Faculty Bibliography

Idiopathic generalized epilepsy (IGE) is associated with widespread cortical network abnormalities on electroencephalography. Resting state functional connectivity (RSFC), based on fMRI, can assess the brain's global functional organization and its disruption in clinical conditions. We compared RSFC associated with the 'default mode network' (DMN) between people with IGE and healthy controls. Strength of functional connectivity within the DMN associated with seeds in the posterior cingulate cortex (PCC) and medial prefrontal cortices (MPFC) was compared between people with IGE and healthy controls and was correlated with seizure duration, age of seizure onset and age at scan. Those with IGE showed markedly reduced functional network connectivity between anterior and posterior cortical seed regions. Seizure duration positively correlates with RSFC between parahippocampal gyri and the PCC but negatively correlates with connectivity between the PCC and frontal lobe. The observed pattern of disruption provides evidence for integration- and segregation-type network abnormalities and supports aberrant network organization among people with IGE.

Depression in patients with temporal lobe epilepsy (TLE) is highly prevalent and carries significant morbidity and mortality. Its neural basis is poorly understood. We used quantitative, surface-based MRI analysis to correlate brain morphometry with severity of depressive symptoms in 38 patients with TLE and 45 controls. Increasing severity of depressive symptoms was associated with orbitofrontal cortex (OFC) thinning in controls, but with OFC thickening in TLE patients. These results demonstrate distinct neuroanatomical substrates for depression with and without TLE, and suggest a unique role for OFC, a limbic region for emotional processing strongly interconnected with medial temporal structures, in TLE-related depressive symptoms

Septal nuclei, components of basal forebrain, are strongly and reciprocally connected with hippocampus, and have been shown in animals to play a critical role in memory. In humans, the septal forebrain has received little attention. To examine the role of human septal forebrain in memory, we acquired high-resolution magnetic resonance imaging scans from 25 healthy subjects and calculated septal forebrain volume using recently developed probabilistic cytoarchitectonic maps. We indexed memory with the California Verbal Learning Test-II. Linear regression showed that bilateral septal forebrain volume was a significant positive predictor of recognition memory accuracy. More specifically, larger septal forebrain volume was associated with the ability to recall item source/context accuracy. Results indicate specific involvement of septal forebrain in human source memory, and recall the need for additional research into the role of septal nuclei in memory and other impairments associated with human diseases. (JINS, 2012, 18, 157-161)

Despite decades of cognitive, neuropsychological and neuroimaging studies, it is unclear if letters are identified before word-form encoding during reading, or if letters and their combinations are encoded simultaneously and interactively. Here using functional magnetic resonance imaging, we show that a 'letter-form' area (responding more to consonant strings than false fonts) can be distinguished from an immediately anterior 'visual word-form area' in ventral occipito-temporal cortex (responding more to words than consonant strings). Letter-selective magnetoencephalographic responses begin in the letter-form area approximately 60 ms earlier than word-selective responses in the word-form area. Local field potentials confirm the latency and location of letter-selective responses. This area shows increased high-gamma power for approximately 400 ms, and strong phase-locking with more anterior areas supporting lexico-semantic processing. These findings suggest that during reading, visual stimuli are first encoded as letters before their combinations are encoded as words. Activity then rapidly spreads anteriorly, and the entire network is engaged in sustained integrative processing.

Functional neuroimaging implicates hyperactivity of amygdala-orbitofrontal circuitry as a common neurobiological mechanism underlying the development of anxiety. Less is known about anxiety-related structural differences in this network. In this study, a sample of healthy adults with no history of anxiety disorders completed a 3T MRI scan and self-report mood inventories. Post-processing quantitative MRI image analysis included segmentation and volume estimation of subcortical structures, which were regressed on anxiety inventory scores, with depression scores used to establish discriminant validity. We then used a quantitative vertex-based post-processing method to correlate (1) anxiety scores and (2) left amygdala volumes with cortical thickness across the whole cortical mantle. Left amygdala volumes predicted anxiety, with decreased amygdala volume associated with higher anxiety on both state and trait anxiety measures. A negative correlation between left amygdala volume and cortical thickness overlapped with a positive correlation between anxiety and cortical thickness in left lateral orbitofrontal cortex. These results suggest a structural anxiety network that corresponds with a large body of evidence from functional neuroimaging. Such findings raise the possibility that structural abnormalities may result in a greater vulnerability to anxiety or conversely that elevated anxiety symptoms may result in focal structural changes

Blurring of the cortical gray and white matter border on MRI is associated with normal aging, pathological aging, and the presence of focal cortical dysplasia. However, it remains unclear whether normal variations in signal intensity contrast at the gray and white matter junction reflect the functional integrity of subjacent tissue. This study explores the relationship between verbal abilities and gray and white matter contrast (GWC) in healthy human adults. Participants were scanned at 3 T MRI and administered standardized measures of verbal expression and verbal working memory. GWC was estimated by calculating the non-normalized T1 image intensity contrast above and below the cortical gray/white matter interface. Spherical averaging and whole-brain correlational analyses were performed. Sulcal regions exhibited higher contrast compared to gyral regions. We found a strongly lateralized and regionally specific profile with reduced verbal expression abilities associated with blurring in left hemisphere inferior frontal cortex and temporal pole. Reduced verbal working memory was associated with blurring in widespread left frontal and temporal cortices. Such lateralized and focal results provide support for GWC as a measure of regional functional integrity and highlight its potential role in probing the neuroanatomical substrates of cognition in healthy and diseased populations

Postictal psychosis (PIP), the occurrence of psychotic episodes following a seizure, is a common and serious comorbidity in patients with epilepsy. Yet, the anatomical correlates remain poorly defined. Here, we used quantitative MRI morphometry to identify structural abnormalities in the cortex of patients with PIP relative to patients with epilepsy without PIP and age- and gender-matched normal healthy controls. Comparison of patients with epilepsy and PIP with patients with epilepsy without PIP revealed increased cortical thickness in the right lateral prefrontal cortex, right anterior cingulate cortex, and right middle temporal gyrus. The PIP group was distinguished from the EC and NC groups by thicker cortex in the right rostral anterior cingulate cortex and thinner cortex in the right angular gyrus and the left middle temporal region. Findings indicate that PIP is associated with thickening of the right anterior cingulate cortex, which may serve as a marker for patients at risk for developing PIP

Magnetic resonance imaging has revolutionized the detection of structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine visual inspection. Here we use an automated, surface-based method for quantifying morphometric features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries. Using MRI morphometry at 3T with surface-based spherical averaging techniques that precisely align anatomical structures between individual brains, we compared single patients with known lesions to a large normal control group to detect clusters of abnormal cortical thickness, gray-white matter contrast, local gyrification, sulcal depth, jacobian distance and curvature. To assess the effects of threshold and smoothing on detection sensitivity and specificity, we systematically varied these parameters with different thresholds and smoothing levels. To test the effectiveness of the technique to detect lesions of epileptogenic character, we compared the detected structural abnormalities to expert-tracings, intracranial EEG, pathology and surgical outcome in a homogeneous patient sample. With optimal parameters and by combining thickness and GWC, the surface-based detection method identified 92% of cortical lesions (sensitivity) with few false positives (96% specificity), successfully discriminating patients from controls 94% of the time. The detected structural abnormalities were related to the seizure onset zones, abnormal histology and positive outcome in all surgical patients. However, the method failed to adequately describe lesion extent in most cases. Automated surface-based MRI morphometry, if used with optimized parameters, may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore could improve identification of patients with intractable focal epilepsy who may benefit from surgery