Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies
Abstract Background We present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing approaches for creating those models...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-09-01
|
| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1788-4 |
| _version_ | 1828388776619016192 |
|---|---|
| author | Marwan Abdellah Juan Hernando Nicolas Antille Stefan Eilemann Henry Markram Felix Schürmann |
| author_facet | Marwan Abdellah Juan Hernando Nicolas Antille Stefan Eilemann Henry Markram Felix Schürmann |
| author_sort | Marwan Abdellah |
| collection | DOAJ |
| description | Abstract Background We present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing approaches for creating those models are explained, and then, a multi-stage pipeline is discussed to overcome those limitations. Starting from the neuronal morphologies, we create smooth piecewise watertight polygonal models that can be efficiently utilized to synthesize continuous and plausible volumetric models of the neurons with solid voxelization. The somata of the neurons are reconstructed on a physically-plausible basis relying on the physics engine in Blender. Results Our pipeline is applied to create 55 exemplar neurons representing the various morphological types that are reconstructed from the somatsensory cortex of a juvenile rat. The pipeline is then used to reconstruct a volumetric slice of a cortical circuit model that contains ∼210,000 neurons. The applicability of our pipeline to create highly realistic volumetric models of neocortical circuits is demonstrated with an in silico imaging experiment that simulates tissue visualization with brightfield microscopy. The results were evaluated with a group of domain experts to address their demands and also to extend the workflow based on their feedback. Conclusion A systematic workflow is presented to create large scale synthetic tissue models of the neocortical circuitry. This workflow is fundamental to enlarge the scale of in silico neuroscientific optical experiments from several tens of cubic micrometers to a few cubic millimeters. AMS Subject Classification Modelling and Simulation |
| first_indexed | 2024-12-10T06:18:20Z |
| format | Article |
| id | doaj.art-9b9cc0f5af3f488f8307a7acf4dbac5d |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-10T06:18:20Z |
| publishDate | 2017-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-9b9cc0f5af3f488f8307a7acf4dbac5d2022-12-22T01:59:24ZengBMCBMC Bioinformatics1471-21052017-09-0118S10395010.1186/s12859-017-1788-4Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studiesMarwan Abdellah0Juan Hernando1Nicolas Antille2Stefan Eilemann3Henry Markram4Felix Schürmann5Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL)Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL)Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL)Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL)Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL)Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL)Abstract Background We present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing approaches for creating those models are explained, and then, a multi-stage pipeline is discussed to overcome those limitations. Starting from the neuronal morphologies, we create smooth piecewise watertight polygonal models that can be efficiently utilized to synthesize continuous and plausible volumetric models of the neurons with solid voxelization. The somata of the neurons are reconstructed on a physically-plausible basis relying on the physics engine in Blender. Results Our pipeline is applied to create 55 exemplar neurons representing the various morphological types that are reconstructed from the somatsensory cortex of a juvenile rat. The pipeline is then used to reconstruct a volumetric slice of a cortical circuit model that contains ∼210,000 neurons. The applicability of our pipeline to create highly realistic volumetric models of neocortical circuits is demonstrated with an in silico imaging experiment that simulates tissue visualization with brightfield microscopy. The results were evaluated with a group of domain experts to address their demands and also to extend the workflow based on their feedback. Conclusion A systematic workflow is presented to create large scale synthetic tissue models of the neocortical circuitry. This workflow is fundamental to enlarge the scale of in silico neuroscientific optical experiments from several tens of cubic micrometers to a few cubic millimeters. AMS Subject Classification Modelling and Simulationhttp://link.springer.com/article/10.1186/s12859-017-1788-4Modeling and simulationPolygonal and volumetric modelsNeocortical brain modelsIn silico neuroscience |
| spellingShingle | Marwan Abdellah Juan Hernando Nicolas Antille Stefan Eilemann Henry Markram Felix Schürmann Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies BMC Bioinformatics Modeling and simulation Polygonal and volumetric models Neocortical brain models In silico neuroscience |
| title | Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies |
| title_full | Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies |
| title_fullStr | Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies |
| title_full_unstemmed | Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies |
| title_short | Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies |
| title_sort | reconstruction and visualization of large scale volumetric models of neocortical circuits for physically plausible in silico optical studies |
| topic | Modeling and simulation Polygonal and volumetric models Neocortical brain models In silico neuroscience |
| url | http://link.springer.com/article/10.1186/s12859-017-1788-4 |
| work_keys_str_mv | AT marwanabdellah reconstructionandvisualizationoflargescalevolumetricmodelsofneocorticalcircuitsforphysicallyplausibleinsilicoopticalstudies AT juanhernando reconstructionandvisualizationoflargescalevolumetricmodelsofneocorticalcircuitsforphysicallyplausibleinsilicoopticalstudies AT nicolasantille reconstructionandvisualizationoflargescalevolumetricmodelsofneocorticalcircuitsforphysicallyplausibleinsilicoopticalstudies AT stefaneilemann reconstructionandvisualizationoflargescalevolumetricmodelsofneocorticalcircuitsforphysicallyplausibleinsilicoopticalstudies AT henrymarkram reconstructionandvisualizationoflargescalevolumetricmodelsofneocorticalcircuitsforphysicallyplausibleinsilicoopticalstudies AT felixschurmann reconstructionandvisualizationoflargescalevolumetricmodelsofneocorticalcircuitsforphysicallyplausibleinsilicoopticalstudies |