Donald J. Hagler

Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data

Cortical surface-based analysis of fMRI data has proven to be a useful method with several advantages over 3-dimensional volumetric analyses. Many of the statistical methods used in 3D analyses can be adapted for use with surface-based analyses. Operating within the framework of the FreeSurfer software package, we have implemented a surface-based version of the cluster size exclusion method used for multiple comparisons correction. Furthermore, we have a developed a new method for generating regions of interest on the cortical surface using a sliding threshold of cluster exclusion followed by cluster growth. Cluster size limits for multiple probability thresholds were estimated using random field theory and validated with Monte Carlo simulation. A prerequisite of RFT or cluster size simulation is an estimate of the smoothness of the data. In order to estimate the intrinsic smoothness of group analysis statistics, independent of true activations, we conducted a group analysis of simulated noise data sets. Because smoothing on a cortical surface mesh is typically implemented using an iterative method, rather than directly applying a Gaussian blurring kernel, it is also necessary to determine the width of the equivalent Gaussian blurring kernel as a function of smoothing steps. Iterative smoothing has previously been modeled as continuous heat diffusion, providing a theoretical basis for predicting the equivalent kernel width, but the predictions of the model were not empirically tested. We generated an empirical heat diffusion kernel width function by performing surface-based smoothing simulations and found a large disparity between the expected and actual kernel widths.

Brain development and aging: Overlapping and unique patterns of change

Early-life development is characterized by dramatic changes, impacting lifespan function more than changes in any other period. Developmental origins of neurocognitive late-life functions are acknowledged, but detailed longitudinal magnetic resonance imaging studies of brain maturation and direct comparisons with aging are lacking. To these aims, a novel method was used to measure longitudinal volume changes in development (n=85, 8-22 years) and aging (n=142, 60-91 years). Developmental reductions exceeded 1% annually in much of the cortex, more than double to that seen in aging, with a posterior-to-anterior gradient. Cortical reductions were greater than the subcortical during development, while the opposite held in aging. The pattern of lateral cortical changes was similar across development and aging, but the pronounced medial temporal reduction in aging was not precast in development. Converging patterns of change in adolescents and elderly, particularly in the medial prefrontal areas, suggest that late developed cortices are especially vulnerable to atrophy in aging. A key question in future research will be to disentangle the neurobiological underpinnings for the differences and the similarities between brain changes in development and aging.

A Novel Integrated MEG and EEG Analysis Method for Dipolar Sources

The ability of magnetoencephalography (MEG) to accurately localize neuronal currents and obtain tangential components of the source is largely due to MEGs insensitivity to the conductivity profile of the head tissues. However, MEG cannot reliably detect the radial component of the neuronal current. In contrast, the localization accuracy of electroencephalography (EEG) is not as good as MEG, but EEG can detect both the tangential and radial components of the source. In the present study, we investigated the conductivity dependence in a new approach that combines MEG and EEG to accurately obtain, not only the location and tangential components, but also the radial component of the source. In this approach, the source location and tangential components are obtained from MEG alone, and optimal conductivity values of the EEG model are estimated by best-fitting EEG signal, while precisely matching the tangential components of the source in EEG and MEG. Then, the radial components are obtained from EEG using the previously estimated optimal conductivity values. Computer simulations testing this integrated approach demonstrated two main findings. First, there are well-organized optimal combinations of the conductivity values that provide an accurate fit to the combined MEG and EEG data. Second, the radial component, in addition to the location and tangential components, can be obtained with high accuracy without needing to know the precise conductivity profile of the head. We then demonstrated that this new approach performed reliably in an analysis of the 20-ms component from human somatosensory responses elicited by electric median-nerve stimulation.

Six-month atrophy in MTL structures is associated with subsequent memory decline in elderly controls.

Neurodegeneration precedes the onset of dementias such as Alzheimers by several years. Recent advances in volumetric imaging allow quantification of subtle neuroanatomical change over time periods as short as six months. This study investigates whether neuroanatomical change in medial temporal lobe subregions is associated with later memory decline in elderly controls. Using high-resolution, T1-weighted magnetic resonance images acquired at baseline and six-month follow-up, change in cortical thickness and subcortical volumes was measured in 142 healthy elderly subjects (aged 59-90 years) from the ADNI cohort. Regression analysis was used to identify whether change in fourteen subregions, selected a priori, was associated with declining performance on memory tests from baseline to two-year follow-up. Percent thickness change in the right fusiform and inferior temporal cortices and expansion of the right inferior lateral ventricle were found to be significant predictors of subsequent decline on memory-specific neuropsychological measures. These results demonstrate that six-month regional neurodegeneration can be quantified in the healthy elderly and might help identify those at risk for subsequent cognitive decline.

Phonetically irregular word pronunciation and cortical thickness in the adult brain

Accurate pronunciation of phonetically irregular words (exception words) requires prior exposure to unique relationships between orthographic and phonemic features. Whether such word knowledge is accompanied by structural variation in areas associated with orthographic-to-phonemic transformations has not been investigated. We used high-resolution MRI to determine whether performance on a visual word-reading test composed of phonetically irregular words, the Wechsler Test of Adult Reading (WTAR), is associated with regional variations in cortical structure. A sample of 60 right-handed, neurologically intact individuals were administered the WTAR and underwent 3T volumetric MRI. Using quantitative, surface-based image analysis, cortical thickness was estimated at each vertex on the cortical mantle and correlated with WTAR scores while controlling for age. Higher scores on the WTAR were associated with thicker cortex in bilateral anterior superior temporal gyrus, bilateral angular gyrus/posterior superior temporal gyrus, and left hemisphere intraparietal sulcus. Higher scores were also associated with thinner cortex in left hemisphere posterior fusiform gyrus and central sulcus, bilateral inferior frontal gyrus, and right hemisphere lingual gyrus and supramarginal gyrus. These results suggest that the ability to correctly pronounce phonetically irregular words is associated with structural variations in cortical areas that are commonly activated in functional neuroimaging studies of word reading, including areas associated with grapheme-to-phonemic conversion.

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.

Does degree of gyrification underlie the phenotypic and genetic associations between cortical surface area and cognitive ability

The phenotypic and genetic relationship between global cortical size and general cognitive ability (GCA) appears to be driven by surface area (SA) and not cortical thickness (CT). Gyrification (cortical folding) is an important property of the cortex that helps to increase SA within a finite space, and may also improve connectivity by reducing distance between regions. Hence, gyrification may be what underlies the SA-GCA relationship. In previous phenotypic studies, a 3-dimensional gyrification index (3DGI) has been positively associated with cognitive ability and negatively associated with mild cognitive impairment, Alzheimers disease, and psychiatric disorders affecting cognition. However, the differential genetic associations of 3DGI and SA with GCA are still unclear. We examined the heritability of 3DGI, and the phenotypic, genetic, and environmental associations of 3DGI with SA and GCA in a large sample of adult male twins (N = 512). Nearly 85% of the variance in 3DGI was due to genes, and 3DGI had a strong phenotypic and genetic association with SA. Both 3DGI and total SA had positive phenotypic correlations with GCA. However, the SA-GCA correlation remained significant after controlling for 3DGI, but not the other way around. There was also significant genetic covariance between SA and GCA, but not between 3DGI and GCA. Thus, despite the phenotypic and genetic associations between 3DGI and SA, our results do not support the hypothesis that gyrification underlies the association between SA and GCA.

The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites

The ABCD study is recruiting and following the brain development and health of over 10,000 9–10 year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisition Workgroup. Imaging methods and assessments were selected, optimized and harmonized across all 21 sites to measure brain structure and function relevant to adolescent development and addiction. This article provides an overview of the imaging procedures of the ABCD study, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature.

Genetic and environmental influences on cortical mean diffusivity

Abstract Magnetic resonance imaging (MRI) has become an important tool in the early detection of age‐related and neuropathological brain changes. Recent studies suggest that changes in mean diffusivity (MD) of cortical gray matter derived from diffusion MRI scans may be useful in detecting early effects of Alzheimers disease (AD), and that these changes may be detected earlier than alterations associated with standard structural MRI measures such as cortical thickness. Thus, due to its potential clinical relevance, we examined the genetic and environmental influences on cortical MD in middle‐aged men to provide support for the biological relevance of this measure and to guide future gene association studies. It is not clear whether individual differences in cortical MD reflect neuroanatomical variability similarly detected by other MRI measures, or whether unique features are captured. For instance, variability in cortical MD may reflect morphological variability more commonly measured by cortical thickness. Differences among individuals in cortical MD may also arise from breakdowns in myelinated fibers running through the cortical mantle. Thus, we investigated whether genetic influences on variation in cortical MD are the same or different from those influencing cortical thickness and MD of white matter (WM) subjacent to the cortical ribbon. Univariate twin analyses indicated that cortical MD is heritable in the majority of brain regions; the average of regional heritability estimates ranged from 0.38 in the cingulate cortex to 0.66 in the occipital cortex, consistent with the heritability of other MRI measures of the brain. Trivariate analyses found that, while there was some shared genetic variance between cortical MD and each of the other two measures, this overlap was not complete (i.e., the correlation was statistically different from 1). A significant amount of distinct genetic variance influences inter‐individual variability in cortical MD; therefore, this measure could be useful for further investigation in studies of neurodegenerative diseases and gene association studies. HighlightsAltered mean diffusivity (MD) of cortical gray matter may indicate early degeneration.MD was heritable in a majority of cortical regions.Some genetic correlation between cortical MD, thickness and white matter MD.There are distinct genetic influences on individual variability in cortical MD.

Decreased neurite density within frontostriatal networks is associated with executive dysfunction in temporal lobe epilepsy

OBJECTIVE Executive dysfunction is observed in a sizable number of patients with refractory temporal lobe epilepsy (TLE). The frontostriatal network has been proposed to play a significant role in executive functioning, however, because of the complex architecture of these tracts, it is difficult to generate measures of fiber tract microstructure using standard diffusion tensor imaging. To examine the association between frontostriatal network compromise and executive dysfunction in TLE, we applied an advanced, multishell diffusion model, restriction spectrum imaging (RSI), that isolates measures of intraaxonal diffusion and may provide better estimates of fiber tract compromise in TLE. METHODS Restriction spectrum imaging scans were obtained from 32 patients with TLE [16 right TLE (RTLE); 16 left TLE (LTLE)] and 24 healthy controls (HC). An RSI-derived measure of intraaxonal anisotropic diffusion (neurite density; ND) was calculated for the inferior frontostriatal tract (IFS) and superior frontostriatal tract (SFS) and compared between patients with TLE and HC. Spearman correlations were performed to evaluate the relationships between ND of each tract and verbal (i.e., D-KEFS Category Switching Accuracy and Color-Word Interference Inhibition/Switching) and visuomotor (Trail Making Test) set-shifting performances in patients with TLE. RESULTS Patients with TLE demonstrated reductions in ND of the left and right IFS, but not SFS, compared with HC. Reduction in ND of left and right IFS was associated with poorer performance on verbal set-shifting in TLE. Increases in extracellular diffusion (isotropic hindered; IH) were not associated with executive dysfunction in the patient group. SIGNIFICANCE Restriction spectrum imaging-derived ND revealed microstructural changes within the IFS in patients with TLE, which was associated with poorer executive functioning. This suggests that axonal/myelin loss to fiber networks connecting the striatum to the inferior frontal cortex is likely contributing to executive dysfunction in TLE.