Skilled reaching tasks for head-fixed mice using a robotic manipulandum

Cortico-basal ganglia plasticity in motor learning

One key function of the brain is to control our body's movements, allowing us to interact with the world around us. Yet, many motor behaviors are not innate but require learning through repeated practice. Among the brain's motor regions, the cortico-basal ganglia circuit is particularly crucial for acquiring and executing motor skills, and neuronal activity in these regions is directly linked to movement parameters. Cell-type-specific adaptations of activity patterns and synaptic connectivity support the learning of new motor skills. Functionally, neuronal activity sequences become structured and associated with learned movements. On the synaptic level, specific connections become potentiated during learning through mechanisms such as long-term synaptic plasticity and dendritic spine dynamics, which are thought to mediate functional circuit plasticity. These synaptic and circuit adaptations within the cortico-basal ganglia circuitry are thus critical for motor skill acquisition, and disruptions in this plasticity can contribute to movement disorders.

A cerebellar granule cell-climbing fiber computation to learn to track long time intervals

In classical cerebellar learning, Purkinje cells (PkCs) associate climbing fiber (CF) error signals with predictive granule cells (GrCs) that were active just prior (∼150 ms). The cerebellum also contributes to behaviors characterized by longer timescales. To investigate how GrC-CF-PkC circuits might learn seconds-long predictions, we imaged simultaneous GrC-CF activity over days of forelimb operant conditioning for delayed water reward. As mice learned reward timing, numerous GrCs developed anticipatory activity ramping at different rates until reward delivery, followed by widespread time-locked CF spiking. Relearning longer delays further lengthened GrC activations. We computed CF-dependent GrC→PkC plasticity rules, demonstrating that reward-evoked CF spikes sufficed to grade many GrC synapses by anticipatory timing. We predicted and confirmed that PkCs could thereby continuously ramp across seconds-long intervals from movement to reward. Learning thus leads to new GrC temporal bases linking predictors to remote CF reward signals-a strategy well suited for learning to track the long intervals common in cognitive domains.

Exploration biases forelimb reaching strategies

The brain can generate actions, such as reaching to a target, using different movement strategies. We investigate how such strategies are learned in a task where perched head-fixed mice learn to reach to an invisible target area from a set start position using a joystick. This can be achieved by learning to move in a specific direction or to a specific endpoint location. As mice learn to reach the target, they refine their variable joystick trajectories into controlled reaches, which depend on the sensorimotor cortex. We show that individual mice learned strategies biased to either direction- or endpoint-based movements. This endpoint/direction bias correlates with spatial directional variability with which the workspace was explored during training. Model-free reinforcement learning agents can generate both strategies with similar correlation between variability during training and learning bias. These results provide evidence that reinforcement of individual exploratory behavior during training biases the reaching strategies that mice learn.

Exploration biases how forelimb reaches to a spatial target are learned

The brain can learn to generate actions, such as reaching to a target, using different movement strategies. Understanding how different variables bias which strategies are learned to produce such a reach is important for our understanding of the neural bases of movement. Here we introduce a novel spatial forelimb target task in which perched head-fixed mice learn to reach to a circular target area from a set start position using a joystick. These reaches can be achieved by learning to move into a specific direction or to a specific endpoint location. We find that mice gradually learn to successfully reach the covert target. With time, they refine their initially exploratory complex joystick trajectories into controlled targeted reaches. The execution of these controlled reaches depends on the sensorimotor cortex. Using a probe test with shifting start positions, we show that individual mice learned to use strategies biased to either direction or endpoint-based movements. The degree of endpoint learning bias was correlated with the spatial directional variability with which the workspace was explored early in training. Furthermore, we demonstrate that reinforcement learning model agents exhibit a similar correlation between directional variability during training and learned strategy. These results provide evidence that individual exploratory behavior during training biases the control strategies that mice use to perform forelimb covert target reaches.

Peripersonal encoding of forelimb proprioception in the mouse somatosensory cortex

Conscious perception of limb movements depends on proprioceptive neural responses in the somatosensory cortex. In contrast to tactile sensations, proprioceptive cortical coding is barely studied in the mammalian brain and practically non-existent in rodent research. To understand the cortical representation of this important sensory modality we developed a passive forelimb displacement paradigm in behaving mice and also trained them to perceptually discriminate where their limb is moved in space. We delineated the rodent proprioceptive cortex with wide-field calcium imaging and optogenetic silencing experiments during behavior. Our results reveal that proprioception is represented in both sensory and motor cortical areas. In addition, behavioral measurements and responses of layer 2/3 neurons imaged with two-photon microscopy reveal that passive limb movements are both perceived and encoded in the mouse cortex as a spatial direction vector that interfaces the limb with the body's peripersonal space.

AutoRG: An automatized reach-to-grasp platform technology for assessing forelimb motor function, neural circuit activation, and cognition in rodents

BACKGROUND

Rodent reach-to-grasp function assessment is a translationally powerful model for evaluating neurological function impairments and recovery responses. Existing assessment platforms are experimenter-dependent, costly, or low-throughput with limited output measures. Further, a direct histologic comparison of neural activation has never been conducted between any novel, automated platform and the well-established single pellet skilled reach task (SRT).

NEW METHOD

To address these technological and knowledge gaps, we designed an open-source, low-cost Automatized Reach-to-Grasp (AutoRG) pull platform that reduces experimenter interventions and variability. We assessed reach-to-grasp function in rats across seven progressively difficult stages using AutoRG. We mapped AutoRG and SRT-activated motor circuitries in the rat brain using volumetric imaging of the immediate early gene-encoded Arc (activity-regulated cytoskeleton-associated) protein.

RESULTS

Rats demonstrated robust forelimb reaching and pulling behavior after training in AutoRG. Reliable force versus time responses were recorded for individual reach events in real time, which were used to derive several secondary functional measures of performance. Moreover, we provide the first demonstration that for a training period of 30 min, AutoRG and SRT both engage similar neural responses in the caudal forelimb area (CFA), rostral forelimb area (RFA), and sensorimotor area (S1).

CONCLUSION

AutoRG is the first low-cost, open-source pull system designed for the scale-up of volitional forelimb motor function testing and characterization of rodent reaching behavior. The similarities in neuronal activation patterns observed in the rat motor cortex after SRT and AutoRG assessments validate the AutoRG as a rigorously characterized, scalable alternative to the conventional SRT and expensive commercial systems.

An open-source head-fixation and implant-protection system for mice

Mice are widely used in neuroscience experiments, which often require head-fixation and attachment of skull-mounted hardware. For many experiments, these components must remain intact over weeks to months, ideally with animals group housed. Many labs have designed ad-hoc head-fixation systems, which is an inefficient process. For example, when reinventing these solutions in our lab, we faced challenges with group housing, wherein mice would chew and damage implanted cannulas and electrodes of their cage mates. We performed several non-trivial design iterations to solve this problem, and present the most successful designs as an open-source collection. The designs include a standard mounting headbar compatible with most skull-mounted hardware, a snap-on protective mouse hat (headhat) to prevent mice from chewing the hardware, and a head-fixation station to facilitate common experimental procedures. We provide 3D-printing files, detail vendors and software used to make the components of the system, and provide editable design files for maximum flexibility to individual lab requirements.

A Novel Device of Reaching, Grasping, and Retrieving Task for Head-Fixed Mice

Reaching, grasping, and retrieving movements are essential to our daily lives and are common in many mammalian species. To understand the mechanism for controlling this movement at the neural circuit level, it is necessary to observe the activity of individual neurons involved in the movement. For stable electrophysiological or optical recordings of neural activity in a behaving animal, head fixation effectively minimizes motion artifacts. Here, we developed a new device that allows mice to perform reaching, grasping, and retrieving movements during head fixation. In this method, agar cubes were presented as target objects in front of water-restricted mice, and the mice were able to reach, grasp, and retrieve them with their forelimb. The agar cubes were supplied by a custom-made automatic dispenser, which uses a microcontroller to control the two motors to push out the agar cubes. This agar presentation system supplied approximately 20 agar cubes in consecutive trials. We confirmed that each agar cube could be presented to the mouse with an average weight of 55 ± 3 mg and positional accuracy of less than 1 mm. Using this system, we showed that head-fixed mice could perform reaching, grasping, and retrieving tasks after 1 week of training. When the agar cube was placed near the mice, they could grasp it with a high success rate without extensive training. On the other hand, when the agar cube was presented far from the mice, the success rate was initially low and increased with subsequent test sessions. Furthermore, we showed that activity in the primary motor cortex is required for reaching movements in this task. Therefore, our system can be used to study neural circuit mechanisms for the control and learning of reaching, grasping, and retrieving movements under head-fixed conditions.

Preclinical upper limb neurorobotic platform to assess, rehabilitate, and develop therapies

Numerous neurorehabilitative, neuroprosthetic, and repair interventions aim to address the consequences of upper limb impairments after neurological disorders. Although these therapies target widely different mechanisms, they share the common need for a preclinical platform that supports the development, assessment, and understanding of the therapy. Here, we introduce a neurorobotic platform for rats that meets these requirements. A four-degree-of-freedom end effector is interfaced with the rat's wrist, enabling unassisted to fully assisted execution of natural reaching and retrieval movements covering the entire body workspace. Multimodal recording capabilities permit precise quantification of upper limb movement recovery after spinal cord injury (SCI), which allowed us to uncover adaptations in corticospinal tract neuron dynamics underlying this recovery. Personalized movement assistance supported early neurorehabilitation that improved recovery after SCI. Last, the platform provided a well-controlled and practical environment to develop an implantable spinal cord neuroprosthesis that improved upper limb function after SCI.

Current approaches to characterize micro- and macroscale circuit mechanisms of Parkinson's disease in rodent models

Accelerating technological progress in experimental neuroscience is increasing the scale as well as specificity of both observational and perturbational approaches to study circuit physiology. While these techniques have also been used to study disease mechanisms, a wider adoption of these approaches in the field of experimental neurology would greatly facilitate our understanding of neurological dysfunctions and their potential treatments at cellular and circuit level. In this review, we will introduce classic and novel methods ranging from single-cell electrophysiological recordings to state-of-the-art calcium imaging and cell-type specific optogenetic or chemogenetic stimulation. We will focus on their application in rodent models of Parkinson’s disease while also presenting their use in the context of motor control and basal ganglia function. By highlighting the scope and limitations of each method, we will discuss how they can be used to study pathophysiological mechanisms at local and global circuit levels and how novel frameworks can help to bridge these scales.

The primary motor cortex: the hub of motor learning in rodents

The primary motor cortex, a dynamic center for overall motion control and decision making, undergoes significant alterations upon neural stimulation. Over the last few decades, data from numerous studies using rodent models have improved our understanding of the morphological and functional plasticity of the primary motor cortex. In particular, spatially specific formation of dendritic spines and their maintenance during distinct behaviors is considered crucial for motor learning. However, whether the modifications of specific synapses are associated with motor learning should be studied further. In this review, we summarized the findings of prior studies on the features and dynamics of the primary motor cortex in rodents.

The relationship between birth timing, circuit wiring, and physiological response properties of cerebellar granule cells

Cerebellar granule cells (GrCs) are usually regarded as a uniform cell type that collectively expands the coding space of the cerebellum by integrating diverse combinations of mossy fiber inputs. Accordingly, stable molecularly or physiologically defined GrC subtypes within a single cerebellar region have not been reported. The only known cellular property that distinguishes otherwise homogeneous GrCs is the correspondence between GrC birth timing and the depth of the molecular layer to which their axons project. To determine the role birth timing plays in GrC wiring and function, we developed genetic strategies to access early- and late-born GrCs. We initiated retrograde monosynaptic rabies virus tracing from control (birth timing unrestricted), early-born, and late-born GrCs, revealing the different patterns of mossy fiber input to GrCs in vermis lobule 6 and simplex, as well as to early- and late-born GrCs of vermis lobule 6: sensory and motor nuclei provide more input to early-born GrCs, while basal pontine and cerebellar nuclei provide more input to late-born GrCs. In vivo multidepth two-photon Ca2+ imaging of axons of early- and late-born GrCs revealed representations of diverse task variables and stimuli by both populations, with modest differences in the proportions encoding movement, reward anticipation, and reward consumption. Our results suggest neither organized parallel processing nor completely random organization of mossy fiber→GrC circuitry but instead a moderate influence of birth timing on GrC wiring and encoding. Our imaging data also provide evidence that GrCs can represent generalized responses to aversive stimuli, in addition to recently described reward representations.

A cross-species neural integration of gravity for motor optimization

Recent kinematic results, combined with model simulations, have provided support for the hypothesis that the human brain shapes motor patterns that use gravity effects to minimize muscle effort. Because many different muscular activation patterns can give rise to the same trajectory, here, we specifically investigate gravity-related movement properties by analyzing muscular activation patterns during single-degree-of-freedom arm movements in various directions. Using a well-known decomposition method of tonic and phasic electromyographic activities, we demonstrate that phasic electromyograms (EMGs) present systematic negative phases. This negativity reveals the optimal motor plan's neural signature, where the motor system harvests the mechanical effects of gravity to accelerate downward and decelerate upward movements, thereby saving muscle effort. We compare experimental findings in humans to monkeys, generalizing the Effort-optimization strategy across species.

From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior

Understanding how brain activity encodes information and controls behavior is a long-standing question in neuroscience. This complex problem requires converging efforts from neuroscience and engineering, including technological solutions to perform high-precision and large-scale recordings of neuronal activity in vivo as well as unbiased methods to reliably measure and quantify behavior. Thanks to advances in genetics, molecular biology, engineering, and neuroscience, in recent decades, a variety of optical imaging and electrophysiological approaches for recording neuronal activity in awake animals have been developed and widely applied in the field. Moreover, sophisticated computer vision and machine learning algorithms have been developed to analyze animal behavior. In this review, we provide an overview of the current state of technology for neuronal recordings with a focus on optical and electrophysiological methods in rodents. In addition, we discuss areas that future technological development will need to cover in order to further our understanding of the neural activity underlying behavior.