Circuit reconstruction tools today

Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, United States.
Current Opinion in Neurobiology (Impact Factor: 6.63). 11/2007; 17(5):601-8. DOI: 10.1016/j.conb.2007.11.004
Source: PubMed


To understand how a brain processes information, we must understand the structure of its neural circuits-especially circuit interconnection topologies and the cell and synapse molecular architectures that determine circuit-signaling dynamics. Our information on these key aspects of neural circuit structure has remained incomplete and fragmentary, however, because of limitations of the best available imaging methods. Now, new transgenic tool mice and new image acquisition tools appear poised to permit very significant advances in our abilities to reconstruct circuit connection topologies and molecular architectures.

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    • "As a result, the reconstruction of large tissue volumes is usually not possible. The recent development of automated or semi-automated electron microscopy techniques (which require much less labor-intensive human interaction and training than conventional electron microcopy) represents an important advance in the study of the synaptome (Denk and Horstmann, 2004; Smith, 2007; Helmstaedter et al., 2008; Knott et al., 2008; Merchán-Pérez et al., 2009). For example, the 3D reconstruction method involving the combination of focused ion beam milling and scanning electron microscopy (FIB/SEM; Figures 3D–G) permits the rapid and automatic serial reconstruction of relatively large tissue volumes (Knott et al., 2008; Merchán-Pérez et al., 2009). "
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    ABSTRACT: Over the years the field of neuroanatomy has evolved considerably but unraveling the extraordinary structural and functional complexity of the brain seems to be an unattainable goal, partly due to the fact that it is only possible to obtain an imprecise connection matrix of the brain. The reasons why reaching such a goal appears almost impossible to date is discussed here, together with suggestions of how we could overcome this anatomical problem by establishing new methodologies to study the brain and by promoting interdisciplinary collaboration. Generating a realistic computational model seems to be the solution rather than attempting to fully reconstruct the whole brain or a particular brain region.
    Full-text · Article · Sep 2015 · Frontiers in Neuroanatomy
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    • "Connectomics methods based on light microscopy (LM) are well suited for the mesoscopic level (Osten and Margrie, 2013), but can also reveal microscale connectivity through the visualization of intrinsic or genetically encoded synaptic markers. Array Tomography (AT; Micheva and Smith, 2007; Micheva et al., 2010) uses serial application of antibodies directed against endogenous proteins known to localize to vesicles or the PSD. Validated by correlative EM studies, synapse identification can be >80% reliable , which is extremely useful in the context of high-throughput capacity (Rah et al., 2013). "
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    ABSTRACT: The recent development of powerful tools for high-throughput mapping of synaptic networks promises major advances in understanding brain function. One open question is how circuits integrate and store information. Competing models based on random vs. structured connectivity make distinct predictions regarding the dendritic addressing of synaptic inputs. In this article we review recent experimental tests of one of these models, the input clustering hypothesis. Across circuits, brain regions and species, there is growing evidence of a link between synaptic co-activation and dendritic location, although this finding is not universal. The functional implications of input clustering and future challenges are discussed.
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    • "Understanding neuronal connectivity in brains is a major goal in neuroscience. With recent advances in microscopy, genetically expressed marker proteins and the development of suitable software and computational power to reconstruct large high-resolution anatomical datasets in 3D [see e.g., (Briggman and Denk, 2006; Smith, 2007; Cardona et al., 2010; Mishchenko, 2011)], large scale anatomical “connectomics” studies have now become possible. "
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    ABSTRACT: Peptidergic neurons are not easily integrated into current connectomics concepts, since their peptide messages can be distributed via non-synaptic paracrine signaling or volume transmission. Moreover, the polarity of peptidergic interneurons in terms of in- and out-put sites can be hard to predict and is very little explored. We describe in detail the morphology and the subcellular distribution of fluorescent vesicle/dendrite markers in CCAP neurons (NCCAP), a well defined set of peptidergic neurons in the Drosophila larva. NCCAP can be divided into five morphologically distinct subsets. In contrast to other subsets, serial homologous interneurons in the ventral ganglion show a mixed localization of in- and output markers along ventral neurites that defy a classification as dendritic or axonal compartments. Ultrastructurally, these neurites contain both pre- and postsynaptic sites preferably at varicosities. A significant portion of the synaptic events are due to reciprocal synapses. Peptides are mostly non-synaptically or parasynaptically released, and dense-core vesicles and synaptic vesicle pools are typically well separated. The responsiveness of the NCCAP to ecdysis-triggering hormone may be at least partly dependent on a tonic synaptic inhibition, and is independent of ecdysteroids. Our results reveal a remarkable variety and complexity of local synaptic circuitry within a chemically defined set of peptidergic neurons. Synaptic transmitter signaling as well as peptidergic paracrine signaling and volume transmission from varicosities can be main signaling modes of peptidergic interneurons depending on the subcellular region. The possibility of region-specific variable signaling modes should be taken into account in connectomic studies that aim to dissect the circuitry underlying insect behavior and physiology, in which peptidergic neurons act as important regulators.
    No preview · Article · Aug 2013 · Frontiers in Neural Circuits
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