Parallel transmit (pTx) with online pulse design for task-based fMRI at 7 T.

PURPOSE: Parallel transmission (pTx) is an approach to improve image uniformity for ultra-high field imaging. In this study, we modified an echo planar imaging (EPI) sequence to design subject-specific pTx pulses online. We compared its performance against EPI with conventional circularly polarised (CP) pulses. METHODS: We compared the pTx-EPI and CP-EPI sequences in a short EPI acquisition protocol and for two different functional paradigms in six healthy volunteers (2 female, aged 23-36 years, mean age 29.2 years). We chose two paradigms that are typically affected by signal dropout at 7 T: a visual objects localiser to determine face/scene selective brain regions and a semantic-processing task. RESULTS: Across all subjects, pTx-EPI improved whole-brain mean temporal signal-to-noise ratio (tSNR) by 11.0% compared to CP-EPI. We also compared the ability of pTx-EPI and CP-EPI to detect functional activation for three contrasts over the two paradigms: face > object and scene > object for the visual objects localiser and semantic association > pattern matching for the semantic-processing paradigm. Across all three contrasts, pTx-EPI showed higher median z-scores and detected more active voxels in relevant areas, as determined from previous 3 T studies. CONCLUSION: We have demonstrated a workflow for EPI acquisitions with online per-subject pulse calculations. We saw improved performance in both tSNR and functional acquisitions from pTx-EPI. Thus, we believe that online calculation pTx-EPI is robust enough for future fMRI studies, especially where activation is expected in brain areas liable to significant signal dropout.

Correcting for Superficial Bias in 7T Gradient Echo fMRI.

The arrival of submillimeter ultra high-field fMRI makes it possible to compare activation profiles across cortical layers. However, the blood oxygenation level dependent (BOLD) signal measured by gradient echo (GE) fMRI is biased toward superficial layers of the cortex, which is a serious confound for laminar analysis. Several univariate and multivariate analysis methods have been proposed to correct this bias. We compare these methods using computational simulations of 7T fMRI data from regions of interest (ROI) during a visual attention paradigm. We also tested the methods on a pilot dataset of human 7T fMRI data. The simulations show that two methods-the ratio of ROI means across conditions and a novel application of Deming regression-offer the most robust correction for superficial bias. Deming regression has the additional advantage that it does not require that the conditions differ in their mean activation over voxels within an ROI. When applied to the pilot dataset, we observed strikingly different layer profiles when different attention metrics were used, but were unable to discern any differences in laminar attention across layers when Deming regression or ROI ratio was applied. Our simulations demonstrates that accurate correction of superficial bias is crucial to avoid drawing erroneous conclusions from laminar analyses of GE fMRI data, and this is affirmed by the results from our pilot 7T fMRI data.

Improved motion correction of submillimetre 7T fMRI time series with Boundary-Based Registration (BBR).

Ultra-high field functional magnetic resonance imaging (fMRI) has allowed us to acquire images with submillimetre voxels. However, in order to interpret the data clearly, we need to accurately correct head motion and the resultant distortions. Here, we present a novel application of Boundary Based Registration (BBR) to realign functional Magnetic Resonance Imaging (fMRI) data and evaluate its effectiveness on a set of 7T submillimetre data, as well as millimetre 3T data for comparison. BBR utilizes the boundary information from high contrast present in structural data to drive registration of functional data to the structural data. In our application, we realign each functional volume individually to the structural data, effectively realigning them to each other. In addition, this realignment method removes the need for a secondary aligning of functional data to structural data for purposes such as laminar segmentation or registration to data from other scanners. We demonstrate that BBR realignment outperforms standard realignment methods across a variety of data analysis methods. For instance, the method results in a 15% increase in linear discriminant contrast, a cross-validated estimate of multivariate discriminability. Further analysis shows that this benefit is an inherent property of the BBR cost function and not due to the difference in target volume. Our results show that BBR realignment is able to accurately correct head motion in 7T data and can be utilized in preprocessing pipelines to improve the quality of 7T data.

Prospective motion correction improves the sensitivity of fMRI pattern decoding.

We evaluated the effectiveness of prospective motion correction (PMC) on a simple visual task when no deliberate subject motion was present. The PMC system utilizes an in-bore optical camera to track an external marker attached to the participant via a custom-molded mouthpiece. The study was conducted at two resolutions (1.5 mm vs 3 mm) and under three conditions (PMC On and Mouthpiece On vs PMC Off and Mouthpiece On vs PMC Off and Mouthpiece Off). Multiple data analysis methods were conducted, including univariate and multivariate approaches, and we demonstrated that the benefit of PMC is most apparent for multi-voxel pattern decoding at higher resolutions. Additional testing on two participants showed that our inexpensive, commercially available mouthpiece solution produced comparable results to a dentist-molded mouthpiece. Our results showed that PMC is increasingly important at higher resolutions for analyses that require accurate voxel registration across time.

Adjudicating between face-coding models with individual-face fMRI responses.

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging.

Strength of retinotopic representation of visual memories is modulated by strategy.

Human visual cortex shows retinotopic organization during both perception and attention, but whether this remains true for visual short-term memory (VSTM) is uncertain. In 2 functional magnetic resonance imaging experiments, we separated retinotopic activation during perception, attention, and VSTM maintenance. The 2 experiments differed in whether spatial encoding of the VSTM stimuli and prospective attention to the locations of the remembered items was encouraged or discouraged. Using multivoxel pattern analysis to extract a measure of spatial coding in early visual cortex, we saw sensory and attentional retinotopic coding in both experiments. However, significant spatial coding during memory maintenance was only seen where a spatial strategy was encouraged. Furthermore, individual differences in attentional spatial coding predicted performance in both experiments, while individual differences in maintenance spatial coding predicted performance in neither. We conclude that retinotopic coding in the early visual cortex during VSTM maintenance is not obligatory, that attentional processes during stimulus perception modulate memory performance, and that different attentional strategies are used depending on the task in hand.

Choosing the rules: distinct and overlapping frontoparietal representations of task rules for perceptual decisions.

Behavior is governed by rules that associate stimuli with responses and outcomes. Human and monkey studies have shown that rule-specific information is widely represented in the frontoparietal cortex. However, it is not known how establishing a rule under different contexts affects its neural representation. Here, we use event-related functional MRI (fMRI) and multivoxel pattern classification methods to investigate the human brain's mechanisms of establishing and maintaining rules for multiple perceptual decision tasks. Rules were either chosen by participants or specifically instructed to them, and the fMRI activation patterns representing rule-specific information were compared between these contexts. We show that frontoparietal regions differ in the properties of their rule representations during active maintenance before execution. First, rule-specific information maintained in the dorsolateral and medial frontal cortex depends on the context in which it was established (chosen vs specified). Second, rule representations maintained in the ventrolateral frontal and parietal cortex are independent of the context in which they were established. Furthermore, we found that the rule-specific coding maintained in anticipation of stimuli may change with execution of the rule: representations in context-independent regions remain invariant from maintenance to execution stages, whereas rule representations in context-dependent regions do not generalize to execution stage. The identification of distinct frontoparietal systems with context-independent and context-dependent task rule representations, and the distinction between anticipatory and executive rule representations, provide new insights into the functional architecture of goal-directed behavior.

The neural basis of eye gaze processing.

Humans are highly sensitive to another's gaze direction, and use this information to support a range of social cognitive functions. Here we review recent studies that have begun to delineate a neural system for gaze perception. We focus in particular on a set of core gaze processes: perceptual coding of another's eye gaze direction, which may involve anterior superior temporal sulcus (STS); gaze-cued attentional orienting, which may be mediated by lateral parietal regions; and the experience of joint attention with another individual, which recruits medial prefrontal cortex. We conclude that understanding this gaze processing system will require a combination of multivariate pattern analysis approaches to characterise the role of individual nodes as well as connectivity-based methods to study interactions at the systems level.

Direction-sensitive codes for observed head turns in human superior temporal sulcus.

Humans and other primates are adept at using the direction of another's gaze or head turn to infer where that individual is attending. Research in macaque neurophysiology suggests that anterior superior temporal sulcus (STS) contains a direction-sensitive code for such social attention cues. By contrast, most human functional Magnetic resonance imaging (fMRI) studies report that posterior STS is responsive to social attention cues. It is unclear whether this functional discrepancy is caused by a species difference or by experimental design differences. Furthermore, social attention cues are dynamic in naturalistic social interaction, but most studies to date have been restricted to static displays. In order to address these issues, we used multivariate pattern analysis of fMRI data to test whether response patterns in human right STS distinguish between leftward and rightward dynamic head turns. Such head turn discrimination was observed in right anterior STS/superior temporal gyrus (STG). Response patterns in this region were also significantly more discriminable for head turn direction than for rotation direction in physically matched ellipsoid control stimuli. Our findings suggest a role for right anterior STS/STG in coding the direction of motion in dynamic social attention cues.

A head view-invariant representation of gaze direction in anterior superior temporal sulcus.

Humans show a remarkable ability to discriminate others' gaze direction, even though a given direction can be conveyed by many physically dissimilar configurations of different eye positions and head views. For example, eye contact can be signaled by a rightward glance in a left-turned head or by direct gaze in a front-facing head. Such acute gaze discrimination implies considerable perceptual invariance. Previous human research found that superior temporal sulcus (STS) responds preferentially to gaze shifts [1], but the underlying representation that supports such general responsiveness remains poorly understood. Using multivariate pattern analysis (MVPA) of human functional magnetic resonance imaging (fMRI) data, we tested whether STS contains a higher-order, head view-invariant code for gaze direction. The results revealed a finely graded gaze direction code in right anterior STS that was invariant to head view and physical image features. Further analyses revealed similar gaze effects in left anterior STS and precuneus. Our results suggest that anterior STS codes the direction of another's attention regardless of how this information is conveyed and demonstrate how high-level face areas carry out fine-grained, perceptually relevant discrimination through invariance to other face features.