The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy.

ObjectiveThe distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.MethodsT1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.ResultsThe SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance.ConclusionThe SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance

Spatial patterns of gray and white matter compromise relate to age of seizure onset in temporal lobe epilepsy

Objective: Temporal Lobe Epilepsy (TLE) is frequently a neurodevelopmental disorder, involving subcortical volume loss, cortical atrophy, and white matter (WM) disruption. However, few studies have addressed how these pathological changes in TLE relate to one another. In this study, we investigate spatial patterns of gray and white matter degeneration in TLE and evaluate the hypothesis that the relationship among these patterns varies as a function of the age at which seizures begin.Methods: Eighty-two patients with TLE and 59 healthy controls were enrolled. T1-weighted images were used to obtain hippocampal volumes and cortical thickness estimates. Diffusion-weighted imaging was used to obtain fractional anisotropy (FA) and mean diffusivity (MD) of the superficial WM (SWM) and deep WM tracts. Analysis of covariance was used to examine patterns of WM and gray matter alterations in TLE relative to controls, controlling for age and sex. Sliding window correlations were then performed to examine the relationships between SWM degeneration, cortical thinning, and hippocampal atrophy across ages of seizure onset.Results: Cortical thinning in TLE followed a widespread, bilateral pattern that was pronounced in posterior centroparietal regions, whereas SWM and deep WM loss occurred mostly in ipsilateral, temporolimbic regions compared to controls. Window correlations revealed a relationship between hippocampal volume loss and whole brain SWM disruption in patients who developed epilepsy during childhood. On the other hand, in patients with adult-onset TLE, co-occurring cortical and SWM alterations were observed in the medial temporal lobe ipsilateral to the seizure focus.Significance: Our results suggest that although cortical, hippocampal and WM alterations appear spatially discordant at the group level, the relationship among these features depends on the age at which seizures begin. Whereas neurodevelopmental aspects of TLE may result in co-occurring WM and hippocampal degeneration near the epileptogenic zone, the onset of seizures in adulthood may set off a cascade of SWM microstructural loss and cortical atrophy of a neurodegenerative nature

Event-based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional data

Objective: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features. Methods: We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. Results: In MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI. Significance: From cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features. Keywords: MTLE; disease progression; duration of illness; event-based model; patient staging

Event-based modelling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional data

OBJECTIVE: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multi-centre cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features. METHODS: We extracted regional measures of cortical thickness, surface area and subcortical brain volumes from T1-weighted (T1W) MRI scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1,625 healthy controls from 25 centres. Features with a moderate case-control effect size (Cohen's d≥0.5) were used to train an Event-Based Model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age of onset and anti-seizure medicine (ASM) resistance. RESULTS: In MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume and, finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated to duration of illness (Spearman's ρ=0.293, p=7.03x10-16 ), age of onset (ρ=-0.18, p=9.82x10-7 ) and ASM resistance (AUC=0.59, p=0.043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM stage zero, which represents MTLE-HS with mild or non-detectable abnormality on T1W MRI. SIGNIFICANCE: From cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features

A Motor Theory of Reading: The interaction of visual and auditory language

Reading is learned in the presence of an already formed auditory language network. However, unlike auditory language reading is a recent cultural invention made possible by an extensive period of learning. Understanding the relationship of visual language with auditory language is key to understanding the novel human construct of reading. Articulatory motor movements are a potential bridge between the existing auditory language network and the developing visual reading network. Children who vocalize while learning to read and who understand the relationships between letters and sounds learn at a faster and more successful rate. However, in neuroanatomical models of silent reading the precentral gyrus, associated with articulatory motor movements, is largely omitted. The first section of the dissertation presents evidence that the precentral gyrus is involved in the dorsal reading route, putatively in grapheme-to-phoneme conversion. Chapter 1 presents evidence from a speeded semantic decision task. Word-level linguistic effects in the Precentral Gyrus and significant early phase-locking activity between the Fusiform and Precetral Gyrus were identified. Chapter 2 presents evidence from a Match/Mismatch task between sequentially presented graphemes and phonemes. Again, the precentral gyrus is implicated as a central hub by the combination of letter-specific effects, Mismatch effects, and significant connectivity with the Fusiform Gyrus. Chapter 3 examines the overlap and separation of Visual and Auditory language using a semantic decision task performed in each sensory modality. We find that while the Visual language processing that was present significantly overlaps with Auditory language processing, only a fraction of the Auditory language network is recruited during Visual language processing. The second section details methodological advances to aid in the study of language using intracranial iEEG. Chapter 4 details the use of carbon-based electrodes to increase the possible spatial resolution that iEEG can measure while retaining high signal-to-noise ratio. Chapter 5 details a multimedia tablet which was created to facilitate increased data collection on patients without increasing the effort necessary from either patients or staff. By increasing the possible spatial resolution and the possible amount of data collected, these two chapters demonstrate how to build upon the work in the first three chapters

A Motor Theory of Reading: The interaction of visual and auditory language

Reading is learned in the presence of an already formed auditory language network. However, unlike auditory language reading is a recent cultural invention made possible by an extensive period of learning. Understanding the relationship of visual language with auditory language is key to understanding the novel human construct of reading. Articulatory motor movements are a potential bridge between the existing auditory language network and the developing visual reading network. Children who vocalize while learning to read and who understand the relationships between letters and sounds learn at a faster and more successful rate. However, in neuroanatomical models of silent reading the precentral gyrus, associated with articulatory motor movements, is largely omitted. The first section of the dissertation presents evidence that the precentral gyrus is involved in the dorsal reading route, putatively in grapheme-to-phoneme conversion. Chapter 1 presents evidence from a speeded semantic decision task. Word-level linguistic effects in the Precentral Gyrus and significant early phase-locking activity between the Fusiform and Precetral Gyrus were identified. Chapter 2 presents evidence from a Match/Mismatch task between sequentially presented graphemes and phonemes. Again, the precentral gyrus is implicated as a central hub by the combination of letter-specific effects, Mismatch effects, and significant connectivity with the Fusiform Gyrus. Chapter 3 examines the overlap and separation of Visual and Auditory language using a semantic decision task performed in each sensory modality. We find that while the Visual language processing that was present significantly overlaps with Auditory language processing, only a fraction of the Auditory language network is recruited during Visual language processing. The second section details methodological advances to aid in the study of language using intracranial iEEG. Chapter 4 details the use of carbon-based electrodes to increase the possible spatial resolution that iEEG can measure while retaining high signal-to-noise ratio. Chapter 5 details a multimedia tablet which was created to facilitate increased data collection on patients without increasing the effort necessary from either patients or staff. By increasing the possible spatial resolution and the possible amount of data collected, these two chapters demonstrate how to build upon the work in the first three chapters

Interregional correlations in Parkinson disease and Parkinson-related dementia with resting functional MR imaging.

PurposeTo apply a recently developed native-space (or native-surface) method to compare resting functional magnetic resonance (MR) imaging correlations (functional connectivity) measured in patients with Parkinson-related dementia (PRD) to those measured in cognitively unimpaired, age-matched control subjects with or without Parkinson disease (PD).Materials and methodsThe study was approved by the institutional review board and complied with HIPAA regulations. Participants included cognitively unimpaired elderly individuals (n = 19), cognitively unimpaired patients with PD (n = 19), and patients with PRD (n = 18). Resting functional MR data were assessed by calculating correlation coefficients between blood oxygen level-dependent time series of a seed region and of other regions of interest selected a priori. Two seeds were used: a medial parietal region that contributes to the default network affected in Alzheimer disease and the caudate, which is affected by loss of dopaminergic inputs in PD. Correlation analyses were performed in the native space of individual subjects to avoid confounds from transformation to an average brain. Two-sample t tests were applied to data from each native-surface region of interest, and vertex-wise comparisons were made by using two-sample t tests at each vertex on the group surface; statistical results were corrected for multiple comparisons. Cortical thickness and striatal volumes were also compared across groups for the regions of interest.ResultsCorticostriatal functional correlations were decreased in PRD patients relative to elderly control subjects in bilateral prefrontal regions; largest difference was observed in the right caudal middle frontal region (r = 0.48 in PRD patients and 0.81 in elderly control subjects, uncorrected P = .001). Conversely, there was no significant difference across groups in the strength of default-network correlations. There was also no significant difference across groups in cortical thickness or striatal volume.ConclusionPRD was associated with selective disruption of corticostriatal resting functional MR imaging correlations, which suggests that resting functional MR imaging analyzed in subject-native space may be a useful biomarker in this disease. Additionally, at least in the present cohort, this technique was more sensitive to PRD changes than was quantitative structural MR imaging