PyOKR: A Semi-Automated Method for Quantifying Optokinetic Reflex Tracking Ability.

The study of behavioral responses to visual stimuli is a key component of understanding visual system function. One notable response is the optokinetic reflex (OKR), a highly conserved innate behavior necessary for image stabilization on the retina. The OKR provides a robust readout of image tracking ability and has been extensively studied to understand visual system circuitry and function in animals from different genetic backgrounds. The OKR consists of two phases: a slow tracking phase as the eye follows a stimulus to the edge of the visual plane and a compensatory fast phase saccade that resets the position of the eye in the orbit. Previous methods of tracking gain quantification, although reliable, are labor intensive and can be subjective or arbitrarily derived. To obtain more rapid and reproducible quantification of eye tracking ability, we have developed a novel semi-automated analysis program, PyOKR, that allows for quantification of two-dimensional eye tracking motion in response to any directional stimulus, in addition to being adaptable to any type of video-oculography equipment. This method provides automated filtering, selection of slow tracking phases, modeling of vertical and horizontal eye vectors, quantification of eye movement gains relative to stimulus speed, and organization of resultant data into a usable spreadsheet for statistical and graphical comparisons. This quantitative and streamlined analysis pipeline, readily accessible via PyPI import, provides a fast and direct measurement of OKR responses, thereby facilitating the study of visual behavioral responses.

A semi-automated method for quantifying optokinetic reflex tracking acuity.

The study of murine behavioral responses to visual stimuli is a key component of understanding mammalian visual circuitry. One notable response is the optokinetic reflex (OKR), a highly conserved innate behavior necessary for image stabilization on the retina. The OKR provides a robust readout of image tracking ability and has been extensively studied to understand the logic of visual system circuitry and function in mice from different genetic backgrounds. The OKR consists of two phases: a slow tracking phase as the eye follows a stimulus to the edge of the visual plane, and a compensatory fast phase saccade that maintains the image within the visual field. Assessment of the OKR has previously relied on counting individual compensatory eye saccades to estimate tracking speed. To obtain a more direct quantification of tracking ability, we have developed a novel, semi-automated analysis program that allows for rapid and reproducible quantification of unidirectional tracking gains, in addition to being adaptable to any video-oculography equipment. Our analysis program allows for the selection of slow tracking phases, modeling of the vertical and horizontal eye vectors, quantification of eye movement relative to the stimulus, and organization of resultant data into a usable spreadsheet for statistical and graphical comparisons. This quantitative and streamlined analysis pipeline provides a faster and more direct measurement of OKR responses, thereby facilitating further study of visual behavior responses. SUMMARY: We describe here a semi-automated quantitative analysis method that directly measures eye tracking resulting from murine visual system responses to two-dimensional image motion. A Python-based user interface and analysis algorithm allows for higher throughput and more quantitative measurements of eye tracking parameters than previous methods.

The transcription factor Tbx5 regulates direction-selective retinal ganglion cell development and image stabilization.

The diversity of visual input processed by the mammalian visual system requires the generation of many distinct retinal ganglion cell (RGC) types, each tuned to a particular feature. The molecular code needed to generate this cell-type diversity is poorly understood. Here, we focus on the molecules needed to specify one type of retinal cell: the upward-preferring ON direction-selective ganglion cell (up-oDSGC) of the mouse visual system. Single-cell transcriptomic profiling of up- and down-oDSGCs shows that the transcription factor Tbx5 is selectively expressed in up-oDSGCs. The loss of Tbx5 in up-oDSGCs results in a selective defect in the formation of up-oDSGCs and a corresponding inability to detect vertical motion. A downstream effector of Tbx5, Sfrp1, is also critical for vertical motion detection but not up-oDSGC formation. These results advance our understanding of the molecular mechanisms that specify a rare retinal cell type and show how disrupting this specification leads to a corresponding defect in neural circuitry and behavior.