Computational protocol: Visually Evoked Visual Auditory Changes Associated with Auditory Performance in Children with Cochlear Implants

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Protocol publication

[…] Comparison of latency and amplitude of ERP is sensor level-based. To further investigate cortical evolution of CI users and compare cortical activity differences between CI users and controls, we also conducted a source level activation analysis. Data analysis was performed with Brainstorm, which is documented and freely available for download online under the GNU general public license (). Brainstorm integrates various distributed source model methods and can readily conduct source analyses. We used Brainstorm to estimate primary auditory cortex (PAC), primary visual cortex (PVC), and parietal lobe cortex (PLC) activation. PAC and PVC have been described in the literature as involving cross modal reorganization by deaf children since these two parameters are directly related to the two most important sensations for deaf children. In fact, the parietal lobe, as the visual-auditory association cortex, integrates sensory information among various modalities and may also play a crucial role for deaf children in order to obtain auditory language ability. Several areas of the parietal lobe are important in language processing. Portions of the parietal lobe are involved in visuospatial processing (). Therefore, in this study we also analyzed its activation pre- and post-CI. We applied the method of standardized low-resolution electromagnetic tomography analysis (sLORETA) to identify and evaluate active sources (). The sLORETA method is based on a minimum norm estimation (MNE) and the activity (current density) is normalized by an individual estimate of the source standard deviation at each location. It has been identified as an efficient tool for functional mapping since it is consistent with physiology and capable of correct localization. The default anatomy ICBM152 in Brainstorm was used for all the subjects as the template brain. The brain template was generated from the non-linear average of 152 subjects. Cortical surface was divided into 15,002 grid points (sources). In our study, when source current density was calculated, source orientation was constrained and was perpendicular to the cortical surface. In a first step, sLORETA source estimation was calculated based on 128-channel ERP data re-referenced to a common average. Secondly, based on our hypotheses, regions of interest (ROI) for primary visual and auditory areas and the parietal cortex were defined prior to statistical computations. The average source activation between duration 130–180 ms (exactly covering the N1 component for the ‘sound’ condition) in these ROIs were statistically compared between CI users and controls. These ROIs were defined based on the Mindboggle-atlas implemented in Brainstorm, which relies on automatic parcellation using a surface-based alignment of the cortical folding (). PVC encompassed the lingual gyrus and pericalcarine sulcus (in Mindboggle atlas: ‘lingual L/R’ and ‘pericalcarine L/R’ approximately make up of PVC). Regarding PAC, previous studies have reported cross-modal activity in Brodmann areas 41 and 42 of deaf individuals and CI users (). Similarly, we defined the PAC as a small region in order to get a close approximation to Brodmann areas 41 and 42 (Mindboggle: transverse temporal L/R). PLC was defined as a combination of three small regions (Mindboggle: ‘inferiorparietal L/R,’ ‘precuneus L/R,’ ‘superiorparietal L/R,’ ‘supramarginal L/R’). The locations of the three ROIs on the cortex were outlined in Figure using red solid lines; PAC was indicated in Figure , PLC in Figure , and PVC in Figure . Consistent with the ERP analysis, the source analysis focused on the time window of the N1 component. The individual absolute peak magnitude of the ROI source activation was defined as the average of a 50 ms window around the peak and was subjected to statistical analyses. Where appropriate, two-sample t-tests between the groups (deaf children with CI and controls) were applied for each ROI and each time duration after CI. In addition, two-sample t-tests between CI users with good outcome and those with poor outcome were also applied for each ROI and each time duration after CI. […]

Pipeline specifications

Software tools Brainstorm, Mindboggle
Application Magnetic resonance imaging
Organisms Homo sapiens
Diseases Vision Disorders
Chemicals Phencyclidine