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      OLM interneurons differentially modulate CA3 and entorhinal inputs to hippocampal CA1 neurons

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          The vast diversity of GABAergic interneurons is believed to endow hippocampal microcircuits with the required flexibility for memory encoding and retrieval. However, dissection of the functional roles of defined interneuron types have been hampered by the lack of cell specific tools. Here we report a precise molecular marker for a population of hippocampal GABAergic interneurons known as oriens lacunosum-moleculare (OLM) cells. By combining novel transgenic mice and optogenetic tools, we demonstrate that OLM cells have a key role in gating the information flow in CA1, facilitating the transmission of intrahippocampal information (from CA3) while reducing the influence of extrahippocampal inputs (from the entorhinal cortex). We further demonstrate that OLM cells are interconnected by gap junctions, receive direct cholinergic inputs from subcortical afferents, and account for the effect of nicotine on synaptic plasticity of the Schaffer collateral pathway. Our results suggest that acetylcholine acting through OLM cells can control the mnemonic processes executed by the hippocampus.

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          Most cited references 48

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          A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.

          A key obstacle to understanding neural circuits in the cerebral cortex is that of unraveling the diversity of GABAergic interneurons. This diversity poses general questions for neural circuit analysis: how are these interneuron cell types generated and assembled into stereotyped local circuits and how do they differentially contribute to circuit operations that underlie cortical functions ranging from perception to cognition? Using genetic engineering in mice, we have generated and characterized approximately 20 Cre and inducible CreER knockin driver lines that reliably target major classes and lineages of GABAergic neurons. More select populations are captured by intersection of Cre and Flp drivers. Genetic targeting allows reliable identification, monitoring, and manipulation of cortical GABAergic neurons, thereby enabling a systematic and comprehensive analysis from cell fate specification, migration, and connectivity, to their functions in network dynamics and behavior. As such, this approach will accelerate the study of GABAergic circuits throughout the mammalian brain. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Interneurons of the hippocampus.

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              Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex.

              Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project.

                Author and article information

                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                18 September 2012
                07 October 2012
                November 2012
                01 May 2013
                : 15
                : 11
                : 1524-1530
                [1 ]Developmental Genetics, Department of Neuroscience, Uppsala University, Box 593, 751 24 Uppsala, Sweden
                [2 ]Brain Institute, Federal University of Rio Grande do Norte, Natal, RN 59056, Brazil
                [3 ]R. D. Berlin Center for Cell Analysis and Modeling, UConn Health Center, Farmington, CT 06030, United States
                [4 ]Science for Life Laboratory, Department of Neuroscience, Uppsala University, Box 593, 751 24 Uppsala, Sweden
                Author notes
                Correspondence and requests for materials should be addressed to Klas.Kullander@ 123456neuro.uu.se or Richardson.Leao@ 123456neuro.uu.se

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                Funded by: National Institute of Biomedical Imaging and Bioengineering : NIBIB
                Award ID: R01 EB001963 || EB
                Funded by: National Center for Research Resources : NCRR
                Award ID: P41 RR000954 || RR



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