[{"article_processing_charge":"No","date_updated":"2023-09-05T12:13:34Z","volume":129,"oa_version":"None","quality_controlled":"1","acknowledgement":"The authors gratefully thank Dr. Silvia Arber, University of Basel and Friedrich Miescher Institute for Biomedical Research, for support and in whose lab the data were collected. For advice on statistical analysis, we thank Michael Bottomley from the Statistical Consulting Center, College of Science and Mathematics, Wright State University.","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication_identifier":{"issn":["0022-3077"],"eissn":["1522-1598"]},"pmid":1,"_id":"12562","citation":{"short":"D.R. Ladle, S. Hippenmeyer, Journal of Neurophysiology 129 (2023) 501–512.","ista":"Ladle DR, Hippenmeyer S. 2023. Loss of ETV1/ER81 in motor neurons leads to reduced monosynaptic inputs from proprioceptive sensory neurons. Journal of Neurophysiology. 129(3), 501–512.","ama":"Ladle DR, Hippenmeyer S. Loss of ETV1/ER81 in motor neurons leads to reduced monosynaptic inputs from proprioceptive sensory neurons. <i>Journal of Neurophysiology</i>. 2023;129(3):501-512. doi:<a href=\"https://doi.org/10.1152/jn.00172.2022\">10.1152/jn.00172.2022</a>","mla":"Ladle, David R., and Simon Hippenmeyer. “Loss of ETV1/ER81 in Motor Neurons Leads to Reduced Monosynaptic Inputs from Proprioceptive Sensory Neurons.” <i>Journal of Neurophysiology</i>, vol. 129, no. 3, American Physiological Society, 2023, pp. 501–12, doi:<a href=\"https://doi.org/10.1152/jn.00172.2022\">10.1152/jn.00172.2022</a>.","chicago":"Ladle, David R., and Simon Hippenmeyer. “Loss of ETV1/ER81 in Motor Neurons Leads to Reduced Monosynaptic Inputs from Proprioceptive Sensory Neurons.” <i>Journal of Neurophysiology</i>. American Physiological Society, 2023. <a href=\"https://doi.org/10.1152/jn.00172.2022\">https://doi.org/10.1152/jn.00172.2022</a>.","ieee":"D. R. Ladle and S. Hippenmeyer, “Loss of ETV1/ER81 in motor neurons leads to reduced monosynaptic inputs from proprioceptive sensory neurons,” <i>Journal of Neurophysiology</i>, vol. 129, no. 3. American Physiological Society, pp. 501–512, 2023.","apa":"Ladle, D. R., &#38; Hippenmeyer, S. (2023). Loss of ETV1/ER81 in motor neurons leads to reduced monosynaptic inputs from proprioceptive sensory neurons. <i>Journal of Neurophysiology</i>. American Physiological Society. <a href=\"https://doi.org/10.1152/jn.00172.2022\">https://doi.org/10.1152/jn.00172.2022</a>"},"publication_status":"published","keyword":["Physiology","General Neuroscience"],"author":[{"first_name":"David R.","full_name":"Ladle, David R.","last_name":"Ladle"},{"id":"37B36620-F248-11E8-B48F-1D18A9856A87","last_name":"Hippenmeyer","full_name":"Hippenmeyer, Simon","orcid":"0000-0003-2279-1061","first_name":"Simon"}],"abstract":[{"lang":"eng","text":"Presynaptic inputs determine the pattern of activation of postsynaptic neurons in a neural circuit. Molecular and genetic pathways that regulate the selective formation of subsets of presynaptic inputs are largely unknown, despite significant understanding of the general process of synaptogenesis. In this study, we have begun to identify such factors using the spinal monosynaptic stretch reflex circuit as a model system. In this neuronal circuit, Ia proprioceptive afferents establish monosynaptic connections with spinal motor neurons that project to the same muscle (termed homonymous connections) or muscles with related or synergistic function. However, monosynaptic connections are not formed with motor neurons innervating muscles with antagonistic functions. The ETS transcription factor ER81 (also known as ETV1) is expressed by all proprioceptive afferents, but only a small set of motor neuron pools in the lumbar spinal cord of the mouse. Here we use conditional mouse genetic techniques to eliminate Er81 expression selectively from motor neurons. We find that ablation of Er81 in motor neurons reduces synaptic inputs from proprioceptive afferents conveying information from homonymous and synergistic muscles, with no change observed in the connectivity pattern from antagonistic proprioceptive afferents. In summary, these findings suggest a role for ER81 in defined motor neuron pools to control the assembly of specific presynaptic inputs and thereby influence the profile of activation of these motor neurons."}],"isi":1,"doi":"10.1152/jn.00172.2022","year":"2023","title":"Loss of ETV1/ER81 in motor neurons leads to reduced monosynaptic inputs from proprioceptive sensory neurons","external_id":{"pmid":["36695533"],"isi":["000957721600001"]},"page":"501-512","publication":"Journal of Neurophysiology","issue":"3","type":"journal_article","day":"01","status":"public","intvolume":"       129","department":[{"_id":"SiHi"}],"date_created":"2023-02-15T14:46:14Z","date_published":"2023-03-01T00:00:00Z","article_type":"original","month":"03","language":[{"iso":"eng"}],"publisher":"American Physiological Society"},{"citation":{"ama":"Tomm C, Avermann M, Petersen C, Gerstner W, Vogels TP. Connection-type-specific biases make uniform random network models consistent with cortical recordings. <i>Journal of Neurophysiology</i>. 2014;112(8):1801-1814. doi:<a href=\"https://doi.org/10.1152/jn.00629.2013\">10.1152/jn.00629.2013</a>","mla":"Tomm, Christian, et al. “Connection-Type-Specific Biases Make Uniform Random Network Models Consistent with Cortical Recordings.” <i>Journal of Neurophysiology</i>, vol. 112, no. 8, American Physiological Society, 2014, pp. 1801–14, doi:<a href=\"https://doi.org/10.1152/jn.00629.2013\">10.1152/jn.00629.2013</a>.","ista":"Tomm C, Avermann M, Petersen C, Gerstner W, Vogels TP. 2014. Connection-type-specific biases make uniform random network models consistent with cortical recordings. Journal of Neurophysiology. 112(8), 1801–1814.","short":"C. Tomm, M. Avermann, C. Petersen, W. Gerstner, T.P. Vogels, Journal of Neurophysiology 112 (2014) 1801–1814.","ieee":"C. Tomm, M. Avermann, C. Petersen, W. Gerstner, and T. P. Vogels, “Connection-type-specific biases make uniform random network models consistent with cortical recordings,” <i>Journal of Neurophysiology</i>, vol. 112, no. 8. American Physiological Society, pp. 1801–1814, 2014.","apa":"Tomm, C., Avermann, M., Petersen, C., Gerstner, W., &#38; Vogels, T. P. (2014). Connection-type-specific biases make uniform random network models consistent with cortical recordings. <i>Journal of Neurophysiology</i>. American Physiological Society. <a href=\"https://doi.org/10.1152/jn.00629.2013\">https://doi.org/10.1152/jn.00629.2013</a>","chicago":"Tomm, Christian, Michael Avermann, Carl Petersen, Wulfram Gerstner, and Tim P Vogels. “Connection-Type-Specific Biases Make Uniform Random Network Models Consistent with Cortical Recordings.” <i>Journal of Neurophysiology</i>. American Physiological Society, 2014. <a href=\"https://doi.org/10.1152/jn.00629.2013\">https://doi.org/10.1152/jn.00629.2013</a>."},"publication_status":"published","abstract":[{"text":"Uniform random sparse network architectures are ubiquitous in computational neuroscience, but the implicit hypothesis that they are a good representation of real neuronal networks has been met with skepticism. Here we used two experimental data sets, a study of triplet connectivity statistics and a data set measuring neuronal responses to channelrhodopsin stimuli, to evaluate the fidelity of thousands of model networks. Network architectures comprised three neuron types (excitatory, fast spiking, and nonfast spiking inhibitory) and were created from a set of rules that govern the statistics of the resulting connection types. In a high-dimensional parameter scan, we varied the degree distributions (i.e., how many cells each neuron connects with) and the synaptic weight correlations of synapses from or onto the same neuron. These variations converted initially uniform random and homogeneously connected networks, in which every neuron sent and received equal numbers of synapses with equal synaptic strength distributions, to highly heterogeneous networks in which the number of synapses per neuron, as well as average synaptic strength of synapses from or to a neuron were variable. By evaluating the impact of each variable on the network structure and dynamics, and their similarity to the experimental data, we could falsify the uniform random sparse connectivity hypothesis for 7 of 36 connectivity parameters, but we also confirmed the hypothesis in 8 cases. Twenty-one parameters had no substantial impact on the results of the test protocols we used.","lang":"eng"}],"author":[{"first_name":"Christian","last_name":"Tomm","full_name":"Tomm, Christian"},{"full_name":"Avermann, Michael","last_name":"Avermann","first_name":"Michael"},{"full_name":"Petersen, Carl","last_name":"Petersen","first_name":"Carl"},{"first_name":"Wulfram","last_name":"Gerstner","full_name":"Gerstner, Wulfram"},{"full_name":"Vogels, Tim P","last_name":"Vogels","orcid":"0000-0003-3295-6181","first_name":"Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"}],"article_processing_charge":"No","date_updated":"2021-01-12T08:16:35Z","volume":112,"oa":1,"publication_identifier":{"issn":["0022-3077"],"eissn":["1522-1598"]},"extern":"1","_id":"8023","pmid":1,"quality_controlled":"1","oa_version":"Published Version","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","doi":"10.1152/jn.00629.2013","year":"2014","title":"Connection-type-specific biases make uniform random network models consistent with cortical recordings","external_id":{"pmid":["24944218"]},"tmp":{"name":"Creative Commons Attribution 3.0 Unported (CC BY 3.0)","short":"CC BY (3.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/3.0/legalcode"},"ddc":["570"],"day":"15","type":"journal_article","intvolume":"       112","status":"public","publication":"Journal of Neurophysiology","issue":"8","page":"1801-1814","file_date_updated":"2020-07-16T10:12:13Z","month":"10","date_published":"2014-10-15T00:00:00Z","article_type":"original","publisher":"American Physiological Society","language":[{"iso":"eng"}],"has_accepted_license":"1","license":"https://creativecommons.org/licenses/by/3.0/","file":[{"success":1,"file_id":"8122","creator":"cziletti","relation":"main_file","content_type":"application/pdf","checksum":"7c06a086da6f924342650de6dc555c3f","date_created":"2020-07-16T10:12:13Z","file_size":1632295,"file_name":"2014_JNeurophysiol_Tomm.pdf","access_level":"open_access","date_updated":"2020-07-16T10:12:13Z"}],"date_created":"2020-06-25T13:08:30Z"},{"type":"journal_article","day":"01","status":"public","intvolume":"       103","page":"1646 - 1657","issue":"3","publication":"Journal of Neurophysiology","date_published":"2010-03-01T00:00:00Z","article_type":"original","month":"03","language":[{"iso":"eng"}],"publisher":"American Physiological Society","date_created":"2018-12-11T11:51:14Z","publication_status":"published","citation":{"mla":"Schnell, Bettina, et al. “Processing of Horizontal Optic Flow in Three Visual Interneurons of the Drosophila Brain.” <i>Journal of Neurophysiology</i>, vol. 103, no. 3, American Physiological Society, 2010, pp. 1646–57, doi:<a href=\"https://doi.org/10.1152/jn.00950.2009\">10.1152/jn.00950.2009</a>.","ama":"Schnell B, Jösch MA, Förstner F, et al. Processing of horizontal optic flow in three visual interneurons of the Drosophila brain. <i>Journal of Neurophysiology</i>. 2010;103(3):1646-1657. doi:<a href=\"https://doi.org/10.1152/jn.00950.2009\">10.1152/jn.00950.2009</a>","ista":"Schnell B, Jösch MA, Förstner F, Raghu S, Otsuna H, Ito K, Borst A, Reiff D. 2010. Processing of horizontal optic flow in three visual interneurons of the Drosophila brain. Journal of Neurophysiology. 103(3), 1646–1657.","short":"B. Schnell, M.A. Jösch, F. Förstner, S. Raghu, H. Otsuna, K. Ito, A. Borst, D. Reiff, Journal of Neurophysiology 103 (2010) 1646–1657.","apa":"Schnell, B., Jösch, M. A., Förstner, F., Raghu, S., Otsuna, H., Ito, K., … Reiff, D. (2010). Processing of horizontal optic flow in three visual interneurons of the Drosophila brain. <i>Journal of Neurophysiology</i>. American Physiological Society. <a href=\"https://doi.org/10.1152/jn.00950.2009\">https://doi.org/10.1152/jn.00950.2009</a>","ieee":"B. Schnell <i>et al.</i>, “Processing of horizontal optic flow in three visual interneurons of the Drosophila brain,” <i>Journal of Neurophysiology</i>, vol. 103, no. 3. American Physiological Society, pp. 1646–1657, 2010.","chicago":"Schnell, Bettina, Maximilian A Jösch, Friedrich Förstner, Shamprasad Raghu, Hideo Otsuna, Kei Ito, Alexander Borst, and Dierk Reiff. “Processing of Horizontal Optic Flow in Three Visual Interneurons of the Drosophila Brain.” <i>Journal of Neurophysiology</i>. American Physiological Society, 2010. <a href=\"https://doi.org/10.1152/jn.00950.2009\">https://doi.org/10.1152/jn.00950.2009</a>."},"author":[{"full_name":"Schnell, Bettina","last_name":"Schnell","first_name":"Bettina"},{"id":"2BD278E6-F248-11E8-B48F-1D18A9856A87","last_name":"Jösch","full_name":"Jösch, Maximilian A","orcid":"0000-0002-3937-1330","first_name":"Maximilian A"},{"last_name":"Förstner","full_name":"Förstner, Friedrich","first_name":"Friedrich"},{"full_name":"Raghu, Shamprasad","last_name":"Raghu","first_name":"Shamprasad"},{"first_name":"Hideo","full_name":"Otsuna, Hideo","last_name":"Otsuna"},{"full_name":"Ito, Kei","last_name":"Ito","first_name":"Kei"},{"first_name":"Alexander","full_name":"Borst, Alexander","last_name":"Borst"},{"last_name":"Reiff","full_name":"Reiff, Dierk","first_name":"Dierk"}],"abstract":[{"lang":"eng","text":"Motion vision is essential for navigating through the environment. Due to its genetic amenability, the fruit fly Drosophila has been serving for a lengthy period as a model organism for studying optomotor behavior as elicited by large-field horizontal motion. However, the neurons underlying the control of this behavior have not been studied in Drosophila so far. Here we report the first whole cell recordings from three cells of the horizontal system (HSN, HSE, and HSS) in the lobula plate of Drosophila. All three HS cells are tuned to large-field horizontal motion in a direction-selective way; they become excited by front-to-back motion and inhibited by back-to-front motion in the ipsilateral field of view. The response properties of HS cells such as contrast and velocity dependence are in accordance with the correlation-type model of motion detection. Neurobiotin injection suggests extensive coupling among ipsilateral HS cells and additional coupling to tangential cells that have their dendrites in the contralateral hemisphere of the brain. This connectivity scheme accounts for the complex layout of their receptive fields and explains their sensitivity both to ipsilateral and to contralateral motion. Thus the main response properties of Drosophila HS cells are strikingly similar to the responses of their counterparts in the blowfly Calliphora, although we found substantial differences with respect to their dendritic structure and connectivity. This long-awaited functional characterization of HS cells in Drosophila provides the basis for the future dissection of optomotor behavior and the underlying neural circuitry by combining genetics, physiology, and behavior."}],"volume":103,"publist_id":"5971","date_updated":"2021-01-12T06:49:44Z","article_processing_charge":"No","acknowledgement":"This work was supported by the Max-Planck-Society and by a Human Frontier Science Program grant to K. Ito, A. Borst, and B. Nelson.","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","oa_version":"None","quality_controlled":"1","_id":"1301","pmid":1,"publication_identifier":{"eissn":["1522-1598"],"issn":[" 0022-3077"]},"extern":"1","doi":"10.1152/jn.00950.2009","year":"2010","external_id":{"pmid":["20089816"]},"title":"Processing of horizontal optic flow in three visual interneurons of the Drosophila brain"}]