1
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A realistic morpho-anatomical connection strategy for modelling full-scale point-neuron microcircuits. Sci Rep 2022; 12:13864. [PMID: 35974119 PMCID: PMC9381785 DOI: 10.1038/s41598-022-18024-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 08/03/2022] [Indexed: 01/03/2023] Open
Abstract
The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.
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2
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Reconstruction of the Hippocampus. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1359:261-283. [DOI: 10.1007/978-3-030-89439-9_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
AbstractThe hippocampus is a widely studied brain region thought to play an important role in higher cognitive functions such as learning, memory, and navigation. The amount of data on this region increases every day and delineates a complex and fragmented picture, but an integrated understanding of hippocampal function remains elusive. Computational methods can help to move the research forward, and reconstructing a full-scale model of the hippocampus is a challenging yet feasible task that the research community should undertake.In this chapter, we present strategies for reconstructing a large-scale model of the hippocampus. Based on a previously published approach to reconstruct and simulate brain tissue, which is also explained in Chap. 10, we discuss the characteristics of the hippocampus in the light of its special anatomical and physiological features, data availability, and existing large-scale hippocampus models. A large-scale model of the hippocampus is a compound model of several building blocks: ion channels, morphologies, single cell models, connections, synapses. We discuss each of those building blocks separately and discuss how to merge them back and simulate the resulting network model.
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3
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Chou ZZ, Yu GJ, Berger TW. Generation of Granule Cell Dendritic Morphologies by Estimating the Spatial Heterogeneity of Dendritic Branching. Front Comput Neurosci 2020; 14:23. [PMID: 32327990 PMCID: PMC7160759 DOI: 10.3389/fncom.2020.00023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 03/13/2020] [Indexed: 11/13/2022] Open
Abstract
Biological realism of dendritic morphologies is important for simulating electrical stimulation of brain tissue. By adding point process modeling and conditional sampling to existing generation strategies, we provide a novel means of reproducing the nuanced branching behavior that occurs in different layers of granule cell dendritic morphologies. In this study, a heterogeneous Poisson point process was used to simulate branching events. Conditional distributions were then used to select branch angles depending on the orthogonal distance to the somatic plane. The proposed method was compared to an existing generation tool and a control version of the proposed method that used a homogeneous Poisson point process. Morphologies were generated with each method and then compared to a set of digitally reconstructed neurons. The introduction of a conditionally dependent branching rate resulted in the generation of morphologies that more accurately reproduced the emergent properties of dendritic material per layer, Sholl intersections, and proximal passive current flow. Conditional dependence was critically important for the generation of realistic granule cell dendritic morphologies.
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Affiliation(s)
- Zane Z Chou
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Gene J Yu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Theodore W Berger
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
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4
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Mishra P, Narayanan R. Heterogeneities in intrinsic excitability and frequency-dependent response properties of granule cells across the blades of the rat dentate gyrus. J Neurophysiol 2020; 123:755-772. [PMID: 31913748 PMCID: PMC7052640 DOI: 10.1152/jn.00443.2019] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 12/25/2019] [Accepted: 01/07/2020] [Indexed: 12/18/2022] Open
Abstract
The dentate gyrus (DG), the input gate to the hippocampus proper, is anatomically segregated into three different sectors, namely, the suprapyramidal blade, the crest region, and the infrapyramidal blade. Although there are well-established differences between these sectors in terms of neuronal morphology, connectivity patterns, and activity levels, differences in electrophysiological properties of granule cells within these sectors have remained unexplored. Here, employing somatic whole cell patch-clamp recordings from the rat DG, we demonstrate that granule cells in these sectors manifest considerable heterogeneities in their intrinsic excitability, temporal summation, action potential characteristics, and frequency-dependent response properties. Across sectors, these neurons showed positive temporal summation of their responses to inputs mimicking excitatory postsynaptic currents and showed little to no sag in their voltage responses to pulse currents. Consistently, the impedance amplitude profile manifested low-pass characteristics and the impedance phase profile lacked positive phase values at all measured frequencies and voltages and for all sectors. Granule cells in all sectors exhibited class I excitability, with broadly linear firing rate profiles, and granule cells in the crest region fired significantly fewer action potentials compared with those in the infrapyramidal blade. Finally, we found weak pairwise correlations across the 18 different measurements obtained individually from each of the three sectors, providing evidence that these measurements are indeed reporting distinct aspects of neuronal physiology. Together, our analyses show that granule cells act as integrators of afferent information and emphasize the need to account for the considerable physiological heterogeneities in assessing their roles in information encoding and processing.NEW & NOTEWORTHY We employed whole cell patch-clamp recordings from granule cells in the three subregions of the rat dentate gyrus to demonstrate considerable heterogeneities in their intrinsic excitability, temporal summation, action potential characteristics, and frequency-dependent response properties. Across sectors, granule cells did not express membrane potential resonance, and their impedance profiles lacked inductive phase leads at all measured frequencies. Our analyses also show that granule cells manifest class I excitability characteristics, categorizing them as integrators of afferent information.
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Affiliation(s)
- Poonam Mishra
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
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5
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A Network Model Reveals That the Experimentally Observed Switch of the Granule Cell Phenotype During Epilepsy Can Maintain the Pattern Separation Function of the Dentate Gyrus. ACTA ACUST UNITED AC 2019. [DOI: 10.1007/978-3-319-99103-0_23] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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6
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Kumaraswamy A, Kai K, Ai H, Ikeno H, Wachtler T. Spatial registration of neuron morphologies based on maximization of volume overlap. BMC Bioinformatics 2018; 19:143. [PMID: 29669537 PMCID: PMC5907365 DOI: 10.1186/s12859-018-2136-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 03/26/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Morphological features are widely used in the study of neuronal function and pathology. Invertebrate neurons are often structurally stereotypical, showing little variance in gross spatial features but larger variance in their fine features. Such variability can be quantified using detailed spatial analysis, which however requires the morphologies to be registered to a common frame of reference. RESULTS We outline here new algorithms - Reg-MaxS and Reg-MaxS-N - for co-registering pairs and groups of morphologies, respectively. Reg-MaxS applies a sequence of translation, rotation and scaling transformations, estimating at each step the transformation parameters that maximize spatial overlap between the volumes occupied by the morphologies. We test this algorithm with synthetic morphologies, showing that it can account for a wide range of transformation differences and is robust to noise. Reg-MaxS-N co-registers groups of more than two morphologies by iteratively calculating an average volume and registering all morphologies to this average using Reg-MaxS. We test Reg-MaxS-N using five groups of morphologies from the Droshophila melanogaster brain and identify the cases for which it outperforms existing algorithms and produce morphologies very similar to those obtained from registration to a standard brain atlas. CONCLUSIONS We have described and tested algorithms for co-registering pairs and groups of neuron morphologies. We have demonstrated their application to spatial comparison of stereotypic morphologies and calculation of dendritic density profiles, showing how our algorithms for registering neuron morphologies can enable new approaches in comparative morphological analyses and visualization.
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Affiliation(s)
- Ajayrama Kumaraswamy
- Department of Biology II, Ludwig-Maximilians-Universität München, Grosshadernerstr, 2, Planegg-Martinsried, 82152, Germany.
| | - Kazuki Kai
- Department of Earth System Science, Fukuoka University, 8-19-1 Nanakuma, Jonan-ku, Fukuoka-shi, Fukuoka, 814-0180, Japan
| | - Hiroyuki Ai
- Department of Earth System Science, Fukuoka University, 8-19-1 Nanakuma, Jonan-ku, Fukuoka-shi, Fukuoka, 814-0180, Japan
| | - Hidetoshi Ikeno
- School of Human Science and Environment, University of Hyogo, 1-1-12 Shinazaike-Honcho, Himeji, 670-0092, Hyogo, Japan
| | - Thomas Wachtler
- Department of Biology II, Ludwig-Maximilians-Universität München, Grosshadernerstr, 2, Planegg-Martinsried, 82152, Germany
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7
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Rougier NP. A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds. Front Neuroinform 2018; 12:12. [PMID: 29615887 PMCID: PMC5869184 DOI: 10.3389/fninf.2018.00012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Accepted: 02/27/2018] [Indexed: 11/13/2022] Open
Abstract
We introduce a graphical method originating from the computer graphics domain that is used for the arbitrary placement of cells over a two-dimensional manifold. Using a bitmap image whose luminance provides cell density, this method guarantees a discrete distribution of the positions of the cells respecting the local density. This method scales to any number of cells, allows one to specify arbitrary enclosing shapes and provides a scalable and versatile alternative to the more classical assumption of a uniform spatial distribution. The method is illustrated on a discrete homogeneous neural field, on the distribution of cones and rods in the retina and on the neural density of a flattened piece of cortex.
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Affiliation(s)
- Nicolas P Rougier
- UMR5293 Institut des Maladies Neurodégénératives (IMN), Bordeaux, France.,UMR5800 Laboratoire Bordelais de Recherche en Informatique (LaBRI), Talence, France.,Inria Bordeaux - Sud-Ouest Research Centre, Talence, France
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8
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Beining M, Mongiat LA, Schwarzacher SW, Cuntz H, Jedlicka P. T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells. eLife 2017; 6:e26517. [PMID: 29165247 PMCID: PMC5737656 DOI: 10.7554/elife.26517] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 11/21/2017] [Indexed: 12/18/2022] Open
Abstract
Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.
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Affiliation(s)
- Marcel Beining
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurtGermany
- Frankfurt Institute for Advanced StudiesFrankfurtGermany
- Institute of Clinical Neuroanatomy, Neuroscience CenterGoethe UniversityFrankfurtGermany
- Faculty of BiosciencesGoethe UniversityFrankfurtGermany
| | - Lucas Alberto Mongiat
- Instituto de Investigación en Biodiversidad y MedioambienteUniversidad Nacional del Comahue-CONICETSan Carlos de BarilocheArgentina
| | | | - Hermann Cuntz
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurtGermany
- Frankfurt Institute for Advanced StudiesFrankfurtGermany
| | - Peter Jedlicka
- Institute of Clinical Neuroanatomy, Neuroscience CenterGoethe UniversityFrankfurtGermany
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9
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Zandt BJ, Losnegård A, Hodneland E, Veruki ML, Lundervold A, Hartveit E. Semi-automatic 3D morphological reconstruction of neurons with densely branching morphology: Application to retinal AII amacrine cells imaged with multi-photon excitation microscopy. J Neurosci Methods 2017; 279:101-118. [PMID: 28115187 DOI: 10.1016/j.jneumeth.2017.01.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Revised: 01/10/2017] [Accepted: 01/11/2017] [Indexed: 01/30/2023]
Abstract
BACKGROUND Accurate reconstruction of the morphology of single neurons is important for morphometric studies and for developing compartmental models. However, manual morphological reconstruction can be extremely time-consuming and error-prone and algorithms for automatic reconstruction can be challenged when applied to neurons with a high density of extensively branching processes. NEW METHOD We present a procedure for semi-automatic reconstruction specifically adapted for densely branching neurons such as the AII amacrine cell found in mammalian retinas. We used whole-cell recording to fill AII amacrine cells in rat retinal slices with fluorescent dyes and acquired digital image stacks with multi-photon excitation microscopy. Our reconstruction algorithm combines elements of existing procedures, with segmentation based on adaptive thresholding and reconstruction based on a minimal spanning tree. We improved this workflow with an algorithm that reconnects neuron segments that are disconnected after adaptive thresholding, using paths extracted from the image stacks with the Fast Marching method. RESULTS By reducing the likelihood that disconnected segments were incorrectly connected to neighboring segments, our procedure generated excellent morphological reconstructions of AII amacrine cells. COMPARISON WITH EXISTING METHODS Reconstructing an AII amacrine cell required about 2h computing time, compared to 2-4days for manual reconstruction. To evaluate the performance of our method relative to manual reconstruction, we performed detailed analysis using a measure of tree structure similarity (DIADEM score), the degree of projection area overlap (Dice coefficient), and branch statistics. CONCLUSIONS We expect our procedure to be generally useful for morphological reconstruction of neurons filled with fluorescent dyes.
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Affiliation(s)
- Bas-Jan Zandt
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Are Losnegård
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | | | | | - Arvid Lundervold
- Department of Biomedicine, University of Bergen, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Espen Hartveit
- Department of Biomedicine, University of Bergen, Bergen, Norway.
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10
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Zandt BJ, Liu JH, Veruki ML, Hartveit E. AII amacrine cells: quantitative reconstruction and morphometric analysis of electrophysiologically identified cells in live rat retinal slices imaged with multi-photon excitation microscopy. Brain Struct Funct 2017; 222:151-182. [PMID: 26951289 PMCID: PMC5225199 DOI: 10.1007/s00429-016-1206-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 02/20/2016] [Indexed: 11/01/2022]
Abstract
AII amacrine cells have been found in all mammalian retinas examined and play an important role for visual processing under both scotopic and photopic conditions. Whereas ultrastructural investigations have provided a detailed understanding of synaptic connectivity, there is little information available with respect to quantitative properties and variation of cellular morphology. Here, we performed whole-cell recordings from AII amacrine cells in rat retinal slices and filled the cells with fluorescent dyes. Multi-photon excitation microscopy was used to acquire image stacks and after deconvolution, we performed quantitative morphological reconstruction by computer-aided manual tracing. We reconstructed and performed morphometric analysis on 43 AII amacrine cells, with a focus on branching pattern, dendritic lengths and diameters, surface area, and number and distribution of dendritic varicosities. Compared to previous descriptions, the most surprising result was the considerable extent of branching, with the maximum branch order ranging from approximately 10-40. We found that AII amacrine cells conform to a recently described general structural design principle for neural arbors, where arbor density decreases proportionally to increasing territory size. We confirmed and quantified the bi-stratified morphology of AII amacrine cells by analyzing the arborizations as a function of retinal localization or with Sholl spheres. Principal component and cluster analysis revealed no evidence for morphological subtypes of AII amacrines. These results establish a database of morphometric properties important for studies of development, regeneration, degeneration, and disease processes, as well as a workflow compatible with compartmental modeling.
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Affiliation(s)
- Bas-Jan Zandt
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5009, Bergen, Norway
| | - Jian Hao Liu
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5009, Bergen, Norway
| | - Margaret Lin Veruki
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5009, Bergen, Norway
| | - Espen Hartveit
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5009, Bergen, Norway.
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11
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Bezaire MJ, Raikov I, Burk K, Vyas D, Soltesz I. Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit. eLife 2016; 5:e18566. [PMID: 28009257 DOI: 10.7554/elife.18566.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2016] [Accepted: 12/15/2016] [Indexed: 05/25/2023] Open
Abstract
The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations.
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Affiliation(s)
- Marianne J Bezaire
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
| | - Ivan Raikov
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
- Department of Neurosurgery, Stanford University, Stanford, United States
| | - Kelly Burk
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
| | - Dhrumil Vyas
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, United States
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12
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Bezaire MJ, Raikov I, Burk K, Vyas D, Soltesz I. Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit. eLife 2016; 5. [PMID: 28009257 PMCID: PMC5313080 DOI: 10.7554/elife.18566] [Citation(s) in RCA: 117] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2016] [Accepted: 12/15/2016] [Indexed: 12/16/2022] Open
Abstract
The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations. DOI:http://dx.doi.org/10.7554/eLife.18566.001
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Affiliation(s)
- Marianne J Bezaire
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
| | - Ivan Raikov
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States.,Department of Neurosurgery, Stanford University, Stanford, United States
| | - Kelly Burk
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
| | - Dhrumil Vyas
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, United States
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13
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Beining M, Jungenitz T, Radic T, Deller T, Cuntz H, Jedlicka P, Schwarzacher SW. Adult-born dentate granule cells show a critical period of dendritic reorganization and are distinct from developmentally born cells. Brain Struct Funct 2016; 222:1427-1446. [PMID: 27514866 DOI: 10.1007/s00429-016-1285-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Accepted: 08/02/2016] [Indexed: 02/05/2023]
Abstract
Adult-born dentate granule cells (abGCs) exhibit a critical developmental phase during function integration. The time window of this phase is debated and whether abGCs become indistinguishable from developmentally born mature granule cells (mGCs) is uncertain. We analyzed complete dendritic reconstructions from abGCs and mGCs using viral labeling. AbGCs from 21-77 days post intrahippocampal injection (dpi) exhibited comparable dendritic arbors, suggesting that structural maturation precedes functional integration. In contrast, significant structural differences were found compared to mGCs: AbGCs had more curved dendrites, more short terminal segments, a different branching pattern, and more proximal terminal branches. Morphological modeling attributed these differences to developmental dendritic pruning and postnatal growth of the dentate gyrus. We further correlated GC morphologies with the responsiveness to unilateral medial perforant path stimulation using the immediate-early gene Arc as a marker of synaptic activation. Only abGCs at 28 and 35 dpi but neither old abGCs nor mGCs responded to stimulation with a remodeling of their dendritic arbor. Summarized, abGCs stay distinct from mGCs and their dendritic arbor can be shaped by afferent activity during a narrow critical time window.
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Affiliation(s)
- Marcel Beining
- Institute of Clinical Neuroanatomy, Goethe University, 60528, Frankfurt am Main, Germany. .,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Deutschordenstr. 46, 60528, Frankfurt am Main, Germany. .,Frankfurt Institute for Advanced Studies (FIAS), 60438, Frankfurt am Main, Germany.
| | - Tassilo Jungenitz
- Institute of Clinical Neuroanatomy, Goethe University, 60528, Frankfurt am Main, Germany
| | - Tijana Radic
- Institute of Clinical Neuroanatomy, Goethe University, 60528, Frankfurt am Main, Germany
| | - Thomas Deller
- Institute of Clinical Neuroanatomy, Goethe University, 60528, Frankfurt am Main, Germany
| | - Hermann Cuntz
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Deutschordenstr. 46, 60528, Frankfurt am Main, Germany.,Frankfurt Institute for Advanced Studies (FIAS), 60438, Frankfurt am Main, Germany
| | - Peter Jedlicka
- Institute of Clinical Neuroanatomy, Goethe University, 60528, Frankfurt am Main, Germany
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14
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Anton-Sanchez L, Bielza C, Benavides-Piccione R, DeFelipe J, Larrañaga P. Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons. Neuroinformatics 2016; 14:453-64. [PMID: 27345531 PMCID: PMC5010609 DOI: 10.1007/s12021-016-9309-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
The way in which a neuronal tree expands plays an important role in its functional and computational characteristics. We aimed to study the existence of an optimal neuronal design for different types of cortical GABAergic neurons. To do this, we hypothesized that both the axonal and dendritic trees of individual neurons optimize brain connectivity in terms of wiring length. We took the branching points of real three-dimensional neuronal reconstructions of the axonal and dendritic trees of different types of cortical interneurons and searched for the minimal wiring arborization structure that respects the branching points. We compared the minimal wiring arborization with real axonal and dendritic trees. We tested this optimization problem using a new approach based on graph theory and evolutionary computation techniques. We concluded that neuronal wiring is near-optimal in most of the tested neurons, although the wiring length of dendritic trees is generally nearer to the optimum. Therefore, wiring economy is related to the way in which neuronal arborizations grow irrespective of the marked differences in the morphology of the examined interneurons.
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Affiliation(s)
- Laura Anton-Sanchez
- Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Madrid, Spain.
| | - Concha Bielza
- Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Madrid, Spain
| | - Ruth Benavides-Piccione
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain.,Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain.,Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain
| | - Pedro Larrañaga
- Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Madrid, Spain
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15
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Budd JML, Cuntz H, Eglen SJ, Krieger P. Editorial: Quantitative Analysis of Neuroanatomy. Front Neuroanat 2015; 9:143. [PMID: 26617494 PMCID: PMC4641246 DOI: 10.3389/fnana.2015.00143] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2015] [Accepted: 10/26/2015] [Indexed: 11/13/2022] Open
Affiliation(s)
- Julian M L Budd
- Department of Informatics, School of Engineering and Informatics, University of Sussex Brighton, UK
| | - Hermann Cuntz
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society Frankfurt/Main, Germany ; Frankfurt Institute for Advanced Studies Frankfurt/Main, Germany
| | - Stephen J Eglen
- Department of Applied Mathematics and Theoretical Physics, Cambridge Computational Biology Institute, University of Cambridge Cambridge, UK
| | - Patrik Krieger
- Department of Systems Neuroscience, Medical Faculty, Ruhr University Bochum Bochum, Germany
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Bui A, Kim HK, Maroso M, Soltesz I. Microcircuits in Epilepsy: Heterogeneity and Hub Cells in Network Synchronization. Cold Spring Harb Perspect Med 2015; 5:5/11/a022855. [PMID: 26525454 DOI: 10.1101/cshperspect.a022855] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Epilepsy is a complex disorder involving neurological alterations that lead to the pathological development of spontaneous, recurrent seizures. For decades, seizures were thought to be largely repetitive, and had been examined at the macrocircuit level using electrophysiological recordings. However, research mapping the dynamics of large neuronal populations has revealed that seizures are not simply recurrent bursts of hypersynchrony. Instead, it is becoming clear that seizures involve a complex interplay of different neurons and circuits. Herein, we will review studies examining microcircuit changes that may underlie network hyperexcitability, discussing observations from network theory, computational modeling, and optogenetics. We will delve into the idea of hub cells as pathological centers for seizure activity, and will explore optogenetics as a novel avenue to target and treat pathological circuits. Finally, we will conclude with a discussion on future directions in the field.
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Affiliation(s)
- Anh Bui
- Department of Anatomy and Neurobiology, University of California, Irvine, California 92697
| | - Hannah K Kim
- Department of Anatomy and Neurobiology, University of California, Irvine, California 92697
| | - Mattia Maroso
- Department of Anatomy and Neurobiology, University of California, Irvine, California 92697
| | - Ivan Soltesz
- Department of Anatomy and Neurobiology, University of California, Irvine, California 92697
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