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Wilke, S. A.

Publications and source records attributed to Wilke, S. A..

2 recordsLinked to original sources

BehaviorDEPOT: a tool for automated behavior classification and analysis in rodents

Quantitative descriptions of animal behavior are essential to understand the underlying neural substrates. Many behavioral analyses are performed by hand or with expensive and inflexible commercial software that often fail on animals with attached head implants, such as those used for in vivo optogenetics and calcium imaging. With the development of machine learning algorithms that can estimate animal positions across time and space, it is becoming easier for users with no prior coding experience to perform automated animal tracking in behavioral video recordings. Yet classifying discrete behaviors based on positional tracking data remains a significant challenge. To achieve this, we must start with reliable ground truth definitions of behavior, a process that is hindered by unreliable human annotations. To overcome these barriers, we developed BehaviorDEPOT (DEcoding behavior based on POsitional Tracking), a MATLAB-based application comprising six independent modules and a graphical user interface. In the Analysis Module we provide hard-coded classifiers for freezing and rearing. Optionally applied spatiotemporal filters allow users to analyze behaviors in varied experimental designs (e.g. cued tasks or optogenetic manipulations). Even inexperienced users can generate organized behavioral data arrays that can be seamlessly aligned with neurophysiological recordings for detailed analyses of the neural substrates. Four additional modules create an easy-to-use pipeline for establishing reliable ground-truth definitions of behaviors as well as custom behavioral classifiers. Finally, our Experiment Module runs fear conditioning experiments using an Arduino-based design that interfaces with commercialhardware and significantly reduces associated costs. We demonstrate the utility and flexibility of BehaviorDEPOT in widely used behavioral assays including fear conditioning, avoidance, and decision-making tasks. We also demonstrate the robustness of the BehaviorDEPOT freezing classifier across multiple camera types and in mice and rats wearing optogenetic patch cables and head-mounted Miniscopes. BehaviorDEPOT provides a simple, flexible, automated pipeline to move from pose tracking to reliably quantifying a wide variety of task-relevant behaviors.

neuroscience

Convergence of clinically relevant manipulations on dopamine-regulated prefrontal activity underlying stress-coping responses

BackgroundDepression is a pleiotropic condition that can be produced or ameliorated by diverse genetic, environmental, and pharmacological manipulations. In this context, identifying patterns of circuit activity on which many of these manipulations converge would be important, because studying these patterns could reveal underlying biological processes related to depression and/or new therapies. In particular, the prefrontal cortex and dopaminergic signaling have both been implicated in depression. Nevertheless, how dopamine influences disease-relevant patterns of prefrontal circuit activity remains unknown. MethodsWe used calcium imaging in brain slices to identify depression-relevant patterns of activity in prefrontal microcircuits, and measure how these are modulated by dopamine D2 receptors (D2Rs). Then, we used optogenetic and genetic manipulations to test how dopamine and D2Rs contribute to stress-coping behavior in a paradigm commonly used to assay how manipulations promote or ameliorate depression-like states. ResultsPatterns of correlated activity in prefrontal microcircuits are enhanced by D2R stimulation as well as by two mechanistically distinct antidepressants: ketamine and fluoxetine. Conversely, this D2R-driven effect was disrupted in two etiologically distinct models of depression: a genetic susceptibility model and chronic social defeat. Phasic stimulation of dopamine afferents to prefrontal cortex increased effortful responses to tail suspension stress. Conversely, deleting prefrontal D2R receptors reduced the duration of individual struggling episodes. ConclusionsCorrelated prefrontal microcircuit activity represents a point of convergence for multiple depression-related manipulations. Prefrontal D2Rs enhance this activity. Through this mechanism, prefrontal dopamine signaling may promote network states associated with antidepressant actions that manifest as effortful responses to stress.

neuroscience