AlphaTracker: a multi-animal tracking and behavioral analysis tool

Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics

Nature

The ability to associate temporally segregated information and assign positive or negative valence to environmental cues is paramount for survival. Studies have shown that different basolateral amygdala (BLA) projections are potentiated following reward or punishment learning1–7. However, we do not yet understand how valence specific information is routed to the BLA neurons with the appropriate downstream projections. Nor do we understand how to reconcile the subsecond timescales of synaptic plasticity8–11 with the longer timescales separating the predictive cues from their outcomes. Here, we demonstrate that neurotensin (NT) neurons in the paraventricular nucleus of the thalamus (PVT) projecting to the BLA (PVT-BLA:NT) mediate valence assignment by exerting concentration-dependent modulation in BLA during associative learning. We found that optogenetic activation of the PVT-BLA:NT projection promotes reward learning, while PVT-BLA projection-specific Nt gene knockout augments punishment learning. Using genetically encoded calcium and NT sensors, we further revealed that both calcium dynamics within the PVT-BLA:NT projection and NT concentrations in the BLA are enhanced after reward learning and reduced after punishment learning. Finally, we showed that CRISPR-mediated knockout of the Nt gene in the PVT-BLA pathway blunts BLA neural dynamics and attenuates the preference to active behavioral strategies to reward and punishment predictive cues. Taken together, we have identified NT as a neuropeptide that signals valence in the BLA, and showed that NT is a critical neuromodulator that orchestrates positive and negative valence assignment in amygdala neurons by extending valence-specific plasticity to behaviorally-relevant timescales

Thalamus sends information about arousal but not valence to the amygdala

Abstract Rationale The basolateral amygdala (BLA) and medial geniculate nucleus of the thalamus (MGN) have both been shown to be necessary for the formation of associative learning. While the role that the BLA plays in this process has long been emphasized, the MGN has been less well-studied and surrounded by debate regarding whether the relay of sensory information is active or passive. Objectives We seek to understand the role the MGN has within the thalamoamgydala circuit in the formation of associative learning. Methods Here, we use optogenetics and in vivo electrophysiological recordings to dissect the MGN-BLA circuit and explore the specific subpopulations for evidence of learning and synthesis of information that could impact downstream BLA encoding. We employ various machine learning techniques to investigate function within neural subpopulations. We introduce a novel method to investigate tonic changes across trial-by-trial structure, which offers an alternative approach to traditional trial-averaging techniques. Results We find that the MGN appears to encode arousal but not valence, unlike the BLA which encodes for both. We find that the MGN and the BLA appear to react differently to expected and unexpected outcomes; the BLA biased responses toward reward prediction error and the MGN focused on anticipated punishment. We uncover evidence of tonic changes by visualizing changes across trials during inter-trial intervals (baseline epochs) for a subset of cells. Conclusion We conclude that the MGN-BLA projector population acts as both filter and transferer of information by relaying information about the salience of cues to the amygdala, but these signals are not valence-specified

Monoclonal Antibody Targeting of Fibroblast Growth Factor Receptor 1c Ameliorates Obesity and Glucose Intolerance via Central Mechanisms

We have generated a novel monoclonal antibody targeting human FGFR1c (R1c mAb) that caused profound body weight and body fat loss in diet-induced obese mice due to decreased food intake (with energy expenditure unaltered), in turn improving glucose control. R1c mAb also caused weight loss in leptin-deficient ob/ob mice, leptin receptor-mutant db/db mice, and in mice lacking either the melanocortin 4 receptor or the melanin-concentrating hormone receptor 1. In addition, R1c mAb did not change hypothalamic mRNA expression levels of Agrp, Cart, Pomc, Npy, Crh, Mch, or Orexin, suggesting that R1c mAb could cause food intake inhibition and body weight loss via other mechanisms in the brain. Interestingly, peripherally administered R1c mAb accumulated in the median eminence, adjacent arcuate nucleus and in the circumventricular organs where it activated the early response gene c-Fos. As a plausible mechanism and coinciding with the initiation of food intake suppression, R1c mAb induced hypothalamic expression levels of the cytokines Monocyte chemoattractant protein 1 and 3 and ERK1/2 and p70 S6 kinase 1 activation