Imaging episodic memory during development and childhood epilepsy

Abstract Epilepsy affects 2.2 million adults in the USA, with 1 in 26 people developing epilepsy at some point in their lives. Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy as medial structures, and the hippocampus in particular, are prone to generating seizures. Selective anterior temporal resection (which removes the hippocampus) is the most effective intractable TLE treatment, but given the critical role of the mesial temporal lobe in memory functioning, resection can have negative effects on this crucial cognitive skill. To minimize the adverse impact of temporal lobe surgery on memory functioning, reliable pre-surgical guides are needed. Clinical functional magnetic resonance imaging (fMRI) provides reliable, noninvasive guidance of language functioning and plays a growing role in the pre-surgical evaluation for epilepsy patients; however, localization of memory function in children with epilepsy using fMRI has not been established. Aside from the lack of neuroimaging memory studies in children with TLE, studies of typical development are limited. This review will focus on the functional anatomy of memory systems throughout development, with a focus on TLE. TLE provides the ideal model from which to understand memory function and the limits of plasticity and compensation/reorganization throughout development

Fluency patterns in narratives from children with localization related epilepsy

This study assessed the relationship between fluency and language demand in children with epilepsy, a group known to demonstrate depressed language skills. Disfluency type and frequencies were analyzed in elicited narratives from 52 children. Half of these children had localization-related epilepsy (CWE), while the others were age- and gender-matched typically developing (TD) peers. CWE were found to be significantly more disfluent overall than their matched TD peers during narrative productions, and demonstrated a higher proportion of stutter-like disfluencies, particularly prolongations. The current study adds to an emerging literature that has found depressed language skills and listener perceptions of verbal ability in children with chronic seizure activity, and contributes to the small but growing literature that suggests that disfluency during spoken language tasks may be a subtle marker of expressive language impairment

The writings of James Madison, comprising his public papers and his private correspondence,

Mode of access: Internet

The relationship of language and explicit memory in pediatric epilepsy

Objective: Memory and language are often at risk in pediatric epilepsy but findings are mixed. We investigated the relationship between explicit memory and language in children with epilepsy and controls using data-driven statistical methods applying model-based clustering to explore if different cognitive profiles emerge. Participants and Methods: 276 children ages 6.1 to 17.5 were evaluated as part of ongoing studies. 149 patients with focal epilepsy (EPI) and 127 typically developing children (TD) completed language (EOWPVT, WASI VIQ) and memory (CVLT-C) measures. Six normative z-scores were used (4 from CVLT-C) for: (1) Pearson r correlations and (2) the model-based clustering procedure. For the latter, we applied Gaussian finite mixture model-based clustering on the 6 scores through R package mclust using Bayes Information Criterion to determine if scores clustered into distinct profiles and how EPI and TD fell in each profile. Epilepsy variables were compared to ascertain if they related to group membership. Results: Language scores were positively correlated with all memory scores (r’s\u3e0.26, p’s ≤ 0.001). The optimal cluster number was 2 across TD and EPI; language and memory separated into high (n=206, M z= 0.44, EPI=46%, TD=54%) and low performance groups (n=70, M z=-1.04, EPI=77%, TD=23%). The groups did not differ on age. Within EPI only, 2 was also the optimal number of clusters. Even though the majority of the low group was EPI, it represented only 1/3 of all patients. Epilepsy variables were no different across groups. Conclusions: Language and memory are associated and when included in model-based clustering two distinct groups were revealed. The method found heterogeneity within EPI that may explain prior mixed results. Parsing groups in a data driven manner may reveal subgroups that may have biomarkers for their cognitive profiles thus indicating a protective factor or a risk. Further studies will test for biomarkers (e.g. findings from structural or functional imaging) that predict these cognitive profiles