Inhibitory medial zona incerta pathway drives exploratory behavior by inhibiting glutamatergic cuneiform neurons.

The cuneiform nucleus (CnF) regulates locomotor activity, which is canonically viewed as being primarily involved in initiating locomotion and regulating speed. Recent research shows greater context dependency in the locomotor functions of this nucleus. Glutamatergic neurons, which contain vesicular glutamate transporter 2 (vGLUT2), regulate context-dependent locomotor speed in the CnF and play a role in defensive behavior. Here, we identify projections from the medial zona incerta (mZI) to CnF vGLUT2 neurons that promote exploratory behavior. Using fiber photometry recordings in male mice, we find that mZI gamma-aminobutyric acid (GABA) neurons increase activity during periods of exploration. Activation of mZI GABAergic neurons is associated with reduced spiking of CnF neurons. Additionally, activating both retrogradely labeled mZI-CnF GABAergic projection neurons and their terminals in the CnF increase exploratory behavior. Inhibiting CnF vGLUT2 neuronal activity also increases exploratory behavior. These findings provide evidence for the context-dependent dynamic regulation of CnF vGLUT2 neurons, with the mZI-CnF circuit shaping exploratory behavior.

High-throughput gait acquisition system for freely moving mice.

Normal and pathological locomotion can be discriminated by analyzing an animal's gait on a linear walkway. This step is labor intensive and introduces experimental bias due to the handling involved while placing and removing the animal between trials. We designed a system consisting of a runway embedded within a larger arena, which can be traversed ad libitum by unsupervised, freely moving mice, triggering the recording of short clips of locomotor activity. Multiple body parts were tracked using DeepLabCut and fed to an analysis pipeline (GaitGrapher) to extract gait metrics. We compared the results from unsupervised against the standard experimenter-supervised approach and found that gait parameters analyzed via the new approach were similar to a previously validated approach (Visual Gait Lab). These data show the utility of incorporating an unsupervised, automated, approach for collecting kinematic data for gait analysis.NEW & NOTEWORTHY The acquisition and analysis of walkway data is a time-consuming task. Here, we provide an unmonitored approach for collecting gait metrics that reduces the handling and stress of mice and saves time. A detailed pipeline is outlined that provides for the collection and analysis of data using an integrated suite of tools.