Faculty Bibliography

Malformations of cortical development are found at higher rates in autism spectrum disorder (ASD) than in healthy controls on postmortem neuropathological evaluation but are more variably observed on visual review of in-vivo MRI brain scans. This may be due to the visually elusive nature of many malformations on MRI. Here, we utilize a quantitative approach to determine whether a volumetric measure of heterotopic gray matter in the white matter is elevated in people with ASD, relative to typically developing controls (TDC). Data from a primary sample of 48 children/young adults with ASD and 48 age-, and gender-matched TDCs, selected from the Autism Brain Imaging Data Exchange (ABIDE) open-access database, were analyzed to compare groups on (1) blinded review of high-resolution T1-weighted research sequences; and (2) quantitative measurement of white matter hypointensity (WMH) volume calculated from the same T1-weighted scans. Groupwise WMH volume comparisons were repeated in an independent, multi-site sample (80 ASD/80 TDC), also selected from ABIDE. Visual review resulted in equivalent proportions of imaging abnormalities in the ASD and TDC group. However, quantitative analysis revealed elevated periventricular and deep subcortical WMH volumes in ASD. This finding was replicated in the independent, multi-site sample. Periventricular WMH volume was not associated with age but was associated with greater restricted repetitive behaviors on both parent-reported and clinician-rated assessment inventories. Thus, findings demonstrate that periventricular WMH volume is elevated in ASD and associated with a higher degree of repetitive behaviors and restricted interests. Although the etiology of focal WMH clusters is unknown, the absence of age effects suggests that they may reflect a static anomaly.

Focal cortical dysplasia (FCD) is a malformation of cortical development that is associated with high rates of cognitive morbidity. However, the degree to which specific irregularities of dysplastic tissue directly impact cognition remains unknown. This study investigates the relationship between blurring of the cortical gray and white matter boundary on magnetic resonance imaging (MRI) and global cognitive abilities in FCD. Gray-white blurring (GWB) is quantified by sampling the non-normalized T1 image intensity contrast above and below the gray and white matter interface along the cortical mantle. Spherical averaging is used to compare resulting GWB for patients with histopathologically verified FCD with matched controls. Whole-brain correlational analyses are used to investigate the relationship between blurring and general cognitive abilities, controlling for epilepsy duration. Results show that cognitive performance is reduced in patients with FCD relative to controls. Patients show increased GWB in bilateral temporal, parietal, and frontal regions. Furthermore, increased GWB in these regions is linearly related to decreased cognition and mediates group differences in cognitive performance. These findings demonstrate that GWB is a marker of reduced cognitive efficiency in FCD that can potentially be used to probe general and domain-specific cognitive functions in other neurological disorders.

Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epilepsy. Advances in MRI have revolutionized the diagnosis of FCD, resulting in higher success rates for resective epilepsy surgery. However, many patients with histologically confirmed FCD have normal presurgical MRI studies ('MRI-negative'), making presurgical diagnosis difficult. The purpose of this study was to test whether a novel MRI postprocessing method successfully detects histopathologically verified FCD in a sample of patients without visually appreciable lesions. We applied an automated quantitative morphometry approach which computed five surface-based MRI features and combined them in a machine learning model to classify lesional and nonlesional vertices. Accuracy was defined by classifying contiguous vertices as "lesional" when they fell within the surgical resection region. Our multivariate method correctly detected the lesion in 6 of 7 MRI-positive patients, which is comparable with the detection rates that have been reported in univariate vertex-based morphometry studies. More significantly, in patients that were MRI-negative, machine learning correctly identified 14 out of 24 FCD lesions (58%). This was achieved after separating abnormal thickness and thinness into distinct classifiers, as well as separating sulcal and gyral regions. Results demonstrate that MRI-negative images contain sufficient information to aid in the in vivo detection of visually elusive FCD lesions.

Etiological factors that contribute to a high comorbidity between autism spectrum disorder (ASD) and epilepsy are the subject of much debate. Does epilepsy cause ASD or are there common underlying brain abnormalities that increase the risk of developing both disorders? This review summarizes evidence from quantitative MRI studies to suggest that abnormalities of brain structure are not necessarily the consequence of ASD and epilepsy but are antecedent to disease expression. Abnormal gray and white matter volumes are present prior to onset of ASD and evident at the time of onset in pediatric epilepsy. Aberrant brain growth trajectories are also common in both disorders, as evidenced by blunted gray matter maturation and white matter maturation. Although the etiological factors that explain these abnormalities are unclear, high heritability estimates for gray matter volume and white matter microstructure demonstrate that genetic factors assert a strong influence on brain structure. In addition, histopathological studies of ASD and epilepsy brain tissue reveal elevated rates of malformations of cortical development (MCDs), such as focal cortical dysplasia and heterotopias, which supports disruption of neuronal migration as a contributing factor. Although MCDs are not always visible on MRI with conventional radiological analysis, quantitative MRI detection methods show high sensitivity to subtle malformations in epilepsy and can be potentially applied to MCD detection in ASD. Such an approach is critical for establishing quantitative neuroanatomic endophenotypes that can be used in genetic research. In the context of emerging drug treatments for seizures and autism symptoms, such as rapamycin and rapalogs, in vivo neuroimaging markers of subtle structural brain abnormalities could improve sample stratification in human clinical trials and potentially extend the range of patients that might benefit from treatment. This article is part of a Special Issue entitled "Autism and Epilepsy".

OBJECTIVE: For patients with medically intractable focal epilepsy, the benefit of epilepsy surgery must be weighed against the risk of cognitive decline. Clinical factors such as age and presurgical cognitive level partially predict cognitive outcome; yet, little is known about the role of cross-hemispheric white matter pathways in supporting postsurgical recovery of cognitive function. The purpose of this study is to determine whether the presurgical corpus callosum (CC) midsagittal area is associated with pre- to postsurgical change following epilepsy surgery. METHODS: In this observational study, we retrospectively identified 24 adult patients from an epilepsy resection series who completed preoperative high-resolution T1 -weighted magnetic resonance imaging (MRI) scans, as well as pre- and postsurgical neuropsychological testing. The total area and seven subregional areas of the CC were measured on the midsagittal MRI slice using an automated method. Standardized indices of auditory-verbal working memory and delayed memory were used to probe cognitive change from pre- to postsurgery. CC total and subregional areas were regressed on memory-change scores, after controlling for overall brain volume, age, presurgical memory scores, and duration of epilepsy. RESULTS: Patients had significantly reduced CC area relative to healthy controls. We found a positive relationship between CC area and change in working memory, but not delayed memory; specifically, the larger the CC, the greater the postsurgical improvement in working memory (beta = 0.523; p = 0.009). Effects were strongest in posterior CC subregions. There was no relationship between CC area and presurgical memory scores. SIGNIFICANCE: Findings indicate that larger CC area, measured presurgically, is related to improvement in working memory abilities following epilepsy surgery. This suggests that transcallosal pathways may play an important, yet little understood, role in postsurgical recovery of cognitive functions.

Abnormalities in cortical structure are commonly observed in children with dyslexia in key regions of the "reading network." Whether alteration in cortical features reflects pathology inherent to dyslexia or environmental influence (e.g., impoverished reading experience) remains unclear. To address this question, we compared MRI-derived metrics of cortical thickness (CT), surface area (SA), gray matter volume (GMV), and their lateralization across three different groups of children with a historical diagnosis of dyslexia, who varied in current reading level. We compared three dyslexia subgroups with: (1) persistent reading and spelling impairment; (2) remediated reading impairment (normal reading scores), and (3) remediated reading and spelling impairments (normal reading and spelling scores); and a control group of (4) typically developing children. All groups were matched for age, gender, handedness, and IQ. We hypothesized that the dyslexia group would show cortical abnormalities in regions of the reading network relative to controls, irrespective of remediation status. Such a finding would support that cortical abnormalities are inherent to dyslexia and are not a consequence of abnormal reading experience. Results revealed increased CT of the left fusiform gyrus in the dyslexia group relative to controls. Similarly, the dyslexia group showed CT increase of the right superior temporal gyrus, extending into the planum temporale, which resulted in a rightward CT asymmetry on lateralization indices. There were no group differences in SA, GMV, or their lateralization. These findings held true regardless of remediation status. Each reading level group showed the same "double hit" of atypically increased left fusiform CT and rightward superior temporal CT asymmetry. Thus, findings provide evidence that a developmental history of dyslexia is associated with CT abnormalities, independent of remediation status.

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

This article is part of a Special 15th Anniversary Issue.