Biology subjects

Jessen, Z. F.

Publications and source records attributed to Jessen, Z. F..

2 recordsLinked to original sources

bioRxiv2024

Visual Identification of Conspecifics Shapes Social Behavior in Mice

Recognizing conspecifics in order to determine how to interact with them appropriately is a fundamental goal of animal sensory systems. It has undergone selective pressure in nearly all species. Mice have a large repertoire of social behaviors that are the subject of a rapidly growing field of study in neuroscience. Mouse social interactions likely incorporate all available sensory modalities, and the vast majority of studies have not attempted to isolate them. Specifically the role of vision in mouse social interactions remains unclear. We developed a behavioral platform that allowed us to present a subject mouse the visual information of stimulus mice in isolation from olfactory, acoustic, and tactile cues. Our results indicate that the visual identification of the sex or individual identity of other mice influences behavior. These findings highlight the underappreciated role of vision in mouse social interactions and open new avenues to study the visual circuits underlying social behavior.

neuroscience↗

bioRxiv2021

Unified classification of mouse retinal ganglion cells using function, morphology, and gene expression

Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We used visually-evoked responses to classify 1859 mouse RGCs into 42 types. We also obtained morphological or transcriptomic data from subsets and used these measurements to align the functional classification to publicly available morphological and transcriptomic data sets. We created an online database that allows users to browse or download the data and to classify RGCs from their light responses using a machine learning algorithm. This work provides a resource for studies of RGCs, their upstream circuits in the retina, and their projections in the brain, and establishes a framework for future efforts in neuronal classification and open data distribution.

neuroscience↗