Meta-analysis of the moral brain: patterns of neural engagement assessed using multilevel kernel density analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 534-547
Author(s):  
Samantha J. Fede ◽  
Kent A. Kiehl
Keyword(s):  
Meta Analysis ◽  
Kernel Density ◽  
Density Analysis ◽  
Kernel Density Analysis ◽  
Multilevel Kernel Density Analysis

scholarly journals The Brain Network for Deductive Reasoning: A Quantitative Meta-analysis of 28 Neuroimaging Studies

2011 ◽  
Vol 23 (11) ◽  
pp. 3483-3497 ◽  
Author(s):  
Jérôme Prado ◽  
Angad Chadha ◽  
James R. Booth
Keyword(s):  
Deductive Reasoning ◽  
Meta Analysis ◽  
Brain Network ◽  
Cognitive Organization ◽  
Quantitative Evidence ◽  
Density Analysis ◽  
Neural Bases ◽  
Kernel Density Analysis ◽  
The Brain ◽  
Multilevel Kernel Density Analysis

Over the course of the past decade, contradictory claims have been made regarding the neural bases of deductive reasoning. Researchers have been puzzled by apparent inconsistencies in the literature. Some have even questioned the effectiveness of the methodology used to study the neural bases of deductive reasoning. However, the idea that neuroimaging findings are inconsistent is not based on any quantitative evidence. Here, we report the results of a quantitative meta-analysis of 28 neuroimaging studies of deductive reasoning published between 1997 and 2010, combining 382 participants. Consistent areas of activations across studies were identified using the multilevel kernel density analysis method. We found that results from neuroimaging studies are more consistent than what has been previously assumed. Overall, studies consistently report activations in specific regions of a left fronto-parietal system, as well as in the left BG. This brain system can be decomposed into three subsystems that are specific to particular types of deductive arguments: relational, categorical, and propositional. These dissociations explain inconstancies in the literature. However, they are incompatible with the notion that deductive reasoning is supported by a single cognitive system relying either on visuospatial or rule-based mechanisms. Our findings provide critical insight into the cognitive organization of deductive reasoning and need to be accounted for by cognitive theories.

scholarly journals Coupling ITO3dE model and GIS for spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing in China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kang-wen Zhu ◽  
Zhi-min Yang ◽  
Lei Huang ◽  
Yu-cheng Chen ◽  
Sheng Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Point Source ◽  
Kernel Density ◽  
Point Source Pollution ◽  
Spatiotemporal Evolution ◽  
Matrix Kernel ◽  
Medium Risk ◽  
Density Analysis ◽  
Kernel Density Analysis ◽  
Non Point Source Pollution

AbstractTo determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an ‘Input-Translate-Output’ three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.40–2.28, 0.41–2.57, and 0.41–2.28, respectively, with the main distribution regions being the western regions of Chongqing (Dazu, Jiangjin, etc.) and other counties such as Dianjiang, Liangping, Kaizhou, Wanzhou, and Zhongxian. The spatiotemporal transition matrix could well exhibit the risk transition situation, and the risks generally showed no changes over time. The proportions of ‘no-risk no-change’, ‘low-risk no-change’, and ‘medium-risk no-change’ were 10.86%, 33.42%, and 17.25%, respectively, accounting for 61.53% of the coverage area of Chongqing. The proportions of risk increase, risk decline, and risk fluctuation were 13.45%, 17.66%, and 7.36%, respectively. Kernel density analysis was suitable to explore high-risk gathering areas. The peak values of kernel density in the three periods were around 1110, suggesting that the maximum gathering degree of medium-risk pattern spots basically showed no changes, but the spatial positions of high-risk gathering areas somehow changed. Getis-Ord Gi* analysis was suitable to explore the relationships between hot and cold spots. Counties with high pollution risks were Yongchuan, Shapingba, Dianjiang, Liangping, northwestern Fengdu, and Zhongxian, while counties with low risks were Chengkou, Wuxi, Wushan, Pengshui, and Rongchang. High-value hot spot zones gradually dominated in the northeast of Chongqing, while low-value cold spot zones gradually dominated in the Midwest. Our results provide a scientific base for the development of strategies to prevent and control AGNPS in Chongqing.

Regional Spatial-Temporal Spread of Citrus Huanglongbing Is Affected by Rain in Florida

2018 ◽  
Vol 108 (12) ◽  
pp. 1420-1428 ◽  
Author(s):  
M. M. Shimwela ◽  
T. S. Schubert ◽  
M. Albritton ◽  
S. E. Halbert ◽  
D. J. Jones ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Incidence ◽  
Kernel Density ◽  
Candidatus Liberibacter Asiaticus ◽  
Candidatus Liberibacter ◽  
Citrus Huanglongbing ◽  
Density Analysis ◽  
Liberibacter Asiaticus ◽  
Kernel Density Analysis ◽  
Temporal Spread

Citrus huanglongbing (HLB), associated with ‘Candidatus Liberibacter asiaticus’ (Las), disseminated by Asian citrus psyllid (ACP), has devastated citrus in Florida since 2005. Data on HLB occurrence were stored in databases (2005 to 2012). Cumulative HLB-positive citrus blocks were subjected to kernel density analysis and kriging. Relative disease incidence per county was calculated by dividing HLB numbers by relative tree numbers and maximum incidence. Spatiotemporal HLB distributions were correlated with weather. Relative HLB incidence correlated positively with rainfall. The focus expansion rate was 1626 m month−1, similar to that in Brazil. Relative HLB incidence in counties with primarily large groves increased at a lower rate (0.24 year−1) than in counties with smaller groves in hotspot areas (0.67 year−1), confirming reports that large-scale HLB management may slow epidemic progress.

Kernel density analysis reveals a halo pattern of breast cancer incidence in Connecticut

2018 ◽  
Vol 26 ◽  
pp. 143-151 ◽  
Author(s):  
Natalya Rybnikova ◽  
Richard G. Stevens ◽  
David I. Gregorio ◽  
Holly Samociuk ◽  
Boris A. Portnov
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Breast Cancer Incidence ◽  
Kernel Density ◽  
Density Analysis ◽  
Kernel Density Analysis

scholarly journals Spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing, China, based on the ITO3dE model and GIS

2020 ◽  
Author(s):  
Kang-wen ZHU ◽  
Zhi-min YANG ◽  
Lei HUANG ◽  
Yu-cheng CHEN ◽  
Sheng ZHANG ◽  
...  
Keyword(s):  
High Risk ◽  
Point Source ◽  
Kernel Density ◽  
Point Source Pollution ◽  
Spatiotemporal Evolution ◽  
Matrix Kernel ◽  
Medium Risk ◽  
Density Analysis ◽  
Kernel Density Analysis ◽  
Non Point Source Pollution

Abstract To determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an ‘Input-Translate-Output’ three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.40–2.28, 0.41–2.57, and 0.41–2.28, respectively, with the main distribution regions being the western regions of Chongqing (Dazu, Jiangjin, etc.) and other counties such as Dianjiang, Liangping, Kaizhou, Wanzhou, and Zhongxian. The spatiotemporal transition matrix could well exhibit the risk transition situation, and the risks generally showed no changes over time. The proportions of ‘no-risk no-change’, ‘low-risk no-change’, and ‘medium-risk no-change’ were 10.86%, 33.42%, and 17.25%, respectively, accounting for 61.53% of the coverage area of Chongqing. The proportions of risk increase, risk decline, and risk fluctuation were 13.45%, 17.66%, and 7.36%, respectively. Kernel density analysis was suitable to explore high-risk gathering areas. The peak values of kernel density in the three periods were around 1,110, suggesting that the maximum gathering degree of medium-risk pattern spots basically showed no changes, but the spatial positions of high-risk gathering areas somehow changed. Getis-Ord Gi* analysis was suitable to explore the relationships between hot and cold spots. Counties with high pollution risks were Yongchuan, Shapingba, Dianjiang, Liangping, northwestern Fengdu, and Zhongxian, while counties with low risks were Chengkou, Wuxi, Wushan, Pengshui, and Rongchang. High-value hot spot zones gradually dominated in the northeast of Chongqing, while low-value cold spot zones gradually dominated in the Midwest. Our results provide a scientific base for the development of strategies to prevent and control AGNPS in Chongqing.

scholarly journals CREMATION VS. INHUMATION: MODELING CULTURAL CHANGES IN FUNERARY PRACTICES FROM THE MESOLITHIC TO THE MIDDLE AGES IN BELGIUM USING KERNEL DENSITY ANALYSIS ON 14C DATA

Radiocarbon ◽  
2020 ◽  
pp. 1-24
Author(s):  
Giacomo Capuzzo ◽  
Christophe Snoeck ◽  
Mathieu Boudin ◽  
Sarah Dalle ◽  
Rica Annaert ◽  
...  
Keyword(s):  
Bronze Age ◽  
Middle Ages ◽  
Kernel Density ◽  
Cultural Changes ◽  
Social Transformations ◽  
Density Analysis ◽  
Funerary Ritual ◽  
Kernel Density Analysis ◽  
Mesolithic Period ◽  
The Middle Ages

ABSTRACT The adoption of a new funerary ritual with all its social and cognitive meanings is of great importance to understanding social transformations of past societies. The first known occurrence of cremation in the territory corresponding to modern Belgium dates back to the Mesolithic period. From the end of the Neolithic onward, the practice of cremation was characterized by periods in which this rite was predominant and periods of contractions, defined by a decrease in the use of this funerary ritual. This paper aims to quantify such phenomenon for the first time by modeling discontinuities in burial practices through kernel density analysis of 1428 radiocarbon (14C) dates from 311 archaeological sites located in Belgium from the Mesolithic to the Middle Ages. Despite possible taphonomic and sampling biases, the results highlight the existence of periods with a large uptake of cremation rite followed by periods of contractions; such discontinuities took place in correlation with changes in the socio-economical structure of local communities, as, for example, during the later Middle Bronze Age and at the end of the Roman Period.

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