Neural Networks of the Mouse Neocortex

Tyagi, Rahul

doi:10.5214/ans.0972.7531.220409

Cited by 89 publications

(185 citation statements)

References 1 publication

(1 reference statement)

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“…However, such exhaustive studies even in mouse only represent a small fraction of the whole brain or retina, on the order of 1 mm 3 (Helmstaedter et al, 2013). In mouse the determination of regional or mesoscopic neuronal structural connectivity is quite advanced and benefits from robust tracing and imaging methods that are implemented in the living brain (Matyas et al, 2010;Oh et al, 2014;Zingg et al, 2014), while tracing in human tissue is restricted to histological samples.…”

Section: The Brain's Connectome Assessed By Multiple Measures and Scalesmentioning

confidence: 99%

“…Recently, the definition of the brain connectomes has proceeded in earnest. A database of mouse brain connectivity based on anterograde tracing (outward axonal projections) has been made available by the Allen Institute (Oh et al, 2014) and UCLA consortia (Zingg et al, 2014). Before initiating a new line of experimentation in mouse, it is now possible to visualize afferent and efferent axonal projections for literally hundreds of brain regions; see Figure 2B for an example of raw data (Oh et al, 2014).…”

Section: The Brain's Connectome Assessed By Multiple Measures and Scalesmentioning

confidence: 99%

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Stroke and the Connectome: How Connectivity Guides Therapeutic Intervention

Silasi

Murphy

2014

Neuron

185

146

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Connections between neurons are affected within 3 min of stroke onset by massive ischemic depolarization and then delayed cell death. Some connections can recover with prompt reperfusion; others associated with the dying infarct do not. Disruption in functional connectivity is due to direct tissue loss and indirect disconnections of remote areas known as diaschisis. Stroke is devastating, yet given the brain's redundant design, collateral surviving networks and their connections are well-positioned to compensate. Our perspective is that new treatments for stroke may involve a rational functional and structural connections-based approach. Surviving, affected, and at-risk networks can be identified and targeted with scenario-specific treatments. Strategies for recovery may include functional inhibition of the intact hemisphere, rerouting of connections, or setpoint-mediated network plasticity. These approaches may be guided by brain imaging and enabled by patient- and injury-specific brain stimulation, rehabilitation, and potential molecule-based strategies to enable new connections.

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Section: The Brain's Connectome Assessed By Multiple Measures and Scalesmentioning

confidence: 99%

Section: The Brain's Connectome Assessed By Multiple Measures and Scalesmentioning

confidence: 99%

Stroke and the Connectome: How Connectivity Guides Therapeutic Intervention

Silasi

Murphy

2014

Neuron

185

146

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“…In this instance, the correspondence would be between fly central complex and mammalian ACA, PTL, and RSP cortical areas, as well as basal ganglia. The relevant interconnections among these regions, ACA, PTL, and RSP [40], and basal ganglia [46][47][48], have all been demonstrated.…”

Section: Information Flow During Behaviorsmentioning

confidence: 90%

“…Strikingly, several network attributes detected in the brain of Drosophila have analogs in the brains of other species, for example the existence of modules, interconnecting hubs, and a densely connected RC. A particularly intriguing comparison is with the network map of the rodent neocortex [40] This map resembles our fly scheme in the convergence of inputs from sensory modalities, visual and auditory in particular, into an interconnected set of structures-anterior cingulate (ACA), posterior parietal (PTL), and retrosplenial (RSP) cortical areas-that have extensive outputs to motor areas and an important role in motor decisions [41][42][43]. Thus, the ACA/ PTL/RSP network may have genetic or further connectivity similarities to the fly auditory/mechanosensory/motor area and deserves further investigation.…”

Section: Discussionmentioning

confidence: 99%

Connectomics-Based Analysis of Information Flow in the Drosophila Brain

et al. 2015

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Understanding the overall patterns of information flow within the brain has become a major goal of neuroscience. In the current study, we produced a first draft of the Drosophila connectome at the mesoscopic scale, reconstructed from 12,995 images of neuron projections collected in FlyCircuit (version 1.1). Neuron polarities were predicted according to morphological criteria, with nodes of the network corresponding to brain regions designated as local processing units (LPUs). The weight of each directed edge linking a pair of LPUs was determined by the number of neuron terminals that connected one LPU to the other. The resulting network showed hierarchical structure and small-world characteristics and consisted of five functional modules that corresponded to sensory modalities (olfactory, mechanoauditory, and two visual) and the pre-motor center. Rich-club organization was present in this network and involved LPUs in all sensory centers, and rich-club members formed a putative motor center of the brain. Major intra- and inter-modular loops were also identified that could play important roles for recurrent and reverberant information flow. The present analysis revealed whole-brain patterns of network structure and information flow. Additionally, we propose that the overall organizational scheme showed fundamental similarities to the network structure of the mammalian brain.

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“…Double co-injection tract tracing techniques allow the identification of both input and output of projections (Thompson and Swanson 2010). Such types of data have been made available recently at high-throughput scale (Zingg et al 2014). We will extend our current study to these types of data in the future.…”

Section: Discussionmentioning

confidence: 99%

Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci

et al. 2014

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The recently released Allen Mouse Brain Connectivity Atlas provides a comprehensive mouse brain neuronal connectivity map from brain-wide injection sites via anterograde tracers coupled with serial two-photon tomography. In addition, the Allen Mouse Brain Atlas offers a genome-wide gene expression database built upon a series of in situ hybridization images, covering comprehensive expression energy of over 4,000 genes in coronal sections and over 20,000 genes in sagittal sections across the whole mouse brain. These concurrent and co-registered datasets provide an unparalleled opportunity for systematically analyzing and characterizing spatial neuronal connectivity and gene expression patterns. Inspired by our recent macroscale neuroimaging results showing that there are significantly different structural and functional connectivity patterns on the gyri and sulci of cerebral cortex in primate brains, the present work systematically examines the axonal connectivity and gene expression patterns on gyri and sulci of the cerebellum. Our results demonstrate that the cerebellum gyri and sulci of rodent brains are significantly different in both axonal connectivity and gene expression patterns. This discovery enriches and extends our prior findings in macroscale neuroimaging studies in primates. Additionally, this work offers novel insights on the molecular and structural architectures of the cerebellum in particular and the brain in general.

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Neural Networks of the Mouse Neocortex

Cited by 89 publications

References 1 publication

Stroke and the Connectome: How Connectivity Guides Therapeutic Intervention

Stroke and the Connectome: How Connectivity Guides Therapeutic Intervention

Connectomics-Based Analysis of Information Flow in the Drosophila Brain

Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci

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