Accounting for Time Series Errors in Partially Linear Model With Single- or Multiple-Runs

This article concerns statistical estimation of the partially linear model (PLM) for time course measurements, which are temporally correlated and allow multiple-runs for repeated measurements to enhance experimental accuracy without extending the number of time points within each trial. Such features arise naturally from biomedical data, for example, in brain fMRI, and call for special treatment beyond classical methods in either a purely nonparametric regression model or a PLM with independent errors. We develop a stepwise procedure for estimating the parametric and nonparametric components of the multiple-run PLM and making inference for parameters of interest, adaptive to either single- or multiple-run, in the presence of error temporal dependence. Simulation study and real fMRI data applications illustrate the computational simplicity and effectiveness of the proposed methods. Supplementary material for this article is available online.     

Hippocampus＇s role in forming ＂task-related＂ associations： Flashing to the things you are looking for

Eichenbaum and colleagues observed that the same place did or did not activate the ＂goal-approach＂ cells in hippocampus depending on whether the place was the way for rats to approach specific goal. Parallel with this, the present neuroimage study revealed that, the same type of items could activate the hippocampus more when it was related to the task at hand than when it not. Participants were scanned by fMRI while they made judgments on the type of relationships contained in the word-pairs （e.g., Does the word pair, ＂furniture-table＂, contain a ＂category-exemplar＂ relationship？）. Event-related analysis revealed that the forming of ＂task-related＂ association activated hippocampus more than that of ＂task-unrelated＂, even if it was the same type of items, and, this hippocampal difference was not caused by the different judgment requirements, nor by the effects of ＂yes＂ response. Consistently, the post-judgment cued-recall test exhibited a better retrieval performance for ＂task-related＂ associations than for the same type but ＂task-unrelated＂ associations. Results also showed that, the semantic relatedness between the to-be-associated individual words （e.g., the related word pair ＂healthy-hospital＂ versus the unrelated word pair ＂price-way＂） was not enough to activate the hippocampus when it was ＂task-unrelated＂. Generally, we proposed that, through participating in forming of ＂task-related＂ associations and consolidating of episodic memory, hippocampus enabled the organism to keep the information that owned great survival values in mind for future usage.     

Sparse representation of global features of visual images in human primary visual cortex: Evidence from fMRI

In fMRI experiments on object representation in visual cortex, we designed two types of stimuli： one is the gray face image and its line drawing, and the other is the illusion and its corresponding completed illusion. Both of them have the same global features with different minute details so that the results of fMRI experiments can be compared with each other. The first kind of visual stimuli was used in a block design fMRI experiment, and the second was used in an event-related fMRI experiment. Comparing and analyzing interesting visual cortex activity patterns and blood oxygenation level dependent （BOLD）- fMRI signal, we obtained results to show some invariance of global features of visual images. A plausible explanation about the invariant mechanism is related with the cooperation of synchronized response to the global features of the visual image with a feedback of shape perception from higher cortex to cortex V1, namely the integration of global features and embodiment of sparse representation and distributed population code.     

The task dependent interaction of the deactivation regions

Although deactivation has been found frequently in former functional brain imaging researches, only recently has it become a focus of systematic study because of its not well understood physiological mechanism. However, most of the researches concentrated on the brain areas that would present deactivation, and, to our knowledge, the deactivation connectivity between these brain areas during the cognitive tasks has rarely been reported in literature. In this work, using the functional connectivity method WlCA （within-condition interregional covariance analysis）, we analyzed the deactivations in two different cognitive tasks symbol orientation and number comparison. The results revealed deactivations in the posterior cingulate, precuneus, anterior cingulate and prefrontal cortex in both tasks. However, the interaction between the deactivated regions shows many differences. Our result further indicates that the potential implication of special deactivation connectivity may be related to the different task or attention resource. Further research is needed to clarify the exact reason.     

A new quantitative analysis of significant timing differences between externally cued and self-initiated motor tasks in an fMRI study

It is generally accepted that the temporal resolution of blood oxygenation level dependent functional MRI is limited due to the inherent latency and longevity of the haemodynamic response. However, in this study we introduce a technique for measurement of timing differences from within the same brain region in two (or more) separate tasks that allows accurate determination of cortical timing differences 200 ms. Our technique, based on a novel use of linear regression analysis, is shown to yield accurate results both in simulated and experimental data. We show that cortical timing differences measured using fMRI are consistent with published electrophysiological results. Measurement of timing differences using this technique could prove a useful strategy for identifying neural network components in a wide range of cognitive paradigms.     

A serial functional connectivity MRI study in healthy individuals assessing the variability of connectivity measures: reduced interhemispheric connectivity in the motor network during continuous performance

To date, little data is available on the reproducibility of functional connectivity MRI (fcMRI) studies. Here, we tested the variability and reproducibility of both the functional connectivity itself and different statistical methods to analyze this phenomenon. In the main part of our study, we repeatedly examined two healthy subjects in 10 sessions over 6 months with fcMRI. Cortical areas involved in motor function were examined under two different cognitive states: during continuous performance (CP) of a flexion/extension task of the fingers of the right hand and while subjects were at rest. Connectivity to left primary motor cortex (lSM1) was calculated by correlation analysis. The resulting correlation coefficients were transformed to z-scores of the standard normal distribution. For each subject, multisession statistical analyses were carried out with the z-score maps of the resting state (RS) and the CP experiments. First, voxel based t tests between the two groups of fcMRI experiments were performed. Second, ROI analyses were carried out for contralateral right SM1 and for supplementary motor area (SMA). For both ROI, mean and maximum z-score were calculated for each experiment. Also, the fraction of significantly (P<.05) correlated voxels (FCV) in each ROI was calculated. To evaluate the differences between the RS and the CP condition, paired t tests were performed for the mean and maximum z-scores, and Wilcoxon signed ranks tests for matched pairs were carried out for the FCV. All statistical methods and connectivity measures under investigation yielded a distinct loss in left–right SM1 connectivity under the CP condition. For SMA, interindividual differences were apparent. We therefore repeated the fcMRI experiments and the ROI analyses in a group of seven healthy subjects (including the two subjects of the main study). In this substudy, we were able to verify the reduction of left–right SM1 connectivity during unilateral performance. Still, the direction of SMA to lSM1 connectivity change during the CP condition remained undefined as four subjects showed a connectivity increase and three showed a decrease. In summary, we were able to demonstrate a distinct reduction in left–right SM1 synchrony in the CP condition compared to the RS both in the longitudinal and in the multisubject study. This effect was reproducible with all statistical methods and all measures of connectivity under investigation. We conclude that despite intra- and interindividual variability, serial and cross-sectional assessment of functional connectivity reveals stable and reliable results.     

融合t-分布随机邻域嵌入与自动谱聚类的脑功能精细分区方法

本文针对目前脑功能分区不够准确的问题，基于静息态功能磁共振数据，提出了一种融合t-分布随机邻域嵌入（t-SNE）与自动谱聚类（ASC）的人脑功能精细分区的算法.首先，基于静息态功能磁共振图像，对需功能划分的脑区与全脑的时间序列作相关分析，得到需划分脑区的功能连接模式；然后，利用t-SNE算法提取高维功能连接模式特征；最后，通过基于本征间隙的ASC算法自动确定聚类数目，并对降维后的脑区特征分类，得到精细划分的脑亚区.模拟种子区域上的实验结果表明，相较谱聚类算法，以及结合主成分分析的谱聚类算法，本文方法对脑功能体素划分更优.进一步将本方法应用到真实人脑的功能分区中，成功地将海马旁回分为左右半球各3个亚区.本研究表明使用t-SNE与ASC融合的算法可提高脑功能分区准确性，是脑功能精细分区、进而构建脑功能图谱的一种有效方法.     

Input permutation method to detect active voxels in fMRI study

Correctly identifying voxels or regions of interest (ROI) that actively respond to a given stimulus is often an important objective/step in many functional magnetic resonance imaging (fMRI) studies. In this article, we study a nonparametric method to detect active voxels, which makes minimal assumption about the distribution of blood oxygen level-dependent (BOLD) signals. Our proposal has several interesting features. It uses time lagged correlation to take into account the delay in response to the stimulus, due to hemodynamic variations. We introduce an input permutation method (IPM), a type of block permutation method, to approximate the null distribution of the test statistic. Also, we propose to pool the permutation-derived statistics of preselected voxels for a better approximation to the null distribution. Finally, we control multiple testing error rate using the local false discovery rate (FDR) by Efron [Correlation and large-scale simultaneous hypothesis testing. J Am Stat Assoc 102 (2007) 93–103] and Park et al. [Estimation of empirical null using a mixture of normals and its use in local false discovery rate. Comput Stat Data Anal 55 (2011) 2421–2432] to select the active voxels.     

FMRI connectivity analysis of acupuncture effects on the whole brain network in mild cognitive impairment patients

The increased risk for the elderly with mild cognitive impairment (MCI) to progress to Alzheimer's disease makes it an appropriate condition for investigation. While the use of acupuncture as a complementary therapeutic method for treating MCI is popular in certain parts of the world, the underlying mechanism is still elusive. We sought to investigate the acupuncture effects on the functional connectivity throughout the entire brain in MCI patients compared to healthy controls (HC). The functional magnetic resonance imaging experiment was performed with two different paradigms, namely, deep acupuncture (DA) and superficial acupuncture (SA), at acupoint KI3. We first identified regions showing abnormal functional connectivity in the MCI group compared to HC during the resting state and subsequently tested whether these regions could be modulated by acupuncture. Then, we made the comparison of MCI vs. HC to test whether there were any specific modulatory patterns in the poststimulus resting brain between the two groups. Finally, we made the comparisons of DA vs. SA in each group to test the effect of acupuncture with different needling depths. We found the temporal regions (hippocampus, thalamus, fusiform gyrus) showing abnormal functional connectivity during the resting state. These regions are implicated in memory encoding and retrieving. Furthermore, we found significant changes in functional connectivity related with the abnormal regions in MCI patients following acupuncture. Compared to HC, the correlations related with the temporal regions were enhanced in the poststimulus resting brain in MCI patients. Compared to SA, significantly increased correlations related with the temporal regions were found for the DA condition. The enhanced correlations in the memory-related brain regions following acupuncture may be related to the purported therapeutically beneficial effects of acupuncture for the treatment of MCI. The heterogeneous modulatory patterns between DA and SA may suggest that deep muscle insertion of acupuncture is necessary to achieve the appreciable clinical effect.