Different Effects of Peer Sex on Operant Responding for Social Interaction and Striatal Dopamine Activity.

When rats are given discrete choices between social interactions with a peer and opioid or psychostimulant drugs, they choose social interaction, even after extensive drug self-administration experience. Studies show that like drug and nondrug food reinforcers, social interaction is an operant reinforcer and induces dopamine release. However, these studies were conducted with same-sex peers. We examined if peer sex influences operant social interaction and the role of estrous cycle and striatal dopamine in same- versus opposite-sex social interaction. We trained male and female rats (n = 13 responders/12 peers) to lever-press (fixed-ratio 1 [FR1] schedule) for 15 s access to a same- or opposite-sex peer for 16 d (8 d/sex) while tracking females' estrous cycle. Next, we transfected GRAB-DA2m and implanted optic fibers into nucleus accumbens (NAc) core and dorsomedial striatum (DMS). We then retrained the rats for 15 s social interaction (FR1 schedule) for 16 d (8 d/sex) and recorded striatal dopamine during operant responding for a peer for 8 d (4 d/sex). Finally, we assessed economic demand by manipulating FR requirements for a peer (10 d/sex). In male, but not female rats, operant responding was higher for the opposite-sex peer. Female's estrous cycle fluctuations had no effect on operant social interaction. Striatal dopamine signals for operant social interaction were dependent on the peer's sex and striatal region (NAc core vs DMS). Results indicate that estrous cycle fluctuations did not influence operant social interaction and that NAc core and DMS dopamine activity reflect sex-dependent features of volitional social interaction.

A rat model of operant negative reinforcement in opioid-dependent males and females.

RATIONALE AND OBJECTIVE: Avoidance of opioid withdrawal plays a key role in human opioid addiction. Here, we present a procedure for studying operant negative reinforcement in rats that was inspired by primate procedures where opioid-dependent subjects lever-press to prevent naloxone infusions. METHODS: In Experiment 1, we trained rats (n = 30, 15 females) to lever-press to escape and then avoid mild footshocks (0.13-0.27 mA) for 35 days (30 trials/d). Next, we catheterized them and implanted minipumps containing methadone (10 mg/kg/day) or saline. We then paired (4 times, single session) a light cue (20-s) with a naloxone infusion (20 µg/kg, i.v) that precipitated opioid withdrawal. Next, we trained the rats to escape naloxone injections for 10 days (30 trials/d). Each trial started with the onset of the opioid-withdrawal cue. After 20-s, the lever extended, and an infusion of naloxone (1 to 2.2 µg/kg/infusion) began; a lever-press during an 11-s window terminated the withdrawal-paired cue and the infusion. In Experiment 2, we trained rats (n = 34, 17 females) on the same procedure but decreased the footshock escape/avoidance training to 20 days. RESULTS: All rats learned to lever-press to escape or avoid mild footshocks. In both experiments, a subset, 56% (10/18) and 33% (8/24) of methadone-dependent rats learned to lever-press to escape naloxone infusions. CONCLUSIONS: We introduce an operant negative reinforcement procedure where a subset of opioid-dependent rats learned to lever-press to escape withdrawal-inducing naloxone infusions. The procedure can be used to study mechanisms of individual differences in opioid negative reinforcement-related behaviors in opioid-dependent rats.

Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience.

The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitigates some of these issues through the inclusion of accessible and explainable model interpretation. To decrease barriers to access, and with an emphasis on accessible model explainability, we developed the open-source Simple Behavioral Analysis (SimBA) platform for behavioral neuroscientists. SimBA introduces several machine learning interpretability tools, including SHapley Additive exPlanation (SHAP) scores, that aid in creating explainable and transparent behavioral classifiers. Here we show how the addition of explainability metrics allows for quantifiable comparisons of aggressive social behavior across research groups and species, reconceptualizing behavior as a sharable reagent and providing an open-source framework. We provide an open-source, graphical user interface (GUI)-driven, well-documented package to facilitate the movement toward improved automation and sharing of behavioral classification tools across laboratories.

An implantable device for wireless monitoring of diverse physio-behavioral characteristics in freely behaving small animals and interacting groups.

Comprehensive, continuous quantitative monitoring of intricately orchestrated physiological processes and behavioral states in living organisms can yield essential data for elucidating the function of neural circuits under healthy and diseased conditions, for defining the effects of potential drugs and treatments, and for tracking disease progression and recovery. Here, we report a wireless, battery-free implantable device and a set of associated algorithms that enable continuous, multiparametric physio-behavioral monitoring in freely behaving small animals and interacting groups. Through advanced analytics approaches applied to mechano-acoustic signals of diverse body processes, the device yields heart rate, respiratory rate, physical activity, temperature, and behavioral states. Demonstrations in pharmacological, locomotor, and acute and social stress tests and in optogenetic studies offer unique insights into the coordination of physio-behavioral characteristics associated with healthy and perturbed states. This technology has broad utility in neuroscience, physiology, behavior, and other areas that rely on studies of freely moving, small animal models.