Impact of sampling rate on statistical significance for single subject fMRI connectivity analysis

A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity.     

基于德兴市中药材种植统计数据的时空挖掘分析

目的:对江西省德兴市中药材种植统计数据的空间和时间特征进行挖掘分析,提供研究空间和时间相结合的中药材种植特征分析方法,为指导德兴市中药材生产和宏观决策提供可靠的数据和方法。方法:利用德兴市中药材统计数据与土地利用等数据相结合,在乡镇尺度上通过统计分析、空间自相关分析等方法对德兴市各乡镇中药材种植面积、种类、结构多个空间分异特征及机制进行分析。结果:德兴市各乡镇中药材种植面积、种类和结构在空间上差异很大,种植面积及种类都较多的乡镇土地利用类型主要以耕地和林地为主。2018—2021年,德兴市中药材种植总面积、总产量和总产值都呈逐年递增趋势。结论:研究结果可为德兴市中药产业布局提供数据支撑,有助于政府制定合理的中药材种植规划,确保市场的供需平衡,避免出现供应不足或过剩等情况。     

贵州省2015—2018年涂阳肺结核流行及空间分布特征分析

目的 分析2015—2018年贵州省涂阳肺结核发病的流行及空间分布特征,为全省传染性肺结核防治工作提供依据。方法 数据来源于结核病管理信息系统,整理2015—2018年贵州省88个县（市、区）涂阳肺结核患者登记信息和人口数据,采用ArcGIS 10.0软件构建地理信息数据库、结果可视化、空间自相关分析。结果 2015—2018年贵州省共报告涂阳肺结核45 560例,年均发病率为31.93/10万,总体呈下降趋势,居前3位地区为:安顺、毕节、铜仁市,最低为六盘水市;冬、夏季（1—2月、5—8月）为疫情高发时间,男性发病数均高于女性（发病数比为2.01∶1）,农民、年龄≥60岁人群发病数最多;涂阳肺结核报告发病率全局空间自相关Moran’s I介于0.069～0.254之间（2016、2017年P＜0.05）,热点主要在望谟县,冷点地区主要在花溪、观山湖、万山区。结论 贵州省涂阳肺结核发病存在空间聚集,应对农民、男性、老年患者等高风险人群和高发病率及热点地区给予重点关注和政策倾斜,增加肺结核专项经费和人力资源等的投入,加大宣传教育,开展创新模式有效发现和管理患者,从而降低涂阳肺结核发病率。     

Geographic spatial autocorrelation and United States suicide patterns

Research on aggregated geographical data in such fields as genetics and epidemiology have produced inefficient findings when spatial autocorrelation is present. This inefficiency results from the bias in the standard errors of the regression coefficients for multi-variate studies. It is unclear as to whether the numerous suicide studies that utilize geographical units of analysis am also flawed. The present study employs Odland's test for spatial autocorrelation to ascertain whether this error is present in geographical suicide studies. Two typical studies that employ state and county (parish) data art examined to decide whether spatial autocorrelation limits the findings of these studies. Using a conservative randomization test with Moran's I, it is concluded that for these studies spatial autocorrelation is not a serious problem. However, other weight matrices, and less conservative tests are needed to further support the findings of this paper.     

An accumulator model for spontaneous neural activity prior to self-initiated movement

A gradual buildup of neuronal activity known as the “readiness potential” reliably precedes voluntary self-initiated movements, in the average time locked to movement onset. This buildup is presumed to reflect the final stages of planning and preparation for movement. Here we present a different interpretation of the premovement buildup. We used a leaky stochastic accumulator to model the neural decision of “when” to move in a task where there is no specific temporal cue, but only a general imperative to produce a movement after an unspecified delay on the order of several seconds. According to our model, when the imperative to produce a movement is weak, the precise moment at which the decision threshold is crossed leading to movement is largely determined by spontaneous subthreshold fluctuations in neuronal activity. Time locking to movement onset ensures that these fluctuations appear in the average as a gradual exponential-looking increase in neuronal activity. Our model accounts for the behavioral and electroencephalography data recorded from human subjects performing the task and also makes a specific prediction that we confirmed in a second electroencephalography experiment: Fast responses to temporally unpredictable interruptions should be preceded by a slow negative-going voltage deflection beginning well before the interruption itself, even when the subject was not preparing to move at that particular moment.     

Slowing down as an early warning signal for abrupt climate change

In the Earth's history, periods of relatively stable climate have often been interrupted by sharp transitions to a contrasting state. One explanation for such events of abrupt change is that they happened when the earth system reached a critical tipping point. However, this remains hard to prove for events in the remote past, and it is even more difficult to predict if and when we might reach a tipping point for abrupt climate change in the future. Here, we analyze eight ancient abrupt climate shifts and show that they were all preceded by a characteristic slowing down of the fluctuations starting well before the actual shift. Such slowing down, measured as increased autocorrelation, can be mathematically shown to be a hallmark of tipping points. Therefore, our results imply independent empirical evidence for the idea that past abrupt shifts were associated with the passing of critical thresholds. Because the mechanism causing slowing down is fundamentally inherent to tipping points, it follows that our way to detect slowing down might be used as a universal early warning signal for upcoming catastrophic change. Because tipping points in ecosystems and other complex systems are notoriously hard to predict in other ways, this is a promising perspective.     

2011—2020年安徽省钉螺分布时空分析

目的　分析2011—2020年安徽省钉螺分布时空特征,为全省钉螺精准防控提供参考。方法　收集2011—2020年安徽省实有钉螺面积、新发钉螺面积和感染性钉螺面积等钉螺分布指标并进行描述性分析,对实有和新发钉螺面积进行空间自相关、热点分析、标准差椭圆分析及时空扫描等分析,探索安徽省钉螺聚集与扩散高风险区。结果　2011—2020年,安徽省实有钉螺面积逐渐降低。2020年全省实有钉螺面积26 238.85 hm2,主要分布在湖沼型血吸虫病流行区。各年份间新发钉螺面积波动较大,2016年最高（1 287.65 hm2）;2020年在池州市贵池区新发现1.96 hm2感染性钉螺面积。空间自相关和热点分析显示,2011—2020年安徽省实有钉螺面积分布具有空间聚集性（Z = 3.00 ~ 3.43,P均 < 0.01）,热点主要集中在湖沼型流行区并沿长江南岸分布;冷点主要集中在皖南山区。2011—2020年安徽省新发钉螺面积分布在整体上不存在空间聚集性（Z = -2.20 ~ 1.71,P均> 0.05）,局部呈散点分布。标准差椭圆分析显示,2011—2020年安徽省实有钉螺面积分布相对稳定,与长江流向一致;新发钉螺面积分布重心逐渐从长江安徽段下游向上游移动。时空扫描分析显示,2011—2020年安徽省实有钉螺面积两个高值聚集区以从长江安徽段下游到中游的顺序出现;新发钉螺面积两个高值聚集区聚集时间和范围类似,均分布在山区。结论　2011—2020年安徽省钉螺分布呈空间聚集性,存在向长江南岸、上游聚集的趋势,但山区钉螺扩散问题亦不容忽视,需加强对山区和长江沿岸新发钉螺孳生地的监测力度。     

山东省发热伴血小板减少综合征时空流行特征分析

目的 分析山东省发热伴血小板减少综合征(SFTS)的时空分布特征,为查找重点区域及聚集时间,采取针对性的干预措施,优化卫生资源配置提供科学依据。方法 基于2010-2016年山东省各县(市、区)网络报告的SFTS疫情数据,结合人口数据、地理数据,建立地理信息数据库,采用Open GeoDa 1.2.0软件进行空间自相关分析,采用SaTScan 9.4软件进行时空扫描聚类分析。结果 2010-2016年山东省累计报告SFTS病例2 319例,平均发病率为0.34/10万,累计报告死亡病例230例,平均病死率9.92%,发病数和发病率逐年增多。全局自相关分析显示,2012-2016年SFTS空间分布均具有自相关性,呈聚集性分布, Moran’s I值均为正值(P<0.05);局部自相关分析结果表明,高-高流行区主要位于淄博、泰安、莱芜、威海、烟台等市的相关县区。时空扫描分析发现3个时空聚集区域:1)2012年1月至2015年1月,以烟台市芝罘区为中心点,共覆盖16个县(市、区)(LLR=677.15,RR=11.58,P<0.001)。2)2013年1月至2016年12月,以泰安市新泰市为中心点,共覆盖6个县(市、区)(LLR=457.51,RR=9.25,P<0.001)。3) 2013年1月至2014年1月,以潍坊市安丘市为中心点,共覆盖28个县(市、区)(LLR=142.59, RR=4.97,P<0.001)。结论 山东省发热伴血小板减少综合征疫情分布存在明显的时空聚集特征,主要集中在泰安、莱芜、烟台、威海的相关县(市、区),是我省预防控制该病的重点区域。     

湖北省2008－2012年血吸虫病空间流行分析

目的 分析湖北省血吸虫病流行区县(市、区)级别血吸虫病的流行状况以及空间分布规律. 方法 回顾性分析2008－2012年湖北省血吸虫病流行县(市、区)人群疫情数据资料,并与湖北省GIS地理空间数据库进行匹配,构建湖北省血吸虫病的空间分析数据库.运用全局空间自相关的Moran''s I指标以及局部空间自相关的Getis-Ord Gi^*指标分析湖北省血吸虫病的空间聚集性.结果 2008－2012年湖北省血吸虫病人数、居民血吸虫感染率均呈下降趋势.5年间居民血吸虫感染率的全局空间自相关分析结果有统计学意义(Moran''s I>0,P<0.01).局部空间自相关分析结果显示,居民血吸虫感染率高值聚集县(市、区)数在8～11个,呈现先增加后减少的趋势.高值聚集区主要分布在荆州区、沙市区、江陵县、公安县、石首市、监利县、洪湖市和赤壁市8个县(市、区).结论 2008－2012年湖北省县(市、区)级居民血吸虫感染率分布存在空间自相关,有空间聚集现象,且高值聚集区主要分布在长江流域江汉平原范围.