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  What the mouse eye tells the mouse brain: Fingerprinting the retinal ganglion cell types of the mouse retina

Franke, K., Baden, T., Berens, P., Rezac, M., Bethge, M., & Euler, T. (2014). What the mouse eye tells the mouse brain: Fingerprinting the retinal ganglion cell types of the mouse retina. In 15th Conference of Junior Neuroscientists of Tübingen (NeNa 2014): The Changing Face of Publishing and Scientific Evaluation (pp. 10-10).

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Franke, K, Author
Baden, T, Author
Berens, Philipp1, 2, Author           
Rezac, M, Author
Bethge, Matthias1, 2, Author           
Euler, T, Author
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1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: The retinal ganglion cells (RGCs) relay the output of each parallel feature detecting channel established through complex interactions in the retinas two synaptic layers to higher visual centres. Understanding how the visual scenery is encoded by the outputs of the 20 RGC types will thus yield a complete picture of the representation of the visual scene available to the brain. To reliably record from each RGC type in the mouse retina, we bulk-electroporated the tissue with a synthetic calcium indicator (OGB-1) and used two-photon calcium imaging to record light stimulus-evoked activity at the level of the ganglion cell layer (GCL) (Briggman Euler, J Neurophysiol 2011). So far, our database contains recordings of >10,000 cells from the GCL. In addition, we obtained recordings from transgenic PV and PCP2 mice, in which 13 morphologically distinct RGC types are fluorescently labelled and can be identified based on their anatomy (Farrow et al., Neuron 2013; Ivanova et al., J Comp Neuol 2013). Moreover, we performed electrical single-cell recordings from RGCs to relate their spiking responses to the somatic Ca2+ signals and to compare their morphologies with published RGC catalogues (e.g., Völgyi et al., JCN 2009). We implemented a probabilistic clustering framework for separating RGCs into functional types based on features extracted from their responses to the different visual stimuli using PCA. We employed an automated mixture of Gaussians Clustering algorithm to cluster the cells based on their physiological properties. Subsequently, clusters were grouped according to genetic labels and morphological criteria (e.g. soma size). For our data, we obtain 35 functional groups, which separate into 25 RGC groups and 10 displaced amacrine cell (dAC) groups, as verified using glutamatedecarboxylase (GAD) immunostaining. These numbers match well the number of RGC and dAC types expected in mouse retina. The RGC types include many known cell types (OFF and ON alpha, W3, ON-OFF direction-selective), as verified using our genetic label and single cell data (e.g. alpha RGCs) and additional information available (e.g. soma size/shape and retinal tiling). In addition, they include new functional RGC types, such as (1) an OFF orientation selective RGC, (2) an ON transient DS RGC with single cardinal direction and, (3) a contrast-suppressed type. Our results suggest that a functional fingerprint for each RGC in the mouse retina is within reach.

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 Dates: 2014-10
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: FrankeBBRBE2014
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Title: 15th Conference of Junior Neuroscientists of Tübingen (NeNa 2014): The Changing Face of Publishing and Scientific Evaluation
Place of Event: Schramberg, Germany
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Title: 15th Conference of Junior Neuroscientists of Tübingen (NeNa 2014): The Changing Face of Publishing and Scientific Evaluation
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 10 - 10 Identifier: -