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      A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

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          Abstract

          Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly’s head direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

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          Fully integrated silicon probes for high-density recording of neural activity

          Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal–oxide–semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.
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            Conserved cell types with divergent features in human versus mouse cortex

            Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we applied single nucleus RNA-sequencing to perform a comprehensive analysis of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuronal types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of human cell type properties. Despite this general conservation, we also find extensive differences between homologous human and mouse cell types, including dramatic alterations in proportions, laminar distributions, gene expression, and morphology. These species-specific features emphasize the importance of directly studying human brain.
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              Shared and distinct transcriptomic cell types across neocortical areas

              The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                26 October 2021
                2021
                : 10
                : e66039
                Affiliations
                [1 ] Janelia Research Campus, Howard Hughes Medical Institute ( https://ror.org/013sk6x84) Ashburn United States
                Emory University ( https://ror.org/03czfpz43) United States
                Emory University ( https://ror.org/03czfpz43) United States
                Emory University ( https://ror.org/03czfpz43) United States
                Lund University ( https://ror.org/012a77v79) Sweden
                Brandeis University ( https://ror.org/05abbep66) United States
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-7117-7036
                https://orcid.org/0000-0002-6135-131X
                https://orcid.org/0000-0002-4440-7297
                https://orcid.org/0000-0002-8020-0170
                https://orcid.org/0000-0003-2400-6426
                https://orcid.org/0000-0002-8681-1749
                https://orcid.org/0000-0002-0041-9229
                https://orcid.org/0000-0002-8951-4248
                https://orcid.org/0000-0002-8060-2807
                https://orcid.org/0000-0002-0377-0516
                https://orcid.org/0000-0001-8762-8703
                https://orcid.org/0000-0003-3680-7378
                Article
                66039
                10.7554/eLife.66039
                9477501
                34696823
                87a8b079-6a92-4ff8-b42c-6649dbd0510c
                © 2021, Hulse, Haberkern, Franconville et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 23 December 2020
                : 07 September 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                An analysis of the first complete synaptic resolution connectome of Drosophila's navigation circuit uncovers neural network motifs supporting broadly relevant sensorimotor computations.

                Life sciences
                central complex,connectome,navigation,sleep,sensorimotor,insect,d. melanogaster
                Life sciences
                central complex, connectome, navigation, sleep, sensorimotor, insect, d. melanogaster

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