Variable precision registration via wavelets: optimal spatial scales for inter-subject registration of functional MRI

The detection of significantly activated brain regions in multi-subject functional magnetic resonance imaging (fMRI) studies almost invariably entails the coregistration of individual subjects' data in a standard space. Here, we investigate how sensitivity to detect loci of generic activation in such studies may be conditioned by the precision of anatomical registration. We describe a novel algorithm, implemented in the wavelet domain, for inhomogeneous deformation of individual images to match a template. The algorithm matches anatomical features in a coarse-to-fine fashion, first minimising a cost function in terms of relatively coarse spatial features and then proceeding iteratively to match the images in terms of progressively more detailed anatomical features. Applying the method to data acquired from two groups of 12 healthy volunteers (with mean age 27 and 70 years, respectively), during performance of a paired associate learning task, we show that geometrical overlap between template and individual images is monotonically improved, compared to an affine transform, by additional inhomogeneous deformations informed by more detailed features. Likewise, sensitivity to detect activated voxels can be substantially improved, by a factor of 4 or more, if wavelet-mediated deformations informed by medium-sized anatomical features are applied in addition to a preliminary affine transform. However, sensitivity to detect activated voxels was reduced by "over-registering" data or matching anatomical features at the finest scales of the wavelet transform. The benefits of variable precision registration are particularly salient for data acquired in older subjects, which showed evidence of greater inter-subject anatomic variability and generally required more extensive local deformation to achieve a satisfactory match to the template image. We conclude that major benefits in sensitivity to detect functional activation in multi-subject fMRI studies can be attained with an inhomogeneous deformation applied over appropriate spatial scales.     

Task-induced deactivations during successful paired associates learning: an effect of age but not Alzheimer's disease

Task-induced fMRI deactivations during successful encoding and retrieval of visuospatial paired associates were examined at different levels of task difficulty in younger and older adults (Experiment 1), and older adults with and without mild probable Alzheimer's disease (AD) (Experiment 2). Irrespective of the level of task difficulty, common deactivations (determined through the use of conjunction analyses) were observed in the lateral and medial prefrontal, anterior and posterior cingulate, and temporal brain regions and in the claustrum during both encoding and retrieval in younger and older adults (Experiment 1). In AD patients and healthy older adults, common deactivations were found in posterior cingulate, temporal, and lateral parietal regions and in the insula and claustrum during encoding and retrieval of paired associates (Experiment 2). As task difficulty increased, irrespective of the type of task, the magnitude of task-induced deactivations increased in the medial prefrontal/superior frontal gyrus and middle/posterior cingulate cortex in younger and older adults (Experiment 1), and in the middle cingulate cortex in older adults with and without AD (Experiment 2). In Experiment 1, greater deactivation was observed in the anterior cingulate gyrus in older compared to younger adults during retrieval of paired associates which was attributed to greater suppression of task-unrelated thoughts in the older group. No significant differences in task-induced deactivation, or in the type of relationship exhibited between deactivation and task difficulty, were observed between older adults with and without AD (Experiment 2). It was suggested that this was related to the matching of successful task performance and task difficulty across patient and control groups. Following previous proposals, task-induced deactivations were suggested to underlie a shifting of attentional focus from monitoring of the self and the environment (through attenuation of these activities) to external, goal-directed behaviour.     

Cognitive fitness of cost-efficient brain functional networks

The human brain''s capacity for cognitive function is thought to depend on coordinated activity in sparsely connected, complex networks organized over many scales of space and time. Recent work has demonstrated that human brain networks constructed from neuroimaging data have economical small-world properties that confer high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of complex brain networks functioning at different frequencies can be related to behavioral performance on cognitive tasks. Here, we show that impaired accuracy of working memory could be related to suboptimal cost efficiency of brain functional networks operating in the classical β frequency band, 15–30 Hz. We analyzed brain functional networks derived from magnetoencephalography data recorded during working-memory task performance in 29 healthy volunteers and 28 people with schizophrenia. Networks functioning at higher frequencies had greater global cost efficiency than low-frequency networks in both groups. Superior task performance was positively correlated with global cost efficiency of the β-band network and specifically with cost efficiency of nodes in left lateral parietal and frontal areas. These results are consistent with biophysical models highlighting the importance of β-band oscillations for long-distance functional connections in brain networks and with pathophysiological models of schizophrenia as a dysconnection syndrome. More generally, they echo the saying that “less is more”: The information processing performance of a network can be enhanced by a sparse or low-cost configuration with disproportionately high efficiency.     

Resampling methods for improved wavelet-based multiple hypothesis testing of parametric maps in functional MRI

Two- or three-dimensional wavelet transforms have been considered as a basis for multiple hypothesis testing of parametric maps derived from functional magnetic resonance imaging (fMRI) experiments. Most of the previous approaches have assumed that the noise variance is equally distributed across levels of the transform. Here we show that this assumption is unrealistic; fMRI parameter maps typically have more similarity to a 1/f-type spatial covariance with greater variance in 2D wavelet coefficients representing lower spatial frequencies, or coarser spatial features, in the maps. To address this issue we resample the fMRI time series data in the wavelet domain (using a 1D discrete wavelet transform [DWT]) to produce a set of permuted parametric maps that are decomposed (using a 2D DWT) to estimate level-specific variances of the 2D wavelet coefficients under the null hypothesis. These resampling-based estimates of the "wavelet variance spectrum" are substituted in a Bayesian bivariate shrinkage operator to denoise the observed 2D wavelet coefficients, which are then inverted to reconstitute the observed, denoised map in the spatial domain. Multiple hypothesis testing controlling the false discovery rate in the observed, denoised maps then proceeds in the spatial domain, using thresholds derived from an independent set of permuted, denoised maps. We show empirically that this more realistic, resampling-based algorithm for wavelet-based denoising and multiple hypothesis testing has good Type I error control and can detect experimentally engendered signals in data acquired during auditory-linguistic processing.     

Atypically rightward cerebral asymmetry in male adults with autism stratifies individuals with and without language delay

In humans, both language and fine motor skills are associated with left‐hemisphere specialization, whereas visuospatial skills are associated with right‐hemisphere specialization. Individuals with autism spectrum conditions (ASC) show a profile of deficits and strengths that involves these lateralized cognitive functions. Here we test the hypothesis that regions implicated in these functions are atypically rightward lateralized in individuals with ASC and, that such atypicality is associated with functional performance. Participants included 67 male, right‐handed adults with ASC and 69 age‐ and IQ‐matched neurotypical males. We assessed group differences in structural asymmetries in cortical regions of interest with voxel‐based analysis of grey matter volumes, followed by correlational analyses with measures of language, motor and visuospatial skills. We found stronger rightward lateralization within the inferior parietal lobule and reduced leftward lateralization extending along the auditory cortex comprising the planum temporale, Heschl's gyrus, posterior supramarginal gyrus, and parietal operculum, which was more pronounced in ASC individuals with delayed language onset compared to those without. Planned correlational analyses showed that for individuals with ASC, reduced leftward asymmetry in the auditory region was associated with more childhood social reciprocity difficulties. We conclude that atypical cerebral structural asymmetry is a potential candidate neurophenotype of ASC. Hum Brain Mapp 37:230–253, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.