1
|
Rohrmann A, Kirby E, Schwanghart W. Accelerated Miocene incision along the Yangtze River driven by headward drainage basin expansion. SCIENCE ADVANCES 2023; 9:eadh1636. [PMID: 37682992 PMCID: PMC10491212 DOI: 10.1126/sciadv.adh1636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 08/09/2023] [Indexed: 09/10/2023]
Abstract
Along the southeastern margin of the Tibetan Plateau, the onset of rapid fluvial incision during the Miocene is commonly attributed to growth of high topography. Recent recognition of lacustrine strata preserved atop interfluves, however, suggest that headward expansion of river networks drove migration of the topographic divide. Here, we explore the impact of this process on fluvial incision along the Yangtze River. Landscape evolution simulations demonstrate that expansion of the Yangtze watershed since the Late Miocene could be responsible for 1 to 2 kilometers of fluvial incision. The distribution of modern knickpoints and river profiles is consistent with this hypothesis. We suggest that increased erosive power associated with capture and basin integration drove accelerated incision during the Late Miocene. Our results imply that eastern Tibet was elevated before middle Cenozoic time and that the tempo of fluvial incision may be out of phase with uplift of plateau topography.
Collapse
Affiliation(s)
- Alexander Rohrmann
- Institute of Geological Sciences, Freie Universität Berlin, Berlin, Germany
| | - Eric Kirby
- Department of Earth, Marine, and Environmental Sciences, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Wolfgang Schwanghart
- Institute of Environmental Science and Geography, University of Potsdam, 14476 Potsdam-Golm, Germany
| |
Collapse
|
2
|
Llagostera P, Comas C, López N. Modeling road traffic safety based on point patterns of wildlife-vehicle collisions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 846:157237. [PMID: 35817101 DOI: 10.1016/j.scitotenv.2022.157237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 06/16/2022] [Accepted: 07/04/2022] [Indexed: 06/15/2023]
Abstract
Wildlife-vehicle collisions represent one of the main coexistence problems that appear between human populations and the environment. In general terms, this affects road safety, wildlife management, and the building of road infrastructures. These accidents are a great danger to the life and safety of car drivers, cause property damage to vehicles, and affect wildlife populations. In this work, we develop a new approach based on algorithms used to obtain minimum paths between vertices in weighted networks to get the optimal (safest) route between two points (departure and destination points) in a road structure based on wildlife-vehicle collision point patterns together with other road variables such as traffic volume (traffic flow information), road speed limits, and vegetation density around roads. For this purpose, we have adapted the road structure into a mathematical linear network as described in the field of Graph Theory and added weights to each linear segment based on the intensity of accidents. Then, the resulting network structure allows us to consider some graph theory methodologies to manipulate and apply different calculations to analyze the network. This new approach has been illustrated with a real data set involving the locations of 491 wildlife-vehicle collisions in a square region (40 km × 40 km) around the city of Lleida, during the period 2010-2014, in the region of Catalonia, North-East of Spain. Our results show the usefulness of our new approach to model road traffic safety based on point patterns of wildlife-vehicle collisions. As such, optimal path selection on linear networks based on wildlife-vehicle collisions can be considered to find the safest path between two pairs of points, avoiding more dangerous routes and even routes containing hotspots of accidents.
Collapse
Affiliation(s)
- P Llagostera
- Department of Mathematics, Universitat de Lleida, St/Jaume II, 69, Lleida 25001, Spain.
| | - C Comas
- Department of Mathematics, Universitat de Lleida, St/Jaume II, 69, Lleida 25001, Spain
| | - N López
- Department of Mathematics, Universitat de Lleida, St/Jaume II, 69, Lleida 25001, Spain
| |
Collapse
|
3
|
Arnone E, Ferraccioli F, Pigolotti C, Sangalli LM. A roughness penalty approach to estimate densities over two-dimensional manifolds. Comput Stat Data Anal 2022. [DOI: 10.1016/j.csda.2022.107527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
|
4
|
Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks. Stat Pap (Berl) 2022. [DOI: 10.1007/s00362-022-01338-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
AbstractPoint processes on linear networks are increasingly being considered to analyse events occurring on particular network-based structures. In this paper, we extend Local Indicators of Spatio-Temporal Association (LISTA) functions to the non-Euclidean space of linear networks, allowing to obtain information on how events relate to nearby events. In particular, we propose the local version of two inhomogeneous second-order statistics for spatio-temporal point processes on linear networks, the K- and the pair correlation functions. We put particular emphasis on the local K-functions, deriving come theoretical results which enable us to show that these LISTA functions are useful for diagnostics of models specified on networks, and can be helpful to assess the goodness-of-fit of different spatio-temporal models fitted to point patterns occurring on linear networks. Our methods do not rely on any particular model assumption on the data, and thus they can be applied for whatever is the underlying model of the process. We finally present a real data analysis of traffic accidents in Medellin (Colombia).
Collapse
|
5
|
Schneble M, Kauermann G. Intensity estimation on geometric networks with penalized splines. Ann Appl Stat 2022. [DOI: 10.1214/21-aoas1522] [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]
Affiliation(s)
- Marc Schneble
- Department of Statistics, Ludwig-Maximilians-Universität Munich
| | - Göran Kauermann
- Department of Statistics, Ludwig-Maximilians-Universität Munich
| |
Collapse
|
6
|
D’Angelo N, Adelfio G, Abbruzzo A, Mateu J. Inhomogeneous spatio-temporal point processes on linear networks for visitors’ stops data. Ann Appl Stat 2022. [DOI: 10.1214/21-aoas1519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Nicoletta D’Angelo
- Dipartimento di Scienze Economiche, Aziendali e Statistiche, Università degli Studi di Palermo
| | - Giada Adelfio
- Dipartimento di Scienze Economiche, Aziendali e Statistiche, Università degli Studi di Palermo
| | - Antonino Abbruzzo
- Dipartimento di Scienze Economiche, Aziendali e Statistiche, Università degli Studi di Palermo
| | - Jorge Mateu
- Department of Mathematics, University Jaume I
| |
Collapse
|
7
|
D’Angelo N, Payares D, Adelfio G, Mateu J. Self-exciting point process modelling of crimes on linear networks. STAT MODEL 2022. [DOI: 10.1177/1471082x221094146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Although there are recent developments for the analysis of first and second-order characteristics of point processes on networks, there are very few attempts in introducing models for network data. Motivated by the analysis of crime data in Bucaramanga (Colombia), we propose a spatiotemporal Hawkes point process model adapted to events living on linear networks. We first consider a non-parametric modelling strategy, for which we follow a non-parametric estimation of both the background and the triggering components. Then we consider a semi-parametric version, including a parametric estimation of the background based on covariates, and a non-parametric one of the triggering effects. Our model can be easily adapted to multi-type processes. Our network model outperforms a planar version, improving the fitting of the self-exciting point process model.
Collapse
Affiliation(s)
- Nicoletta D’Angelo
- Department of Economics, Business and Statistics, University of Palermo, Sicily, Italy
| | - David Payares
- Department of Earth Observation Science, University of Twente, Overijssel, Netherlands
| | - Giada Adelfio
- Department of Economics, Business and Statistics, University of Palermo, Sicily, Italy
| | - Jorge Mateu
- Department of Mathematics, Universitat Jaume I, Valencian Community, Spain
| |
Collapse
|
8
|
Decision-Making Tool for the Selection of Priority Areas for Building Rehabilitation in Barcelona. BUILDINGS 2022. [DOI: 10.3390/buildings12020247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
The promotion of rehabilitation is an urgent necessity in today’s consolidated cities, both due to the need to update their buildings to achieve habitability and safety standards that are required nowadays, as well as to stop the deterioration of buildings in vulnerable environments, where paradoxically the obtainment of economic resources to invest in building maintenance and upgrade is scarcer. Decision making on the delimitation of areas in which the need to invest is higher is extremely complex and often relies on large secondary data studies that are contrasted with local stakeholders’ intuition and knowledge on the ground. Usually, rehabilitation aids are directed to relatively large areas, where a certain need may be found. However, these areas are often excessively wide and specific needs that would require special focus can be diluted in the whole. The current trend of area-based and site-specific rehabilitation programs calls for precise and focused data studies and methodologies. The research presented here provides a methodology for the selection of priority areas to promote rehabilitation in the context of Barcelona’s vulnerable neighborhoods. The selection methodology combines primary and secondary data with a very high level of disaggregation that identifies where the needs are greatest, and it also provides a tool that is still based on primary disaggregated data for the delimitation of areas. The results obtained highlight specific priority areas such as parts of the Raval, Carmel and Besòs-Maresme neighborhoods within larger zones that had been previously defined as vulnerable. The proposed methodology seeks to provide tools to foster evidence-based decision making, thus improving both the understanding of reality and its spatial distribution through data mining techniques and data visualization.
Collapse
|
9
|
Baddeley A, Davies TM, Rakshit S, Nair G, McSwiggan G. Diffusion Smoothing for Spatial Point Patterns. Stat Sci 2022. [DOI: 10.1214/21-sts825] [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]
Affiliation(s)
- Adrian Baddeley
- Adrian Baddeley is John Curtin Distinguished Professor, School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, GPO Box U1987, Perth WA 6845, Australia
| | - Tilman M. Davies
- Tilman M. Davies is Senior Lecturer, Department of Mathematics and Statistics, University of Otago, PO Box 56, Dunedin 9054, New Zealand
| | - Suman Rakshit
- Suman Rakshit is Lecturer, School of Electrical Engineering, Computing and Mathematical Sciences, and Research Fellow, SAGI-West, Curtin University, GPO Box U1987, Perth WA 6845, Australia
| | - Gopalan Nair
- Gopalan Nair is Senior Lecturer, Department of Mathematics and Statistics, University of Western Australia, 35 Stirling Hwy, Nedlands WA 6009, Australia
| | - Greg McSwiggan
- Greg McSwiggan is PhD graduate, Department of Mathematics and Statistics, University of Western Australia, and professional consulting engineer, PO Box 2697 New Farm, Queensland 4005, Australia
| |
Collapse
|
10
|
Analysis of Water Deer Roadkills Using Point Process Modeling in Chungcheongnamdo, South Korea. FORESTS 2022. [DOI: 10.3390/f13020209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The expansion of road networks and increased traffic loads have resulted in an increase in the problem of wildlife roadkill, which has a serious impact on both human safety and the wildlife population. However, roadkill data are collected primarily from the incidental sighting, thus they often lack the true-absence information. This study aims to identify the factors associated with Korean water deer (Hydropotes inermis) roadkill in Korea using the point processing modeling (PPM) approach. Water deer roadkill point data were fitted with explanatory variables derived from forest cover type, topography, and human demography maps and an animal distribution survey. Water deer roadkill showed positive associations with road density, human population density, road width, and water deer detection point density. Slope and elevation showed negative associations with roadkill. The traffic volume and adjacent water deer population may be the major driving factors in roadkill events. The results also imply that the PPM can be a flexible tool for developing roadkill mitigation strategy, providing analytical advantages of roadkill data, such as clarification of model specification and interpretation, while avoiding issues derived from a lack of true-absence information.
Collapse
|
11
|
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
|
12
|
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]
|
13
|
Ferraccioli F, Arnone E, Finos L, Ramsay JO, Sangalli LM. Nonparametric density estimation over complicated domains. J R Stat Soc Series B Stat Methodol 2021. [DOI: 10.1111/rssb.12415] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Federico Ferraccioli
- Department of Statistical Sciences University of Padova Padova Veneto Italy
- MOX—Department of Mathematics Politecnico di Milano Milano Lombardia Italy
| | - Eleonora Arnone
- MOX—Department of Mathematics Politecnico di Milano Milano Lombardia Italy
| | - Livio Finos
- Department of Developmental Psychology and Socialisation University of Padova Padova Veneto Italy
| | | | - Laura M. Sangalli
- MOX—Department of Mathematics Politecnico di Milano Milano Lombardia Italy
| |
Collapse
|
14
|
Chaudhuri S, Moradi M, Mateu J. On the trend detection of time-ordered intensity images of point processes on linear networks. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.1881116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Somnath Chaudhuri
- Institute of New Imaging Technologies (INIT), GEOTEC, University Jaume I, Castellón, Spain
| | - Mehdi Moradi
- Department of Statistics, Computer Science, and Mathematics, and Institute of Advanced Materials and Mathematics (InaMat2), Public University of Navarre, Pamplona, Spain
| | - Jorge Mateu
- Department of Mathematics, University Jaume I, Castellón, Spain
| |
Collapse
|
15
|
|
16
|
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
|
17
|
Briz-Redón Á, Martínez-Ruiz F, Montes F. Identification of differential risk hotspots for collision and vehicle type in a directed linear network. ACCIDENT; ANALYSIS AND PREVENTION 2019; 132:105278. [PMID: 31518763 DOI: 10.1016/j.aap.2019.105278] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 04/03/2019] [Accepted: 08/19/2019] [Indexed: 06/10/2023]
Abstract
Traffic accidents can take place in very different ways and involve a substantially distinct number and types of vehicles. Thus, it is of interest to know which parts of a road structure present an overrepresentation of a specific type of traffic accident, specially for some typologies of collisions and vehicles that tend to trigger more severe consequences for the users being involved. In this study, a spatial approach is followed to estimate the risk that different types of collisions and vehicles present in the central area of Valencia (Spain), considering the accidents observed in this city during the period 2014-2017. A directed spatial linear network representing the non-pedestrian road structure of the area of interest was employed to guarantee an accurate analysis of the point pattern. A kernel density estimation technique was used to approximate the probability of risk along the network for each collision and vehicle type. A procedure based on these estimates and the sample size locally available within the network was designed and tested to determine a set of differential risk hotspots for each typology of accident considered. A Monte Carlo based simulation process was then defined to assess the statistical significance of each of the differential risk hotspots found, allowing the elaboration of rankings of importance and the possible rejection of the least significant ones.
Collapse
Affiliation(s)
- Álvaro Briz-Redón
- Statistics and Operations Research, University of València, C/ Dr. Moliner, 50, 46100 Burjassot Spain.
| | | | - Francisco Montes
- Statistics and Operations Research, University of València, C/ Dr. Moliner, 50, 46100 Burjassot Spain
| |
Collapse
|
18
|
Briz-Redón Á, Martínez-Ruiz F, Montes F. Spatial analysis of traffic accidents near and between road intersections in a directed linear network. ACCIDENT; ANALYSIS AND PREVENTION 2019; 132:105252. [PMID: 31437743 DOI: 10.1016/j.aap.2019.07.028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 07/25/2019] [Accepted: 07/26/2019] [Indexed: 06/10/2023]
Abstract
Although most of the literature on traffic safety analysis has been developed over areal zones, there is a growing interest in using the specific road structure of the region under investigation, which is known as a linear network in the field of spatial statistics. The use of linear networks entails several technical complications, ranging from the accurate location of traffic accidents to the definition of covariates at a spatial micro-level. Therefore, the primary goal of this study was to display a detailed analysis of a dataset of traffic accidents recorded in Valencia (Spain), which were located into a linear network representing more than 30 km of urban road structure corresponding to one district of the city. A set of traffic-related covariates was constructed at the road segment level for performing the analysis. Several issues and methodological approaches that are inherent to linear networks have been shown and discussed. In particular, the network was defined in a way that allowed the explicit investigation of traffic accidents around road intersections and the consideration of traffic flow directionality. Zero-inflated negative binomial count models accounting for spatial heterogeneity were used. Traffic safety at road intersections was specifically taken into account in the analysis by considering the higher variability and number of zeros that can be observed at these road entities and the differential contribution of the covariates depending on the proximity of a road intersection. To complement the results obtained from the count models fitted, coldspots and hotspots along the network were also detected, with explanatory objectives. The models confirmed that spatial heterogeneity, overdispersion and the close presence of road intersections explain the accident counts observed in the road network analyzed. Hotspot detection revealed that several covariates whose contribution was unclear in the modelling approaches may also be affecting accident counts at the road segment level.
Collapse
Affiliation(s)
- Álvaro Briz-Redón
- Statistics and Operations Research, University of Valencia, C/ Dr. Moliner, 50, 46100 Burjassot, Spain.
| | - Francisco Martínez-Ruiz
- Statistics and Operations Research, University of Valencia, C/ Dr. Moliner, 50, 46100 Burjassot, Spain
| | - Francisco Montes
- Statistics and Operations Research, University of Valencia, C/ Dr. Moliner, 50, 46100 Burjassot, Spain
| |
Collapse
|
19
|
Rakshit S, Davies T, Moradi MM, McSwiggan G, Nair G, Mateu J, Baddeley A. Fast Kernel Smoothing of Point Patterns on a Large Network using Two‐dimensional Convolution. Int Stat Rev 2019. [DOI: 10.1111/insr.12327] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
|
20
|
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
|
21
|
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
|
22
|
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
|