Multimodal neurocognitive markers of frontal lobe epilepsy: Insights from ecological text processing

Sebastian Moguilner,Agustina Birba,Daniel Fino,Roberto Isoardi,Celeste Huetagoyena,Raúl Otoya,Viviana Tirapu,Fabián Cremaschi,Lucas Sedeño,Agustín Ibáñez,Adolfo M García

doi:10.1016/j.neuroimage.2021.117998

Abstract

The pressing call to detect sensitive cognitive markers of frontal lobe epilepsy (FLE) remains poorly addressed. Standard frameworks prove nosologically unspecific (as they reveal deficits that also emerge across other epilepsy subtypes), possess low ecological validity, and are rarely supported by multimodal neuroimaging assessments. To bridge these gaps, we examined naturalistic action and non-action text comprehension, combined with structural and functional connectivity measures, in 19 FLE patients, 19 healthy controls, and 20 posterior cortex epilepsy (PCE) patients. Our analyses integrated inferential statistics and data-driven machine-learning classifiers. FLE patients were selectively and specifically impaired in action comprehension, irrespective of their neuropsychological profile. These deficits selectively and specifically correlated with (a) reduced integrity of the anterior thalamic radiation, a subcortical structure underlying motoric and action-language processing as well as epileptic seizure spread in this subtype; and (b) hypoconnectivity between the primary motor cortex and the left-parietal/supramarginal regions, two putative substrates of action-language comprehension. Moreover, machine-learning classifiers based on the above neurocognitive measures yielded 75% accuracy rates in discriminating individual FLE patients from both controls and PCE patients. Briefly, action-text assessments, combined with structural and functional connectivity measures, seem to capture ecological cognitive deficits that are specific to FLE, opening new avenues for discriminatory characterizations among epilepsy types.

Highlights

Cognitive assessments in frontal lobe epilepsy (FLE) reveal diverse deficits (Carreno and Donaire, 2008) which contribute to characterizing the pathology and its comorbidities (Braakman et al, 2013)
The need arises for establishing cognitive deficits that are differentially present in FLE, indicative of everyday performance, and mapped to its core anatomo-functional signatures (Elger et al, 2004)
The three groups were matched on age, sex, and education; handedness, determined via the Edinburgh Inventory (Oldfield, 1971); overall cognitive status, attention, and general language skills, established with the Montreal Cognitive Assessment (MoCA) and relevant subtests (Nasreddine et al, 2005); overall executive functions, working memory and inhibitory controls, assessed with the INECO Frontal Screening (IFS) battery and relevant substests (Torralva et al, 2009); and IQ, evaluated with the Weschler Abbreviated Scale of Intelligence (WASI) (Wechsler, 1999). (Fig. 1A)

Summary

Introduction

Cognitive assessments in frontal lobe epilepsy (FLE) reveal diverse deficits (Carreno and Donaire, 2008) which contribute to characterizing the pathology and its comorbidities (Braakman et al, 2013). A promising avenue is afforded by tasks tapping action language, a NeuroImage 235 (2021) 117998 cognitive domain that hinges on cortico-subcortical motor networks (Pulvermuller, 2018, Llano, 2013, Akinina et al, 2019, Garcia et al, 2019) which are distinctively affected in FLE (Carreno and Donaire, 2008) To explore this novel view, we implemented a multimodal approach combining inferential statistics and machine learning to tap naturalistic action-language comprehension and its anatomo-functional correlates (via diffusion tensor imaging [DTI] and fMRI-derived restingstate functional connectivity [rsFC]) in FLE patients relative to both healthy controls and PCE patients

Methods

Results

Discussion

Conclusion