MRI diffusion tractography study in individuals with schizotypal features: a pilot study.

Diffusion tensor imaging (DTI) studies have identified changes in white matter tracts in schizophrenia patients and those at high risk of transition. Schizotypal samples represent a group on the schizophrenia continuum that share some aetiological risk factors but without the confounds of illness. The aim of the current study was to compare tract microstructural coherence as measured by fractional anisotropy (FA) between 12 psychometrically defined schizotypes and controls. We investigated bilaterally the uncinate and arcuate fasciculi (UF and AF) via a probabilistic tractography algorithm (PICo), with FA values compared between groups. Partial correlations were also examined between measures of subclinical hallucinatory/delusional experiences and FA values. Participants with schizotypal features were found to have increased FA values in the left hemisphere UF only. In the whole sample there was a positive correlation between FA values and measures of hallucinatory experience in the right AF. These findings suggest subtle changes in microstructural coherence are found in individuals with schizotypal features, but are not similar to changes predominantly observed in clinical samples. Correlations between mild hallucinatory experience and FA values could indicate increasing tract coherence could be associated with symptom formation.

Both the middle temporal gyrus and the ventral anterior temporal area are crucial for multimodal semantic processing: distortion-corrected fMRI evidence for a double gradient of information convergence in the temporal lobes.

Most contemporary theories of semantic memory assume that concepts are formed from the distillation of information arising in distinct sensory and verbal modalities. The neural basis of this distillation or convergence of information was the focus of this study. Specifically, we explored two commonly posed hypotheses: (a) that the human middle temporal gyrus (MTG) provides a crucial semantic interface given the fact that it interposes auditory and visual processing streams and (b) that the anterior temporal region-especially its ventral surface (vATL)-provides a critical region for the multimodal integration of information. By utilizing distortion-corrected fMRI and an established semantic association assessment (commonly used in neuropsychological investigations), we compared the activation patterns observed for both the verbal and nonverbal versions of the same task. The results are consistent with the two hypotheses simultaneously: Both MTG and vATL are activated in common for word and picture semantic processing. Additional planned, ROI analyses show that this result follows from two principal axes of convergence in the temporal lobe: both lateral (toward MTG) and longitudinal (toward the anterior temporal lobe).

The ventral and inferolateral aspects of the anterior temporal lobe are crucial in semantic memory: evidence from a novel direct comparison of distortion-corrected fMRI, rTMS, and semantic dementia.

Although there is an emerging consensus that the anterior temporal lobes (ATLs) are involved in semantic memory, it is currently unclear which specific parts of this region are implicated in semantic representation. Answers to this question are difficult to glean from the existing literature for 3 reasons: 1) lesions of relevant patient groups tend to encompass the whole ATL region; 2) while local effects of repetitive transcranial magnetic stimulation (rTMS) are spatially more specific, only the lateral aspects of the ATL are available to stimulation; and 3) until recently, functional magnetic resonance imaging (fMRI) studies were hindered by technical limitations such as signal distortion and dropout due to magnetic inhomogeneities and also, in some cases, by methodological factors, including a restricted field of view and the choice of baseline contrast for subtraction analysis. By utilizing the same semantic task across semantic dementia, rTMS, and distortion-corrected fMRI in normal participants, we directly compared the results across the 3 methods for the first time. The findings were highly convergent and indicated that crucial regions within the ATL for semantic representation include the anterior inferior temporal gyrus, anterior fusiform gyrus, and the anterior superior temporal sulcus.

Distortion correction for diffusion-weighted MRI tractography and fMRI in the temporal lobes.

Single shot echo-planar imaging (EPI) sequences are currently the most commonly used sequences for diffusion-weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) as they allow relatively high signal to noise with rapid acquisition time. A major drawback of EPI is the substantial geometric distortion and signal loss that can occur due to magnetic field inhomogeneities close to air-tissue boundaries. If DWI-based tractography and fMRI are to be applied to these regions, then the distortions must be accurately corrected to achieve meaningful results. We describe robust acquisition and processing methods for correcting such distortions in spin echo (SE) EPI using a variant of the reversed direction k space traversal method with a number of novel additions. We demonstrate that dual direction k space traversal with maintained diffusion-encoding gradient strength and direction results in correction of the great majority of eddy current-associated distortions in DWI, in addition to those created by variations in magnetic susceptibility. We also provide examples to demonstrate that the presence of severe distortions cannot be ignored if meaningful tractography results are desired. The distortion correction routine was applied to SE-EPI fMRI acquisitions and allowed detection of activation in the temporal lobe that had been previously found using PET but not conventional fMRI.

Using the model-based residual bootstrap to quantify uncertainty in fiber orientations from Q-ball analysis.

Bootstrapping of repeated diffusion-weighted image datasets enables nonparametric quantification of the uncertainty in the inferred fiber orientation. The wild bootstrap and the residual bootstrap are model-based residual resampling methods which use a single dataset. Previously, the wild bootstrap method has been presented as an alternative to conventional bootstrapping for diffusion tensor imaging. Here we present a study of an implementation of model-based residual bootstrapping using q -ball analysis and compare the outputs with conventional bootstrapping. We show that model-based residual bootstrap q-ball generates results that closely match the output of the conventional bootstrap. Both the residual and conventional bootstrap of multifiber methods can be used to estimate the probability of different numbers of fiber populations existing in different brain tissues. Also, we have shown that these methods can be used to provide input for probabilistic tractography, avoiding existing limitations associated with data calibration and model selection.

Probabilistic fibre tracking: differentiation of connections from chance events.

Probabilistic tractography methods that use Monte Carlo sampling of voxelwise fibre orientation probability density functions suffer from distance-related artefacts due to the propagation of uncertainty along the tract path. These are manifested as a preferential weighting of regions close to the tracking start point at the expense of more distant regions--an effect that can mask genuine anatomical connections. We propose a methodology based on comparison of the conventional connection probability map with a null connection map that defines the distribution of connections expected by a random tracking process and that is dominated by the same distance effects. When the connection probability is significantly greater than the result of the null tracking result this identifies voxels where the diffusion information is providing more evidence of connection than that expected from random tracking. We show that the null connection probability map used is governed by Poisson statistics within each voxel, allowing analytical estimation of connection values that are significantly different to the null connection values. The resultant significant connection maps can be combined with the conventional probabilistic tractography output to produce maps of significant connections which reduce distance-related artefacts by removing areas where the observed frequency of connection is dominated simply by distance effects and not the diffusion information. This is achieved by applying an objective statistical interpretation of observed patterns of connection which cannot be achieved by simple thresholding of conventional probabilistic tractography maps due to the distance effect.

Distortion correction for a double inversion-recovery sequence with an echo-planar imaging readout.

A double inversion-recovery (DIR) sequence with an echo-planar imaging (EPI) readout can be used to image selectively the grey matter of the brain, and this has previously been applied to improve the sensitivity of the statistical analysis of functional magnetic resonance imaging (fMRI) data. If a procedure were to be implemented to remove the distortions that are inherent in the EPI-based fMRI data set, then a similar technique would have to be applied to the DIR-EPI image also to ensure that it matches the geometry of the functional data. A comparison of candidate methodologies for correcting distortions in DIR-EPI images, based on the reversed-gradient method, is presented. A corrected image could be calculated from two DIR-EPI images acquired with k-space traversal in opposite directions, but that method was not able to cope with the large regions of low signal intensity corresponding to the nulled white matter. It was found that the optimal procedure to apply the reversed-gradient method to DIR-EPI images was to acquire two additional EPI images (without the two inversion pulses) with opposite-direction k-space traversal; the distortion-correction information calculated from those EPI images was then applied to the DIR-EPI data.