Arm movements induced by noninvasive optogenetic stimulation of the motor cortex in the common marmoset

Deciphering social traits and pathophysiological conditions from natural behaviors in common marmosets

Nonhuman primates (NHPs) are indispensable animal models by virtue of the continuity of behavioral repertoires across primates, including humans. However, behavioral assessment at the laboratory level has so far been limited. Employing the application of three-dimensional (3D) pose estimation and the optimal integration of subsequent analytic methodologies, we demonstrate that our artificial intelligence (AI)-based approach has successfully deciphered the ethological, cognitive, and pathological traits of common marmosets from their natural behaviors. By applying multiple deep neural networks trained with large-scale datasets, we established an evaluation system that could reconstruct and estimate the 3D poses of the marmosets, a small NHP that is suitable for analyzing complex natural behaviors in laboratory setups. We further developed downstream analytic methodologies to quantify a variety of behavioral parameters beyond motion kinematics. We revealed the distinct parental roles of male and female marmosets through automated detections of food-sharing behaviors using a spatial-temporal filter on 3D poses. Employing a recurrent neural network to analyze 3D pose time series data during social interactions, we additionally discovered that marmosets adjusted their behaviors based on others' internal state, which is not directly observable but can be inferred from the sequence of others' actions. Moreover, a fully unsupervised approach enabled us to detect progressively appearing symptomatic behaviors over a year in a Parkinson's disease model. The high-throughput and versatile nature of an AI-driven approach to analyze natural behaviors will open a new avenue for neuroscience research dealing with big-data analyses of social and pathophysiological behaviors in NHPs.

Acute Neuropixels Recordings in the Marmoset Monkey

High-density linear probes, such as Neuropixels, provide an unprecedented opportunity to understand how neural populations within specific laminar compartments contribute to behavior. Marmoset monkeys, unlike macaque monkeys, have a lissencephalic (smooth) cortex that enables recording perpendicular to the cortical surface, thus making them an ideal animal model for studying laminar computations. Here we present a method for acute Neuropixels recordings in the common marmoset (Callithrix jacchus). The approach replaces the native dura with an artificial silicon-based dura that grants visual access to the cortical surface, which is helpful in avoiding blood vessels, ensures perpendicular penetrations, and could be used in conjunction with optical imaging or optogenetic techniques. The chamber housing the artificial dura is simple to maintain with minimal risk of infection and could be combined with semichronic microdrives and wireless recording hardware. This technique enables repeated acute penetrations over a period of several months. With occasional removal of tissue growth on the pial surface, recordings can be performed for a year or more. The approach is fully compatible with Neuropixels probes, enabling the recording of hundreds of single neurons distributed throughout the cortical column.

Development of an assessment method for freely moving nonhuman primates' eating behavior using manual and deep learning analysis

Purpose

Although eating is imperative for survival, few comprehensive methods have been developed to assess freely moving nonhuman primates' eating behavior. In the current study, we distinguished eating behavior into appetitive and consummatory phases and developed nine indices to study them using manual and deep learning-based (DeepLabCut) techniques.

Method

The indices were utilized to three rhesus macaques by different palatability and hunger levels to validate their utility. To execute the experiment, we designed the eating behavior cage and manufactured the artificial food. The total number of trials was 3, with 1 trial conducted using natural food and 2 trials using artificial food.

Result

As a result, the indices of highest utility for hunger effect were approach frequency and consummatory duration. Appetitive composite score and consummatory duration showed the highest utility for palatability effect. To elucidate the effects of hunger and palatability, we developed 2D visualization plots based on manual indices. These 2D visualization methods could intuitively depict the palatability perception and hunger internal state. Furthermore, the developed deep learning-based analysis proved accurate and comparable with manual analysis. When comparing the time required for analysis, deep learning-based analysis was 24-times faster than manual analysis. Moreover, temporal and spatial dynamics were visualized via manual and deep learning-based analysis. Based on temporal dynamics analysis, the patterns were classified into four categories: early decline, steady decline, mid-peak with early incline, and late decline. Heatmap of spatial dynamics and trajectory-related visualization could elucidate a consumption posture and a higher spatial occupancy of food zone in hunger and with palatable food.

Discussion

Collectively, this study describes a newly developed and validated multi-phase method for assessing freely moving nonhuman primate eating behavior using manual and deep learning-based analyses. These effective tools will prove valuable in food reward (palatability effect) and homeostasis (hunger effect) research.

Change detection in the primate auditory cortex through feedback of prediction error signals

Although cortical feedback signals are essential for modulating feedforward processing, no feedback error signal across hierarchical cortical areas has been reported. Here, we observed such a signal in the auditory cortex of awake common marmoset during an oddball paradigm to induce auditory duration mismatch negativity. Prediction errors to a deviant tone presentation were generated as offset calcium responses of layer 2/3 neurons in the rostral parabelt (RPB) of higher-order auditory cortex, while responses to non-deviant tones were strongly suppressed. Within several hundred milliseconds, the error signals propagated broadly into layer 1 of the primary auditory cortex (A1) and accumulated locally on top of incoming auditory signals. Blockade of RPB activity prevented deviance detection in A1. Optogenetic activation of RPB following tone presentation nonlinearly enhanced A1 tone response. Thus, the feedback error signal is critical for automatic detection of unpredicted stimuli in physiological auditory processing and may serve as backpropagation-like learning.

Favoring the cognitive-motor process in the closed-loop of BCI mediated post stroke motor function recovery: challenges and approaches

The brain-computer interface (BCI)-mediated rehabilitation is emerging as a solution to restore motor skills in paretic patients after stroke. In the human brain, cortical motor neurons not only fire when actions are carried out but are also activated in a wired manner through many cognitive processes related to movement such as imagining, perceiving, and observing the actions. Moreover, the recruitment of motor cortexes can usually be regulated by environmental conditions, forming a closed-loop through neurofeedback. However, this cognitive-motor control loop is often interrupted by the impairment of stroke. The requirement to bridge the stroke-induced gap in the motor control loop is promoting the evolution of the BCI-based motor rehabilitation system and, notably posing many challenges regarding the disease-specific process of post stroke motor function recovery. This review aimed to map the current literature surrounding the new progress in BCI-mediated post stroke motor function recovery involved with cognitive aspect, particularly in how it refired and rewired the neural circuit of motor control through motor learning along with the BCI-centric closed-loop.

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.

Timing is Everything: Stochastic Optogenetic Stimulation Reduces Adaptation in Retinal Ganglion Cells

Optogenetics gives us unprecedented power to investigate brain connectivity. The ability to activate neural circuits with single cell resolution and its ease of application has provided a wealth of knowledge in brain function. More recently, optogenetics has shown tremendous utility in prosthetics applications, including vision restoration for patients with retinitis pigmentosa. One of the disadvantages of optogenetics, however, is its poor temporal bandwidth, i.e. the cell's inability to fire at a rate that matches the optical stimulation rate at high frequencies (>30 Hz). This research proposes a new strategy to overcome the temporal limits of optogenetic stimulation. Using whole-cell current clamp recordings in mouse retinal ganglion cells expressing channelrhodopsin-2 (H134R variant), we observed that randomizing inter-pulse intervals can significantly increase a retinal ganglion cell's temporal response to high frequency stimulation.Clinical Relevance- A significant disadvantage of optogenetic stimulation is its poor temporal dynamics which prohibit its widespread use in retinal prosthetics. We have shown that randomizing the interval between stimulation pulses reduces adaptation in retinal ganglion cells. This stimulation strategy may contribute to new levels of functional restoration in therapeutics which incorporate optogenetics.

Behavioral optogenetics in nonhuman primates; a psychological perspective

Optogenetics has been a promising and developing technology in systems neuroscience throughout the past decade. It has been difficult though to reliably establish the potential behavioral effects of optogenetic perturbation of the neural activity in nonhuman primates. This poses a challenge on the future of optogenetics in humans as the concepts and technology need to be developed in nonhuman primates first. Here, I briefly summarize the viable approaches taken to improve nonhuman primate behavioral optogenetics, then focus on one approach: improvements in the measurement of behavior. I bring examples from visual behavior and show how the choice of method of measurement might conceal large behavioral effects. I will then discuss the "cortical perturbation detection" task in detail as an example of a sensitive task that can record the behavioral effects of optogenetic cortical stimulation with high fidelity. Finally, encouraged by the rich scientific landscape ahead of behavioral optogenetics, I invite technology developers to improve the chronically implantable devices designed for simultaneous neural recording and optogenetic intervention in nonhuman primates.

Optogenetics in primate cortical networks

The implementation of optogenetics in studies on non-human primates has generally proven quite difficult, but recent successes have paved the way for its rapid increase. Limitations in the genetic tractability in primates, have been somewhat overcome by implementing tailored vectors and promoters to maximize expression and specificity in primates. More recently, implantable devices, including microLED arrays, have made it possible to deliver light deeper into brain tissue, allowing targeting of deeper structures. However, the greatest limitation in applying optogenetics to the primate brain is the complex connections that exist within many neural circuits. In the past, relatively cruder methods such as cooling or pharmacological blockade have been used to examine neural circuit functions, though their limitations were well recognized. In some ways, similar shortcomings remain for optogenetics, with the ability to target a single component of complex neural circuits being the greatest challenge in applying optogenetics to systems neuroscience in primate brains. Despite this, some recent approaches combining Cre-expressing and Cre-dependent vectors have overcome some of these limitations. Here we suggest that optogenetics provides its greatest advantage to systems neuroscientists when applied as a specific tool to complement the techniques of the past, rather than necessarily replacing them.

Effects of motor cortex neuromodulation on the specificity of corticospinal tract spinal axon outgrowth and targeting in rats

BACKGROUND

Neural activity helps construct neural circuits during development and this function is leveraged by neuromodulation protocols to promote connectivity and repair in maturity. Neuromodulation targeting the motor cortex (MCX) strengthens connections for evoking muscle contraction (MEPs). Mechanisms include promoting local MCX and corticospinal tract (CST) synaptic efficacy and also axon terminal structural changes.

OBJECTIVE

In this study, we address the question of potential causality between neuronal activation and the neuronal structural response.

METHODS

We used patterned optogenetic activation (ChR2-EYFP), daily for 10-days, to deliver intermittent theta burst stimulation (iTBS) to activate MCX neurons within the forelimb representation in healthy rats, while differentiating them from neurons in the same population that were not activated. We used chemogenetic DREADD activation to produce a daily period of non-patterned neuronal activation.

RESULTS

We found a significant increase in CST axon length, axon branching, contacts targeted to a class of premotor interneuron (Chx10), as well as projections into the motor pools in the ventral horn in optically activated but not neighboring non-activated neurons. A period of 2-h of continuous activation daily for 10 days using DREADD chemogenetic activation with systemic clozapine N-oxide (CNO) administration also increased CST axon length and branching, but not the ventral horn and Chx10 targeting effects. Both patterned optical and chemogenetic activation reduced MCX MEP thresholds.

CONCLUSION

Our findings show that targeting of CST axon sprouting is dependent on patterned activation, but that CST spinal axon outgrowth and branching are not. Our optogenetic findings, by distinguishing optically activated and non-activated CST axons, suggests that the switch for activity-dependent axonal outgrowth is neuron-intrinsic.

Evaluation of mouse behavioral responses to nutritive versus nonnutritive sugar using a deep learning-based 3D real-time pose estimation system

Animals are able to detect the nutritional content of sugar independently of taste. When given a choice between nutritive sugar and nonnutritive sugar, animals develop a preference for nutritive sugar over nonnutritive sugar during a period of food deprivation (Buchanan et al., 2022; Dus et al., 2011; 2015; Tan et al., 2020; Tellez et al., 2016). To quantify behavioral features during an episode of licking nutritive versus nonnutritive sugar, we implemented a multi-vision, deep learning-based 3D pose estimation system, termed the AI Vision Analysis for Three-dimensional Action in Real-Time (AVATAR)(Kim et al., 2022). Using this method, we found that mice exhibit significantly different approach behavioral responses toward nutritive sugar versus nonnutritive sugar even before licking a sugar solution. Notably, the behavioral sequences during the approach toward nutritive versus nonnutritive sugar became significantly different over time. These results suggest that the nutritional value of sugar not only promotes its consumption but also elicits distinct repertoires of feeding behavior in deprived mice.

Multi-area recordings and optogenetics in the awake, behaving marmoset

The common marmoset has emerged as a key model in neuroscience. Marmosets are small in size, show great potential for genetic modification and exhibit complex behaviors. Thus, it is necessary to develop technology that enables monitoring and manipulation of the underlying neural circuits. Here, we describe a novel approach to record and optogenetically manipulate neural activity in awake, behaving marmosets. Our design utilizes a light-weight, 3D printed titanium chamber that can house several high-density silicon probes for semi-chronic recordings, while enabling simultaneous optogenetic stimulation. We demonstrate the application of our method in male marmosets by recording multi- and single-unit data from areas V1 and V6 with 192 channels simultaneously, and show that optogenetic activation of excitatory neurons in area V6 can influence behavior in a detection task. This method may enable future studies to investigate the neural basis of perception and behavior in the marmoset.

Acclimatizing and training freely viewing marmosets for behavioral and electrophysiological experiments in oculomotor tasks

The marmoset is a small-bodied primate with behavioral capacities and brain structures comparable to macaque monkeys and humans. Its amenability to modern biotechnological techniques like optogenetics, chemogenetics, and generation of transgenic primates have attracted neuroscientists' attention to use it as a model in neuroscience. In the past decade, several laboratories have been developing and refining tools and techniques for performing behavioral and electrophysiological experiments in this new model. In this regard, we developed a protocol to acclimate the marmoset to sit calmly in a primate chair; a method to calibrate the eye-tracking system while marmosets were freely viewing the screen; and a procedure to map motor field of neurons in the SC in freely viewing marmosets. Using a squeeze-walled transfer box, the animals were acclimatized, and chair trained in less than 4 weeks, much shorter than what other studies reported. Using salient stimuli allowed quick and accurate calibration of the eye-tracking system in untrained freely viewing marmosets. Applying reverse correlation to spiking activity and saccadic eye movements, we were able to map motor field of SC neurons in freely viewing marmosets. These refinements shortened the acclimation period, most likely reduced stress to the subjects, and allowed more efficient eye calibration and motor field mapping in freely viewing marmosets. With a penetration angle of 38 degrees, all 16 channels of the electrode array, that is, all recorded neurons across SC layers, had overlapping visual receptive and motor fields, indicating perpendicular penetration to the SC.

Using deep learning to study emotional behavior in rodent models

Quantifying emotional aspects of animal behavior (e.g., anxiety, social interactions, reward, and stress responses) is a major focus of neuroscience research. Because manual scoring of emotion-related behaviors is time-consuming and subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones of an apparatus (e.g., open vs. closed arms of an elevated plus maze). Recent advancements have made it easier to extract pose information from videos, and multiple approaches for extracting nuanced information about behavioral states from pose estimation data have been proposed. These include supervised, unsupervised, and self-supervised approaches, employing a variety of different model types. Representations of behavioral states derived from these methods can be correlated with recordings of neural activity to increase the scope of connections that can be drawn between the brain and behavior. In this mini review, we will discuss how deep learning techniques can be used in behavioral experiments and how different model architectures and training paradigms influence the type of representation that can be obtained.

Modelling behaviors relevant to brain disorders in the nonhuman primate: Are we there yet?

Recent years have seen a profound resurgence of activity with nonhuman primates (NHPs) to model human brain disorders. From marmosets to macaques, the study of NHP species offers a unique window into the function of primate-specific neural circuits that are impossible to examine in other models. Examining how these circuits manifest into the complex behaviors of primates, such as advanced cognitive and social functions, has provided enormous insights to date into the mechanisms underlying symptoms of numerous neurological and neuropsychiatric illnesses. With the recent optimization of modern techniques to manipulate and measure neural activity in vivo, such as optogenetics and calcium imaging, NHP research is more well-equipped than ever to probe the neural mechanisms underlying pathological behavior. However, methods for behavioral experimentation and analysis in NHPs have noticeably failed to keep pace with these advances. As behavior ultimately lies at the junction between preclinical findings and its translation to clinical outcomes for brain disorders, approaches to improve the integrity, reproducibility, and translatability of behavioral experiments in NHPs requires critical evaluation. In this review, we provide a unifying account of existing brain disorder models using NHPs, and provide insights into the present and emerging contributions of behavioral studies to the field.

Marmosets: a promising model for probing the neural mechanisms underlying complex visual networks such as the frontal-parietal network

The technology, methodology and models used by visual neuroscientists have provided great insights into the structure and function of individual brain areas. However, complex cognitive functions arise in the brain due to networks comprising multiple interacting cortical areas that are wired together with precise anatomical connections. A prime example of this phenomenon is the frontal–parietal network and two key regions within it: the frontal eye fields (FEF) and lateral intraparietal area (area LIP). Activity in these cortical areas has independently been tied to oculomotor control, motor preparation, visual attention and decision-making. Strong, bidirectional anatomical connections have also been traced between FEF and area LIP, suggesting that the aforementioned visual functions depend on these inter-area interactions. However, advancements in our knowledge about the interactions between area LIP and FEF are limited with the main animal model, the rhesus macaque, because these key regions are buried in the sulci of the brain. In this review, we propose that the common marmoset is the ideal model for investigating how anatomical connections give rise to functionally-complex cognitive visual behaviours, such as those modulated by the frontal–parietal network, because of the homology of their cortical networks with humans and macaques, amenability to transgenic technology, and rich behavioural repertoire. Furthermore, the lissencephalic structure of the marmoset brain enables application of powerful techniques, such as array-based electrophysiology and optogenetics, which are critical to bridge the gaps in our knowledge about structure and function in the brain.

Functional Organization of Frontoparietal Cortex in the Marmoset Investigated with Awake Resting-State fMRI

Frontoparietal networks contribute to complex cognitive functions in humans and macaques, such as working memory, attention, task-switching, response suppression, grasping, reaching, and eye movement control. However, there has been no comprehensive examination of the functional organization of frontoparietal networks using functional magnetic resonance imaging in the New World common marmoset monkey (Callithrix jacchus), which is now widely recognized as a powerful nonhuman primate experimental animal. In this study, we employed hierarchical clustering of interareal blood oxygen level-dependent signals to investigate the hypothesis that the organization of the frontoparietal cortex in the marmoset follows the organizational principles of the macaque frontoparietal system. We found that the posterior part of the lateral frontal cortex (premotor regions) was functionally connected to the anterior parietal areas, while more anterior frontal regions (frontal eye field [FEF]) were connected to more posterior parietal areas (the region around the lateral intraparietal area [LIP]). These overarching patterns of interareal organization are consistent with a recent macaque study. These findings demonstrate parallel frontoparietal processing streams in marmosets and support the functional similarities of FEF-LIP and premotor-anterior parietal pathways between marmoset and macaque.

Functional visualization and manipulation in the marmoset brain using viral vectors

The common marmoset, a New World monkey, has a primate-specific cortex with approximately 40 Brodmann areas. Genetically encoded calcium indicator (GECI) techniques have been applied to study the functional organization of the marmoset cortex. The success of GCaMP (a green fluorescent of GECI) imaging and other advances, including optogenetic approaches, provide an interesting and exciting opportunity to study the primate brain at the molecular and cellular levels, leading to an understanding of primate neural circuits. These approaches will help advance our knowledge on cognition in primates, including humans, and therapy for human neurological and psychiatric disorders.

Afferent Connections of Cytoarchitectural Area 6M and Surrounding Cortex in the Marmoset: Putative Homologues of the Supplementary and Pre-supplementary Motor Areas

Cortical projections to the caudomedial frontal cortex were studied using retrograde tracers in marmosets. We tested the hypothesis that cytoarchitectural area 6M includes homologues of the supplementary and pre-supplementary motor areas (SMA and pre-SMA) of other primates. We found that, irrespective of the injection sites' location within 6M, over half of the labeled neurons were located in motor and premotor areas. Other connections originated in prefrontal area 8b, ventral anterior and posterior cingulate areas, somatosensory areas (3a and 1-2), and areas on the rostral aspect of the dorsal posterior parietal cortex. Although the origin of afferents was similar, injections in rostral 6M received higher percentages of prefrontal afferents, and fewer somatosensory afferents, compared to caudal injections, compatible with differentiation into SMA and pre-SMA. Injections rostral to 6M (area 8b) revealed a very different set of connections, with increased emphasis on prefrontal and posterior cingulate afferents, and fewer parietal afferents. The connections of 6M were also quantitatively different from those of the primary motor cortex, dorsal premotor areas, and cingulate motor area 24d. These results show that the cortical motor control circuit is conserved in simian primates, indicating that marmosets can be valuable models for studying movement planning and control.

Measuring and modeling the motor system with machine learning

The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data. The field of movement science already elegantly incorporates theory and engineering principles to guide experimental work, and in this review we discuss the growing use of machine learning: from pose estimation, kinematic analyses, dimensionality reduction, and closed-loop feedback, to its use in understanding neural correlates and untangling sensorimotor systems. We also give our perspective on new avenues, where markerless motion capture combined with biomechanical modeling and neural networks could be a new platform for hypothesis-driven research.

Visual Neuroscience Methods for Marmosets: Efficient Receptive Field Mapping and Head-Free Eye Tracking

The marmoset has emerged as a promising primate model system, in particular for visual neuroscience. Many common experimental paradigms rely on head fixation and an extended period of eye fixation during the presentation of salient visual stimuli. Both of these behavioral requirements can be challenging for marmosets. Here, we present two methodological developments, each addressing one of these difficulties. First, we show that it is possible to use a standard eye-tracking system without head fixation to assess visual behavior in the marmoset. Eye-tracking quality from head-free animals is sufficient to obtain precise psychometric functions from a visual acuity task. Second, we introduce a novel method for efficient receptive field (RF) mapping that does not rely on moving stimuli but uses fast flashing annuli and wedges. We present data recorded during head-fixation in areas V1 and V6 and show that RF locations are readily obtained within a short period of recording time. Thus, the methodological advancements presented in this work will contribute to establish the marmoset as a valuable model in neuroscience.

DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection

In general, animal behavior can be described as the neuronal-driven sequence of reoccurring postures through time. Most of the available current technologies focus on offline pose estimation with high spatiotemporal resolution. However, to correlate behavior with neuronal activity it is often necessary to detect and react online to behavioral expressions. Here we present DeepLabStream, a versatile closed-loop tool providing real-time pose estimation to deliver posture dependent stimulations. DeepLabStream has a temporal resolution in the millisecond range, can utilize different input, as well as output devices and can be tailored to multiple experimental designs. We employ DeepLabStream to semi-autonomously run a second-order olfactory conditioning task with freely moving mice and optogenetically label neuronal ensembles active during specific head directions.

An Open Resource for Non-human Primate Optogenetics

Optogenetics has revolutionized neuroscience in small laboratory animals, but its effect on animal models more closely related to humans, such as non-human primates (NHPs), has been mixed. To make evidence-based decisions in primate optogenetics, the scientific community would benefit from a centralized database listing all attempts, successful and unsuccessful, of using optogenetics in the primate brain. We contacted members of the community to ask for their contributions to an open science initiative. As of this writing, 45 laboratories around the world contributed more than 1,000 injection experiments, including precise details regarding their methods and outcomes. Of those entries, more than half had not been published. The resource is free for everyone to consult and contribute to on the Open Science Framework website. Here we review some of the insights from this initial release of the database and discuss methodological considerations to improve the success of optogenetic experiments in NHPs.

Current Status of and Perspectives on the Application of Marmosets in Neurobiology

The common marmoset (Callithrix jacchus), a small New World primate, is receiving substantial attention in the neuroscience and biomedical science fields because its anatomical features, functional and behavioral characteristics, and reproductive features and its amenability to available genetic modification technologies make it an attractive experimental subject. In this review, I outline the progress of marmoset neuroscience research and summarize both the current status (opportunities and limitations) of and the future perspectives on the application of marmosets in neuroscience and disease modeling.

Future Portrait of the Athletic Brain: Mechanistic Understanding of Human Sport Performance Via Animal Neurophysiology of Motor Behavior

Sport performances are often showcases of skilled motor control. Efforts to understand the neural processes subserving such movements may teach us about general principles of behavior, similarly to how studies on neurological patients have guided early work in cognitive neuroscience. While investigations on non-human animal models offer valuable information on the neural dynamics of skilled motor control that is still difficult to obtain from humans, sport sciences have paid relatively little attention to these mechanisms. Similarly, knowledge emerging from the study of sport performance could inspire innovative experiments in animal neurophysiology, but the latter has been only partially applied. Here, we advocate that fostering interactions between these two seemingly distant fields, i.e., animal neurophysiology and sport sciences, may lead to mutual benefits. For instance, recording and manipulating the activity from neurons of behaving animals offer a unique viewpoint on the computations for motor control, with potentially untapped relevance for motor skills development in athletes. To stimulate such transdisciplinary dialog, in the present article, we also discuss steps for the reverse translation of sport sciences findings to animal models and the evaluation of comparability between animal models of a given sport and athletes. In the final section of the article, we envision that some approaches developed for animal neurophysiology could translate to sport sciences anytime soon (e.g., advanced tracking methods) or in the future (e.g., novel brain stimulation techniques) and could be used to monitor and manipulate motor skills, with implications for human performance extending well beyond sport.

Minimally invasive neural stimulation with a novel ultra-sensitive step function opsin: implications and future directions

Optogenetics has become a popular tool to probe the link between neural circuits and behavior, since the technique was first introduced in 2005. Recently, Gong et al. (Gong X, Mendoza-Halliday D, Ting JT, Kaiser T, Sun X, Bastos AM, Wimmer RD, Guo B, Chen Q, Zhou Y, Pruner M, Wu CWH, Park D, Deisseroth K, Barak B, Boyden ES, Miller EK, Halassa MM, Fu Z, Bi G, Desimone R, Feng G. Neuron 107: 38-51, 2020) developed an ultra-sensitive step-function opsin capable of activating any region of the mouse brain and cortical areas in macaques with external illumination, thus aiming toward minimally invasive light delivery. In this article, we highlight and discuss the new opsin's potential in nonhuman primate research.

New era of optogenetics: from the central to peripheral nervous system

Optogenetics has recently gained recognition as a biological technique to control the activity of cells using light stimulation. Many studies have applied optogenetics to cell lines in the central nervous system because it has the potential to elucidate neural circuits, treat neurological diseases and promote nerve regeneration. There have been fewer studies on the application of optogenetics in the peripheral nervous system. This review introduces the basic principles and approaches of optogenetics and summarizes the physiology and mechanism of opsins and how the technology enables bidirectional control of unique cell lines with superior spatial and temporal accuracy. Further, this review explores and discusses the therapeutic potential for the development of optogenetics and its capacity to revolutionize treatment for refractory epilepsy, depression, pain, and other nervous system disorders, with a focus on neural regeneration, especially in the peripheral nervous system. Additionally, this review synthesizes the latest preclinical research on optogenetic stimulation, including studies on non-human primates, summarizes the challenges, and highlights future perspectives. The potential of optogenetic stimulation to optimize therapy for peripheral nerve injuries (PNIs) is also highlighted. Optogenetic technology has already generated exciting, preliminary evidence, supporting its role in applications to several neurological diseases, including PNIs.

Arm movements induced by noninvasive optogenetic stimulation of the motor cortex in the common marmoset

Which brain area drives hand/arm movements after learning or brain injury? When does motor cortical activity generate appropriate hand/arm movements? To address these issues, it is necessary to manipulate motor cortical activity in a controlled manner. Optogenetic tools allow neuronal activity to be manipulated in a variety of animals, but forelimb movements in nonhuman primates have not previously been optogenetically induced or modulated. Here, we improved a method of optogenetic cortical stimulation and induced overt forelimb movements in the common marmoset, a New World monkey. Photostimulation also modulated voluntary forelimb movements, with the modulated movement trajectories depending on the stimulation site and timing. Our results open doors for noninvasive interrogation of motor circuits in behaving nonhuman primates.

Optogenetics is now a fundamental tool for investigating the relationship between neuronal activity and behavior. However, its application to the investigation of motor control systems in nonhuman primates is rather limited, because optogenetic stimulation of cortical neurons in nonhuman primates has failed to induce or modulate any hand/arm movements. Here, we used a tetracycline-inducible gene expression system carrying CaMKII promoter and the gene encoding a Channelrhodopsin-2 variant with fast kinetics in the common marmoset, a small New World monkey. In an awake state, forelimb movements could be induced when Channelrhodopsin-2−expressing neurons in the motor cortex were illuminated by blue laser light with a spot diameter of 1 mm or 2 mm through a cranial window without cortical invasion. Forelimb muscles responded 10 ms to 50 ms after photostimulation onset. Long-duration (500 ms) photostimulation induced discrete forelimb movements that could be markerlessly tracked with charge-coupled device cameras and a deep learning algorithm. Long-duration photostimulation mapping revealed that the primary motor cortex is divided into multiple domains that can induce hand and elbow movements in different directions. During performance of a forelimb movement task, movement trajectories were modulated by weak photostimulation, which did not induce visible forelimb movements at rest, around the onset of task-relevant movement. The modulation was biased toward the movement direction induced by the strong photostimulation. Combined with calcium imaging, all-optical interrogation of motor circuits should be possible in behaving marmosets.