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Bohlen, M. O.

Publications and source records attributed to Bohlen, M. O..

4 recordsLinked to original sources

Projection Targeting with Phototagging to Study the Structure and Function of Retinal Ganglion Cells

Visual information from the retina is sent to diverse targets throughout the brain by different retinal ganglion cells (RGCs). Much of our knowledge about the different RGC types and how they are routed to these brain targets is based on mice, largely due to the extensive library of genetically modified mouse lines. To alleviate the need for using genetically modified animal models for studying retinal projections, we developed a high-throughput approach called projection targeting with phototagging that combines retrograde viral labeling, optogenetic identification, functional characterization using multi-electrode arrays, and morphological analysis. This method enables the simultaneous investigation of projections, physiology, and structure-function relationships across dozens to hundreds of cells in a single experiment. We validated this method in rats by targeting RGCs projecting to the superior colliculus, revealing multiple functionally defined cell types that align with prior studies in mice. By integrating established techniques into a scalable workflow, this framework enables comparative investigations of visual circuits across species, expanding beyond genetically tractable models. MotivationVisual information from the retina is distributed to diverse targets throughout the brain. Much of our knowledge about how visual information is processed and routed to these brain targets is based on mice because of the large library of genetically modified mouse lines. For most other species, such libraries are not available. Therefore, we were motivated to develop an approach for characterizing diverse retinal projections into the brain that can be applied to other species. We aimed to achieve projection targeting with retrograde viral vectors, followed by identification of circuit-specific retinal ganglion cells (RGCs) with optogenetics, functional characterization with multi-electrode array (MEA) recordings, and morphological description with in situ and confocal microscopy. The resulting high-throughput approach permits functional and morphological investigation of dozens to hundreds of cells in individual experiments. By replacing the need for genetically modified animals with a suite of standard techniques, this approach should improve cross-species comparisons of the initial stages of visual processing. SummaryUnderstanding the structure-function relationships across neurons is challenging, particularly when circuits are composed of dozens of distinct cell types. We refined an approach, called projection targeting with phototagging, that allows simultaneous elucidation of the projections, morphology, and visual response properties of diverse RGC types in the mammalian retina. The approach combines retrograde virally mediated phototagging of RGCs, microscopy, and large-scale MEA measurements. Importantly, the approach does not rely on transgenic animals and thus is generalizable across species. We validated this approach in rats by targeting retinal projections to the superior colliculus (SC). We showed that multiple RGC types project to the SC and that these results in rats align well with prior findings from transgenic mouse studies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=194 HEIGHT=200 SRC="FIGDIR/small/661576v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1003310org.highwire.dtl.DTLVardef@1881cdorg.highwire.dtl.DTLVardef@f1dba1org.highwire.dtl.DTLVardef@8a539f_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe viral vector, AAV2retro, is effective for delivering opsins to retinal ganglion cells (RGCs) for phototagging and projection mapping. C_LIO_LIPhototagging allows matching RGC visual responses to morphology, while also identifying their central projections. C_LIO_LIThe approach does not rely on genetically modified animals and thus is generalizable across species. C_LI

neuroscience↗

Decomposition of retinal ganglion cell electrical images for cell type and functional inference

ObjectiveIdentifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and for the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. ApproachThe electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based algorithm to decompose electrical image into a low-dimensional, biophysically-based representation: the temporally-shifted superposition of three learned basis waveforms corresponding to spike waveforms produced in the somatic, dendritic and axonal cellular compartments. ResultsThe decomposition was evaluated using large-scale multi-electrode recordings from the macaque retina. The decomposition accurately localized the somatic and dendritic compartments of the cell. The imputed dendritic fields of RGCs correctly predicted the location and shape of their visual receptive fields. The inferred waveform amplitudes and shapes accurately identified the four major primate RGC types (ON and OFF midget and parasol cells) substantially more accurately than previous approaches. SignificanceThese findings contribute to more accurate inference of RGC types and their original light responses based purely on their electrical features, with potential implications for vision restoration technology.

neuroscience↗

Direct comparison of epifluorescence and immunostaining for assessing viral mediated gene expression in the primate brain

Viral vector technologies are commonly used in neuroscience research to understand and manipulate neural circuits, but successful applications of these technologies in non-human primate models have been inconsistent. An essential component to improve these technologies is an impartial and accurate assessment of the effectiveness of different viral constructs in the primate brain. We tested a diverse array of viral vectors delivered to the brain and extraocular muscles of macaques and compared three methods for histological assessment of viral-mediated fluorescent transgene expression: epifluorescence (Epi), immunofluorescence (IF), and immunohistochemistry (IHC). Importantly, IF and IHC identified a greater number of transduced neurons compared to Epi. Furthermore, IF and IHC reliably provided enhanced visualization of transgene in most cellular compartments (i.e., dendritic, axonal, and terminal fields), whereas the degree of labeling provided by Epi was inconsistent and predominantly restricted to somas and apical dendrites. Because Epi signals are unamplified (in contrast to IF and IHC), Epi likely provides a more veridical assessment for the amount of accumulated transgene and, thus, the potential to chemo- or optogenetically manipulate neuronal activity. The comparatively weak Epi signals suggest that the current generations of viral constructs, regardless of delivered transgene, are not optimized for primates. This reinforces an emerging viewpoint that viral vectors tailored for the primate brain are necessary for basic research and human gene therapy.

neuroscience↗

A single-cell multi-omic atlas spanning the adult rhesus macaque brain

Cataloging the diverse cellular architecture of the primate brain is crucial for understanding cognition, behavior and disease in humans. Here, we generated a brain-wide single-cell multimodal molecular atlas of the rhesus macaque brain. Altogether, we profiled 2.58M transcriptomes and 1.59M epigenomes from single nuclei sampled from 30 regions across the adult brain. Cell composition differed extensively across the brain, revealing cellular signatures of region-specific functions. We also identified 1.19M candidate regulatory elements, many novel, allowing us to explore the landscape of cis-regulatory grammar and neurological disease risk in a cell-type-specific manner. Together, this multi-omic atlas provides an open resource for investigating the evolution of the human brain and identifying novel targets for disease interventions.

neuroscience↗