Subject fMRI Research Articles

Attention-Dependent Representation of a Size Illusion in Human V1

One of the most fundamental properties of human primary visual cortex (V1) is its retinotopic organization, which makes it an ideal candidate for encoding spatial properties, such as size, of objects. However, three-dimensional (3D) contextual information can lead to size illusions that are reflected in the spatial pattern of activity in V1 [1]. A critical question is how complex 3D contextual information can influence spatial activity patterns in V1. Here, we assessed whether changes in the spatial distribution of activity in V1 depend on the focus of attention, which would be suggestive of feedback of 3D contextual information from higher visual areas. We presented two 3D rings at close and far apparent depths in a 3D scene. When subjects fixated its center, the far ring appeared to be larger and occupy a more eccentric portion of the visual field, relative to the close ring. Using functional magnetic resonance imaging, we found that the spatial distribution of V1 activity induced by the far ring was also shifted toward a more eccentric representation of the visual field, whereas that induced by the close ring was shifted toward the foveal representation, consistent with their perceptual appearances. This effect was significantly reduced when the focus of spatial attention was narrowed with a demanding central fixation task. We reason that focusing attention on the fixation task resulted in reduced activity in--and therefore reduced feedback from--higher visual areas that process the 3D depth cues.

Investigation of spatial resolution, partial volume effects and smoothing in functional MRI using artificial 3D time series

This work addresses the balance between temporal signal-to-noise ratio (tSNR) and partial volume effects (PVE) in functional magnetic resonance imaging (fMRI) and investigates the impact of the choice of spatial resolution and smoothing. In fMRI, since physiological time courses are monitored, tSNR is of greater importance than image SNR. Improving SNR by an increase in voxel volume may be of negligible benefit when physiological fluctuations dominate the noise. Furthermore, at large voxel volumes, PVE are more pronounced, leading to an overall loss in performance. Artificial fMRI time series, based on high-resolution anatomical data, were used to simulate BOLD activation in a controlled manner. The performance was subsequently quantified as a measure of how well the resulted activation matched the simulated activation. The performance was highly dependent on the spatial resolution. At high contrast-to-noise ratio (CNR), the optimal voxel volume was small, i.e. in the region of 23 mm3. It was also shown that using a substantially larger voxel volume in this case could potentially negate the CNR benefits. The optimal smoothing kernel width was dependent on the CNR, being larger at poor CNR. At CNR >1, little or no smoothing proved advantageous. The use of artificial time series gave an opportunity to quantitatively investigate the effects of partial volume and smoothing in single subject fMRI. It was shown that a proper choice of spatial resolution and smoothing kernel width is important for fMRI performance.

An evaluation of spatial thresholding techniques in fMRI analysis

Many fMRI experiments have a common objective of identifying active voxels in a neuroimaging dataset. This is done in single subject experiments, for example, by performing individual voxel-wise tests of the null hypothesis that the observed time course is not significantly related to an assigned reference function. A voxel activation map is then constructed by applying a thresholding rule to the resulting statistics (e.g., t-statistics). Typically the task-related activation is expected to occur in clusters of voxels rather than in isolated single voxels. A variety of spatial thresholding techniques have been proposed to reflect this belief, including smoothing the raw t-statistics, cluster size inference, and spatial mixture modeling. We study two aspects of these spatial thresholding procedures applied to single subject fMRI analysis through simulation. First, we examine the performance of these procedures in terms of sensitivity to detect voxel activation, using receiver operating characteristic curves. Second, we consider the accuracy of these spatial thresholding procedures in estimation of the size of the activation region, both in terms of bias and variance. The findings indicate that smoothing has the highest sensitivity to modest magnitude signals, but tend to overestimate the size of the activation region. Spatial mixture models estimate the size of a spatially distributed activation region well, but may be less sensitive to modest magnitude signals, indicating that additional research into more sensitive spatial mixture models is needed. Finally, the methods are illustrated with a real bilateral finger-tapping fMRI experiment.

Brain Activity Associated with Expectancy-Enhanced Placebo Analgesia as Measured by Functional Magnetic Resonance Imaging

In this study, a well established expectancy manipulation model was combined with a novel placebo intervention, a validated sham acupuncture needle, to investigate the brain network involved in placebo analgesia. Sixteen subjects completed the experiment. We found that after placebo acupuncture treatment, subjective pain rating reduction (pre minus post) on the placebo-treated side was significantly greater than on the control side. When we calculated the contrast that subtracts the functional magnetic resonance imaging (fMRI) signal difference between post-treatment and pretreatment during pain application on placebo side from the same difference on control side [e.g., placebo (post - pre) - control (post - pre)], significant differences were observed in the bilateral rostral anterior cingulate cortex (rACC), lateral prefrontal cortex, right anterior insula, supramarginal gyrus, and left inferior parietal lobule. The simple regression (correlation) analysis between each subject's fMRI signal difference of post-treatment and pretreatment difference on placebo and control side and the corresponding subjective pain rating difference showed that significant negative correlation was observed in the bilateral lateral/orbital prefrontal cortex, rACC, cerebellum, right fusiform, parahippocampus, and pons. These results are different from a previous study that found decreased activity in pain-sensitive regions such as the thalamus, insula, and ACC when comparing the response to noxious stimuli applied to control and placebo cream-treated areas of the skin. Our results suggest that placebo analgesia may be configured through multiple brain pathways and mechanisms.

Resampling fMRI time series

The problem of selecting a threshold for the statistical parameter maps in functional MRI (fMRI) is a delicate issue. The use of advanced test statistics and/or the complex dependence structure of fMRI noise may preclude parametric statistical methods for finding appropriate thresholds. Non-parametric statistical methodology has been presented as a feasible alternative. In this paper, we discuss resampling methods for finding thresholds in single subject fMRI analysis. It is shown that the presence of a BOLD response in the time series biases the estimation of the temporal autocorrelation, which in turn leads to biased thresholds. Therefore, proposed resampling methods based on Fourier and wavelet transforms, which employ implicit and weak models of the temporal noise characteristic, may produce erroneous thresholds. In contrast, resampling based on a pre-whitening transform, which is driven by an explicit noise model, is robust to the presence of a BOLD response. The size of the bias is, however, largely dependent on the complexity of the experimental design. While blocked designs can induce large biases, event-related designs generate significantly smaller biases. Results supporting these claims are provided.