Mimicking opioid analgesia in cortical pain circuits.

The anterior cingulate cortex plays a pivotal role in the cognitive and affective aspects of pain perception. Both endogenous and exogenous opioid signaling within the cingulate mitigate cortical nociception, reducing pain unpleasantness. However, the specific functional and molecular identities of cells mediating opioid analgesia in the cingulate remain elusive. Given the complexity of pain as a sensory and emotional experience, and the richness of ethological pain-related behaviors, we developed a standardized, deep-learning platform for deconstructing the behavior dynamics associated with the affective component of pain in mice-LUPE (Light aUtomated Pain Evaluator). LUPE removes human bias in behavior quantification and accelerated analysis from weeks to hours, which we leveraged to discover that morphine altered attentional and motivational pain behaviors akin to affective analgesia in humans. Through activity-dependent genetics and single-nuclei RNA sequencing, we identified specific ensembles of nociceptive cingulate neuron-types expressing mu-opioid receptors. Tuning receptor expression in these cells bidirectionally modulated morphine analgesia. Moreover, we employed a synthetic opioid receptor promoter-driven approach for cell-type specific optical and chemical genetic viral therapies to mimic morphine's pain-relieving effects in the cingulate, without reinforcement. This approach offers a novel strategy for precision pain management by targeting a key nociceptive cortical circuit with on-demand, non-addictive, and effective analgesia.

Deep behavioural phenotyping of the Q175 Huntington disease mouse model: effects of age, sex, and weight.

BACKGROUND: Huntington disease (HD) is a neurodegenerative disorder with complex motor and behavioural manifestations. The Q175 knock-in mouse model of HD has gained recent popularity as a genetically accurate model of the human disease. However, behavioural phenotypes are often subtle and progress slowly in this model. Here, we have implemented machine-learning algorithms to investigate behaviour in the Q175 model and compare differences between sexes and disease stages. We explore distinct behavioural patterns and motor functions in open field, rotarod, water T-maze, and home cage lever-pulling tasks. RESULTS: In the open field, we observed habituation deficits in two versions of the Q175 model (zQ175dn and Q175FDN, on two different background strains), and using B-SOiD, an advanced machine learning approach, we found altered performance of rearing in male manifest zQ175dn mice. Notably, we found that weight had a considerable effect on performance of accelerating rotarod and water T-maze tasks and controlled for this by normalizing for weight. Manifest zQ175dn mice displayed a deficit in accelerating rotarod (after weight normalization), as well as changes to paw kinematics specific to males. Our water T-maze experiments revealed response learning deficits in manifest zQ175dn mice and reversal learning deficits in premanifest male zQ175dn mice; further analysis using PyMouseTracks software allowed us to characterize new behavioural features in this task, including time at decision point and number of accelerations. In a home cage-based lever-pulling assessment, we found significant learning deficits in male manifest zQ175dn mice. A subset of mice also underwent electrophysiology slice experiments, revealing a reduced spontaneous excitatory event frequency in male manifest zQ175dn mice. CONCLUSIONS: Our study uncovered several behavioural changes in Q175 mice that differed by sex, age, and strain. Our results highlight the impact of weight and experimental protocol on behavioural results, and the utility of machine learning tools to examine behaviour in more detailed ways than was previously possible. Specifically, this work provides the field with an updated overview of behavioural impairments in this model of HD, as well as novel techniques for dissecting behaviour in the open field, accelerating rotarod, and T-maze tasks.

Forebrain EAAT3 Overexpression Increases Susceptibility to Amphetamine-Induced Repetitive Behaviors.

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder characterized by intrusive obsessive thoughts and compulsive behaviors. Multiple studies have shown the association of polymorphisms in the SLC1A1 gene with OCD. The most common of these OCD-associated polymorphisms increases the expression of the encoded protein, excitatory amino acid transporter 3 (EAAT3), a neuronal glutamate transporter. Previous work has shown that increased EAAT3 expression results in OCD-relevant behavioral phenotypes in rodent models. In this study, we created a novel mouse model with targeted, reversible overexpression of Slc1a1 in forebrain neurons. The mice do not have a baseline difference in repetitive behavior but show increased hyperlocomotion following a low dose of amphetamine (3 mg/kg) and increased stereotypy following a high dose of amphetamine (8 mg/kg). We next characterized the effect of amphetamine on striatal cFos response and found that amphetamine increased cFos throughout the striatum in both control and Slc1a1-overexpressing (OE) mice, but Slc1a1-OE mice had increased cFos expression in the ventral striatum relative to controls. We used an unbiased machine classifier to robustly characterize the behavioral response to different doses of amphetamine and found a unique response to amphetamine in Slc1a1-OE mice, relative to controls. Lastly, we found that the differences in striatal cFos expression in Slc1a1-OE mice were driven by cFos expression specifically in D1 neurons, as Slc1a1-OE mice had increased cFos in D1 ventral medial striatal neurons, implicating this region in the exaggerated behavioral response to amphetamine in Slc1a1-OE mice.

A-SOiD, an active-learning platform for expert-guided, data-efficient discovery of behavior.

To identify and extract naturalistic behavior, two methods have become popular: supervised and unsupervised. Each approach carries its own strengths and weaknesses (for example, user bias, training cost, complexity and action discovery), which the user must consider in their decision. Here, an active-learning platform, A-SOiD, blends these strengths, and in doing so, overcomes several of their inherent drawbacks. A-SOiD iteratively learns user-defined groups with a fraction of the usual training data, while attaining expansive classification through directed unsupervised classification. In socially interacting mice, A-SOiD outperformed standard methods despite requiring 85% less training data. Additionally, it isolated ethologically distinct mouse interactions via unsupervised classification. We observed similar performance and efficiency using nonhuman primate and human three-dimensional pose data. In both cases, the transparency in A-SOiD's cluster definitions revealed the defining features of the supervised classification through a game-theoretic approach. To facilitate use, A-SOiD comes as an intuitive, open-source interface for efficient segmentation of user-defined behaviors and discovered sub-actions.

Mapping the neuroethological signatures of pain, analgesia, and recovery in mice.

Ongoing pain is driven by the activation and modulation of pain-sensing neurons, affecting physiology, motor function, and motivation to engage in certain behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in non-verbal animals. Here, in mice, we used site-specific electrophysiology to define key time points corresponding to peripheral sensitivity in acute paw inflammation and chronic knee pain models. Using supervised and unsupervised machine learning tools, we uncovered sensory-evoked coping postures unique to each model. Through 3D pose analytics, we identified movement sequences that robustly represent different pain states and found that commonly used analgesics do not return an animal's behavior to a pre-injury state. Instead, these analgesics induce a novel set of spontaneous behaviors that are maintained even after resolution of evoked pain behaviors. Together, these findings reveal previously unidentified neuroethological signatures of pain and analgesia at heightened pain states and during recovery.

Open-source tools for behavioral video analysis: Setup, methods, and best practices.

Recently developed methods for video analysis, especially models for pose estimation and behavior classification, are transforming behavioral quantification to be more precise, scalable, and reproducible in fields such as neuroscience and ethology. These tools overcome long-standing limitations of manual scoring of video frames and traditional 'center of mass' tracking algorithms to enable video analysis at scale. The expansion of open-source tools for video acquisition and analysis has led to new experimental approaches to understand behavior. Here, we review currently available open-source tools for video analysis and discuss how to set up these methods for labs new to video recording. We also discuss best practices for developing and using video analysis methods, including community-wide standards and critical needs for the open sharing of datasets and code, more widespread comparisons of video analysis methods, and better documentation for these methods especially for new users. We encourage broader adoption and continued development of these tools, which have tremendous potential for accelerating scientific progress in understanding the brain and behavior.

Recent Advances in 3D Printing of Biomedical Sensing Devices.

Additive manufacturing, also called 3D printing, is a rapidly evolving technique that allows for the fabrication of functional materials with complex architectures, controlled microstructures, and material combinations. This capability has influenced the field of biomedical sensing devices by enabling the trends of device miniaturization, customization, and elasticity (i.e., having mechanical properties that match with the biological tissue). In this paper, the current state-of-the-art knowledge of biomedical sensors with the unique and unusual properties enabled by 3D printing is reviewed. The review encompasses clinically important areas involving the quantification of biomarkers (neurotransmitters, metabolites, and proteins), soft and implantable sensors, microfluidic biosensors, and wearable haptic sensors. In addition, the rapid sensing of pathogens and pathogen biomarkers enabled by 3D printing, an area of significant interest considering the recent worldwide pandemic caused by the novel coronavirus, is also discussed. It is also described how 3D printing enables critical sensor advantages including lower limit-of-detection, sensitivity, greater sensing range, and the ability for point-of-care diagnostics. Further, manufacturing itself benefits from 3D printing via rapid prototyping, improved resolution, and lower cost. This review provides researchers in academia and industry a comprehensive summary of the novel possibilities opened by the progress in 3D printing technology for a variety of biomedical applications.

CMU Array: A 3D nanoprinted, fully customizable high-density microelectrode array platform.

Microelectrode arrays provide the means to record electrophysiological activity critical to brain research. Despite its fundamental role, there are no means to customize electrode layouts to address specific experimental or clinical needs. Moreover, current electrodes demonstrate substantial limitations in coverage, fragility, and expense. Using a 3D nanoparticle printing approach that overcomes these limitations, we demonstrate the first in vivo recordings from electrodes that make use of the flexibility of the 3D printing process. The customizable and physically robust 3D multi-electrode devices feature high electrode densities (2600 channels/cm2 of footprint) with minimal gross tissue damage and excellent signal-to-noise ratio. This fabrication methodology also allows flexible reconfiguration consisting of different individual shank lengths and layouts, with low overall channel impedances. This is achieved, in part, via custom 3D printed multilayer circuit boards, a fabrication advancement itself that can support several biomedical device possibilities. This effective device design enables both targeted and large-scale recording of electrical signals throughout the brain.

Contralateral Limb Specificity for Movement Preparation in the Parietal Reach Region.

The canonical view of motor control is that distal musculature is controlled primarily by the contralateral cerebral hemisphere; unilateral brain lesions typically affect contralateral but not ipsilateral musculature. Contralateral-only limb deficits following a unilateral lesion suggest but do not prove that control is strictly contralateral: the loss of a contribution of the lesioned hemisphere to the control of the ipsilesional limb could be masked by the intact contralateral drive from the nonlesioned hemisphere. To distinguish between these possibilities, we serially inactivated the parietal reach region, comprising the posterior portion of medial intraparietal area, the anterior portion of V6a, and portions of the lateral occipital parietal area, in each hemisphere of 2 monkeys (23 experimental sessions, 46 injections total) to evaluate parietal reach region's contribution to the contralateral reaching deficits observed following lateralized brain lesions. Following unilateral inactivation, reach reaction times with the contralesional limb were slowed compared with matched blocks of control behavioral data; there was no effect of unilateral inactivation on the reaction time of either ipsilesional limb reaches or saccadic eye movements. Following bilateral inactivation, reaching was slowed in both limbs, with an effect size in each no different from that produced by unilateral inactivation. These findings indicate contralateral organization of reach preparation in posterior parietal cortex.SIGNIFICANCE STATEMENT Unilateral brain lesions typically affect contralateral but not ipsilateral musculature. Contralateral-only limb deficits following a unilateral lesion suggest but do not prove that control is strictly contralateral: the loss of a contribution of the lesioned hemisphere to the control of the ipsilesional limb could be masked by the intact contralateral drive from the nonlesioned hemisphere. Unilateral lesions cannot distinguish between contralateral and bilateral control, but bilateral lesions can. Here we show similar movement initiation deficits after combined unilateral and bilateral inactivation of the parietal reach region, indicating contralateral organization of reach preparation.

B-SOiD, an open-source unsupervised algorithm for identification and fast prediction of behaviors.

Studying naturalistic animal behavior remains a difficult objective. Recent machine learning advances have enabled limb localization; however, extracting behaviors requires ascertaining the spatiotemporal patterns of these positions. To provide a link from poses to actions and their kinematics, we developed B-SOiD - an open-source, unsupervised algorithm that identifies behavior without user bias. By training a machine classifier on pose pattern statistics clustered using new methods, our approach achieves greatly improved processing speed and the ability to generalize across subjects or labs. Using a frameshift alignment paradigm, B-SOiD overcomes previous temporal resolution barriers. Using only a single, off-the-shelf camera, B-SOiD provides categories of sub-action for trained behaviors and kinematic measures of individual limb trajectories in any animal model. These behavioral and kinematic measures are difficult but critical to obtain, particularly in the study of rodent and other models of pain, OCD, and movement disorders.

The two-step task, avoidance, and OCD.

In this invited review, we argue for the need to determine whether appetitive and aversive behaviors, be they goal-directed or habitual, share overlapping neural circuitry. To motivate our argument, we first summarize what is currently known about the neural circuits governing aversive and appetitive behaviors by focusing first on the three hypothesized phases of avoidance learning, and then on goal-directed and habitual reward seeking. We then provide several reasons to believe that the neural circuits of appetitive and aversive instrumental behaviors are not completely overlapping. We next discuss an experimental strategy to determine the extent of overlap based on a new computational framework that improves the identification of goal-directed and habitual actions regardless of valence. Finally, we discuss recent work in obsessive-compulsive disorder that uses this computational framework to determine whether patients perform appetitive and aversive versions of the same task using the same behavioral strategies and neural circuits.

Open-Source Joystick Manipulandum for Decision-Making, Reaching, and Motor Control Studies in Mice.

To make full use of optogenetic and molecular techniques in the study of motor control, rich behavioral paradigms for rodents must rise to the same level of sophistication and applicability. We describe the layout, construction, use and analysis of data from joystick-based reaching in a head-fixed mouse. The step-by-step guide is designed for both experienced rodent motor labs and new groups looking to enter into this research space. Using this platform, mice learn to consistently perform large, easily-quantified reaches, including during a two-armed bandit probabilistic learning task. The metrics of performance (reach trajectory, amplitude, speed, duration, and inter-reach interval) can be used to quantify behavior or administer stimulation in closed loop with behavior. We provide a highly customizable, low cost and reproducible open-source behavior training platform for studying motor control, decision-making, and reaching reaction time. The development of this software and hardware platform enables behavioral work to complement recent advances in rodents, while remaining accessible to smaller institutions and labs, thus providing a high-throughput method to study unexplored features of action selection, motivation, and value-based decisions.

A Proposed Circuit Computation in Basal Ganglia: History-Dependent Gain.

In this Scientific Perspectives we first review the recent advances in our understanding of the functional architecture of basal ganglia circuits. Then we argue that these data can best be explained by a model in which basal ganglia act to control the gain of movement kinematics to shape performance based on prior experience, which we refer to as a history-dependent gain computation. Finally, we discuss how insights from the history-dependent gain model might translate from the bench to the bedside, primarily the implications for the design of adaptive deep brain stimulation. Thus, we explicate the key empirical and conceptual support for a normative, computational model with substantial explanatory power for the broad role of basal ganglia circuits in health and disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Translating Insights From Optogenetics To Therapies For Parkinson's Disease.

Movement disorders including Parkinson's disease and dystonia are caused by neurological dysfunction, typically resulting from the loss of a neuronal input within a circuit. Neuromodulation, specifically deep brain stimulation (DBS), has proven to be a critical development in the treatment of movement disorders. Continuing efforts aim to improve DBS techniques, both in how they exert their effects and in the efficacy of the mechanism involved in eliciting those effects. While optogenetic stimulation is currently infeasible in human patients, opto-DBS research provides an indispensible avenue to understand the mechanisms of DBS therapeutic and adverse effects. We review the benefits of cell-type specific manipulations in understanding the root cause of movement disorders and how DBS might optimally combat those causes. We also explore new circuit-inspired applications of DBS suggested by thorough, high-throughput optogenetic techniques. Maximizing the efficacy and outcome of DBS requires a multi-tiered approach; research employing optogenetics provides the specificity and feasibility to uncover the mechanisms that will help realize these gains in patient care.

Opponent and bidirectional control of movement velocity in the basal ganglia.

For goal-directed behaviour it is critical that we can both select the appropriate action and learn to modify the underlying movements (for example, the pitch of a note or velocity of a reach) to improve outcomes. The basal ganglia are a critical nexus where circuits necessary for the production of behaviour, such as the neocortex and thalamus, are integrated with reward signalling to reinforce successful, purposive actions. The dorsal striatum, a major input structure of basal ganglia, is composed of two opponent pathways, direct and indirect, thought to select actions that elicit positive outcomes and suppress actions that do not, respectively. Activity-dependent plasticity modulated by reward is thought to be sufficient for selecting actions in the striatum. Although perturbations of basal ganglia function produce profound changes in movement, it remains unknown whether activity-dependent plasticity is sufficient to produce learned changes in movement kinematics, such as velocity. Here we use cell-type-specific stimulation in mice delivered in closed loop during movement to demonstrate that activity in either the direct or indirect pathway is sufficient to produce specific and sustained increases or decreases in velocity, without affecting action selection or motivation. These behavioural changes were a form of learning that accumulated over trials, persisted after the cessation of stimulation, and were abolished in the presence of dopamine antagonists. Our results reveal that the direct and indirect pathways can each bidirectionally control movement velocity, demonstrating unprecedented specificity and flexibility in the control of volition by the basal ganglia.

The parietal reach region is limb specific and not involved in eye-hand coordination.

Primates frequently reach toward visual targets. Neurons in early visual areas respond to stimuli in the contralateral visual hemifield and without regard to which limb will be used to reach toward that target. In contrast, neurons in motor areas typically respond when reaches are performed using the contralateral limb and with minimal regard to the visuospatial location of the target. The parietal reach region (PRR) is located early in the visuomotor processing hierarchy. PRR neurons are significantly modulated when targets for either limb or eye movement appear, similar to early sensory areas; however, they respond to targets in either visual field, similar to motor areas. The activity could reflect the subject's attentional locus, movement of a specific effector, or a related function, such as coordinating eye-arm movements. To examine the role of PRR in the visuomotor pathway, we reversibly inactivated PRR. Inactivation effects were specific to contralateral limb movements, leaving ipsilateral limb and saccadic movements intact. Neither visual hemifield bias nor visual attention deficits were observed. Thus our results are consistent with a motoric rather than visual organization in PRR, despite its early location in the visuomotor pathway. We found no effects on the temporal coupling of coordinated saccades and reaches, suggesting that this mechanism lies downstream of PRR. In sum, this study clarifies the role of PRR in the visuomotor hierarchy: despite its early position, it is a limb-specific area influencing reach planning and is positioned upstream from an active eye-hand coordination-coupling mechanism.

Lesions of cortical area LIP affect reach onset only when the reach is accompanied by a saccade, revealing an active eye-hand coordination circuit.

The circuits that drive visually guided eye and arm movements transform generic visual inputs into effector-specific motor commands. As part of the effort to elucidate these circuits, the primate lateral intraparietal area (LIP) has been interpreted as a priority map for saccades (oculomotor-specific) or a salience map of space (not effector-specific). It has also been proposed as a locus for eye-hand coordination. We reversibly inactivated LIP while monkeys performed memory-guided saccades and reaches. Coordinated saccade and reach reaction times were similarly impaired, consistent with a nonspecific role. However, reaches made without an accompanying saccade remained intact, and the relative temporal coupling of saccades and reaches was unchanged. These results suggest that LIP contributes to saccade planning but not to reach planning. Coordinated reaches are delayed as a result of an eye-hand coordination mechanism, located outside of LIP, that actively delays reaches until shortly after the onset of an associated saccade. We conclude with a discussion of how to reconcile specificity for saccades with a possible role in directing attention.

Intention and attention: different functional roles for LIPd and LIPv.

Establishing the circuitry underlying attentional and oculomotor control is a long-standing goal of systems neuroscience. The macaque lateral intraparietal area (LIP) has been implicated in both processes, but numerous studies have produced contradictory findings. Anatomically, LIP consists of a dorsal and ventral subdivision, but the functional importance of this division remains unclear. We injected muscimol, a GABA(A) agonist, and manganese, a magnetic resonance imaging lucent paramagnetic ion, into different portions of LIP, examined the effects of the resulting reversible inactivation on saccade planning and attention, and visualized each injection using anatomical magnetic resonance imaging. We found that dorsal LIP (LIPd) is primarily involved in oculomotor planning, whereas ventral LIP (LIPv) contributes to both attentional and oculomotor processes. Additional testing revealed that the two functions were dissociable, even in LIPv. Using our technique, we found a clear structure-function relationship that distinguishes LIPv from LIPd and found dissociable circuits for attention and eye movements in the posterior parietal cortex.

Intermittent ethanol exposure in adolescent rats: dose-dependent impairments in trace conditioning.

BACKGROUND: Recent studies have revealed that the adolescent brain may be especially vulnerable to ethanol-induced toxicity. Corticolimbic regions are more severely damaged following ethanol exposure during adolescence than during adulthood. The consequences of adolescent ethanol exposure on cognition however, have only recently begun to be explored. METHODS: Male and female rats were administered 0, 1.5, 2.5 or 4.5 g/kg ethanol (20% v/v) by acute intragastric gavage during adolescence (postnatal days [PD] 28, 30, 32 and 34). On PD 40, half of the subjects in each dose group were given 5 pairings of a 10-sec flashing light (CS; conditioned stimulus) immediately followed by mild footshock (US; unconditioned stimulus), a procedure known as delay conditioning. The other half were also given 5 CS-US pairings, but the US was presented 10 sec after CS offset, a procedure known as trace conditioning. All subjects were tested for CS-elicited freezing 24 h later. RESULTS: There was no effect of adolescent ethanol exposure on delay conditioned responding, with all subjects demonstrating comparable levels of CS-elicited freezing. In contrast, the amount of freezing in the trace conditioned subjects was negatively correlated with prior ethanol dose. Specifically, exposure to 2.5 or 4.5 g/kg during adolescence resulted in a deficit in trace conditioned responding. CONCLUSIONS: These data indicate that intermittent exposure to ethanol during adolescence results in impairment in hippocampal-dependent trace conditioning that persists beyond the period of ethanol exposure. Delay conditioning was unaffected by prior ethanol treatment, indicating that there was no difficulty in detecting the CS or US, or in the ability to engage in freezing behavior. These results suggest that the adolescent brain may be particularly vulnerable to the effects of repeated exposure to ethanol that can have consequences for nonspatial, hippocampal-dependent cognitive abilities.