Low frequency overactivation in dyslexia: Evidence from resting state Magnetoencephalography

In this study, we compared the brain activation profiles obtained from resting state Magnetoencephalographic (MEG) activity in 15 dyslexic patients with the profiles of 15 normal controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of dyslexic patients into z-scores in eight distinct frequency bands. We found that dyslexic patients exhibited statistically significant overactivation in the delta band (0.1-4 Hz) in the right temporal (entorhinal and insula), left inferior frontal (Broca's area), and right inferior frontal regions. Overactivation may be interpreted as a compensatory mechanism for reading characterizing dyslexic patients. These findings suggest that resting-state MEG activation maps may be used as specific biomarkers that can help with the diagnosis of and assess the efficacy of intervention in dyslexia.

[1]  F Fazio,et al.  Brain abnormalities underlying altered activation in dyslexia: a voxel based morphometry study. , 2005, Brain : a journal of neurology.

[2]  J. Gabrieli,et al.  Functional and morphometric brain dissociation between dyslexia and reading ability , 2007, Proceedings of the National Academy of Sciences.

[3]  U. Goswami.  The neural basis of dyslexia may originate in primary auditory cortex. , 2014, Brain : a journal of neurology.

[4]  T. Whitlock.  Dyslexia , 1989, The Lancet.

[5]  S. Taulu,et al.  Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements , 2006, Physics in medicine and biology.

[6]  Usha Goswami,et al.  Neural entrainment to rhythmic speech in children with developmental dyslexia , 2013, Front. Hum. Neurosci..

[7]  F. Ramus,et al.  What Phonological Deficit? , 2008, Quarterly journal of experimental psychology.

[8]  Martin Kronbichler,et al.  Meta-analyzing brain dysfunctions in dyslexic children and adults , 2011, NeuroImage.

[9]  Richard M. Leahy,et al.  Brainstorm: A User-Friendly Application for MEG/EEG Analysis , 2011, Comput. Intell. Neurosci..

[10]  S. Taulu,et al.  Applications of the signal space separation method , 2005, IEEE Transactions on Signal Processing.

[11]  L. Siegel,et al.  Perspectives on dyslexia. , 2006, Paediatrics & child health.

[12]  M. Habib,et al.  Chapter 23 – Dyslexia , 2013 .

[13]  Alexandre Gramfort,et al.  Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals , 2015, NeuroImage.

[14]  Elizabeth S Norton,et al.  Neurobiology of dyslexia , 2014, Current Opinion in Neurobiology.

[15]  F. Richlan.  Developmental dyslexia: dysfunction of a left hemisphere reading network , 2012, Front. Hum. Neurosci..

[16]  Ludo Verhoeven,et al.  Different brain activation patterns in dyslexic children: evidence from EEG power and coherence patterns for the double-deficit theory of dyslexia. , 2007, Journal of integrative neuroscience.

[17]  E. Halgren,et al.  Dynamic Statistical Parametric Mapping Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity , 2000, Neuron.

[18]  Robin Morris,et al.  The education of dyslexic children from childhood to young adulthood. , 2008, Annual review of psychology.

[19]  R. Ilmoniemi,et al.  Interpreting magnetic fields of the brain: minimum norm estimates , 2006, Medical and Biological Engineering and Computing.

[20]  Thomas T. Liu,et al.  An automatic MEG low-frequency source imaging approach for detecting injuries in mild and moderate TBI patients with blast and non-blast causes , 2012, NeuroImage.

[21]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[22]  B. Pennington,et al.  Developmental dyslexia , 2012, The Lancet.

[23]  R M Leahy,et al.  A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG. , 1999, Physics in medicine and biology.

[24]  Jack M Fletcher,et al.  Brain activation profiles in dyslexic children during non-word reading: a magnetic source imaging study , 2000, Neuroscience Letters.

[25]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[26]  Cathy J. Price,et al.  A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading , 2012, NeuroImage.

[27]  A. Riecker,et al.  The contribution of white and gray matter differences to developmental dyslexia: Insights from DTI and VBM at 3.0T , 2008, Neuropsychologia.

[28]  John C Gore,et al.  Neural systems for compensation and persistence: young adult outcome of childhood reading disability , 2003, Biological Psychiatry.

[29]  Blair C. Armstrong,et al.  The what, when, where, and how of visual word recognition , 2014, Trends in Cognitive Sciences.

[30]  Fabio Richlan,et al.  Functional neuroanatomy of developmental dyslexia: the role of orthographic depth , 2014, Front. Hum. Neurosci..

[31]  Martin Kronbichler,et al.  Developmental dyslexia: Gray matter abnormalities in the occipitotemporal cortex , 2008, Human brain mapping.

[32]  Anders M. Dale,et al.  Improved Localization of Cortical Activity By Combining EEG and MEG with MRI Cortical Surface Reconstruction , 2002 .