Event-related single-shot volumetric functional magnetic resonance inverse imaging of visual processing

Developments in multi-channel radio-frequency (RF) coil array technology have enabled functional magnetic resonance imaging (fMRI) with higher degrees of spatial and temporal resolution. While modest improvement in temporal acceleration has been achieved by increasing the number of RF coils, the maximum attainable acceleration in parallel MRI acquisition is intrinsically limited only by the amount of independent spatial information in the combined array channels. Since the geometric configuration of a large-n MRI head coil array is similar to that used in EEG electrode or MEG SQUID sensor arrays, the source localization algorithms used in MEG or EEG source imaging can be extended to also process MRI coil array data, resulting in greatly improved temporal resolution by minimizing k-space traversal during signal acquisition. Using a novel approach, we acquire multi-channel MRI head coil array data and then apply inverse reconstruction methods to obtain volumetric fMRI estimates of blood oxygenation level dependent (BOLD) contrast at unprecedented whole-brain acquisition rates of 100 ms. We call this combination of techniques magnetic resonance Inverse Imaging (InI), a method that provides estimates of dynamic spatially-resolved signal change that can be used to construct statistical maps of task-related brain activity. We demonstrate the sensitivity and inter-subject reliability of volumetric InI using an event-related design to probe the hemodynamic signal modulations in primary visual cortex. Robust results from both single subject and group analyses demonstrate the sensitivity and feasibility of using volumetric InI in high temporal resolution investigations of human brain function.     

The Yale experience in first advancing fMRI

In 1992 during a period of only a few months functional brain mapping by MRI became an international research field. This paper gives background to the first studies performed at Yale University during April 1992 which examined the temporal characteristics of the BOLD response in the human visual cortex. For the first time it was shown that even brief visual stimuli could produce a BOLD response which was delayed (due to the hemodynamic response) and was detected by imaging some seconds (on average 1.5s) after the stimuli was over. This observation was the first event-related scanning study by fMRI.     

A comparison of methods for characterizing the event-related BOLD timeseries in rapid fMRI

Information about the shape and temporal duration of the blood oxygenation level dependent (BOLD) response can inform both functional neuroanatomy and psychological theory. However, the BOLD response evolves over 20 s or more, making it difficult to distinguish the unique characteristics of the response evoked by temporally adjacent stimuli. Fortunately, event-related BOLD signals can be extracted given that there is adequate variance in the distribution of inter-stimulus intervals (ISI). Unfortunately, the ISI distribution that yields the highest statistical efficiency is not always optimal from a psychological perspective; variability in the stimulus timing may complicate the interpretation of neuroimaging data in terms of underlying cognitive operations. In the present paper, Monte Carlo simulations are used to evaluate two techniques for estimating the event-related BOLD timeseries-event-related averaging and deconvolution using the Ordinary Least Squares estimate -with respect to maintaining acceptable levels of statistical power and experimental validity. While the unbiased deconvolution technique more robustly estimates the shape of the BOLD response functions, both methods succeed in accurately re-producing known differences between evoked BOLD responses when the stimulus ordering is randomized. However, the deconvolution method is more effective at preserving differences when there are sequential dependencies in the stimulus presentation order and restricted ISI distributions are used; particularly if the second of two sequentially dependent stimuli is omitted on some portion of the trials. Importantly, the successful re-production of the evoked BOLD response using restricted ISI distributions often maximizes the ability to make psychologically valid experimental conclusions.     

Functional magnetic resonance inverse imaging of human visuomotor systems using eigenspace linearly constrained minimum amplitude (eLCMA) beamformer

Recently proposed dynamic magnetic resonance (MR) inverse imaging (InI) is a novel parallel imaging reconstruction technique capable of improving the temporal resolution of blood-oxygen level-dependent (BOLD) contrast functional MRI (fMRI) to the order of milliseconds at the cost of moderate spatial resolution. Volumetric InI reconstructs spatial information from projection data by solving ill-posed inverse problems using simultaneous acquisitions from a RF coil array. Previously a spatial filtering technique based on linearly constrained minimum variance (LCMV) beamformer was suggested to localize the hemodynamic changes of dynamic InI data with improved spatial resolution and sensitivity. Here we report an advancement of the spatial filtering method, which combines the eigenspace projection of the measured data and the L1-norm minimization of the spatial filters' output noise amplitude, to further improve the detection power of BOLD contrast fMRI data. Using numerical simulation and in vivo data, we demonstrate that this eigenspace linearly constrained minimum amplitude (eLCMA) beamformer can reconstruct spatiotemporal hemodynamic signals with high statistical significance values and high spatial resolution in event-related two-choice reaction time visuomotor experiments.     

BOLD responses to stimuli: dependence on frequency, stimulus form, amplitude, and repetition rate

A quantitative theory is developed for the relationship between stimulus and the resulting blood oxygen level-dependent (BOLD) functional MRI signal. The relationship of stimuli to neuronal activity during evoked responses is inferred from recent physiology-based quantitative modeling of evoked response potentials (ERPs). A hemodynamic model is then used to calculate the BOLD response to neuronal activity having the form of an impulse, a sinusoid, or an ERP-like damped sinusoid. Using the resulting equations, the BOLD response is analyzed for different forms, frequencies, and amplitudes of stimuli, in contrast with previous research, which has mostly concentrated on sustained stimuli. The BOLD frequency response is found to be closely linear in the parameter ranges of interest, with the form of a low-pass filter with a weak resonance at approximately 0.07 Hz. An improved BOLD impulse response is systematically obtained which includes initial dip and post-stimulus undershoot for some parameter ranges. It is found that the BOLD response depends strongly on the precise temporal course of the evoked neuronal activity, not just its peak value or typical amplitude. Indeed, for short stimuli, the linear BOLD response is closely proportional to the time-integrated activity change evoked by the stimulus, regardless of amplitude. It is concluded that there can be widely differing proportionalities between BOLD and peak activity, that this is the likely reason for the low level of correspondence seen experimentally between ERP sources and BOLD measurements and that non-BOLD measurements, such as ERPs, can be used to correct for this effect to obtain improved activity estimates. Finally, stimulus sequences that optimize the signal-to-noise ratio in event-related BOLD fMRI (efMRI) experiments are derived using the hemodynamic transfer function.     

Pre-processed image reconstruction applied to breast and brain MR imaging

Magnetic resonance imaging (MRI) has emerged as a powerful tool in medical diagnosis and research. Although high spatial resolution images are essential in medical diagnosis and image analysis, high temporal resolution is equally important in applications of dynamic contrast-enhanced MRI or functional brain MRI. In particular, in breast MRI the ability to differentiate between benign and malignant lesions depends, in part, on the temporal resolution of the dynamic image acquisition. New applications of MRI such as multi-feature analysis of image time series data and full 3D functional MRI or event-related functional MRI require high spatial and high temporal resolution for accurate image analysis on a voxel-by-voxel basis. Currently available partial Fourier reconstruction techniques. which effectively improve the time resolution, suffer from a reduced signal to noise ratio in the reconstructed image, a decrease in spatial resolution or reconstruction artefacts, making numerical image analysis difficult. In this work we present an image reconstruction algorithm based on image recovery theory which effectively doubles the temporal resolution and results in an image quality sufficient for further numerical analysis. The developed algorithm requires a full Fourier space acquisition of a pre-contrast or baseline image prior to the reconstruction procedure of the time series partial Fourier data.     

Functional MRI activation of individual interictal epileptiform spikes

We used spike-triggered functional MRI in a patient with localization-related epilepsy to determine whether individual (as opposed to averaged) focal interictal epileptiform discharges (spikes) were associated with hemodynamic changes detectable with blood oxygen level-dependent functional MRI (fMRI). It was found that 15 of 43 spikes (34.9%) were associated with significant focal fMRI activation. Single event-related fMRI of interictal spikes is feasible in selected patients, giving complementary information to that provided by averaged fMRI data.     

听觉功能MRI研究的实验设计

目的探讨听觉fMRI研究的有效数据采集方式。方法对13例健康年轻受试者分别采用纯音及调幅音两种听觉刺激条件，刺激分别采用组块和事件相关设计进行听觉呈现，以比较连续及稀疏两种采集方式下听觉皮层的fMRI响应，运用SPM2软件进行数据分析和脑功能区定位，并分析两种不同实验数据采集方式下听觉皮层激活的差异。结果调幅声较纯音更易激发听觉皮层的激活；两种刺激条件下，稀疏采集时听觉皮层的fMRI响应明显多于连续采集，比较听觉皮层各区，以初级听觉皮层fMRI响应为著。结论调幅音是听觉fMRI研究中的合适刺激；稀疏采集方式有助于克服环境噪声的负面影响，结合物理衰减方法，可实现听觉功能的fMRI研究。     

Event-related fMRI for the suppression of speech-associated artifacts in stuttering

The purpose of this study was to establish functional magnetic resonance imaging (fMRI) for the investigation of brain function during overt speech production in stuttering. Up to now this technique has rarely been used for the investigation of speech production paradigms because artifacts related to overt speaking largely impair the sensitivity toward task-related activation. Recently, the temporal delay of the hemodynamic response has been exploited to achieve a suppression of speech-related artifacts. By the limitation to very short utterances (one word), a temporal segregation of the respective effects was accomplished by means of an event-related experimental design. However, the investigation of speech production in persons who stutter requires a more extensive speaking situation. Since longer and more complex utterances evoke more symptoms of stuttering than reading of single words, a useful task should at least include the reading of full sentences. In this study we performed simulations to investigate the correlation of speech-related artifacts with the respective hemodynamic response in dependency on speech duration and rate of data sampling. Furthermore, we show that prolonged stimulus durations and repetition times of 3 s still allow an effective suppression of speech-related artifacts in fluent as well as in nonfluent speakers. Not only were obvious false activations at high contrast cerebrospinal fluid tissue borders widely eliminated, subjects also displayed consistent activation in speech-related and motor areas. As these results widely resemble those obtained by earlier neuroimaging studies on language production, event-related fMRI seems to be capable of recording neurophysiological correlates of overt speech production.     

Parietal activity in episodic retrieval measured by fMRI and MEG

Understanding the functional role of the left lateral parietal cortex in episodic retrieval requires characterization of both spatial and temporal features of activity during memory tasks. In a recent study using magnetoencephalography (MEG), we described an early parietal response in a cued-recall task. This response began within 100 milliseconds (ms) of the retrieval cue and lasted less than 400 ms. Spatially, the effect reached significance in all three anatomically defined left lateral parietal subregions included in the study. Here we present a multimodal analysis of both hemodynamic and electrophysiologic responses in the same cued-recall paradigm. Functional MRI (fMRI) was used to more precisely reveal the portion of the parietal cortex with the greatest response. The MEG data set was then reanalyzed to show the early MEG time course of the region identified by fMRI. We found that the hemodynamic response is greatest within the intraparietal sulcus. Further, the MEG pattern in this region shows a strong response during the first 300 ms following the cue to retrieve. Finally, when individual-dipole MEG activity is analyzed for the left cortical surface over the early 300-millisecond time window, significant recall-related activity is limited to a relatively small portion of the left hemisphere that overlaps the region identified by fMRI in the intraparietal sulcus.     

An intrinsic diffusion response function for analyzing diffusion functional MRI time series

To disentangle the temporal profiles of the diffusion and BOLD components of diffusion-weighted functional MRI (DfMRI) during visual activation, we extracted the raw signal from an anatomically defined volume of interest encompassing the visual cortex of 16 subjects. Under the assumption of a linear, time invariant system we were able to define an intrinsic diffusion response function (DRF) from neural tissue, as a counterpart to the hemodynamic response function (HRF) commonly used in BOLD-fMRI. The shape of the DRF response was found to be very similar to the time courses of optical imaging transmittance signals, thought to originate from local geometric changes in brain tissue at the microscopic scale. The overall DfMRI signal response was modeled as the convolution of the stimulation paradigm time course with a DhRF, which is the sum of the DRF and a fractional HRF resulting from residual tissue T2-BOLD contrast. The contribution of the HRF to the DfMRI signal was found to be 26% at peak amplitude, but the DRF component which has a much steeper onset contributed solely at beginning of the response onset. The suitability of this model over the canonical HRF to process DfMRI data was then demonstrated on datasets acquired in 5 other subjects using a rapid event-related design. Some non-linearities in the responses were observed, mainly after the end of the stimulation.     

Characterizing the Hemodynamic Response: Effects of Presentation Rate, Sampling Procedure, and the Possibility of Ordering Brain Activity Based on Relative Timing

Rapid-presentation event-related functional MRI (ER-fMRI) allows neuroimaging methods based on hemodynamics to employ behavioral task paradigms typical of cognitive settings. However, the sluggishness of the hemodynamic response and its variance provide constraints on how ER-fMRI can be applied. In a series of two studies, estimates of the hemodynamic response in or near the primary visual and motor cortices were compared across various paradigms and sampling procedures to determine the limits of ER-fMRI procedures and, more generally, to describe the behavior of the hemodynamic response. The temporal profile of the hemodynamic response was estimated across overlapping events by solving a set of linear equations within the general linear model. No assumptions about the shape were made in solving the equations. Following estimation of the temporal profile, the amplitude and timing were modeled using a γ function. Results indicated that (1) within a region, for a given subject, estimation of the hemodynamic response is extremely stable for both amplitude (r² = 0.98) and time to peak (r² = 0.95), from one series of measurements to the next, and slightly less stable for estimation of time to onset (r² = 0.60). (2) As the trial presentation rate changed (from those spaced 20 s apart to temporally overlapping trials), the hemodynamic response amplitude showed a small, but significant, decrease. Trial onsets spaced (on average) 5 s apart showed a 17–25% reduction in amplitude compared to those spaced 20 s apart. Power analysis indicated that the increased number of trials at fast rates outweighs this decrease in amplitude if statistically reliable response detection is the goal. (3) Knowledge of the amplitude and timing of the hemodynamic response in one region failed to predict those properties in another region, even for within-subject comparisons. (4) Across subjects, the amplitude of the response showed no significant correlation with timing of the response, for either time-to-onset or time-to-peak estimates. (5) The within-region stability of the response was sufficient to allow offsets in the timing of the response to be detected that were under a second, placing event-related fMRI methods in a position to answer questions about the change in relative timing between regions.     

Spatial dependence of the nonlinear BOLD response at short stimulus duration

Most functional magnetic resonance imaging studies use linear models to predict the measured response by convolution of an impulse response with the stimulus profile. Using very short visual presentation times (<2 s), deviation from the linear model in the measured BOLD data from the human brain was found for the response integral, amplitude, and width. In this study, high temporal and spatial resolution were used to quantify nonlinear effects and investigate the spatial dependence. Data at 4 Tesla showed at short stimulus duration a nonlinearity, i.e., deviation from a linear model, with an index up to 400%, whereas data at 7 Tesla exhibited a nonlinearity index up to 40%. The effect was more pronounced for response amplitude than for response area. A reduced width and sharpening of responses at shorter stimulus duration was also found. A voxel-based analysis of 7 Tesla data with 1.2 x 1.2 x 2 mm(3) resolution revealed a correlation between response onset and nonlinearity index. This suggests that the nonlinearity effects are a tissue-specific phenomenon and are likely to be more localized to the site of neuronal activity. The observed magnetic field dependence and the demonstrated nonlinearity in the response width support the hypothesis that the source of the nonlinearity at short stimulus duration has a considerable hemodynamic contribution. The nonlinearity was modeled as a "switch"-type initial hemodynamic response onset. Understanding these nonlinearities in the BOLD response is important for design and the analysis of rapid event-related fMRI experiments with brief stimulus presentations.     

Caffeine increases the linearity of the visual BOLD response

Although the blood oxygenation level dependent (BOLD) signal used in most functional magnetic resonance imaging (fMRI) studies has been shown to exhibit nonlinear characteristics, most analyses assume that the BOLD signal responds in a linear fashion to stimulus. This assumption of linearity can lead to errors in the estimation of the BOLD response, especially for rapid event-related fMRI studies. In this study, we used a rapid event-related design and Volterra kernel analysis to assess the effect of a 200 mg oral dose of caffeine on the linearity of the visual BOLD response. The caffeine dose significantly (p < 0.02) increased the linearity of the BOLD response in a sample of 11 healthy volunteers studied on a 3 T MRI system. In addition, the agreement between nonlinear and linear estimates of the hemodynamic response function was significantly increased (p = 0.013) with the caffeine dose. These findings indicate that differences in caffeine usage should be considered as a potential source of bias in the analysis of rapid event-related fMRI studies.     

The importance of distributed sampling in blocked functional magnetic resonance imaging designs

In this study we demonstrate the importance of distributed sampling of peristimulus time in blocked design fMRI studies. Distributed sampling ensures all the components of an event-related hemodynamic response are sampled and avoids the bias incurred when stimulus presentation is time-locked to data acquisition. We found that differences in the temporal offset between stimulus presentation and data acquisition had a significant effect on some language-related activations. These effects, induced by simply shifting stimulus presentation by a fraction of the interscan interval, suggest that fixed sampling does indeed bias estimated responses, even in blocked designs.     

Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution

The analysis of functional magnetic resonance imaging (fMRI) time-series data can provide information not only about task-related activity, but also about the connectivity (functional or effective) among regions and the influences of behavioral or physiologic states on that connectivity. Similar analyses have been performed in other imaging modalities, such as positron emission tomography. However, fMRI is unique because the information about the underlying neuronal activity is filtered or convolved with a hemodynamic response function. Previous studies of regional connectivity in fMRI have overlooked this convolution and have assumed that the observed hemodynamic response approximates the neuronal response. In this article, this assumption is revisited using estimates of underlying neuronal activity. These estimates use a parametric empirical Bayes formulation for hemodynamic deconvolution.     

Optimized time‐resolved imaging of contrast kinetics (TRICKS) in dynamic contrast‐enhanced MRI after peptide receptor radionuclide therapy in small animal tumor models

Anti‐tumor efficacy of targeted peptide‐receptor radionuclide therapy (PRRT) relies on several factors, including functional tumor vasculature. Little is known about the effect of PRRT on tumor vasculature. With dynamic contrast‐enhanced (DCE‐) MRI, functional vasculature is imaged and quantified using contrast agents. In small animals DCE‐MRI is a challenging application. We optimized a clinical sequence for fast hemodynamic acquisitions, time‐resolved imaging of contrast kinetics (TRICKS), to obtain DCE‐MRI images at both high spatial and high temporal resolution in mice and rats. Using TRICKS, functional vasculature was measured prior to PRRT and longitudinally to investigate the effect of treatment on tumor vascular characteristics. Nude mice bearing H69 tumor xenografts and rats bearing syngeneic CA20948 tumors were used to study perfusion following PRRT administration with ¹⁷⁷lutetium octreotate. Both semi‐quantitative and quantitative parameters were calculated. Treatment efficacy was measured by tumor‐size reduction. Optimized TRICKS enabled MRI at 0.032 mm³ voxel size with a temporal resolution of less than 5 s and large volume coverage, a substantial improvement over routine pre‐clinical DCE‐MRI studies. Tumor response to therapy was reflected in changes in tumor perfusion/permeability parameters. The H69 tumor model showed pronounced changes in DCE‐derived parameters following PRRT. The rat CA20948 tumor model showed more heterogeneity in both treatment outcome and perfusion parameters. TRICKS enabled the acquisition of DCE‐MRI at both high temporal resolution (T_res) and spatial resolutions relevant for small animal tumor models. With the high T_res enabled by TRICKS, accurate pharmacokinetic data modeling was feasible. DCE‐MRI parameters revealed changes over time and showed a clear relationship between tumor size and K_trans. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparing event-related and epoch analysis in blocked design fMRI

In this study we demonstrate that, even in blocked design fMRI, an event-related analysis may provide a more accurate model of the hemodynamic responses than an epoch-related analysis. This is because the temporal shape of the predicted response differs between the event-related and the epoch model, with the former reaching its peak sooner and returning to baseline later than the latter. We present data from a blocked design fMRI study of single word reading alternated with rest. Conventionally, such a design would be analyzed using an epoch analysis with boxcar regressors. However, here we used a combined model in which trials were modeled as both single events and epochs. This allowed us to estimate the variance in the BOLD signal that was explained by either the event-related or the epoch regressors having discounted the effect of the other. We found that, in a number of language regions, the event-related model explained changes in activity that were not accounted for by the epoch model. In addition, we show that the advantage of the event-related over epoch model was engendered by its early onset rather than its late offset, relative to the epoch model.     

Estimation and classification of fMRI hemodynamic response patterns

In this paper, we propose an approach to modeling functional magnetic resonance imaging (fMRI) data that combines hierarchical polynomial models, Bayes estimation, and clustering. A cubic polynomial is used to fit the voxel time courses of event-related design experiments. The coefficients of the polynomials are estimated by Bayes estimation, in a two-level hierarchical model, which allows us to borrow strength from all voxels. The voxel-specific Bayes polynomial coefficients are then transformed to the times and magnitudes of the minimum and maximum points on the hemodynamic response curve, which are in turn used to classify the voxels as being activated or not. The procedure is demonstrated on real data from an event-related design experiment of visually guided saccades and shown to be an effective alternative to existing methods.