Roozbeh Rezaie

Extracting biomarkers of autism from MEG resting-state functional connectivity networks

The present study is a preliminary attempt to use graph theory for deriving distinct features of resting-state functional networks in young adults with autism spectrum disorder (ASD). Networks modeled neuromagnetic signal interactions between sensors using three alternative interdependence measures: (a) a non-linear measure of generalized synchronization (robust interdependence measure [RIM]), (b) mutual information (MI), and (c) partial directed coherence (PDC). To summarize the information contained in each network model we employed well-established global graph measures (average strength, assortativity, clustering, and efficiency) as well as graph measures (average strength of edges) tailored to specific hypotheses concerning the spatial distribution of abnormalities in connectivity among individuals with ASD. Graph measures then served as features in leave-one-out classification analyses contrasting control and ASD participants. We found that combinations of regionally constrained graph measures, derived from RIM, performed best, discriminating between the two groups with 93.75% accuracy. Network visualization revealed that ASD participants displayed significantly reduced interdependence strength, both within bilateral frontal and temporal sensors, as well as between temporal sensors and the remaining recording sites, in agreement with previous studies of functional connectivity in this disorder.

Functional connectivity networks in the autistic and healthy brain assessed using Granger causality

In this study, we analyze brain connectivity based on Granger causality computed from magnetoencephalographic (MEG) activity obtained at the resting state in eight autistic and eight normal subjects along with measures of network connectivity derived from graph theory in an attempt to understand how communication in a human brain network is affected by autism. A connectivity matrix was computed for each subject individually and then group templates were estimated by averaging all matrices in each group. Furthermore, we performed classification of the subjects using support vector machines and Fishers criterion to rank the features and identify the best subset for maximum separation of the groups. Our results show that a combined model based on connectivity matrices and graph theory measures can provide 87.5% accuracy in separating the two groups. These findings suggest that analysis of functional connectivity patterns may provide a valuable method for the early detection of autism.

Is it time to replace the Wada test and put awake craniotomy to sleep

The question we address here is whether the invasive presurgical brain mapping approaches of direct cortical stimulation and of the Wada procedure can be replaced by noninvasive functional neuroimaging methods (functional magnetic resonance imaging [fMRI], magnetoencephalography [MEG], transcranial magnetic stimulation and [TMS]). First, we outline the reasons for contemplating such a replacement. Second, we present evidence to the effect that the efficacy of the invasive and noninvasive methods, while suboptimal, is comparable. Third, we discuss additional advantages of noninvasive presurgical brain mapping and conclude that there are no longer compelling reasons for opting for invasive mapping in many if not most cases provided that the non‐invasive methods are available.

Temporo-parietal brain activity as a longitudinal predictor of response to educational interventions among middle school struggling readers

Spatiotemporal brain activation profiles were obtained from 27 middle school students experiencing difficulties in reading comprehension as well as word-level skills (RD) and 23 age- and IQ-matched non-reading impaired students during performance of an oral pseudoword reading task using Magnetoencephalography (MEG). Based on their scores on standardized reading fluency tests 1 year later, students with RD who showed significant improvement were classified as Adequate Responders (AR) whereas those not demonstrating such gains were classified as Inadequate Responders (IR). At baseline, activation profiles of the AR group featured increased activity in the left supramarginal and angular gyri, as well as in the superior and middle temporal gyri, bilaterally compared to IR. The degree of activity in these regions was a significant predictor of the amount of subsequent gains in reading fluency. These results extend previous functional brain imaging findings of beginning readers, suggesting that recruitment of brain areas that typically serve as key components of the brain circuit for reading is an important factor in determining response to intervention in older struggling readers.

Language mapping using high gamma electrocorticography, fMRI, and TMS versus electrocortical stimulation

OBJECTIVE The aim of the present study was to compare localization of the language cortex using cortical stimulation mapping (CSM), high gamma electrocorticography (hgECoG), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS). METHODS Language mapping using CSM, hgECoG, fMRI, and TMS were compared in nine patients with epilepsy. Considering CSM as reference, we compared language mapping approaches based on hgECoG, fMRI, and TMS using their sensitivity, specificity, and the results of receiver operating characteristic (ROC) analyses. RESULTS Our results show that areas involved in language processing can be identified by hgECoG, fMRI, and TMS. The average sensitivity/specificity of hgECoG, fMRI, and TMS across all patients was 100%/85%, 50%/80%, and 67%/66%, respectively. The average area under the ROC curve of hgECoG, fMRI, and TMS across CSM-positive patients was 0.98, 0.76, and 0.68, respectively. CONCLUSIONS There is considerable concordance between CSM, hgECoG, fMRI, and TMS language mapping. Our results reveal that hgECoG, fMRI, and TMS are valuable tools for presurgical language mapping. SIGNIFICANCE Language mapping on the basis of hgECoG, fMRI, and TMS can provide important additional information, therefore, these methods can be used in conjunction with CSM or as an alternative, when the latter is deemed impractical.

Functional Disruption of the Brain Mechanism for Reading: Effects of Comorbidity and Task Difficulty Among Children With Developmental Learning Problems

OBJECTIVE The study investigated the relative degree and timing of cortical activation associated with phonological decoding in poor readers. METHOD Regional brain activity was assessed during performance of a pseudoword reading task and a less demanding, letter-sound naming task by three groups of students: children who experienced reading difficulties without attention problems (N = 50, RD) and nonreading impaired (NI) readers either with (N = 20) or without attention-deficit/hyperactivity disorder (ADHD; N = 50). Recordings were obtained with a whole-head neuromagnetometer, and activation profiles were computed through a minimum norm algorithm. RESULTS Children with RD showed decreased amplitude of neurophysiological activity in the superior temporal gyrus, bilaterally, and in the left supramarginal and angular gyri during late stages of decoding, compared to typical readers. These effects were restricted to the more demanding pseudoword reading task. No differences were found in degree of activity between NI and ADHD students. Regression analyses provided further support for the crucial role of left hemisphere temporoparietal cortices and the fusiform gyrus for basic reading skills. CONCLUSIONS Results were in agreement with fMRI findings and replicate previous MEG findings with a larger sample, a higher density neuromagnetometer, an overt pseudoword reading task, and a distributed current source-modeling method.

Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury

Cross-frequency coupling (CFC) is thought to represent a basic mechanism of functional integration of neural networks across distant brain regions. In this study, we analyzed CFC profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 30 mild traumatic brain injury (mTBI) patients and 50 controls. We used mutual information (MI) to quantify the phase-to-amplitude coupling (PAC) of activity among the recording sensors in six nonoverlapping frequency bands. After forming the CFC-based functional connectivity graphs, we employed a tensor representation and tensor subspace analysis to identify the optimal set of features for subject classification as mTBI or control. Our results showed that controls formed a dense network of stronger local and global connections indicating higher functional integration compared to mTBI patients. Furthermore, mTBI patients could be separated from controls with more than 90% classification accuracy. These findings indicate that analysis of brain networks computed from resting-state MEG with PAC and tensorial representation of connectivity profiles may provide a valuable biomarker for the diagnosis of mTBI.

Functional connectivity changes in mild traumatic brain injury assessed using magnetoencephalography

In this study, we analyzed brain connectivity profiles from 10 mild traumatic brain injury (mTBI) patients and 10 age- and gender-matched normal controls. We computed Granger causality measures from magnetoencephalographic (MEG) activity obtained at the resting state, in an attempt to understand how the default network is affected by mTBI. A connectivity matrix was computed for each subject individually and then group templates were estimated by averaging all matrices in each group. Furthermore, we performed classification of the subjects using support vector machines and Fishers criterion to rank the features and identify the best subset for maximum separation of the groups. Our results show that a combined model based on connectivity matrices and graph theory measures can provide a minimum of 85% classification accuracy in separating the two groups, with a sensitivity and specificity of 90% and 80%, respectively. These findings suggest that analysis of functional connectivity patterns may provide a valuable tool for early detection of mTBI.

Dynamic task-specific brain network connectivity in children with severe reading difficulties

We investigated patterns of sensor-level functional connectivity derived from single-trial whole-head magnetoencephalography data during a pseudoword reading and a letter-sound naming task in children with reading difficulties (RD) and children with no reading impairments (NI). The Phase Lag Index (PLI), a linear and nonlinear estimator, computed for each pair of sensors, was used to construct graphs and obtain estimates of local and global network efficiency according to graph theory. In the 8-13 Hz (alpha band) and 20-30 Hz (gamma band) range, RD students showed significantly lower global efficiency than NI children, for the entire MEG recording epoch. RD students also displayed reduced local network efficiency in the alpha band. Correlations between phonological decoding ability and graph metrics were particularly evident during the task that posed significant demands for phonological decoding, and followed distinct time courses depending on signal frequency. Results are consistent with the notion of task-dependent, aberrant long- and short-range functional connectivity in RD children.

Assessment of hemispheric dominance for receptive language in pediatric patients under sedation using magnetoencephalography

Non-invasive assessment of hemispheric dominance for receptive language using magnetoencephalography (MEG) is now a well-established procedure used across several epilepsy centers in the context of pre-surgical evaluation of children and adults while awake, alert and attentive. However, the utility of MEG for the same purpose, in cases of sedated patients, is contested. Establishment of the efficiency of MEG is especially important in the case of children who, for a number of reasons, must be assessed under sedation. Here we explored the efficacy of MEG language mapping under sedation through retrospective review of 95 consecutive pediatric patients, who underwent our receptive language test as part of routine clinical evaluation. Localization of receptive language cortex and subsequent determination of laterality was successfully completed in 78% (n = 36) and 55% (n = 27) of non-sedated and sedated patients, respectively. Moreover, the proportion of patients deemed left hemisphere dominant for receptive language did not differ between non-sedated and sedated patients, exceeding 90% in both groups. Considering the challenges associated with assessing brain function in pediatric patients, the success of passive MEG in the context of the cases reviewed in this study support the utility of this method in pre-surgical receptive language mapping.