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      Reduced functional integration of the sensorimotor and language network in rolandic epilepsy

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          Abstract

          Introduction

          Over the last years, evidence has accumulated that rolandic epilepsy (RE) is associated with serious cognitive comorbidities, including language impairment. However, the cerebral mechanism through which epileptiform activity in the rolandic (sensorimotor) areas may affect the language system is unknown. To investigate this, the connectivity between rolandic areas and regions involved in language processing is studied using functional MRI (fMRI).

          Materials and methods

          fMRI data was acquired from 22 children with rolandic epilepsy and 22 age-matched controls (age range: 8–14 years), both at rest and using word-generation and reading tasks. Activation map analysis revealed no group differences (FWE-corrected, p < 0.05) and was therefore used to define regions of interest for pooled (patients and controls combined) language activation. Independent component analysis with dual regression was used to identify the sensorimotor resting-state network in all subjects. The associated functional connectivity maps were compared between groups at the regions of interest for language activation identified from the task data. In addition, neuropsychological language testing (Clinical Evaluation of Language Fundamentals, 4th edition) was performed.

          Results

          Functional connectivity with the sensorimotor network was reduced in patients compared to controls (p = 0.011) in the left inferior frontal gyrus, i.e. Broca's area as identified by the word-generation task. No aberrant functional connectivity values were found in the other regions of interest, nor were any associations found between functional connectivity and language performance. Neuropsychological testing confirmed language impairment in patients relative to controls (reductions in core language score, p = 0.03; language content index, p = 0.01; receptive language index, p = 0.005).

          Conclusion

          Reduced functional connectivity was demonstrated between the sensorimotor network and the left inferior frontal gyrus (Broca's area) in children with RE, which might link epileptiform activity/seizures originating from the sensorimotor cortex to language impairment, and is in line with the identified neuropsychological profile of anterior language dysfunction.

          Graphical abstract

          Highlights

          ► Using fMRI, it was demonstrated that the motor and language system are integrated. ► In rolandic epilepsy, functionally connectivity with the rolandic network is locally decreased. ► These findings provide an physiological explanation of language impairment in RE.

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          Most cited references35

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          Advances and Pitfalls in the Analysis and Interpretation of Resting-State FMRI Data

          The last 15 years have witnessed a steady increase in the number of resting-state functional neuroimaging studies. The connectivity patterns of multiple functional, distributed, large-scale networks of brain dynamics have been recognised for their potential as useful tools in the domain of systems and other neurosciences. The application of functional connectivity methods to areas such as cognitive psychology, clinical diagnosis and treatment progression has yielded promising preliminary results, but is yet to be fully realised. This is due, in part, to an array of methodological and interpretative issues that remain to be resolved. We here present a review of the methods most commonly applied in this rapidly advancing field, such as seed-based correlation analysis and independent component analysis, along with examples of their use at the individual subject and group analysis levels and a discussion of practical and theoretical issues arising from this data ‘explosion’. We describe the similarities and differences across these varied statistical approaches to processing resting-state functional magnetic resonance imaging signals, and conclude that further technical optimisation and experimental refinement is required in order to fully delineate and characterise the gross complexity of the human neural functional architecture.
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            Motor cortex maps articulatory features of speech sounds.

            The processing of spoken language has been attributed to areas in the superior temporal lobe, where speech stimuli elicit the greatest activation. However, neurobiological and psycholinguistic models have long postulated that knowledge about the articulatory features of individual phonemes has an important role in their perception and in speech comprehension. To probe the possible involvement of specific motor circuits in the speech-perception process, we used event-related functional MRI and presented experimental subjects with spoken syllables, including [p] and [t] sounds, which are produced by movements of the lips or tongue, respectively. Physically similar nonlinguistic signal-correlated noise patterns were used as control stimuli. In localizer experiments, subjects had to silently articulate the same syllables and, in a second task, move their lips or tongue. Speech perception most strongly activated superior temporal cortex. Crucially, however, distinct motor regions in the precentral gyrus sparked by articulatory movements of the lips and tongue were also differentially activated in a somatotopic manner when subjects listened to the lip- or tongue-related phonemes. This sound-related somatotopic activation in precentral gyrus shows that, during speech perception, specific motor circuits are recruited that reflect phonetic distinctive features of the speech sounds encountered, thus providing direct neuroimaging support for specific links between the phonological mechanisms for speech perception and production.
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              Brain activity at rest: a multiscale hierarchical functional organization.

              Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.
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                Author and article information

                Contributors
                Journal
                Neuroimage (Amst)
                Neuroimage (Amst)
                NeuroImage : Clinical
                Elsevier
                2213-1582
                18 January 2013
                18 January 2013
                2013
                : 2
                : 239-246
                Affiliations
                [a ]Epilepsy center Kempenhaeghe, Heeze, the Netherlands
                [b ]Research School for Mental Health & Neuroscience, Maastricht University, Maastricht, the Netherlands
                [c ]Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands
                [d ]Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
                Author notes
                [* ]Corresponding author at: Department of Radiology, Maastricht University Medical Center, PB 5800, 6202 AZ Maastricht, The Netherlands. Tel.: + 31 43 3874910; fax: + 31 43 3876909. w.backes@ 123456mumc.nl
                [1]

                Epilepsy center Kempenhaeghe, Postbox 61, 5590 AB Heeze, The Netherlands. Tel.: + 31 40 2279282; fax: + 31 40 2265691.

                Article
                S2213-1582(13)00006-5
                10.1016/j.nicl.2013.01.004
                3777786
                24179777
                387b6e88-dffe-4c8f-8c7c-3b2b74d64694
                © 2013 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 30 August 2012
                : 17 December 2012
                : 10 January 2013
                Categories
                Article

                re, rolandic epilepsy,ica, independent component analysis,rolandic epilepsy,language impairment,resting-state fmri,independent component analysis,resting-state networks,sensorimotor/rolandic network

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