Distinct Populations of Motor Thalamic Neurons Encode Action Initiation, Action Selection, and Movement Vigor.

Motor thalamus (Mthal) comprises the ventral anterior, ventral lateral, and ventral medial thalamic nuclei in rodents. This subcortical hub receives input from the basal ganglia (BG), cerebellum, and reticular thalamus in addition to connecting reciprocally with motor cortical regions. Despite the central location of Mthal, the mechanisms by which it influences movement remain unclear. To determine its role in generating ballistic, goal-directed movement, we recorded single-unit Mthal activity as male rats performed a two-alternative forced-choice task. A large population of Mthal neurons increased their firing briefly near movement initiation and could be segregated into functional groups based on their behavioral correlates. The activity of "initiation" units was more tightly locked to instructional cues than movement onset, did not predict which direction the rat would move, and was anticorrelated with reaction time (RT). Conversely, the activity of "execution" units was more tightly locked to movement onset than instructional cues, predicted which direction the rat would move, and was anticorrelated with both RT and movement time. These results suggest that Mthal influences choice RT performance in two stages: short latency, nonspecific action initiation followed by action selection/invigoration. We discuss the implications of these results for models of motor control incorporating BG and cerebellar circuits.SIGNIFICANCE STATEMENT Motor thalamus (Mthal) is a central node linking subcortical and cortical motor circuits, though its precise role in motor control is unclear. Here, we define distinct populations of Mthal neurons that either encode movement initiation, or both action selection and movement vigor. These results have important implications for understanding how basal ganglia, cerebellar, and motor cortical signals are integrated. Such an understanding is critical to defining the pathophysiology of a range of BG- and cerebellum-linked movement disorders, as well as refining pharmacologic and neuromodulatory approaches to their treatment.

Disruption of corticocortical information transfer during ketamine anesthesia in the primate brain.

The neural mechanisms of anesthetic-induced unconsciousness have yet to be fully elucidated, in part because of the diverse molecular targets of anesthetic agents. We demonstrate, using intracortical recordings in macaque monkeys, that information transfer between structurally connected cortical regions is disrupted during ketamine anesthesia, despite preserved primary sensory representation. Furthermore, transfer entropy, an information-theoretic measure of directed connectivity, decreases significantly between neuronal units in the anesthetized state. This is the first direct demonstration of a general anesthetic disrupting corticocortical information transfer in the primate brain. Given past studies showing that more commonly used GABAergic drugs inhibit surrogate measures of cortical communication, this finding suggests the potential for a common network-level mechanism of anesthetic-induced unconsciousness.

A Wireless Wearable Ecosystem for Social Network Analysis in Free-living Animals.

Studying animal social systems requires understanding variations in contact and interaction, influenced by factors like environmental conditions, resource availability, and predation risk. Traditional observational methods have limitations, but advancements in sensor technologies and data analytics provide new opportunities. We developed a wireless wearable sensor system, "Juxta," with features such as modular battery packs and a smartphone app for data collection. A pilot study on free-living prairie voles (Microtus ochrogaster), a species with complex social behavior, demonstrated Juxta's potential for studying social networks and behavior. We propose a framework for merging temporal, spatial, and event-driven data, which can help explore complex social dynamics across species and environments.

A Wireless Wearable Ecosystem for Social Network Analysis in Free-living Animals.

Understanding the dynamics of animal social systems requires studying variation in contact and interaction, which is influenced by environmental conditions, resource availability, and predation risk, among other factors. Traditional (direct) observational methods have limitations, but advancements in sensor technologies and data analytics provide unprecedented opportunities to study these complex systems in naturalistic environments. Proximity logging and tracking devices, capturing movement, temperature, and social interactions, offer non-invasive means to quantify behavior and develop empirical models of animal social networks. However, challenges remain in integrating different data types, incorporating more sensor modalities, and addressing logistical constraints. To address these gaps, we developed a wireless wearable sensor system with novel features (called "Juxta"), including modular battery packs, memory management for combining data types, reconfigurable deployment modes, and a smartphone app for data collection. We present data from a pilot study on prairie voles ( Microtus ochrogaster ), which is a small mammal species that exhibits relatively complex social behavior. We demonstrate the potential for Juxta to increase our understanding of the social networks and behavior of free-living animals. Additionally, we propose a framework to guide future research in merging temporal, spatial, and event-driven data. By leveraging wireless technology, battery efficiency, and smart sensing modalities, our wearable ecosystem offers a scalable solution for real-time, high-resolution data capture and analysis in animal social network studies, opening new avenues for exploring complex social dynamics across species and environments.

An implantable neurophysiology platform: Broadening research capabilities in free-living and non-traditional animals.

Animal-borne sensors that can record and transmit data ("biologgers") are becoming smaller and more capable at a rapid pace. Biologgers have provided enormous insight into the covert lives of many free-ranging animals by characterizing behavioral motifs, estimating energy expenditure, and tracking movement over vast distances, thereby serving both scientific and conservational endpoints. However, given that biologgers are usually attached externally, access to the brain and neurophysiological data has been largely unexplored outside of the laboratory, limiting our understanding of how the brain adapts to, interacts with, or addresses challenges of the natural world. For example, there are only a handful of studies in free-living animals examining the role of sleep, resulting in a wake-centric view of behavior despite the fact that sleep often encompasses a large portion of an animal's day and plays a vital role in maintaining homeostasis. The growing need to understand sleep from a mechanistic viewpoint and probe its function led us to design an implantable neurophysiology platform that can record brain activity and inertial data, while utilizing a wireless link to enable a suite of forward-looking capabilities. Here, we describe our design approach and demonstrate our device's capability in a standard laboratory rat as well as a captive fox squirrel. We also discuss the methodological and ethical implications of deploying this new class of device "into the wild" to fill outstanding knowledge gaps.

Quantifying the Autonomic Response to Stressors-One Way to Expand the Definition of "Stress" in Animals.

Quantifying how whole organisms respond to challenges in the external and internal environment ("stressors") is difficult. To date, physiological ecologists have mostly used measures of glucocorticoids (GCs) to assess the impact of stressors on animals. This is of course too simplistic as Hans Seyle himself characterized the response of organisms to "noxious stimuli" using multiple physiological responses. Possible solutions include increasing the number of biomarkers to more accurately characterize the "stress state" of animal or just measuring different biomarkers to more accurately characterize the degree of acute or chronic stressors an animal is experiencing. We focus on the latter and discuss how heart rate (HR) and heart rate variability (HRV) may be better predictors of the degree of activation of the sympathetic-adrenal-medullary system and complement or even replace measures of GCs as indicators of animal health, welfare, fitness, or their level of exposure to stressors. The miniaturization of biological sensor technology ("bio-sensors" or "bio-loggers") presents an opportunity to reassess measures of stress state and develop new approaches. We describe some modern approaches to gathering these HR and HRV data in free-living animals with the aim that heart dynamics will be more integrated with measures of GCs as bio-markers of stress state and predictors of fitness in free-living animals.

Interactions Between Motor Thalamic Field Potentials and Single-Unit Spiking Are Correlated With Behavior in Rats.

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1-4 Hz), beta (13-30 Hz), low gamma (30-70 Hz), and high gamma (70-200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Precisely timed dopamine signals establish distinct kinematic representations of skilled movements.

Brain dopamine is critical for normal motor control, as evidenced by its importance in Parkinson Disease and related disorders. Current hypotheses are that dopamine influences motor control by 'invigorating' movements and regulating motor learning. Most evidence for these aspects of dopamine function comes from simple tasks (e.g. lever pressing). Therefore, the influence of dopamine on motor skills requiring multi-joint coordination is unknown. To determine the effects of precisely timed dopamine manipulations on the performance of a complex, finely coordinated dexterous skill, we optogenetically stimulated or inhibited midbrain dopamine neurons as rats performed a skilled reaching task. We found that reach kinematics and coordination between gross and fine movements progressively changed with repeated manipulations. However, once established, rats transitioned abruptly between aberrant and baseline reach kinematics in a dopamine-dependent manner. These results suggest that precisely timed dopamine signals have immediate and long-term influences on motor skill performance, distinct from simply 'invigorating' movement.

An automated rat single pellet reaching system with high-speed video capture.

BACKGROUND: Single pellet reaching is an established task for studying fine motor control in which rats reach for, grasp, and eat food pellets in a stereotyped sequence. Most incarnations of this task require constant attention, limiting the number of animals that can be tested and the number of trials per session. Automated versions allow more interventions in more animals, but must be robust and reproducible. NEW METHOD: Our system automatically delivers single reward pellets for rats to grasp with their forepaw. Reaches are detected using real-time computer vision, which triggers video acquisition from multiple angles using mirrors. This allows us to record high-speed (>300 frames per second) video, and trigger interventions (e.g., optogenetics) with high temporal precision. Individual video frames are triggered by digital pulses that can be synchronized with behavior, experimental interventions, or recording devices (e.g., electrophysiology). The system is housed within a soundproof chamber with integrated lighting and ventilation, allowing multiple skilled reaching systems in one room. RESULTS: We show that rats acquire the automated task similarly to manual versions, that the task is robust, and can be synchronized with optogenetic interventions. COMPARISON WITH EXISTING METHODS: Existing skilled reaching protocols require high levels of investigator involvement, or, if ad libitum, do not allow for integration of high-speed, synchronized data collection. CONCLUSION: This task will facilitate the study of motor learning and control by efficiently recording large numbers of skilled movements. It can be adapted for use with modern neurophysiology, which demands high temporal precision.