Cheryl A. Olman

Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI†

Parallel imaging in the form of multiband radiofrequency excitation, together with reduced k‐space coverage in the phase‐encode direction, was applied to human gradient echo functional MRI at 7 T for increased volumetric coverage and concurrent high spatial and temporal resolution. Echo planar imaging with simultaneous acquisition of four coronal slices separated by 44mm and simultaneous 4‐fold phase‐encoding undersampling, resulting in 16‐fold acceleration and up to 16‐fold maximal aliasing, was investigated. Task/stimulus‐induced signal changes and temporal signal behavior under basal conditions were comparable for multiband and standard single‐band excitation and longer pulse repetition times. Robust, whole‐brain functional mapping at 7 T, with 2 × 2 × 2mm3 (pulse repetition time 1.25 sec) and 1 × 1 × 2mm3 (pulse repetition time 1.5 sec) resolutions, covering fields of view of 256 × 256 × 176mm3 and 192 × 172 × 176mm3, respectively, was demonstrated with current gradient performance. Magn Reson Med 63:1144–1153, 2010.

Metabolic and Hemodynamic Events after Changes in Neuronal Activity: Current Hypotheses, Theoretical Predictions and in vivo NMR Experimental Findings

Unraveling the energy metabolism and the hemodynamic outcomes of excitatory and inhibitory neuronal activity is critical not only for our basic understanding of overall brain function, but also for the understanding of many brain disorders. Methodologies of magnetic resonance spectroscopy (MRS) and magnetic resonance imaging (MRI) are powerful tools for the noninvasive investigation of brain metabolism and physiology. However, the temporal and spatial resolution of in vivo MRS and MRI is not suitable to provide direct evidence for hypotheses that involve metabolic compartmentalization between different cell types, or to untangle the complex neuronal microcircuitry, which results in changes of electrical activity. This review aims at describing how the current models of brain metabolism, mainly built on the basis of in vitro evidence, relate to experimental findings recently obtained in vivo by 1H MRS, 13C MRS, and MRI. The hypotheses related to the role of different metabolic substrates, the metabolic neuron—glia interactions, along with the available theoretical predictions of the energy budget of neurotransmission will be discussed. In addition, the cellular and network mechanisms that characterize different types of increased and suppressed neuronal activity will be considered within the sensitivity-constraints of MRS and MRI.

Spatial relationship between neuronal activity and BOLD functional MRI

Despite the ubiquitous use of functional magnetic resonance imaging (fMRI), the extent to which the magnitude and spatial scale of the fMRI signal correlates with neuronal activity is poorly understood. In this study, we directly compared single and multiunit neuronal activity with blood oxygenation level-dependent (BOLD) fMRI responses across a large area of the cat area 18. Our data suggest that at the scale of several millimeters, the BOLD contrast correlates linearly with the underlying neuronal activity. At the level of individual electrode recording sites, however, the correlation between the two signals varied substantially. We conclude from our study that T(2)*-based positive BOLD signals are a robust predictor for neuronal activity only at supra-millimeter spatial scales.

Layer-Specific fMRI Reflects Different Neuronal Computations at Different Depths in Human V1

Recent work has established that cerebral blood flow is regulated at a spatial scale that can be resolved by high field fMRI to show cortical columns in humans. While cortical columns represent a cluster of neurons with similar response properties (spanning from the pial surface to the white matter), important information regarding neuronal interactions and computational processes is also contained within a single column, distributed across the six cortical lamina. A basic understanding of underlying neuronal circuitry or computations may be revealed through investigations of the distribution of neural responses at different cortical depths. In this study, we used T2-weighted imaging with 0.7 mm (isotropic) resolution to measure fMRI responses at different depths in the gray matter while human subjects observed images with either recognizable or scrambled (physically impossible) objects. Intact and scrambled images were partially occluded, resulting in clusters of activity distributed across primary visual cortex. A subset of the identified clusters of voxels showed a preference for scrambled objects over intact; in these clusters, the fMRI response in middle layers was stronger during the presentation of scrambled objects than during the presentation of intact objects. A second experiment, using stimuli targeted at either the magnocellular or the parvocellular visual pathway, shows that laminar profiles in response to parvocellular-targeted stimuli peak in more superficial layers. These findings provide new evidence for the differential sensitivity of high-field fMRI to modulations of the neural responses at different cortical depths.

BOLD fMRI and psychophysical measurements of contrast response to broadband images

We have measured the relationship between image contrast, perceived contrast, and BOLD fMRI activity in human early visual areas, for natural, whitened, pink noise, and white noise images. As root-mean-square contrast increases, BOLD response to natural images is stronger and saturates more rapidly than response to the whitened images. Perceived contrast and BOLD fMRI responses are higher for pink noise than for white noise patterns, by the same ratio as between natural and whitened images. Spatial phase structure has no measurable effect on perceived contrast or BOLD fMRI response. The fMRI and perceived contrast response results can be described by models of spatial frequency response in V1, that match the contrast sensitivity function at low contrasts, and have more uniform spatial frequency response at high contrasts.

A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes

Recent multi-voxel pattern classification (MVPC) studies have shown that in early visual cortex patterns of brain activity generated during mental imagery are similar to patterns of activity generated during perception. This finding implies that low-level visual features (e.g., space, spatial frequency, and orientation) are encoded during mental imagery. However, the specific hypothesis that low-level visual features are encoded during mental imagery is difficult to directly test using MVPC. The difficulty is especially acute when considering the representation of complex, multi-object scenes that can evoke multiple sources of variation that are distinct from low-level visual features. Therefore, we used a voxel-wise modeling and decoding approach to directly test the hypothesis that low-level visual features are encoded in activity generated during mental imagery of complex scenes. Using fMRI measurements of cortical activity evoked by viewing photographs, we constructed voxel-wise encoding models of tuning to low-level visual features. We also measured activity as subjects imagined previously memorized works of art. We then used the encoding models to determine if putative low-level visual features encoded in this activity could pick out the imagined artwork from among thousands of other randomly selected images. We show that mental images can be accurately identified in this way; moreover, mental image identification accuracy depends upon the degree of tuning to low-level visual features in the voxels selected for decoding. These results directly confirm the hypothesis that low-level visual features are encoded during mental imagery of complex scenes. Our work also points to novel forms of brain-machine interaction: we provide a proof-of-concept demonstration of an internet image search guided by mental imagery.

Distortion and Signal Loss in Medial Temporal Lobe

Background The medial temporal lobe (MTL) contains subregions that are subject to severe distortion and signal loss in functional MRI. Air/tissue and bone/tissue interfaces in the vicinity of the MTL distort the local magnetic field due to differences in magnetic susceptibility. Fast image acquisition and thin slices can reduce the amount of distortion and signal loss, but at the cost of image signal-to-noise ratio (SNR). Methodology/Principal Findings In this paper, we quantify the severity of distortion and signal loss in MTL subregions for three different echo planar imaging (EPI) acquisitions at 3 Tesla: a conventional moderate-resolution EPI (3×3×3 mm), a conventional high-resolution EPI (1.5×1.5×2 mm), and a zoomed high-resolution EPI. We also demonstrate the advantage of reversing the phase encode direction to control the direction of distortion and to maximize efficacy of distortion compensation during data post-processing. With the high-resolution zoomed acquisition, distortion is not significant and signal loss is present only in the most anterior regions of the parahippocampal gyrus. Furthermore, we find that the severity of signal loss is variable across subjects, with some subjects showing negligible loss and others showing more dramatic loss. Conclusions/Significance Although both distortion and signal loss are minimized in a zoomed field of view acquisition with thin slices, this improvement in accuracy comes at the cost of reduced SNR. We quantify this trade-off between distortion and SNR in order to provide a decision tree for design of high-resolution experiments investigating the function of subregions in MTL.

Retinotopic mapping with spin echo BOLD at 7T.

For blood oxygenation level-dependent (BOLD) functional MRI experiments, contrast-to-noise ratio (CNR) increases with increasing field strength for both gradient echo (GE) and spin echo (SE) BOLD techniques. However, susceptibility artifacts and nonuniform coil sensitivity profiles complicate large field-of-view fMRI experiments (e.g., experiments covering multiple visual areas instead of focusing on a single cortical region). Here, we use SE BOLD to acquire retinotopic mapping data in early visual areas, testing the feasibility of SE BOLD experiments spanning multiple cortical areas at 7T. We also use a recently developed method for normalizing signal intensity in T(1)-weighted anatomical images to enable automated segmentation of the cortical gray matter for scans acquired at 7T with either surface or volume coils. We find that the CNR of the 7T GE data (average single-voxel, single-scan stimulus coherence: 0.41) is almost twice that of the 3T GE BOLD data (average coherence: 0.25), with the CNR of the SE BOLD data (average coherence: 0.23) comparable to that of the 3T GE data. Repeated measurements in individual subjects find that maps acquired with 1.8-mm resolution at 3T and 7T with GE BOLD and at 7T with SE BOLD show no systematic differences in either the area or the boundary locations for V1, V2 and V3, demonstrating the feasibility of high-resolution SE BOLD experiments with good sensitivity throughout multiple visual areas.

High-Field fMRI for Human Applications: An Overview of Spatial Resolution and Signal Specificity

In the last decade, dozens of 7 Tesla scanners have been purchased or installed around the world, while 3 Tesla systems have become a standard. This increased interest in higher field strengths is driven by a demonstrated advantage of high fields for available signal-to-noise ratio (SNR) in the magnetic resonance signal. Functional imaging studies have additional advantages of increases in both the contrast and the spatial specificity of the susceptibility based BOLD signal. One use of this resultant increase in the contrast to noise ratio (CNR) for functional MRI studies at high field is increased image resolution. However, there are many factors to consider in predicting exactly what kind of resolution gains might be made at high fields, and what the opportunity costs might be. The first part of this article discusses both hardware and image quality considerations for higher resolution functional imaging. The second part draws distinctions between image resolution, spatial specificity, and functional specificity of the fMRI signals that can be acquired at high fields, suggesting practical limitations for attainable resolutions of fMRI experiments at a given field, given the current state of the art in imaging techniques. Finally, practical resolution limitations and pulse sequence options for studies in human subjects are considered.

Neural correlates of preparatory and regulatory control over positive and negative emotion

This study used functional magnetic resonance imaging to investigate brain activation during preparatory and regulatory control while participants (N = 24) were instructed either to simply view or decrease their emotional response to, pleasant, neutral or unpleasant pictures. A main effect of emotional valence on brain activity was found in the right precentral gyrus, with greater activation during positive than negative emotion regulation. A main effect of regulation phase was evident in the bilateral anterior prefrontal cortex (PFC), precuneus, posterior cingulate cortex, right putamen and temporal and occipital lobes, with greater activity in these regions during preparatory than regulatory control. A valence X regulation interaction was evident in regions of ventromedial PFC and anterior cingulate cortex, reflecting greater activation while regulating negative than positive emotion, but only during active emotion regulation (not preparation). Conjunction analyses revealed common brain regions involved in differing types of emotion regulation including selected areas of left lateral PFC, inferior parietal lobe, temporal lobe, right cerebellum and bilateral dorsomedial PFC. The right lateral PFC was additionally activated during the modulation of both positive and negative valence. Findings demonstrate significant modulation of brain activity during both preparation for, and active regulation of positive and negative emotional states.