1
|
Hessellund KB, Xu G, Guan Y, Waagepetersen R. Second‐order semi‐parametric inference for multivariate log Gaussian Cox processes. J R Stat Soc Ser C Appl Stat 2021. [DOI: 10.1111/rssc.12530] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
| | - Ganggang Xu
- Department of Management Science University of Miami Coral Gables Florida USA
| | - Yongtao Guan
- Department of Management Science University of Miami Coral Gables Florida USA
| | | |
Collapse
|
2
|
Eckardt M, Mateu J. Second-order and local characteristics of network intensity functions. TEST-SPAIN 2021. [DOI: 10.1007/s11749-020-00720-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
AbstractThe last decade has witnessed an increase of interest in the spatial analysis of structured point patterns over networks whose analysis is challenging because of geometrical complexities and unique methodological problems. In this context, it is essential to incorporate the network specificity into the analysis as the locations of events are restricted to areas covered by line segments. Relying on concepts originating from graph theory, we extend the notions of first-order network intensity functions to second-order and local network intensity functions. We consider two types of local indicators of network association functions which can be understood as adaptations of the primary ideas of local analysis on the plane. We develop the nodewise and cross-hierarchical type of local functions. A real data set on urban disturbances is also presented.
Collapse
|
3
|
Density estimation on a network. Comput Stat Data Anal 2021. [DOI: 10.1016/j.csda.2020.107128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
|
4
|
Hessellund KB, Xu G, Guan Y, Waagepetersen R. Semiparametric Multinomial Logistic Regression for Multivariate Point Pattern Data. J Am Stat Assoc 2021. [DOI: 10.1080/01621459.2020.1863812] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
| | - Ganggang Xu
- Department of Management Science, University of Miami, Coral Gables, FL
| | - Yongtao Guan
- Department of Management Science, University of Miami, Coral Gables, FL
| | | |
Collapse
|
5
|
|
6
|
Uppala M, Handcock MS. Modeling wildfire ignition origins in southern California using linear network point processes. Ann Appl Stat 2020. [DOI: 10.1214/19-aoas1309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
|
7
|
Moradi MM, Mateu J. First- and Second-Order Characteristics of Spatio-Temporal Point Processes on Linear Networks. J Comput Graph Stat 2019. [DOI: 10.1080/10618600.2019.1694524] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- M. Mehdi Moradi
- Institute of New Imaging Technologies, University Jaume I, Castellón, Spain
| | - Jorge Mateu
- Department of Mathematics, University Jaume I, Castellón, Spain
| |
Collapse
|
8
|
Rolnick D, Dyer EL. Generative models and abstractions for large-scale neuroanatomy datasets. Curr Opin Neurobiol 2019; 55:112-120. [PMID: 30878806 PMCID: PMC8449855 DOI: 10.1016/j.conb.2019.02.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 01/09/2019] [Accepted: 02/07/2019] [Indexed: 01/09/2023]
Abstract
Neural datasets are increasing rapidly in both resolution and volume. In neuroanatomy, this trend has been accelerated by innovations in imaging technology. As full datasets are impractical and unnecessary for many applications, it is important to identify abstractions that distill useful features of neural structure, organization, and anatomy. In this review article, we discuss several such abstractions and highlight recent algorithmic advances in working with these models. In particular, we discuss the use of generative models in neuroanatomy; such models may be considered 'meta-abstractions' that capture distributions over other abstractions.
Collapse
Affiliation(s)
- David Rolnick
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Eva L Dyer
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| |
Collapse
|
9
|
Eckardt M, Mateu J. Analysing Multivariate Spatial Point Processes with Continuous Marks: A Graphical Modelling Approach. Int Stat Rev 2018. [DOI: 10.1111/insr.12272] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Matthias Eckardt
- Department of Computer ScienceHumboldt‐Universität zu Berlin Berlin Germany
| | - Jorge Mateu
- Department of MathematicsUniversity Jaume I Castellón Spain
| |
Collapse
|
10
|
Moradi MM, Rodríguez-Cortés FJ, Mateu J. On Kernel-Based Intensity Estimation of Spatial Point Patterns on Linear Networks. J Comput Graph Stat 2018. [DOI: 10.1080/10618600.2017.1360782] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- M. Mehdi Moradi
- Institute of New Imaging Technologies (INIT), University Jaume I, Castellon, Spain
| | | | - Jorge Mateu
- Department of Mathematics, University Jaume I, Castellon, Spain
| |
Collapse
|
11
|
Eckardt M, Mateu J. Point Patterns Occurring on Complex Structures in Space and Space-Time: An Alternative Network Approach. J Comput Graph Stat 2018. [DOI: 10.1080/10618600.2017.1391695] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Matthias Eckardt
- Department of Computer Science, Humboldt Universität zu Berlin, Berlin, Germany
| | - Jorge Mateu
- Department of Mathematics, University Jaume I, Castellón, Spain
| |
Collapse
|
12
|
Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons. PLoS One 2017; 12:e0180400. [PMID: 28662210 PMCID: PMC5491215 DOI: 10.1371/journal.pone.0180400] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2017] [Accepted: 06/15/2017] [Indexed: 01/08/2023] Open
Abstract
We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley’s K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains.
Collapse
|
13
|
Baddeley A, Nair G, Rakshit S, McSwiggan G. “Stationary” point processes are uncommon on linear networks. Stat (Int Stat Inst) 2017. [DOI: 10.1002/sta4.135] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Adrian Baddeley
- Department of Mathematics & Statistics Curtin University GPO Box U1987, Perth 6845 WA Australia
- Data 61, CSIRO Leeuwin Centre 65 Brockway Rd, Floreat Perth 6014 WA Australia
| | - Gopalan Nair
- School of Mathematics & Statistics (M019) University of Western Australia 35 Stirling Hwy, Crawley Perth 6009 WA Australia
| | - Suman Rakshit
- Department of Mathematics & Statistics Curtin University GPO Box U1987, Perth 6845 WA Australia
| | - Greg McSwiggan
- School of Mathematics & Statistics (M019) University of Western Australia 35 Stirling Hwy, Crawley Perth 6009 WA Australia
| |
Collapse
|
14
|
McSwiggan G, Baddeley A, Nair G. Kernel Density Estimation on a Linear Network. Scand Stat Theory Appl 2016. [DOI: 10.1111/sjos.12255] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Greg McSwiggan
- School of Mathematics & Statistics University of Western Australia
| | | | - Gopalan Nair
- School of Mathematics & Statistics University of Western Australia
| |
Collapse
|
15
|
Renner IW, Elith J, Baddeley A, Fithian W, Hastie T, Phillips SJ, Popovic G, Warton DI. Point process models for presence‐only analysis. Methods Ecol Evol 2015. [DOI: 10.1111/2041-210x.12352] [Citation(s) in RCA: 253] [Impact Index Per Article: 28.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Ian W. Renner
- School of Mathematical and Physical Sciences The University of Newcastle University Drive Callaghan NSW 2308 Australia
| | - Jane Elith
- School of BioSciences The University of Melbourne Parkville Vic. 3010 Australia
| | - Adrian Baddeley
- Department of Mathematics & Statistics Curtin University GPO Box U1987 Perth WA 6845 Australia
| | - William Fithian
- Department of Statistics Stanford University 390 Serra Mall Stanford CA 94303 USA
| | - Trevor Hastie
- Department of Statistics Stanford University 390 Serra Mall Stanford CA 94303 USA
| | | | - Gordana Popovic
- School of Mathematics and Statistics and Evolution & Ecology Research Centre The University of New South Wales Sydney NSW 2052 Australia
| | - David I. Warton
- School of Mathematics and Statistics and Evolution & Ecology Research Centre The University of New South Wales Sydney NSW 2052 Australia
| |
Collapse
|
16
|
Jammalamadaka A, Suwannatat P, Fisher SK, Manjunath BS, Höllerer T, Luna G. Characterizing spatial distributions of astrocytes in the mammalian retina. Bioinformatics 2015; 31:2024-31. [PMID: 25686636 DOI: 10.1093/bioinformatics/btv097] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2014] [Accepted: 01/31/2015] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION In addition to being involved in retinal vascular growth, astrocytes play an important role in diseases and injuries, such as glaucomatous neuro-degeneration and retinal detachment. Studying astrocytes, their morphological cell characteristics and their spatial relationships to the surrounding vasculature in the retina may elucidate their role in these conditions. RESULTS Our results show that in normal healthy retinas, the distribution of observed astrocyte cells does not follow a uniform distribution. The cells are significantly more densely packed around the blood vessels than a uniform distribution would predict. We also show that compared with the distribution of all cells, large cells are more dense in the vicinity of veins and toward the optic nerve head whereas smaller cells are often more dense in the vicinity of arteries. We hypothesize that since veinal astrocytes are known to transport toxic metabolic waste away from neurons they may be more critical than arterial astrocytes and therefore require larger cell bodies to process waste more efficiently. AVAILABILITY AND IMPLEMENTATION A 1/8th size down-sampled version of the seven retinal image mosaics described in this article can be found on BISQUE (Kvilekval et al., 2010) at http://bisque.ece.ucsb.edu/client_service/view?resource=http://bisque.ece.ucsb.edu/data_service/dataset/6566968.
Collapse
Affiliation(s)
- Aruna Jammalamadaka
- Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Panuakdet Suwannatat
- Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Steven K Fisher
- Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - B S Manjunath
- Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Tobias Höllerer
- Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Gabriel Luna
- Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| |
Collapse
|