Faculty Bibliography

OBJECTIVE: We used whole brain T1-weighted MRI to estimate the age of individuals with medically refractory focal epilepsy, and compared with individuals with newly diagnosed focal epilepsy and healthy controls. The difference between neuroanatomical age and chronological age was compared between the three groups. METHODS: Neuroanatomical age was estimated using a machine learning-based method that was trained using structural MRI scans from a large independent healthy control sample (N=2001). The prediction model was then used to estimate age from MRI scans obtained from newly diagnosed focal epilepsy patients (N=42), medically refractory focal epilepsy patients (N=94) and healthy controls (N=74). RESULTS: Individuals with medically refractory epilepsy had a difference between predicted brain age and chronological age that was on average 4.5 years older than healthy controls (p=4.6x10-5). No significant differences were observed in newly diagnosed focal epilepsy. Earlier age of onset was associated with an increased brain age difference in the medically refractory group (p=0.034). SIGNIFICANCE: Medically refractory focal epilepsy is associated with structural brain changes that resemble premature brain aging.

The differential contribution of medial-temporal lobe regions to verbal declarative memory is debated within the neuroscience, neuropsychology, and cognitive psychology communities. We evaluate whether the extent of surgical resection within medial-temporal regions predicts longitudinal verbal learning and memory outcomes. This single-center retrospective observational study involved patients with refractory temporal lobe epilepsy undergoing unilateral anterior temporal lobe resection from 2007 to 2015. Thirty-two participants with Engel Classes 1 and 2 outcomes were included (14 left, 18 right) and followed for a mean of 2.3 years after surgery (+/-1.5 years). Participants had baseline and postsurgical neuropsychological testing and high-resolution T1-weighted MRI scans. Postsurgical lesions were manually traced and coregistered to presurgical scans to precisely quantify resection extent of medial-temporal regions. Verbal learning and memory change scores were regressed on hippocampal, entorhinal, and parahippocampal resection volume after accounting for baseline performance. Overall, there were no significant differences in learning and memory change between patients who received left and right anterior temporal lobe resection. After controlling for baseline performance, the extent of left parahippocampal resection accounted for 27% (p = .021) of the variance in verbal short delay free recall. The extent of left entorhinal resection accounted for 37% (p = .004) of the variance in verbal short delay free recall. Our findings highlight the critical role that the left parahippocampal and entorhinal regions play in recall for verbal material.

OBJECTIVE: Amygdala enlargement (AE) is observed in patients with temporal lobe epilepsy (TLE), which has led to the suggestion that it represents a distinct TLE subtype; however, it is unclear whether AE is found at similar rates in other epilepsy syndromes or in healthy controls, which would limit its value as a marker for focal epileptogenicity. METHODS: We compared rates of AE, defined quantitatively from high-resolution T1-weighted MRI, in a large multi-site sample of 136 patients with nonlesional localization related epilepsy (LRE), including TLE and extratemporal (exTLE) focal epilepsy, 34 patients with idiopathic generalized epilepsy (IGE), and 233 healthy controls (HCs). RESULTS: AE was found in all groups including HCs; however, the rate of AE was higher in LRE (18.4%) than in IGE (5.9%) and HCs (6.4%). Patients with unilateral LRE were further evaluated to compare rates of concordant ipsilateral AE in TLE and exTLE, with the hypothesis that rates of ipsilateral AE would be higher in TLE. Although ipsilateral AE was higher in TLE (19.4%) than exTLE (10.5%), this difference was not significant. Furthermore, among the 25 patients with unilateral LRE and AE, 13 (52%) had either bilateral AE or AE contralateral to seizure onset. CONCLUSION: Results suggest that AE, as defined with MRI volumetry, may represent an associated feature of nonlesional localization related epilepsy with limited seizure onset localization value.

Verbal working memory (vWM) involves storing and manipulating information in phonological sensory input. An influential theory of vWM proposes that manipulation is carried out by a central executive while storage is performed by two interacting systems: a phonological input buffer that captures sound-based information and an articulatory rehearsal system that controls speech motor output. Whether, when and how neural activity in the brain encodes these components remains unknown. Here we read out the contents of vWM from neural activity in human subjects as they manipulated stored speech sounds. As predicted, we identified storage systems that contained both phonological sensory and articulatory motor representations. Unexpectedly, however, we found that manipulation did not involve a single central executive but rather involved two systems with distinct contributions to successful manipulation. We propose, therefore, that multiple subsystems comprise the central executive needed to manipulate stored phonological input for articulatory motor output in vWM.

The two most common types of temporal lobe epilepsy are medial temporal sclerosis epilepsy (TLE-MTS) and MRI-normal temporal lobe epilepsy (TLE-no). TLE-MTS is specified by its stereotyped focus and spread pattern of neuronal damage, with pronounced neuronal loss in the hippocampus. TLE-no exhibits normal-appearing hippocampus and more widepsread neuronal loss. In both cases neuronal loss spread appears to be constrained by the white matter connections. Both varieties of epilepsy reveal pathological abnormalities in increased mean diffusivity (MD). We model MD distribution as a simple consequence of the propagation of neuronal damage. By applying this model on the structural brain connectivity network of healthy subjects we can predict at group level the mean diffusivity gray matter change in the epilepsy cohorts relative to a control group. DTI images were acquired from 10 patients with TLE-MTS, 11 patients with TLE-no, and 35 healthy subjects. Statistical validation at the group level suggests high correlation with measured neuronal loss (R = 0.56 for the TLE-MTS group and R = 0.364 for the TLE-no group). The results of this exploratory work pave the way for potential future clinical application of the proposed model on individual patients, including predicting neuronal loss spread, identification of seizure onset zones, and helping in surgical planning.

Surface-based cortical thickness (CT) analyses are increasingly being used to investigate variations in brain morphology across the spectrum of brain health, from neurotypical to neuropathological. An outstanding question is whether individual differences in cortical morphology, such as regionally increased or decreased CT, are associated with domain-specific performance deficits in healthy adults. Since CT studies are correlational, they cannot establish causality between brain morphology and cognitive performance. A direct comparison with classic lesion methods is needed to determine whether the regional specificity of CT-cognition correlations is similar to that observed in patients with brain lesions. We address this question by comparing the neuroanatomical overlap of effects when 1) whole brain vertex-wise CT is tested as a correlate of performance variability on a commonly used neuropsychological test of executive function, Trailmaking Test Part B (TMT-B), in healthy adults and 2) voxel-based lesion-symptom mapping (VBLSM) is used to map lesion location to performance decrements on the same task in patients with frontal lobe lesions. We found that reduced performance on the TMT-B was associated with increased CT in bilateral prefrontal regions in healthy adults and that results spatially overlapped in the left dorsomedial prefrontal cortex with findings from the VBLSM analysis in patients with frontal brain lesions. Findings indicate that variations in the structural integrity of the left dorsomedial prefrontal lobe, ranging from individual CT differences in healthy adults to structural lesions in patients with neurological disorders, are associated with poor performance on the TMT-B. These converging results suggest that the left dorsomedial prefrontal region houses a critical region for the complex processing demands of TMT-B, which include visuomotor tracking, sequencing, and cognitive flexibility.

OBJECTIVE: We assessed whether presurgical resting state functional magnetic resonance imaging (fMRI) provides information for distinguishing temporal lobe epilepsy (TLE) with mesial temporal sclerosis (TLE-MTS) from TLE without MTS (TLE-noMTS). METHODS: Thirty-four patients with TLE and 34 sex-/age-matched controls consented to a research imaging protocol. MTS status was confirmed by histologic evaluation of surgical tissue (TLE-MTS = 16; TLE-noMTS = 18). The fractional amplitude of low-frequency fluctuations (fALFFs) in the blood oxygen level-dependent (BOLD) resting-state fMRI signal, a marker of local metabolic demand at rest, was averaged at five regions of interest (ROIs; hippocampus, amygdala, frontal, occipital, and temporal lobe), along with corresponding volume and cortical thickness estimates. ROIs were labeled ipsilateral or contralateral according to seizure lateralization and compared across TLE-MTS, TLE-noMTS, and healthy controls (HCs). MTS status was regressed on ipsilateral hippocampal volume and fALFF to test for independent contributions. RESULTS: The TLE-MTS group had reduced fALFF in the ipsilateral amygdala and hippocampus; whereas, the TLE-noMTS group had marginally reduced fALFF in the ipsilateral amygdala but not hippocampus. These results were consistently obtained with and without application of global signal regression (GSR). Ipsilateral hippocampal volume contributed to 37% of the variance in MTS status (p < 0.001) and fALFF contributed an additional 10% (p = 0.021). Two MTS cases were accurately classified with fALFF but not volume, and three were accurately classified with volume but not fALFF. At the lobar level, fALFF (with GSR) was reduced in the ipsilateral temporal and bilateral frontal lobes of patients with TLE-MTS and bilateral frontal lobes of patients with TLE-noMTS in the context of normal cortical thickness. SIGNIFICANCE: This study indicates that resting-state fMRI provides complementary functional information for MTS classification. Findings validate fALFF as a measure of regional brain integrity in TLE and highlight the value of using multi-modal imaging to provide independent diagnostic information in presurgical epilepsy evaluations.

In animal models, inflammation is both a cause and consequence of seizures. Less is known about the role of inflammation in human epilepsy. We performed positron emission tomography (PET) using a radiotracer sensitive to brain inflammation in a patient with frontal epilepsy ~36 h after a seizure as well as during a seizure-free period. When statistically compared to a group of 12 matched controls, both of the patient's scans identified a frontal (supplementary motor area) region of increased inflammation corresponding to his clinically defined seizure focus, but the postseizure scan showed significantly greater inflammation intensity and spatial extent. These results provide new information about transient and chronic neuroinflammation in human epilepsy and may be relevant to understanding the process of epileptogenesis and guiding therapy.

We present a new approach to extracting low-dimensional neural trajectories that summarize the electrocorticographic (ECoG) signals recorded with high-channel-count electrode arrays implanted subdurally. In our approach, Hidden-Markov Factor Analysis (HMFA), a finite set of factor analyzers are used to model the relationship between the high-dimensional ECoG neural space and a low-dimensional latent neural space; the factor analyzers at different time points are in turn linked together with a hidden Markov model. The recorded ECoG signals were band-pass filtered such that our analysis was focused on a sub-band (76-100Hz) of high gamma. HMFA affords the quantization of the ECoG neural space and dimensionality reduction in a common probabilistic space. We applied this method to the ECoG recordings of 2 subjects who responded with button presses to audiovisual stimuli in an experimental task. Using a goodness-of-fit metric that measures how well the ECoG activity of each electrode can be predicted by all the other electrodes, we found that HMFA performed best when compared with Gaussian-Process Factor Analysis (GPFA) and other related spatiotemporal modeling techniques. In contradistinction to HMFA, GPFA and the other techniques integrate temporal smoothing with dimensionality reduction. We believe that this method will provide a powerful tool for relating high-channel-count ECoG signals to the perception and behavior of subjects.