一种基于独立成份分析的fMRI时-空模型数据处理方法

独立成份分析(ICA)是信号处理领域中斯近发展起来的一种很有应用前景的方法，而脑功能磁共振(fMRI)信号的有效分离与识别是一个正在研究和试验之中的技术领域。因此，发展基于ICA的fMRI数据处理方法具有明显的理论价值和应用前景。本文首先介绍了ICA原理，分析了现行ICA—fMRI方法采用的信号与噪声的空域分布相互独立的信号模型所存在的明显不足，然后提出了微域中的信号与噪声的时域过程相互独立的fMRI信号模型，从而建立了一种新的fMRI数据处理方法：邻域独立成份相关法。合理的fMRI实验数据处理结果验证了新方法的合理性。     

Multimodal Integration of fMRI and EEG Data for High Spatial and Temporal Resolution Analysis of Brain Networks

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli, respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes.     

空间ICA在fMRI数据上的应用与分析

独立成分分析(ICA)技术试图将多维数据分解成若干个相互统计独立的分量。时间ICA和空间ICA都可以用于分析功能核磁共振成像(fMRI)数据。但由于fMRI数据空间维数远远大于时间维数，为计算方便，在分析fMRI数据时。则更多的使用空间ICA方法。本文在单任务激励实验中，利用ICA方法从fMRI数据中分离出若干个与任务相关的独立分量，其中包括与任务相关的恒定分量(CTR)和与任务相关的暂态分量(TTR)；通过将这些独立分量进行空间映射，得到了与任务相关的脑部激活区域。将此结果与SPM的分析比较，得到了一致的结果。在对结果的分析中，我们进一步指出了ICA方法的特点和局限性。     

Integrated MEG/fMRI Model Validated Using Real Auditory Data

The main objective of this paper is to present methods and results for the estimation of parameters of our proposed integrated magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) model. We use real auditory MEG and fMRI datasets from 7 normal subjects to estimate the parameters of the model. The MEG and fMRI data were acquired at different times, but the stimulus profile was the same for both techniques. We use independent component analysis (ICA) to extract activation-related signal from the MEG data. The stimulus-correlated ICA component is used to estimate MEG parameters of the model. The temporal and spatial information of the fMRI datasets are used to estimate fMRI parameters of the model. The estimated parameters have reasonable means and standard deviations for all subjects. Goodness of fit of the real data to our model shows the possibility of using the proposed model to simulate realistic datasets for evaluation of integrated MEG/fMRI analysis methods.     

Data-based functional template for sorting independent components of fMRI activity

In human brain imaging with naturalistic stimuli, hemodynamic responses are difficult to predict and thus data-driven approaches, such as independent component analysis (ICA), may be beneficial. Here we propose inter-subject correlation (ISC) maps as stimulus-sensitive functional templates for sorting the independent components (ICs) to identify the most stimulus-related networks without stimulus-dependent temporal covariates. We collected 3-T functional magnetic resonance imaging (fMRI) data during perception of continuous audiovisual speech. Ten adults viewed a video, in which speech intelligibility was varied by altering the sound level. Five ICs with strongest overlap with the ISC map comprised auditory and visual cortices, and the sixth was a left-hemisphere-dominant network (left posterior superior temporal sulcus, inferior frontal gyrus, anterior superior temporal pole, supplementary motor cortex, and right angular gyrus) that was activated stronger during soft than loud speech. Corresponding temporal-model-based analysis revealed only temporal- and parietal-lobe activations without involvement of the anterior areas. The performance of the ISC-based IC selection was confirmed with fMRI data collected during free viewing of movie. Since ISC–ICA requires no predetermined temporal models on stimulus timing, it seems feasible for fMRI studies where hemodynamic variations are difficult to model because of the complex temporal structure of the naturalistic stimulation.     

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A??V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.     

Data-based functional template for sorting independent components of fMRI activity

In human brain imaging with naturalistic stimuli, hemodynamic responses are difficult to predict and thus data-driven approaches, such as independent component analysis (ICA), may be beneficial. Here we propose inter-subject correlation (ISC) maps as stimulus-sensitive functional templates for sorting the independent components (ICs) to identify the most stimulus-related networks without stimulus-dependent temporal covariates. We collected 3-T functional magnetic resonance imaging (fMRI) data during perception of continuous audiovisual speech. Ten adults viewed a video, in which speech intelligibility was varied by altering the sound level. Five ICs with strongest overlap with the ISC map comprised auditory and visual cortices, and the sixth was a left-hemisphere-dominant network (left posterior superior temporal sulcus, inferior frontal gyrus, anterior superior temporal pole, supplementary motor cortex, and right angular gyrus) that was activated stronger during soft than loud speech. Corresponding temporal-model-based analysis revealed only temporal- and parietal-lobe activations without involvement of the anterior areas. The performance of the ISC-based IC selection was confirmed with fMRI data collected during free viewing of movie. Since ISC-ICA requires no predetermined temporal models on stimulus timing, it seems feasible for fMRI studies where hemodynamic variations are difficult to model because of the complex temporal structure of the naturalistic stimulation.     

Visual stimuli activate auditory cortex in the deaf.

Previous brain imaging studies have demonstrated responses to tactile and auditory stimuli in visual cortex of blind subjects, suggesting that removal of one sensory modality leads to neural reorganization of the remaining modalities. To investigate whether similar 'cross-modal' plasticity occurs in human auditory cortex, we used functional magnetic resonance imaging (fMRI) to measure visually evoked activity in auditory areas of both early-deafened and hearing individuals. Here we find that deaf subjects exhibit activation in a region of the right auditory cortex, corresponding to Brodmann's areas 42 and 22, as well as in area 41 (primary auditory cortex), demonstrating that early deafness results in the processing of visual stimuli in auditory cortex.     

基于独立成分分析的时间自相关方法在功能磁共振激活区自适应提取中的应用

传统基于ICA的激活区检测手段是将分离后的独立成分与参考信号做相关性分析。实际问题中,不同区域的脑血流动力学响应情况不同,因此往往得不到标准的参考信号。针对此类问题,提出时间自相关方法(TSC)与ICA方法结合,在不需要参考信号的情况下,通过检测体素点各周期的时间序列相关性,对fMRI数据进行激活区提取。应用5 邻域ICA方法对fMRI数据逐点处理,然后应用时间自相关算法检测各时间序列周期间的相关性,选择最大的自相关系数作为该体素点的信号值。再通过Z变换将相关系数分布转换为服从N(0,1)的Z分布,提取出具有显著性差异（a=0.05）的激活区。将自相关算法应用于仿真数据和12组双手握拳运动的真实fMRI数据的处理,结果表明该方法能够准确提取出仿真数据中的激活区。对真实数据的处理,该方法在空间准确性上与GLM方法无显著性差别(0.4653±0.1368 vs 0.4905±0.1341),在时间准确性上显著优于GLM方法 (0.6364±0.0111 vs 0.3692±0.0109),具有良好的脑功能激活区检测及空间定位能力。     

Wiener Filter-Magnetoencephalography of Visual Cortical Activity

This paper reports a revised Wiener filter to resolve the inverse problem for magnetoencephalograms (MEGs) according to the structural and functional constraints based on magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI). Wiener filter-MEG imaging for half field stimulation with the chromatic stimulus resolved fast, slow and late responses in V1, V4 and the inferotemporal cortex, respectively. The time courses of these responses were roughly comparable with those reported by unit recording studies of the corresponding monkey visual cortical areas. Wiener filter-MEG imaging had comparable spatial resolution and better signal to noise ratio than fMRI. The background noise was robust in fMRI responses, but became virtually eliminated in Wiener filter responses. Wiener filter-MEG imaging with upper and lower quadrant field stimulation demonstrated V1 responses differentially distributed respectively in the lower and upper banks of the calcarine sulcus. These results demonstrate that responses in two cortical areas facing close to each other can be resolved by Wiener filter-MEG. The present method provides a way to image brain activities with millisecond- and millimeter-order spatiotemporal resolution.     

Spatially specific FMRI repetition effects in human visual cortex

The functional MRI (fMRI) response to a pair of identical, successively presented stimuli can result in a smaller signal than the presentation of two nonidentical stimuli. This "repetition effect" has become a frequently used tool to make inferences about neural selectivity in specific cortical areas. However, little is known about the mechanism(s) underlying the effect. In particular, despite many successful applications of the technique in higher visual areas, repetition effects in lower visual areas [e.g., primary visual cortex (V1)] have been more difficult to characterize. One property that is well understood in early visual areas is the mapping of visual field locations to specific areas of the cortex (i.e., retinotopy). We used the retinotopic organization of V1 to activate progressively different populations of neurons in a rapid fMRI experimental design. We observed a repetition effect (reduced signal) when localized stimulus elements were repeated in identical locations. We show that this effect is spatially tuned and largely independent of both interstimulus interval (100-800 ms) and the focus of attention. Using the same timing parameters for which we observed a large effect of spatial position, we also examined the response to orientation changes and observed no effect of an orientation change on the response to repeated stimuli in V1 but significant effects in other retinotopic areas. Given these results, we discuss the possible causes of these repetition effects as well as the implications for interpreting other experiments that use this potentially powerful imaging technique.     

Activation and deactivation in response to visual stimulation in the occipital cortex of 6-month-old human infants

In an infant's developing cortex, the explanation for the mechanisms underlying the activations and deactivations in response to visual stimuli remains controversial. While previous near-infrared spectroscopy (NIRS) studies in awake infants have demonstrated cortical activations in response to meaningful/attractive visual stimuli, functional magnetic resonance imaging (fMRI) studies performed on sleeping infants showed negative blood oxygenation level-dependent (BOLD) responses to high-luminance unpatterned stimulations, such as a photic stimulation. To examine the effect of the characteristics of visual stimuli on cortical processing in awake infants, we measured cortical hemodynamic responses in 6-month-old infants during the presentation of a high-luminance unpatterned stimulus by using a NIRS system with 94 measurement channels. Results from 35 infants showed dissociated cortical responses between the occipital region and the other parts of the cortex, including the temporal and prefrontal regions. Although the visual stimulus produced sustained increases in oxygenated hemoglobin (oxy-Hb) signals in the temporal and prefrontal regions, it produced a transient increase in oxy-Hb signals followed by a salient decrease in oxy-Hb signals during a trial in a focal region of the occipital visual region. This suggests that the deactivation of the occipital visual region in response to visual stimulation is not a phenomenon that occurs only in the sleeping state, but that a high-luminance unpatterned stimulus can induce deactivation even in the awake infants.     

An Improved Fixed-point Algorithm for Independent Component Analysis of Functional MRI Data

The fixed-point algorithm and infomax algorithm are two of the most popular algorithms in independent component analysis （ICA）. However, it is hard to take both stability and speed into consideration in processing functional magnetic resonance imaging （fMRI） data. In this paper, an optimization model for ICA is presented and an improved fixed-point algorithm based on the model is proposed. In the new algorithms a small step size is added to increase the stability. In order to accelerate the convergence, an improvement on Newton method is made, which makes cubic convergence for the new algorithm. Applying the algorithm and two other algorithms to invivo fMRI data, the results show that the new algorithm separates independent components stably, which has faster convergence speed and less computation than the other two algorithms. The algorithm has obvious advantage in processing fMRI signal with huge data.     

Functional magnetic resonance imaging mirrors recovery of visual perception after repetitive tachistoscopic stimulation in patients with partial cortical blindness

We investigated three patients with partial cortical blindness after brain injury by means of functional magnetic resonance imaging (fMRI) before and after the application of a daily visual stimulation-therapy over a period of 6 months. Before therapy, fMRI data showed a severely reduced blood-oxygen-level-dependent (BOLD) signal in primary visual cortex when compared to healthy volunteers. Following several months of rehabilitative therapy a neuropsychological improvement of visual functions was accompanied by an increase in BOLD signal of residual perilesional regions whereas fMRI data of the control group remained unchanged. A high capacity of functional recovery and synaptic plasticity of surviving perilesional neuronal structures of primary visual cortex followed by an increased input into post-connected visual areas can be discussed as a basis for the reoccurrence of visual functions.     

Responses to rare visual target and distractor stimuli using event-related fMRI

Previous studies have found that the P300 or P3 event-related potential (ERP) component is useful in the diagnosis and treatment of many disorders that influence CNS function. However, the anatomic locations of brain regions involved in this response are not precisely known. In the present event-related functional magnetic resonance imaging (fMRI) study, methods of stimulus presentation, data acquisition, and data analysis were optimized for the detection of brain activity in response to stimuli presented in the three-stimulus oddball task. This paradigm involves the interleaved, pseudorandom presentation of single block-letter target and distractor stimuli that previously were found to generate the P3b and P3a ERP subcomponents, respectively, and frequent standard stimuli. Target stimuli evoked fMRI signal increases in multiple brain regions including the thalamus, the bilateral cerebellum, and the occipital-temporal cortex as well as bilateral superior, medial, inferior frontal, inferior parietal, superior temporal, precentral, postcentral, cingulate, insular, left middle temporal, and right middle frontal gyri. Distractor stimuli evoked an fMRI signal change bilaterally in inferior anterior cingulate, medial frontal, inferior frontal, and right superior frontal gyri, with additional activity in bilateral inferior parietal lobules, lateral cerebellar hemispheres and vermis, and left fusiform, middle occipital, and superior temporal gyri. Significant variation in the amplitude and polarity of distractor-evoked activity was observed across stimulus repetitions. No overlap was observed between target- and distractor-evoked activity. These event-related fMRI results shed light on the anatomy of responses to target and distractor stimuli that have proven useful in many ERP studies of healthy and clinically impaired populations.     

Uncertainty and invariance in the human visual cortex

The way in which input noise perturbs the behavior of a system depends on the internal processing structure of the system. In visual psychophysics, there is a long tradition of using external noise methods (i.e., adding noise to visual stimuli) as tools for system identification. Here, we demonstrate that external noise affects processing of visual scenes at different cortical areas along the human ventral visual pathway, from retinotopic regions to higher occipitotemporal areas implicated in visual shape processing. We found that when the contrast of the stimulus was held constant, the further away from the retinal input a cortical area was the more its activity, as measured with functional magnetic resonance imaging (fMRI), depended on the signal-to-noise ratio (SNR) of the visual stimulus. A similar pattern of results was observed when trials with correct and incorrect responses were analyzed separately. We interpret these findings by extending signal detection theory to fMRI data analysis. This approach reveals the sequential ordering of decision stages in the cortex by exploiting the relation between fMRI response and stimulus SNR. In particular, our findings provide novel evidence that occipitotemporal areas in the ventral visual pathway form a cascade of decision stages with increasing degree of signal uncertainty and feature invariance.     

Human brain activation in response to olfactory stimulation by intravenous administration of odorants

To identify the BOLD effects related to olfaction in humans, we recorded functional magnetic resonance imaging (fMRI) scans in response intravenously instilled thiamine propyl disulfide (TPD) and thiamine tetrahydrofurfuryl disulfide monohydrochloride (TTFD). TPD and TTFD evoked a strong and weak odor sensation, respectively. Since we did not spray the odor stimuli directly, this method is expected to reduce the effect caused by direct stimulation of the trigeminal nerve. For the analysis of fMRI data, statistical parametric mapping (SPM2) was employed and the areas significantly activated during olfactory processing were located. Both strong and weak odorants induced brain activities mainly in the orbitofrontal gyrus (Brodmann's area: BA 11) in the left hemisphere. TPD (a strong odorant) induced activity in the subthalamic nucleus in the left hemisphere and the precentral gyrus (BA 6) and insula in the right hemisphere. TTFD (a weak odorant) induced activity in the superior frontal gyrus (BA 11) in the right hemisphere. In both circumstances, there was an increase in blood flow at the secondary olfactory cortex (SOC) but not the primary olfactory cortex (POC), probably due to a habituation effect in the POC. From the present results, we found brain activity in not only odor-specific regions but also regions whose levels of activity were changed by an intensity difference of odor stimuli.     

基于独立成分分析和时间相关分析的脑功能连通研究方法

目的：利用静息状态功能磁共振成像（functional magnetic resonance imaging，fMRI）技术，提出联合独立成分分析（independent component analysis，ICA）和时间相关分析的人脑功能连通性研究方法。方法：首先采用空间ICA定位任务激活的脑区；然后选择一个激活区作为感兴趣区域（region of interest，ROI），采用时间相关分析方法检测静息状态大脑特定皮层的功能连通性，并通过检测人脑运动皮层的功能连通性验证方法的有效性。结果：大脑运动皮层功能连通网络包括初级运动区、辅助运动区、初级感觉皮层、背侧前运动区和后顶骨体觉区。实验结果表明，静息状态下。时间相关分析检测到的运动皮层的功能连通网络与已知的解剖连通相一致。结论：利用静息fMRI。结合空间ICA和时间相关分析方法。检测了静息时人脑运动皮层的功能连通网络。为脑区间功能连通的研究提供了一种简便的、无损的、有效的研究方法。     

A comparison of signal instability in 2D and 3D EPI resting-state fMRI

Spatiotemporally structured noise, such as physiological noise, is a potential source of artifacts in functional magnetic resonance imaging (fMRI) and is the main limiting factor for the detection of small blood oxygen level-dependent (BOLD) signal variations. fMRI was employed to detect low-frequency BOLD signal fluctuations, which are thought to be related to spontaneous neuronal activity in the resting human brain. The sensitivity to noise, that is, signal variations of non-BOLD origin, was investigated for two- (2D) and three-dimensional (3D) imaging techniques. Incomplete relaxation between subsequent scans increases the level of temporally and spatially correlated signal variations originating from physiological and/or systemic noise. Although inflow effects are suspected to be reduced in 3D echo-planar imaging (EPI) compared with multi-slice 2D EPI, the noise level was higher in the 3D technique. The noise level in 3D fMRI experiments was significantly increased by instabilities of the transverse steady-state magnetization as the repetition time was of the order of T(2). By implementing radiofrequency spoiling, temporal signal fluctuations and erroneous inter-regional correlation in connectivity maps were diminished to a level present in data sets acquired with 2D EPI.     

Spatial attention: more than intrinsic alerting?

It has been proposed that the right hemisphere alerting network co-activates, either directly or via the brainstem, the attention system in the parietal cortex involved in spatial attention. The observation that impaired alertness and sustained attention can predict the outcome of neglect might suggest such a relationship, too. In the present fMRI study, we intended to analyse and compare the functional anatomy of two attentional conditions both involving intrinsic (endogenous) alerting and fixation but differing with respect to the degree of spatially distributed attention by using the same paradigm under two different attentional conditions. In a group of ten participants, both a focused and a distributed visuospatial attention condition evoked similar patterns of activation in dorsolateral prefrontal regions, in the anterior cingulate gyrus, in the superior and inferior parietal cortex as well as in the superior temporal gyrus and in the thalamus. These activation foci were stronger in the right hemisphere under both conditions. After subtraction of the alertness condition with focused spatial attention, distributed spatial attention with stimuli appearing at unpredictable locations within both visual fields induced additional bilateral activations only in the left and right superior parietal cortex and in the right precuneus suggesting that these regions are specific for a more widespread dispersion of spatial attention.