The nature and course of neuropsychological morbidity in chronic temporal lobe epilepsy

Oyegbile, Temitayo O.; Dow, Christian; Jones, Jana E.; Bell, Brian; Rutecki, Paul; Sheth, Raj D.; Seidenberg, Michael; Hermann, Bruce P.

doi:10.1212/01.wnl.0000125186.04867.34

Cited by 283 publications

(211 citation statements)

References 43 publications

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“…As reviewed by Keller and Roberts (2008), VBM studies have found the largest effects in nearby ipsilateral medial temporal cortex, as well as more widespread effects in regions including the thalamus and frontal and parietal lobes. findings of more widespread alterations in cortical morphology that extend beyond the hippocampus are consistent with TLE's comorbid deficits in executive, intellectual and language functioning (Oyegbile et al, 2004). More recently, using methods that reconstruct the cortical surface to more precisely measure gray matter structure, researchers found up to 30% reductions in cortical thickness bilaterally in multiple frontal, temporal and occipital regions in TLE patients with MTS compared to controls (Lin et al, 2007;Bernhardt et al, 2010;Kemmotsu et al, 2011).…”

Section: Introductionmentioning

confidence: 87%

Machine learning classification of mesial temporal sclerosis in epilepsy patients

Rudie¹,

Colby²,

Salamon

2015

Epilepsy Research

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a b s t r a c tBackground and purpose: Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid in the diagnosis and treatment of brain-based disorders such as temporal lobe epilepsy (TLE). Using a large cohort of epilepsy patients with and without mesial temporal sclerosis (MTS), we sought to automatically classify MTS using measures of cortical morphology, and to further relate classification probabilities to measures of disease burden. Materials and methods: Our sample consisted of high-resolution T1 structural scans of 169 adults with epilepsy collected across five different 1.5 T and four different 3 T scanners at UCLA. We applied a multiple support vector machine recursive feature elimination algorithm to morphological measures generated from FreeSurfer's automated segmentation and parcellation in order to classify Epilepsy patients with MTS (n = 85) from those without MTS (N = 84). Results: In addition to hippocampal volume, we found that alterations in cortical thickness, surface area, volume and curvature in inferior frontal and anterior and inferior temporal regions contributed to a classification accuracy of up to 81% (p = 1.3 × 10 −17 ) in identifying MTS. We also found that MTS classification probabilities were associated with a longer duration of disease for epilepsy patients both with and without MTS. Conclusions: In addition to implicating extra-hippocampal involvement of MTS, these findings shed further light on the pathogenesis of TLE and may ultimately assist in the development of automated tools that incorporate multiple neuroimaging measures to assist clinicians in detecting more subtle cases of TLE and MTS.

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Section: Introductionmentioning

confidence: 87%

Machine learning classification of mesial temporal sclerosis in epilepsy patients

Rudie¹,

Colby²,

Salamon

2015

Epilepsy Research

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“…It is generally acknowledged that memory functioning is the primary cognitive morbidity in TLE and is related to the functional adequacy of the hippocampus. Nevertheless, it is also evident that there is a more diffuse disruption of cognition in unilateral TLE (Glosser et al, 1997;Helmstaedter et al, 2003;Hermann et al, 1997) and that there is considerable heterogeneity in cognitive dysfunction among patients with unilateral TLE (Oyegbile et al, 2004). We have previously suggested that abnormalities outside the affected hippocampus and temporal lobe may contribute to nonmemory cognitive impairment (Hermann et al, 2003).…”

Section: Cognitive Functioningmentioning

confidence: 98%

“…Affected brain structures include temporal lobe structures adjacent and closely linked to the hippocampus such as the amygdala and entorhinal cortex (Bernasconi et al, 2005;Moran et al, 2001), as well as extratemporal lobe structures such as the thalamus and basal ganglia (Bonilha et al, 2005;Dreifuss et al, 2001;Natsume et al, 2003). Cognitive impairment in TLE has also been shown to encompass domains other than episodic memory, including intellectual functioning, language, executive functioning, visual perceptual functions, and motor abilities (Glosser et al, 1997;Hermann et al, 1997;Marques et al, 2007;Martin et al, 2000;Oyegbile et al, 2004). These findings raise the possibility that the broader pattern of cognitive impairment in TLE is associated with brain abnormalities in regions outside the temporal lobe.…”

Section: Introductionmentioning

confidence: 99%

Thalamic atrophy and cognition in unilateral temporal lobe epilepsy

Seidenberg

Hermann

Pulsipher

et al. 2008

J Inter Neuropsych Soc

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This study examined quantitative magnetic resonance volumes of the thalamus and hippocampus and determined their relationship with cognitive function and clinical seizure characteristics in a sample of 46 unilateral temporal lobe epilepsy (TLE) subjects (20 left and 26 right) and 29 controls. The hippocampus and thalamus exhibited different patterns of volume abnormality, different associations with clinical seizure characteristics, and different patterns of relationship with cognitive measures. Hippocampal volume reduction was primarily ipsilateral to the seizure focus, and thalamic volume reduction was bilateral. Ipsilateral hippocampal volume was significantly correlated with both early neurodevelopmental features (age of seizure onset) and disease characteristics (duration of epilepsy), whereas thalamus integrity was related only to disease variables. Hippocampal volume showed a selective association with verbal memory performance. In contrast, both left and right thalamic volumes were significantly correlated with performance on both memory and nonmemory cognitive domains. These findings underscore the importance of thalamic atrophy in chronic TLE and its potential implications for cognition. (JINS, 2008, 14, 384-393.)

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“…Cognitive dysfunction is a common comorbidity in temporal lobe epilepsy (TLE) 1. Memory impairment is considered the characteristic cognitive feature of TLE 2, 3.…”

Section: Introductionmentioning

confidence: 99%

Cognitive impairment in epilepsy: the role of reduced network flexibility

Tailby

Kowalczyk

Jackson

2017

Ann Clin Transl Neurol

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ObjectiveThe dominant model of cognitive impairment in focal epilepsy has emphasised structural bases for cognitive deficits. Current theories of cognition in the healthy brain emphasise the importance of the reweighting of brain network interactions in support of task performance. Here, we explore the hypothesis that cognitive deficits in epilepsy arise through abnormalities of dynamic functional network interactions.MethodWe studied 19 healthy controls and 37 temporal lobe epilepsy (TLE) patients, using a behavioural measure of verbal fluency (the Controlled Oral Word Association Test) and an fMRI verbal fluency paradigm (Orthographic Lexical Retrieval).ResultsBehaviourally, verbal fluency was significantly impaired in TLE. Psychophysiological interaction analyses of the fMRI data, which capture state‐dependent changes in network connectivity, revealed reduced task‐dependent modulations of connectivity from left superior medial frontal cortex to left middle frontal gyrus in TLE patients. Individual differences in verbal fluency among TLE cases was correlated with task‐dependent changes in connectivity from left posterior cingulate to left superior medial frontal cortex, and from left superior medial frontal cortex to a range of right predominant brain areas.InterpretationThese data reveal that the typical pattern of task‐driven shifts in network connectivity is not observed in TLE. Our observations go beyond simple structure‐function associations and suggest that failure of network flexibility can be an important contributor to cognitive impairment in epilepsy.

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The nature and course of neuropsychological morbidity in chronic temporal lobe epilepsy

Cited by 283 publications

References 43 publications

Machine learning classification of mesial temporal sclerosis in epilepsy patients

Machine learning classification of mesial temporal sclerosis in epilepsy patients

Thalamic atrophy and cognition in unilateral temporal lobe epilepsy

Cognitive impairment in epilepsy: the role of reduced network flexibility

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