Non-Invasive Mapping of the Neuronal Networks of Language.

This review consists of three main sections. In the first, the Introduction, the main theories of the neuronal mediation of linguistic operations, derived mostly from studies of the effects of focal lesions on linguistic performance, are summarized. These models furnish the conceptual framework on which the design of subsequent functional neuroimaging investigations is based. In the second section, the methods of functional neuroimaging, especially those of functional Magnetic Resonance Imaging (fMRI) and of Magnetoencephalography (MEG), are detailed along with the specific activation tasks employed in presurgical functional mapping. The reliability of these non-invasive methods and their validity, judged against the results of the invasive methods, namely, the "Wada" procedure and Cortical Stimulation Mapping (CSM), is assessed and their use in presurgical mapping is justified. In the third and final section, the applications of fMRI and MEG in basic research are surveyed in the following six sub-sections, each dealing with the assessment of the neuronal networks for (1) the acoustic and phonological, (2) for semantic, (3) for syntactic, (4) for prosodic operations, (5) for sign language and (6) for the operations of reading and the mechanisms of dyslexia.

MEG language mapping using a novel automatic ECD algorithm in comparison with MNE, dSPM, and DICS beamformer.

Introduction: The single equivalent current dipole (sECD) is the standard clinical procedure for presurgical language mapping in epilepsy using magnetoencephalography (MEG). However, the sECD approach has not been widely used in clinical assessments, mainly because it requires subjective judgements in selecting several critical parameters. To address this limitation, we developed an automatic sECD algorithm (AsECDa) for language mapping. Methods: The localization accuracy of the AsECDa was evaluated using synthetic MEG data. Subsequently, the reliability and efficiency of AsECDa were compared to three other common source localization methods using MEG data recorded during two sessions of a receptive language task in 21 epilepsy patients. These methods include minimum norm estimation (MNE), dynamic statistical parametric mapping (dSPM), and dynamic imaging of coherent sources (DICS) beamformer. Results: For the synthetic single dipole MEG data with a typical signal-to-noise ratio, the average localization error of AsECDa was less than 2 mm for simulated superficial and deep dipoles. For the patient data, AsECDa showed better test-retest reliability (TRR) of the language laterality index (LI) than MNE, dSPM, and DICS beamformer. Specifically, the LI calculated with AsECDa revealed excellent TRR between the two MEG sessions across all patients (Cor = 0.80), while the LI for MNE, dSPM, DICS-event-related desynchronization (ERD) in the alpha band, and DICS-ERD in the low beta band ranged lower (Cor = 0.71, 0.64, 0.54, and 0.48, respectively). Furthermore, AsECDa identified 38% of patients with atypical language lateralization (i.e., right lateralization or bilateral), compared to 73%, 68%, 55%, and 50% identified by DICS-ERD in the low beta band, DICS-ERD in the alpha band, MNE, and dSPM, respectively. Compared to other methods, AsECDa's results were more consistent with previous studies that reported atypical language lateralization in 20-30% of epilepsy patients. Discussion: Our study suggests that AsECDa is a promising approach for presurgical language mapping, and its fully automated nature makes it easy to implement and reliable for clinical evaluations.

Presurgical Functional Mapping with Magnetoencephalography.

Noninvasive functional brain imaging with magnetoencephalography (MEG) is regularly used to map the eloquent cortex associated with somatosensory, motor, auditory, visual, and language processing before a surgical resection to determine if the functional areas have been reorganized. Most tasks can also be performed in the pediatric population. To acquire an optimal MEG study for any of these modalities, the patient needs to be well rested and attending to the stimulation.

The auditory and association cortex and language evaluation methods.

This chapter presents a summary of current notions regarding cortical specialization for language and a description of the methods employed for the assessment of that specialization. We distinguish between the "canonical" model of language specialization as it evolved from the early observations of Broca and Wernicke, implicating the inferior frontal gyrus and the posterior temporal cortex of the speech dominant hemisphere (usually the left) and its modern variants that are based on both detailed studies of lesion-symptom correlations and on the results of functional brain mapping methods. The latter fall into two categories. The first includes the invasive ones, namely the Wada procedure for assessing hemispheric dominance for speech and cortical stimulation mapping (whether intraoperative or extraoperative) for identifying cortical nodes or "hubs" of the neuronal network for language. The second category includes the noninvasive methods of functional magnetic resonance imaging, magnetoencephalography, and transcranial magnetic stimulation used for both assessment of hemispheric dominance for language and for localization of the cortical nodes of the language network. The advantages and the shortcomings of all methods are juxtaposed to facilitate selection of particular methods of assessment of the locus of the language network in particular cases.

The power of sample size through a multi-scanner approach in MR neuroimaging regression analysis: evidence from Alzheimer's disease with and without depression.

The inconsistency of volumetric results often seen in MR neuroimaging studies can be partially attributed to small sample sizes and variable data analysis approaches. Increased sample size through multi-scanner studies can tackle the former, but combining data across different scanner platforms and field-strengths may introduce a variability factor capable of masking subtle statistical differences. To investigate the sample size effect on regression analysis between depressive symptoms and grey matter volume (GMV) loss in Alzheimer's disease (AD), a retrospective multi-scanner investigation was conducted. A cohort of 172 AD patients, with or without comorbid depressive symptoms, was studied. Patients were scanned with different imaging protocols in four different MRI scanners operating at either 1.5 T or 3.0 T. Acquired data were uniformly analyzed using the computational anatomy toolbox (CAT12) of the statistical parametric mapping (SPM12) software. Single- and multi-scanner regression analyses were applied to identify the anatomical pattern of correlation between GM loss and depression severity. A common anatomical pattern of correlation between GMV loss and increased depression severity, mostly involving sensorimotor areas, was identified in all patient subgroups imaged in different scanners. Analysis of the pooled multi-scanner data confirmed the above finding employing a more conservative statistical criterion. In the retrospective multi-scanner setting, a significant correlation was also exhibited for temporal and frontal areas. Increasing the sample size by retrospectively pooling multi-scanner data, irrespective of the acquisition platform and parameters employed, can facilitate the identification of anatomical areas with a strong correlation between GMV changes and depression symptoms in AD patients.

The Neural Correlates of Impaired Self-Monitoring Among Individuals With Neurodegenerative Dementias.

OBJECTIVE: Self-monitoring is a crucial component of human empathy and necessary for the formation and repair of social relations. Several studies have brought to light possible neuronal substrates associated with self-monitoring, but the information that they have provided is inconclusive. The authors, therefore, studied a large group of patients with dementia to assess what brain structures are necessary for the self-monitoring function.Methods: Seventy-seven patients with dementia of various types were screened using voxel-based morphometry to assess possible volume reduction in the brain structures of patients with self-monitoring problems, and the decrease of socioemotional expressiveness and modification of self-presentation was estimated using the Revised Self-Monitoring Scale. Regression analysis was employed to investigate the correlation between gray matter loss and deficient self-monitoring.Results: The socioemotional expressiveness scores were associated with decreased gray matter volume in the right olfactory cortex, inferior frontal gyrus, superior temporal pole, parahippocampal gyrus, insula, and medial temporal gyrus bilaterally. Self-presentation scores were associated with bilateral gray matter volume reduction in the olfactory cortex, insula, rectus gyrus and inferior frontal gyrus, right superior temporal pole, and parahippocampal gyrus, as well as the left medial temporal gyrus and anterior superior frontal gyrus.Conclusions: These results suggest that patients with dementia present decreased ability of self-monitoring, probably due to impaired insula and orbitofrontal cortex and their disconnection from structures of the salience network.

Typical and Aberrant Functional Brain Flexibility: Lifespan Development and Aberrant Organization in Traumatic Brain Injury and Dyslexia.

Intrinsic functional connectivity networks derived from different neuroimaging methods and connectivity estimators have revealed robust developmental trends linked to behavioural and cognitive maturation. The present study employed a dynamic functional connectivity approach to determine dominant intrinsic coupling modes in resting-state neuromagnetic data from 178 healthy participants aged 8-60 years. Results revealed significant developmental trends in three types of dominant intra- and inter-hemispheric neuronal population interactions (amplitude envelope, phase coupling, and phase-amplitude synchronization) involving frontal, temporal, and parieto-occipital regions. Multi-class support vector machines achieved 89% correct classification of participants according to their chronological age using dynamic functional connectivity indices. Moreover, systematic temporal variability in functional connectivity profiles, which was used to empirically derive a composite flexibility index, displayed an inverse U-shaped curve among healthy participants. Lower flexibility values were found among age-matched children with reading disability and adults who had suffered mild traumatic brain injury. The importance of these results for normal and abnormal brain development are discussed in light of the recently proposed role of cross-frequency interactions in the fine-grained coordination of neuronal population activity.

Aberrant Whole-Brain Transitions and Dynamics of Spontaneous Network Microstates in Mild Traumatic Brain Injury.

Dynamic Functional Connectivity (DFC) analysis is a promising approach for the characterization of brain electrophysiological activity. In this study, we investigated abnormal alterations due to mild Traumatic Brain Injury (mTBI) using DFC of the source reconstructed magnetoencephalographic (MEG) resting-state recordings. Brain activity in several well-known frequency bands was first reconstructed using beamforming of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase-locking values, which were obtained from 30 mTBI patients and 50 healthy controls (HC). Subsequently, we estimated normalized Laplacian transformations of individual, statistically and topologically filtered quasi-static graphs. The corresponding eigenvalues of each node synchronization were then computed and through the neural-gas algorithm, we quantized the evolution of the eigenvalues resulting in distinct network microstates (NMstates). The discrimination level between the two groups was assessed using an iterative cross-validation classification scheme with features either the NMstates in each frequency band, or the combination of the so-called chronnectomics (flexibility index, occupancy time of NMstate, and Dwell time) with the complexity index over the evolution of the NMstates across all frequency bands. Classification performance based on chronnectomics showed 80% accuracy, 99% sensitivity, and 49% specificity. However, performance was much higher (accuracy: 91-97%, sensitivity: 100%, and specificity: 77-93%) when focusing on the microstates. Exploring the mean node degree within and between brain anatomical networks (default mode network, frontoparietal, occipital, cingulo-opercular, and sensorimotor), a reduced pattern occurred from lower to higher frequency bands, with statistically significant stronger degrees for the HC than the mTBI group. A higher entropic profile on the temporal evolution of the modularity index was observed for both NMstates for the mTBI group across frequencies. A significant difference in the flexibility index was observed between the two groups for the ß frequency band. The latter finding may support a central role of the thalamus impairment in mTBI. The current study considers a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could serve as markers to assess the return of an injured subject back to normality.

Exploring the Profile of Incidental Memory in Patients with Amnestic Mild Cognitive Impairment and Mild Alzheimer's Disease.

Incidental memory can be defined as the ability to acquire information unintentionally. The present study investigated incidental memory performance in amnestic mild cognitive impairment (aMCI) and mild Alzheimer's disease (AD) patients; additionally, hippocampal atrophy between groupswas examined. Twenty-nine aMCI patients (14 with hippocampal atrophy, measured by the Medial Temporal Lobe Atrophy scale), 15 mild AD patients, and 20 cognitively intact individuals underwent a detailed medical and neuropsychological assessment examining intentional memory, using the Hopkins Verbal Learning Test-Revised and the Brief Visuospatial Memory Test. Participants first took part in a driving simulator experiment, followed by an unexpected incidental memory questionnaire referring to elements related to the driving simulation. The mild AD group performed worse than the aMCI group and the control group both in incidental and intentional memory tasks, whereas the aMCI group differed significantly from the control group only in the intentional memory tasks. The incidental recognition memory task was the only measure that differed between aMCI patients with and without hippocampal atrophy. Moreover, incidental memory tasks were the only measures that correlated significantly with both left and right hippocampal atrophy. The current findings indicate that incidental memory testing may provide potentially useful information for detecting aMCI patients with greater hippocampal atrophy, who may be considered at higher risk of developing dementia due to AD.

Aberrant resting-state functional brain networks in dyslexia: Symbolic mutual information analysis of neuromagnetic signals.

Neuroimaging studies have identified a variety of structural and functional connectivity abnormalities in students experiencing reading difficulties. The present study adopted a novel approach to assess the dynamics of resting-state neuromagnetic recordings in the form of symbolic sequences (i.e., repeated patterns of neuromagnetic fluctuations within and/or between sensors). Participants were 25 students experiencing severe reading difficulties (RD) and 27 age-matched non-impaired readers (NI) aged 7-14 years. Sensor-level data were first represented as symbolic sequences in eight conventional frequency bands. Next, dominant types of sensor-to-sensor interactions in the form of intra and cross-frequency coupling were computed and subjected to graph modeling to assess group differences in global network characteristics. As a group RD students displayed predominantly within-frequency interactions between neighboring sensors which may reflect reduced overall global network efficiency and cost-efficiency of information transfer. In contrast, sensor networks among NI students featured a higher proportion of cross-frequency interactions. Brain-reading achievement associations highlighted the role of left hemisphere temporo-parietal functional networks, at rest, for reading acquisition and ability.

Magnetoencephalography Reveals Mismatch Field Enhancement from Unexpected Syntactic Category Errors in English Sentences.

The type of syntactic operations that increase neuronal activation in humans as a result of syntactically erroneous, unexpected lexical items in hearing sentences has remained unclear. In the present study, we used recordings of magnetoencephalographic (MEG) activity to compare bare infinitive and full infinitive constructions in English. This research aims to identify the type of syntactic deviance that may trigger an early syntax-related mismatch field (MMF) component when unexpected words appear in sentences. Six speakers of English as a first language were presented with auditory stimuli of sentences or words in a passive odd-ball paradigm while watching a silent movie. The experimental protocol included four sessions, specifically investigating the sentential (structural) versions of full (with the 'to' infinitival particle) and bare infinitival structures (without the particle) and the lexical (non-structure) versions of the verb either with or without the particle to determine whether the structure processing of sentences was a more crucial factor in the detection of the MMF than the simple processing of lexical items in verb-only conditions. The amplitude analysis of the resulting evoked fields showed that the presence of the syntactic category error of bare infinitival structures against syntactic predictions evoked a significantly larger MMF activation with a peak latency of approximately 200ms in the anterior superior temporal sulci in the left hemisphere, compared with the lexical items that did not have any syntactic status. These results clearly demonstrate that syntactically unexpected, illegal input in the bare infinitival structure is likely to be noticed more robustly in the brain while processing the structural information of the entire sentence than the corresponding verb-only items.

On the relative merits of invasive and non-invasive pre-surgical brain mapping: New tools in ablative epilepsy surgery.

Cortical Stimulation Mapping (CSM) and the Wada procedure have long been considered the gold standard for localizing motor and language-related cortical areas and for determining the language and memory-dominant hemisphere, respectively. In recent years, however, non-invasive methods such as magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS) have emerged as promising alternatives to the aforementioned procedures, particularly in cases where the invasive localization of eloquent cortex has proven to be challenging. To illustrate this point, we will first introduce the evidence of the compatibility of invasive and non-invasive methods and subsequently outline the rationale and the conditions where the latter methods are applicable.

Altered Rich-Club and Frequency-Dependent Subnetwork Organization in Mild Traumatic Brain Injury: A MEG Resting-State Study.

Functional brain connectivity networks exhibit "small-world" characteristics and some of these networks follow a "rich-club" organization, whereby a few nodes of high connectivity (hubs) tend to connect more densely among themselves than to nodes of lower connectivity. The Current study followed an "attack strategy" to compare the rich-club and small-world network organization models using Magnetoencephalographic (MEG) recordings from mild traumatic brain injury (mTBI) patients and neurologically healthy controls to identify the topology that describes the underlying intrinsic brain network organization. We hypothesized that the reduction in global efficiency caused by an attack targeting a model's hubs would reveal the "true" underlying topological organization. Connectivity networks were estimated using mutual information as the basis for cross-frequency coupling. Our results revealed a prominent rich-club network organization for both groups. In particular, mTBI patients demonstrated hyper-synchronization among rich-club hubs compared to controls in the δ band and the δ-γ1, θ-γ1, and ß-γ2 frequency pairs. Moreover, rich-club hubs in mTBI patients were overrepresented in right frontal brain areas, from θ to γ1 frequencies, and underrepresented in left occipital regions in the δ-ß, δ-γ1, θ-ß, and ß-γ2 frequency pairs. These findings indicate that the rich-club organization of resting-state MEG, considering its role in information integration and its vulnerability to various disorders like mTBI, may have a significant predictive value in the development of reliable biomarkers to help the validation of the recovery from mTBI. Furthermore, the proposed approach might be used as a validation tool to assess patient recovery.

A specific pattern of gray matter atrophy in Alzheimer's disease with depression.

Considering the high incidence of depressive symptoms in Alzheimer's disease (AD), we conducted a large-sample study to investigate the pattern of gray matter (GM) abnormalities that differentiates depressive from non-depressive AD patients. We included 201 AD patients who underwent MRI assessment and categorized them into depressive and non-depressive subgroups based on the Geriatric Depression Scale (GDS; cut-off score: ≤9). We performed whole-brain voxel-based morphometry analysis in 173 patients after MRI quality control and used between-group comparisons and regression analysis models to analyze the volumetric data controlling for nuisance variables. Depressive AD patients had extensive GM volume loss mainly in the paracentral region, specifically in post- and pre-central gyrus, supplementary motor areas and thalamus compared to non-depressive patients. Similar findings were obtained for the group of 173 patients using regression analysis and GDS score as predictor variable. We provided the first clear demonstration of a unique pattern of GM atrophy that characterizes AD patients with depression which is consistent with regions implicated in the phenomenon of psychomotor retardation that characterizes depression.

Data-Driven Topological Filtering Based on Orthogonal Minimal Spanning Trees: Application to Multigroup Magnetoencephalography Resting-State Connectivity.

In the present study, a novel data-driven topological filtering technique is introduced to derive the backbone of functional brain networks relying on orthogonal minimal spanning trees (OMSTs). The method aims to identify the essential functional connections to ensure optimal information flow via the objective criterion of global efficiency minus the cost of surviving connections. The OMST technique was applied to multichannel, resting-state neuromagnetic recordings from four groups of participants: healthy adults (n = 50), adults who have suffered mild traumatic brain injury (n = 30), typically developing children (n = 27), and reading-disabled children (n = 25). Weighted interactions between network nodes (sensors) were computed using an integrated approach of dominant intrinsic coupling modes based on two alternative metrics (symbolic mutual information and phase lag index), resulting in excellent discrimination of individual cases according to their group membership. Classification results using OMST-derived functional networks were clearly superior to results using either relative power spectrum features or functional networks derived through the conventional minimal spanning tree algorithm.

Reconfiguration of dominant coupling modes in mild traumatic brain injury mediated by δ-band activity: A resting state MEG study.

During the last few years, rich-club (RC) organization has been studied as a possible brain-connectivity organization model for large-scale brain networks. At the same time, empirical and simulated data of neurophysiological models have demonstrated the significant role of intra-frequency and inter-frequency coupling among distinct brain areas. The current study investigates further the importance of these couplings using recordings of resting-state magnetoencephalographic activity obtained from 30 mild traumatic brain injury (mTBI) subjects and 50 healthy controls. Intra-frequency and inter-frequency coupling modes are incorporated in a single graph to detect group differences within individual rich-club subnetworks (type I networks) and networks connecting RC nodes with the rest of the nodes (type II networks). Our results show a higher probability of inter-frequency coupling for (δ-γ1), (δ-γ2), (θ-ß), (θ-γ2), (α-γ2), (γ1-γ2) and intra-frequency coupling for (γ1-γ1) and (δ-δ) for both type I and type II networks in the mTBI group. Additionally, mTBI and control subjects can be correctly classified with high accuracy (98.6%), whereas a general linear regression model can effectively predict the subject group using the ratio of type I and type II coupling in the (δ, θ), (δ, ß), (δ, γ1), and (δ, γ2) frequency pairs. These findings support the presence of an RC organization simultaneously with dominant frequency interactions within a single functional graph. Our results demonstrate a hyperactivation of intrinsic RC networks in mTBI subjects compared to controls, which can be seen as a plausible compensatory mechanism for alternative frequency-dependent routes of information flow in mTBI subjects.

Concordance of the Resting State Networks in Typically Developing, 6-to 7-Year-Old Children and Healthy Adults.

Though fairly well-studied in adults, less is known about the manifestation of resting state networks (RSN) in children. We examined the validity of RSN derived in an ethnically diverse group of typically developing 6- to 7-year-old children. We hypothesized that the RSNs in young children would be robust and would reliably show significant concordance with previously published RSN in adults. Additionally, we hypothesized that a smaller sample size using this robust technique would be comparable in quality to pediatric RSNs found in a larger cohort study. Furthermore, we posited that compared to the adult RSNs, the primary sensorimotor and the default mode networks (DMNs) in this pediatric group would demonstrate the greatest correspondence, while the executive function networks would exhibit a lesser degree of spatial overlap. Resting state functional magnetic resonance images (rs-fMRI) were acquired in 18 children between 6 and 7 years recruited from an ethnically diverse population in the Mid-South region of the United States. Twenty RSNs were derived using group independent component analysis and their spatial correspondence with previously published adult RSNs was examined. We demonstrate that the rs-fMRI in this group can be deconstructed into the fundamental RSN as all the major RSNs previously described in adults and in a large sample that included older children can be observed in our sample of young children. Further, the primary visual, auditory, and somatosensory networks, as well as the default mode, and frontoparietal networks derived in this group exhibited a greater spatial concordance with those seen in adults. The motor, temporoparietal, executive control, dorsal attention, and cerebellar networks in children had less spatial overlap with the corresponding RSNs in adults. Our findings suggest that several salient RSNs can be mapped reliably in small and diverse pediatric cohort within a narrow age range and the evolution of these RSNs can be studied reliably in such groups during early childhood and adolescence.

The Role of the Primary Sensory Cortices in Early Language Processing.

The results of this magnetoencephalography study challenge two long-standing assumptions regarding the brain mechanisms of language processing: First, that linguistic processing proper follows sensory feature processing effected by bilateral activation of the primary sensory cortices that lasts about 100 msec from stimulus onset. Second, that subsequent linguistic processing is effected by left hemisphere networks outside the primary sensory areas, including Broca's and Wernicke's association cortices. Here we present evidence that linguistic analysis begins almost synchronously with sensory, prelinguistic verbal input analysis and that the primary cortices are also engaged in these linguistic analyses and become, consequently, part of the left hemisphere language network during language tasks. These findings call for extensive revision of our conception of linguistic processing in the brain.

Incidental and Intentional Memory: Their Relation with Attention and Executive Functions.

OBJECTIVE: The aim of the current study was to investigate the impact of gender and age on incidental and intentional memory in healthy participants and to explore the strength of the association of incidental and intentional memory with attentional and executive functioning. METHOD: A total number of 47 participants underwent a driving simulation experiment and went through detailed neuropsychological testing. Incidental memory was assessed with a questionnaire that evaluated the memorization of information related to the driving simulator task while intentional memory was assessed using the Hopkins Verbal Learning Test-Revised and the Brief Visuospatial Memory Test-Revised. RESULTS: The analysis revealed a greater impact of age on incidental as compared to intentional memory. Gender did not appear to have such an effect on either incidental or intentional memory. Finally, attentional and executive functioning were more strongly associated with incidental memory than the intentional memory measures that were utilized in the current study. CONCLUSIONS: Ageing appears to affect incidental rather than intentional memory to a greater extent. In addition, attentional and executive functioning seem to play a more important role in incidental than intentional encoding and consolidation processes.