) is defined as a measure of brain maturity and could help characterize both the typical brain development and neuropsychiatric disorders in mammals. Various biological phenotypes have been successfully applied to predict BA of human using chronological age (CA) as label. However, whether the BA of macaque, one of the most important animal models, can also be reliably predicted is largely unknown. To address this question, we propose a novel deep learning model called Multi-Branch Vision Transformer (MB-ViT) to fuse multi-scale (i.e., from coarse-grained to fine-grained) brain functional connectivity (FC) patterns derived from resting state functional magnetic resonance imaging (rs-fMRI) data to predict BA of macaques. The discriminative functional connections and the related brain regions contributing to the prediction are further identified based on Gradient-weighted Class Activation Mapping (Grad-CAM) method. Our proposed model successfully predicts BA of 450 normal rhesus macaques from the publicly available PRIMatE Data Exchange (PRIME-DE) dataset with lower mean absolute error (MAE) and mean square error (MSE) as well as higher Pearson's correlation coefficient (PCC) and coefficient of determination (R2) compared to other baseline models. The correlation between the predicted BA and CA reaches as high as 0.82 of our proposed method. Furthermore, our analysis reveals that the functional connections predominantly contributing to the prediction results are situated in the primary motor cortex (M1), visual cortex, area v23 in the posterior cingulate cortex, and dysgranular temporal pole. In summary, our proposed deep learning model provides an effective tool to accurately predict BA of primates (macaque in this study), and lays a solid foundation for future studies of age-related brain diseases in those animal models.

Evaluation of registration-based vs. manual segmentation of rhesus macaque brain MRIs

With increasing numbers of magnetic resonance imaging (MRI) datasets becoming publicly available, researchers and clinicians alike have turned to automated methods of segmentation to enable population-level analyses of these data. Although prior research has evaluated the extent to which automated methods recapitulate "gold standard" manual segmentation methods in the human brain, such an evaluation has not yet been carried out for segmentation of MRIs of the macaque brain. Macaques offer the important opportunity to bridge gaps between microanatomical studies using invasive methods like tract tracing, neural recordings, and high-resolution histology and non-invasive macroanatomical studies using methods like MRI. As such, it is important to evaluate whether automated tools derive data of sufficient quality from macaque MRIs to bridge these gaps. We tested the relationship between automated registration-based segmentation using an open source and actively maintained NHP imaging analysis pipeline (AFNI) and gold standard manual segmentation of 4 structures (2 cortical: anterior cingulate cortex and insula; 2 subcortical: amygdala and caudate) across 37 rhesus macaques (Macaca mulatta). We identified some variability in the strength of correlation between automated and manual segmentations across neural regions and differences in relationships with demographic variables like age and sex between the two techniques.

Processing, evaluating, and understanding FMRI data with afni_proc.py

FMRI data are noisy, complicated to acquire, and typically go through many steps of processing before they are used in a study or clinical practice. Being able to visualize and understand the data from the start through the completion of processing, while being confident that each intermediate step was successful, is challenging. AFNI's afni_proc.py is a tool to create and run a processing pipeline for FMRI data. With its flexible features, afni_proc.py allows users to both control and evaluate their processing at a detailed level. It has been designed to keep users informed about all processing steps: it does not just process the data, but also first outputs a fully commented processing script that the users can read, query, interpret, and refer back to. Having this full provenance is important for being able to understand each step of processing; it also promotes transparency and reproducibility by keeping the record of individual-level processing and modeling specifics in a single, shareable place. Additionally, afni_proc.py creates pipelines that contain several automatic self-checks for potential problems during runtime. The output directory contains a dictionary of relevant quantities that can be programmatically queried for potential issues and a systematic, interactive quality control (QC) HTML. All of these features help users evaluate and understand their data and processing in detail. We describe these and other aspects of afni_proc.py here using a set of task-based and resting-state FMRI example commands.

Metformin decelerates aging clock in male monkeys

In a rigorous 40-month study, we evaluated the geroprotective effects of metformin on adult male cynomolgus monkeys, addressing a gap in primate aging research. The study encompassed a comprehensive suite of physiological, imaging, histological, and molecular evaluations, substantiating metformin's influence on delaying age-related phenotypes at the organismal level. Specifically, we leveraged pan-tissue transcriptomics, DNA methylomics, plasma proteomics, and metabolomics to develop innovative monkey aging clocks and applied these to gauge metformin's effects on aging. The results highlighted a significant slowing of aging indicators, notably a roughly 6-year regression in brain aging. Metformin exerts a substantial neuroprotective effect, preserving brain structure and enhancing cognitive ability. The geroprotective effects on primate neurons were partially mediated by the activation of Nrf2, a transcription factor with anti-oxidative capabilities. Our research pioneers the systemic reduction of multi-dimensional biological age in primates through metformin, paving the way for advancing pharmaceutical strategies against human aging.

Changes in cortical manifold structure following stroke and its relation to behavioral recovery in the male macaque

Stroke, a major cause of disability, disrupts brain function and motor skills. Previous research has mainly focused on reorganization of the motor system post-stroke, but the effects on other brain areas and their influence on recovery is poorly understood. Here, we use functional neuroimaging in a nonhuman primate model (23 male Cynomolgus Macaques), we explore how ischemic stroke affects whole-brain cortical architecture and its relation to spontaneous behavioral recovery. By projecting patterns of cortical functional connectivity onto a low-dimensional manifold space, we find that several regions in both sensorimotor cortex and higher-order transmodal cortex exhibit significant shifts in their manifold embedding from pre- to post-stroke. Furthermore, we observe that changes in default mode and limbic network regions, and not preserved sensorimotor cortical regions, are associated with animal behavioral recovery post-stroke. These results establish the whole-brain functional changes associated with stroke, and suggest an important role for higher-order transmodal cortex in post-stroke outcomes.

Object color knowledge representation occurs in the macaque brain despite the absence of a developed language system

Animals guide their behaviors through internal representations of the world in the brain. We aimed to understand how the macaque brain stores such general world knowledge, focusing on object color knowledge. Three functional magnetic resonance imaging (fMRI) experiments were conducted in macaque monkeys: viewing chromatic and achromatic gratings, viewing grayscale images of their familiar fruits and vegetables (e.g., grayscale strawberry), and viewing true- and false-colored objects (e.g., red strawberry and green strawberry). We observed robust object knowledge representations in the color patches, especially the one located around TEO: the activity patterns could classify grayscale pictures of objects based on their memory color and response patterns in these regions could translate between chromatic grating viewing and grayscale object viewing (e.g., red grating-grayscale images of strawberry), such that classifiers trained by viewing chromatic gratings could successfully classify grayscale object images according to their memory colors. Our results showed direct positive evidence of object color memory in macaque monkeys. These results indicate the perceptually grounded knowledge representation as a conservative memory mechanism and open a new avenue to study this particular (semantic) memory representation with macaque models.

Cross-species single-cell spatial transcriptomic atlases of the cerebellar cortex

The molecular and cellular organization of the primate cerebellum remains poorly characterized. We obtained single-cell spatial transcriptomic atlases of macaque, marmoset, and mouse cerebella and identified primate-specific cell subtypes, including Purkinje cells and molecular-layer interneurons, that show different expression of the glutamate ionotropic receptor Delta type subunit 2 (GRID2) gene. Distinct gene expression profiles were found in anterior, posterior, and vestibular regions in all species, whereas region-selective gene expression was predominantly observed in the granular layer of primates and in the Purkinje layer of mice. Gene expression gradients in the cerebellar cortex matched well with functional connectivity gradients revealed with awake functional magnetic resonance imaging, with more lobule-specific differences between primates and mice than between two primate species. These comprehensive atlases and comparative analyses provide the basis for understanding cerebellar evolution and function.

Prefrontal-Limbic Circuitry Is Associated With Reward Sensitivity in Nonhuman Primates

BACKGROUND

Abnormal reward sensitivity is a risk factor for psychiatric disorders, including eating disorders such as overeating and binge-eating disorder, but the brain structural mechanisms that underlie it are not completely understood. Here, we sought to investigate the relationship between multimodal whole-brain structural features and reward sensitivity in nonhuman primates.

METHODS

Reward sensitivity was evaluated through behavioral economic analysis in which monkeys (adult rhesus macaques; 7 female, 5 male) responded for sweetened condensed milk (10%, 30%, 56%), Gatorade, or water using an operant procedure in which the response requirement increased incrementally across sessions (i.e., fixed ratio 1, 3, 10). Animals were divided into high (n = 6) or low (n = 6) reward sensitivity groups based on essential value for 30% milk. Multimodal magnetic resonance imaging was used to measure gray matter volume and white matter microstructure. Brain structural features were compared between groups, and their correlations with reward sensitivity for various stimuli was investigated.

RESULTS

Animals in the high sensitivity group had greater dorsolateral prefrontal cortex, centromedial amygdaloid complex, and middle cingulate cortex volumes than animals in the low sensitivity group. Furthermore, compared with monkeys in the low sensitivity group, high sensitivity monkeys had lower fractional anisotropy in the left dorsal cingulate bundle connecting the centromedial amygdaloid complex and middle cingulate cortex to the dorsolateral prefrontal cortex, and in the left superior longitudinal fasciculus 1 connecting the middle cingulate cortex to the dorsolateral prefrontal cortex.

CONCLUSIONS

These results suggest that neuroanatomical variation in prefrontal-limbic circuitry is associated with reward sensitivity. These brain structural features may serve as predictive biomarkers for vulnerability to food-based and other reward-related disorders.

Brain structure and activity predicting cognitive maturation in adolescence

Cognitive abilities of primates, including humans, continue to improve through adolescence 1,2. While a range of changes in brain structure and connectivity have been documented 3,4, how they affect neuronal activity that ultimately determines performance of cognitive functions remains unknown. Here, we conducted a multilevel longitudinal study of monkey adolescent neurocognitive development. The developmental trajectory of neural activity in the prefrontal cortex accounted remarkably well for working memory improvements. While complex aspects of activity changed progressively during adolescence, such as the rotation of stimulus representation in multidimensional neuronal space, which has been implicated in cognitive flexibility, even simpler attributes, such as the baseline firing rate in the period preceding a stimulus appearance had predictive power over behavior. Unexpectedly, decreases in brain volume and thickness, which are widely thought to underlie cognitive changes in humans 5 did not predict well the trajectory of neural activity or cognitive performance changes. Whole brain cortical volume in particular, exhibited an increase and reached a local maximum in late adolescence, at a time of rapid behavioral improvement. Maturation of long-distance white matter tracts linking the frontal lobe with areas of the association cortex and subcortical regions best predicted changes in neuronal activity and behavior. Our results provide evidence that optimization of neural activity depending on widely distributed circuitry effects cognitive development in adolescence.

A brain subcortical segmentation tool based on anatomy attentional fusion network for developing macaques

Magnetic Resonance Imaging (MRI) plays a pivotal role in the accurate measurement of brain subcortical structures in macaques, which is crucial for unraveling the complexities of brain structure and function, thereby enhancing our understanding of neurodegenerative diseases and brain development. However, due to significant differences in brain size, structure, and imaging characteristics between humans and macaques, computational tools developed for human neuroimaging studies often encounter obstacles when applied to macaques. In this context, we propose an Anatomy Attentional Fusion Network (AAF-Net), which integrates multimodal MRI data with anatomical constraints in a multi-scale framework to address the challenges posed by the dynamic development, regional heterogeneity, and age-related size variations of the juvenile macaque brain, thus achieving precise subcortical segmentation. Specifically, we generate a Signed Distance Map (SDM) based on the initial rough segmentation of the subcortical region by a network as an anatomical constraint, providing comprehensive information on positions, structures, and morphology. Then we construct AAF-Net to fully fuse the SDM anatomical constraints and multimodal images for refined segmentation. To thoroughly evaluate the performance of our proposed tool, over 700 macaque MRIs from 19 datasets were used in this study. Specifically, we employed two manually labeled longitudinal macaque datasets to develop the tool and complete four-fold cross-validations. Furthermore, we incorporated various external datasets to demonstrate the proposed tool's generalization capabilities and promise in brain development research. We have made this tool available as an open-source resource at https://github.com/TaoZhong11/Macaque_subcortical_segmentation for direct application.

Effects of a 5-HT4 receptor antagonist in the caudate nucleus on the performance of macaques in a delayed reward task

Temporal discounting, in which the recipient of a reward perceives the value of that reward to decrease with delay in its receipt, is associated with impulsivity and psychiatric disorders such as depression. Here, we investigate the role of the serotonin 5-HT4 receptor (5-HT4R) in modulating temporal discounting in the macaque dorsal caudate nucleus (dCDh), the neurons of which have been shown to represent temporally discounted value. We first mapped the 5-HT4R distribution in macaque brains using positron emission tomography (PET) imaging and confirmed dense expression of 5-HT4R in the dCDh. We then examined the effects of a specific 5-HT4R antagonist infused into the dCDh. Blockade of 5-HT4R significantly increased error rates in a goal-directed delayed reward task, indicating an increase in the rate of temporal discounting. This increase was specific to the 5-HT4R blockade because saline controls showed no such effect. The results demonstrate that 5-HT4Rs in the dCDh are involved in reward-evaluation processes, particularly in the context of delay discounting, and suggest that serotonergic transmission via 5-HT4R may be a key component in the neural mechanisms underlying impulsive decisions, potentially contributing to depressive symptoms.

Medial to lateral frontal functional connectivity mapping reveals the organization of cingulate cortex

The functional organization of the frontal lobe is a source of debate, focusing on broad functional subdivisions, large-scale networks, or local refined specificities. Multiple neurocognitive models have tried to explain how functional interactions between cingulate and lateral frontal regions contribute to decision making and cognitive control, but their neuroanatomical bases remain unclear. We provide a detailed description of the functional connectivity between cingulate and lateral frontal regions using resting-state functional MRI in rhesus macaques. The analysis focuses on the functional connectivity of the rostral part of the cingulate sulcus with the lateral frontal cortex. Data-driven and seed-based analysis revealed three clusters within the cingulate sulcus organized along the rostro-caudal axis: the anterior, mid, and posterior clusters display increased functional connectivity with, respectively, the anterior lateral prefrontal regions, face-eye lateral frontal motor cortical areas, and hand lateral frontal motor cortex. The location of these clusters can be predicted in individual subjects based on morphological landmarks. These results suggest that the anterior cluster corresponds to the anterior cingulate cortex, whereas the posterior clusters correspond to the face-eye and hand cingulate motor areas within the anterior midcingulate cortex. These data provide a comprehensive framework to identify cingulate subregions based on functional connectivity and local organization.

A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth, and interactive QC with afni_proc.py and more

Quality control (QC) assessment is a vital part of FMRI processing and analysis, and a typically underdiscussed aspect of reproducibility. This includes checking datasets at their very earliest stages (acquisition and conversion) through their processing steps (e.g., alignment and motion correction) to regression modeling (correct stimuli, no collinearity, valid fits, enough degrees of freedom, etc.) for each subject. There are a wide variety of features to verify throughout any single-subject processing pipeline, both quantitatively and qualitatively. We present several FMRI preprocessing QC features available in the AFNI toolbox, many of which are automatically generated by the pipeline-creation tool, afni_proc.py. These items include a modular HTML document that covers full single-subject processing from the raw data through statistical modeling, several review scripts in the results directory of processed data, and command line tools for identifying subjects with one or more quantitative properties across a group (such as triaging warnings, making exclusion criteria, or creating informational tables). The HTML itself contains several buttons that efficiently facilitate interactive investigations into the data, when deeper checks are needed beyond the systematic images. The pages are linkable, so that users can evaluate individual items across a group, for increased sensitivity to differences (e.g., in alignment or regression modeling images). Finally, the QC document contains rating buttons for each "QC block," as well as comment fields for each, to facilitate both saving and sharing the evaluations. This increases the specificity of QC, as well as its shareability, as these files can be shared with others and potentially uploaded into repositories, promoting transparency and open science. We describe the features and applications of these QC tools for FMRI.

A semi-automated pipeline for finite element modeling of electric field induced in nonhuman primates by transcranial magnetic stimulation

BACKGROUND

Transcranial magnetic stimulation (TMS) is used to treat a range of brain disorders by inducing an electric field (E-field) in the brain. However, the precise neural effects of TMS are not well understood. Nonhuman primates (NHPs) are used to model the impact of TMS on neural activity, but a systematic method of quantifying the induced E-field in the cortex of NHPs has not been developed.

NEW METHOD

The pipeline uses statistical parametric mapping (SPM) to automatically segment a structural MRI image of a rhesus macaque into five tissue compartments. Manual corrections are necessary around implants. The segmented tissues are tessellated into 3D meshes used in finite element method (FEM) software to compute the TMS induced E-field in the brain. The gray matter can be further segmented into cortical laminae using a volume preserving method for defining layers.

RESULTS

Models of three NHPs were generated with TMS coils placed over the precentral gyrus. Two coil configurations, active and sham, were simulated and compared. The results demonstrated a large difference in E-fields at the target. Additionally, the simulations were calculated using two different E-field solvers and were found to not significantly differ.

COMPARISON WITH EXISTING METHODS

Current methods segment NHP tissues manually or use automated methods for only the brain tissue. Existing methods also do not stratify the gray matter into layers.

CONCLUSION

The pipeline calculates the induced E-field in NHP models by TMS and can be used to plan implant surgeries and determine approximate E-field values around neuron recording sites.

Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

DeepSeg: A transfer-learning segmentation tool for limited sample training of nonhuman primate MRI

Tissue segmentation of individual magnetic resonance imaging (MRI) is a fundamental step in building accurate head models for brain stimulation. In nonhuman primates (NHPs), due to limited sample size, site variability, and sub-optimal image quality, it is challenging to automate the tissue segmentation process. To overcome these challenges, we leveraged a recent transfer-learning framework for brain extraction and developed an automatic segmentation tool, DeepSeg, a U-Net model for NHP MRI data. We trained two DeepSeg models - a brain tissue model and a full head model - in a relatively large human dataset and then transferred them to limited macaque samples. We demonstrated that both full head and brain tissue models achieved good segmentation performance on the macaque test samples from the same training sites and also showed promising results on multi-site data (Dice coefficient mean±standard deviation for full-head within-site test sample: 0.88 ± 0.08; full-head out-of-site test sample: 0.72 ± 0.17). We further showed that the transferred brain tissue model outperformed a traditional template-driven approach, the prior-based ANTs segmentation (Dice coefficient mean±standard deviation for white matter: 0.90 ± 0.04 vs. 0.85 ± 0.03; gray matter: 0.82±0.07 vs. 0.81±0.04). We then discussed possible solutions to improve model generalizability. Overall, despite limited training samples, our preliminary results demonstrate that DeepSeg is a promising segmentation tool for NHP MRI data.

Deep brain stimulation induces white matter remodeling and functional changes to brain-wide networks

Deep brain stimulation (DBS) is an emerging therapeutic option for treatment resistant neurological and psychiatric disorders, most notably depression. Despite this, little is known about the anatomical and functional mechanisms that underlie this therapy. Here we targeted stimulation to the white matter adjacent to the subcallosal anterior cingulate cortex (SCC-DBS) in macaques, modeling the location in the brain proven effective for depression. We demonstrate that SCC-DBS has a selective effect on white matter macro- and micro-structure in the cingulum bundle distant to where stimulation was delivered. SCC-DBS also decreased functional connectivity between subcallosal and posterior cingulate cortex, two areas linked by the cingulum bundle and implicated in depression. Our data reveal that white matter remodeling as well as functional effects contribute to DBS's therapeutic efficacy.

A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth and interactive QC with afni_proc.py and more

Quality control (QC) assessment is a vital part of FMRI processing and analysis, and a typically under-discussed aspect of reproducibility. This includes checking datasets at their very earliest stages (acquisition and conversion) through their processing steps (e.g., alignment and motion correction) to regression modeling (correct stimuli, no collinearity, valid fits, enough degrees of freedom, etc.) for each subject. There are a wide variety of features to verify throughout any single subject processing pipeline, both quantitatively and qualitatively. We present several FMRI preprocessing QC features available in the AFNI toolbox, many of which are automatically generated by the pipeline-creation tool, afni_proc.py. These items include: a modular HTML document that covers full single subject processing from the raw data through statistical modeling; several review scripts in the results directory of processed data; and command line tools for identifying subjects with one or more quantitative properties across a group (such as triaging warnings, making exclusion criteria or creating informational tables). The HTML itself contains several buttons that efficiently facilitate interactive investigations into the data, when deeper checks are needed beyond the systematic images. The pages are linkable, so that users can evaluate individual items across a group, for increased sensitivity to differences (e.g., in alignment or regression modeling images). Finally, the QC document contains rating buttons for each "QC block", as well as comment fields for each, to facilitate both saving and sharing the evaluations. This increases the specificity of QC, as well as its shareability, as these files can be shared with others and potentially uploaded into repositories, promoting transparency and open science. We describe the features and applications of these QC tools for FMRI.

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

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

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.

Evolutionarily conserved neural responses to affective touch in monkeys transcend consciousness and change with age

Affective touch-a slow, gentle, and pleasant form of touch-activates a different neural network than which is activated during discriminative touch in humans. Affective touch perception is enabled by specialized low-threshold mechanoreceptors in the skin with unmyelinated fibers called C tactile (CT) afferents. These CT afferents are conserved across mammalian species, including macaque monkeys. However, it is unknown whether the neural representation of affective touch is the same across species and whether affective touch's capacity to activate the hubs of the brain that compute socioaffective information requires conscious perception. Here, we used functional MRI to assess the preferential activation of neural hubs by slow (affective) vs. fast (discriminative) touch in anesthetized rhesus monkeys (Macaca mulatta). The insula, anterior cingulate cortex (ACC), amygdala, and secondary somatosensory cortex were all significantly more active during slow touch relative to fast touch, suggesting homologous activation of the interoceptive-allostatic network across primate species during affective touch. Further, we found that neural responses to affective vs. discriminative touch in the insula and ACC (the primary cortical hubs for interoceptive processing) changed significantly with age. Insula and ACC in younger animals differentiated between slow and fast touch, while activity was comparable between conditions for aged monkeys (equivalent to >70 y in humans). These results, together with prior studies establishing conserved peripheral nervous system mechanisms of affective touch transduction, suggest that neural responses to affective touch are evolutionarily conserved in monkeys, significantly impacted in old age, and do not necessitate conscious experience of touch.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications in anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g. thalamic subregions, etc.) derived from high-resolution Mean Apparent Propagator-MRI, T2W, and magnetization transfer ratio images ex vivo. We then confirmed the location and borders of these segmented regions in the MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within Analysis of Functional NeuroImages software. Tracing and validating these important deep brain structures in 3D will improve neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, functional MRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

Differential functional organization of amygdala-medial prefrontal cortex networks in macaque and human

Over the course of evolution, the amygdala (AMG) and medial frontal cortex (mPFC) network, involved in behavioral adaptation, underwent structural changes in the old-world monkey and human lineages. Yet, whether and how the functional organization of this network differs remains poorly understood. Using resting-state functional magnetic resonance imagery, we show that the functional connectivity (FC) between AMG nuclei and mPFC regions differs between humans and awake macaques. In humans, the AMG-mPFC FC displays U-shaped pattern along the corpus callosum: a positive FC with the ventromedial prefrontal (vmPFC) and anterior cingulate cortex (ACC), a negative FC with the anterior mid-cingulate cortex (MCC), and a positive FC with the posterior MCC. Conversely, in macaques, the negative FC shifted more ventrally at the junction between the vmPFC and the ACC. The functional organization divergence of AMG-mPFC network between humans and macaques might help understanding behavioral adaptation abilities differences in their respective socio-ecological niches.

Spontaneous Behavioural Recovery Following Stroke Relates to the Integrity of Parietal and Temporal Regions

Stroke is a devastating disease that results in neurological deficits and represents a leading cause of death and disability worldwide. Following a stroke, there is a degree of spontaneous recovery of function, the neural basis of which is of great interest among clinicians in their efforts to reduce disability following stroke and enhance rehabilitation. Conventionally, work on spontaneous recovery has tended to focus on the neural reorganization of motor cortical regions, with comparably little attention being paid to changes in non-motor regions and how these relate to recovery. Here we show, using structural neuroimaging in a macaque stroke model (N = 31) and by exploiting individual differences in spontaneous behavioural recovery, that the preservation of regions in the parietal and temporal cortices predict animal recovery. To characterize recovery, we performed a clustering analysis using Non-Human Primate Stroke Scale (NHPSS) scores and identified a good versus poor recovery group. By comparing the preservation of brain volumes in the two groups, we found that brain areas in integrity of brain areas in parietal, temporal and somatosensory cortex were associated with better recovery. In addition, a decoding approach performed across all subjects revealed that the preservation of specific brain regions in the parietal, somatosensory and medial frontal cortex predicted recovery. Together, these findings highlight the importance of parietal and temporal regions in spontaneous behavioural recovery.

The neural origin for asymmetric coding of surface color in the primate visual cortex

The coding privilege of end-spectral hues (red and blue) in the early visual cortex has been reported in primates. However, the origin of such bias remains unclear. Here, we provide a complete picture of the end-spectral bias in visual system by measuring fMRI signals and spiking activities in macaques. The correlated end-spectral biases between the LGN and V1 suggest a subcortical source for asymmetric coding. Along the ventral pathway from V1 to V4, red bias against green peaked in V1 and then declined, whereas blue bias against yellow showed an increasing trend. The feedforward and recurrent modifications of end-spectral bias were further revealed by dynamic causal modeling analysis. Moreover, we found that the strongest end-spectral bias in V1 was in layer 4C[Formula: see text]. Our results suggest that end-spectral bias already exists in the LGN and is transmitted to V1 mainly through the parvocellular pathway, then embellished by cortical processing.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications for anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g., thalamic subregions, etc.) derived from the high-resolution MAP-MRI, T2W, and MTR images ex vivo. We then confirmed the location and borders of these segmented regions in MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within AFNI. Tracing and validating these important deep brain structures in 3D improves neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, fMRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

[Whole-brain parcellation for macaque brain magnetic resonance images based on attention mechanism and multi-modality feature fusion]

OBJECTIVE

We propose a novel deep learning algorithm based on attention mechanism and multimodality feature fusion (DDAM) to achieve whole-brain parcellation of macaque brain magnetic resonance (MR) images.

METHODS

We collected multimodality brain MR images of 68 macaques (aged 13 to 36 months) with corresponding ground truth labels. To address the complexity and complementary nature of the multimodality data, we employed a multi- encoder structure to adapt to different modalities and performed feature extraction. In the decoder, an attention mechanism was introduced to construct the Attention-based Multimodality Feature Fusion module (AMFF). Leveraging the rich and complementary information between modalities, AMFF effectively integrated multimodality features of varying scales and complexities to enhance the performance of parcellation. We conducted ablation experiments and statistically analyzed the results.

RESULTS

The incorporation of the multi- encoder structure and attention mechanism significantly improved the performance of the network for integrating the multimodality features, and achieved an average DSC of 0.904 and an ASD as low as 0.131 for macaque whole-brain parcellation (P < 0.05). The ablation experiments validated the effectiveness of each component of the DDAM method.

CONCLUSION

The proposed DDAM method, with its enhanced ability to extract and integrate multimodality features, can significantly improve the accuracy of whole-brain MR image segmentation.

Neural Integration of Audiovisual Sensory Inputs in Macaque Amygdala and Adjacent Regions

Integrating multisensory inputs to generate accurate perception and guide behavior is among the most critical functions of the brain. Subcortical regions such as the amygdala are involved in sensory processing including vision and audition, yet their roles in multisensory integration remain unclear. In this study, we systematically investigated the function of neurons in the amygdala and adjacent regions in integrating audiovisual sensory inputs using a semi-chronic multi-electrode array and multiple combinations of audiovisual stimuli. From a sample of 332 neurons, we showed the diverse response patterns to audiovisual stimuli and the neural characteristics of bimodal over unimodal modulation, which could be classified into four types with differentiated regional origins. Using the hierarchical clustering method, neurons were further clustered into five groups and associated with different integrating functions and sub-regions. Finally, regions distinguishing congruent and incongruent bimodal sensory inputs were identified. Overall, visual processing dominates audiovisual integration in the amygdala and adjacent regions. Our findings shed new light on the neural mechanisms of multisensory integration in the primate brain.