Combined functional and causal connectivity analyses of language networks in children: a feasibility study

Parent Language Input Prior to School Forecasts Change in Children's Language-Related Cortical Structures During Mid-Adolescence

Children differ widely in their early language development, and this variability has important implications for later life outcomes. Parent language input is a strong experiential factor predicting the variability in children's early language skills. However, little is known about the brain or cognitive mechanisms that underlie the relationship. In addressing this gap, we used longitudinal data spanning 15 years to examine the role of early parental language input that children receive during preschool years in the development of brain structures that support language processing during school years. Using naturalistic parent-child interactions, we measured parental language input (amount and complexity) to children between the ages of 18 and 42 months (n = 23). We then assessed longitudinal changes in children's cortical thickness measured at five time points between 9 and 16 years of age. We focused on specific regions of interest (ROIs) that have been shown to play a role in language processing. Our results support the view that, even after accounting for important covariates such as parental intelligence quotient (IQ) and education, the amount and complexity of language input to a young child prior to school forecasts the rate of change in cortical thickness during the 7-year period from 5½ to 12½ years later. Examining the proximal correlates of change in brain and cognitive differences has the potential to inform targets for effective prevention and intervention strategies.

Functional organization of the language network in three- and six-year-old children

The organization of the language network undergoes continuous changes during development as children learn to understand sentences. In the present study, functional magnetic resonance imaging and behavioral measures were utilized to investigate functional activation and functional connectivity (FC) in three-year-old (3yo) and six-year-old (6yo) children during sentence comprehension. Transitive German sentences varying the word order (subject-initial and object-initial) with case marking were presented auditorily. We selected children who were capable of processing the subject-initial sentences above chance level accuracy from each age group to ensure that we were tapping real comprehension. Both age groups showed a main effect of word order in the left posterior superior temporal gyrus (pSTG), with greater activation for object-initial compared to subject-initial sentences. However, age differences were observed in the FC between left pSTG and the left inferior frontal gyrus (IFG). The 6yo group showed stronger FC between the left pSTG and Brodmann area (BA) 44 of the left IFG compared to the 3yo group. For the 3yo group, in turn, the FC between left pSTG and left BA 45 was stronger than with left BA 44. Our study demonstrates that while task-related activation was comparable, the small behavioral differences between age groups were reflected in the underlying functional organization revealing the ongoing development of the neural language network.

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We examined functional connectivity of sentence processing in 3- and 6-year-olds.

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Performance-matched age groups activated left pSTG for processing complex syntax.

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6-year-olds had stronger connectivity between left BA44 and pSTG than 3-year-olds.

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3-year-olds had greater connectivity between left BA45 and pSTG than BA44 and pSTG.

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Functional connectivity results could be related to behavioral performance.

Maturation of language networks in children: A systematic review of 22years of functional MRI

Understanding how language networks change during childhood is important for theories of cognitive development and for identifying the neural causes of language impairment. Despite this, there is currently little systematic evidence regarding the typical developmental trajectory for language from the field of neuroimaging. We reviewed functional MRI (fMRI) studies published between 1992 and 2014, and quantified the evidence for age-related changes in localisation and lateralisation of fMRI activation in the language network (excluding the cerebellum and subcortical regions). Although age-related changes differed according to task type and input modality, we identified four consistent findings concerning the typical maturation of the language system. First, activation in core semantic processing regions increases with age. Second, activation in lower-level sensory and motor regions increases with age as activation in higher-level control regions reduces. We suggest that this reflects increased automaticity of language processing as children become more proficient. Third, the posterior cingulate cortex and precuneus (regions associated with the default mode network) show increasing attenuation across childhood and adolescence. Finally, language lateralisation is established by approximately 5years of age. Small increases in leftward lateralisation are observed in frontal regions, but these are tightly linked to performance.

Language Development across the Life Span: A Neuropsychological/Neuroimaging Perspective

Language development has been correlated with specific changes in brain development. The aim of this paper is to analyze the linguistic-brain associations that occur from birth through senescence. Findings from the neuropsychological and neuroimaging literature are reviewed, and the relationship of language changes observable in human development and the corresponding brain maturation processes across age groups are examined. Two major dimensions of language development are highlighted: naming (considered a major measure of lexical knowledge) and verbal fluency (regarded as a major measure of language production ability). Developmental changes in the brain lateralization of language are discussed, emphasizing that in early life there is an increase in functional brain asymmetry for language, but that this asymmetry changes over time, and that changes in the volume of gray and white matter are age-sensitive. The effects of certain specific variables, such as gender, level of education, and bilingualism are also analyzed. General conclusions are presented and directions for future research are suggested.

Evaluation of net causal influences in the circuit responding to premotor control during the movement-readiness state using conditional Granger causality

As an initialization procedure for brain responding to subsequent movement execution (ME), the movement-readiness (MR) state is important for understanding the formation processes from daily movement training to long-term memory of movement pattern. As such, based on functional magnetic resonance imaging (fMRI), the net causal influences among regions contributing to premotor control during the MR state were explored by means of conditional Granger causality (CGC) and graph-theory methods in the present study. Our results found that net causal circuits responding to unimanual MR were identified during right-hand or left-hand MR, involving in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), upper precuneus (UPCU), caudate nucleus (CN), cingulate motor area (CMA), supplementary motor area (SMA) and primary sensorimotor area (S1M1). Moreover, the contralateral CN, SMA and S1M1 revealed greater net causal influences during unimanual MR, which highlighted the contralateral dominant modulations during unimanual MR. Furthermore, according as the graph-theory analysis, the higher In+Out degrees of upper precuneus (UPCU) during right-hand MR or higher In+Out degrees of cingulate motor area (CMA) and posterior cingulate cortex (PCC) during left-hand MR implied the brain asymmetry of causal connectivity in the circuit responding to right-hand or left-hand MR. This article is part of a Special Issue entitled SI: Brain and Memory.

Vulnerability of the ventral language network in children with focal epilepsy

Croft et al. present fMRI and functional connectivity analyses of the language network in children with epilepsy and healthy controls. In both groups, the network is organised into dorsal and ventral systems. Activation of the ventral network is reduced in children with epilepsy, in association with poorer language function.

Children with focal epilepsy are at increased risk of language impairment, yet the neural substrate of this dysfunction is not yet known. Using functional magnetic resonance imaging we investigated the impact of focal epilepsy on the developing language system using measures of network topology (spatial organization of activation) and synchrony (functional connectivity). We studied healthy children (n = 48, 4–12 years, 24 females) and children with focal epilepsy (n = 21, 5–12 years, nine females) with left hemisphere language dominance. Participants performed an age-adjusted auditory description decision task during functional magnetic resonance imaging, to identify perisylvian language regions. Mean signal change was extracted from eight left perisylvian regions of interest and compared between groups. Paired region of interest functional connectivity analysis was performed on time course data from the same regions, to investigate left network synchrony. Two principal component analyses were performed to extract (i) patterns of activation (using mean signal change data); and (ii) patterns of synchronized regions (using functional connectivity data). For both principal component analyses two components (networks) were extracted, which mapped onto the functional anatomy of dorsal and ventral language systems. Associations among network variables, age, epilepsy-related factors and verbal ability were assessed. Activated networks were affected by age and epilepsy [F(2,60) = 3.74, P = 0.03]: post hoc analyses showed, for healthy children, activation in both ventral and dorsal networks decreased with age (P = 0.02). Regardless of age and task performance, children with epilepsy showed reduced activation of the ventral network (P < 0.001). They also showed a trend for increased activation of the dorsal network (P = 0.08) associated with improved task performance (r = 0.62, P = 0.008). Crucially, decreased activation of the ventral network in patients predicted poorer language outcome ( = 0.47, P = 0.002). This suggests childhood onset epilepsy preferentially alters maturation of the ventral language system, and this is related to poorer language ability.

Functional MRI-guided probabilistic tractography of cortico-cortical and cortico-subcortical language networks in children

In this study, we analyzed the structural connectivity of cortico-cortical and cortico-subcortical language networks in healthy children, using probabilistic tractography based on high angular resolution diffusion imaging. In addition to anatomically defining seed and target regions for tractography, we used fMRI to target inferior frontal and superior temporal cortical language areas on an individual basis. Further, connectivity between these cortical and subcortical (thalamus, caudate nucleus) language regions was assessed. Overall, data from 15 children (8f) aged 8-17 years (mean age 12.1 ±3 years) could be included. A slight but non-significant trend towards leftward lateralization was found in the arcuate fasciculus/superior longitudinal fasciculus (AF/SLF) using anatomically defined masks (p>.05, Wilcoxon rank test), while the functionally-guided tractography showed a significant lateralization to the left (p<.01). Connectivity of the thalamus with language regions was strong but not lateralized. Connectivity of the caudate nucleus with inferior-frontal language regions was also symmetrical, while connectivity with superior-temporal language regions was strongly lateralized to the left (p<.01). To conclude, we could show that tracking the arcuate fasciculus/superior longitudinal fasciculus is possible using both anatomically and functionally-defined seed and target regions. With the latter approach, we could confirm the presence of structurally-lateralized cortico-cortical language networks already in children, and finally, we could demonstrate a strongly asymmetrical connectivity of the caudate nucleus with superior temporal language regions. Further research is necessary in order to assess the usability of such an approach to assess language dominance in children unable to participate in an active fMRI study.

Concordance of MEG and fMRI patterns in adolescents during verb generation

In this study we focused on direct comparison between the spatial distributions of activation detected by functional magnetic resonance imaging (fMRI) and localization of sources detected by magnetoencephalography (MEG) during identical language tasks. We examined the spatial concordance between MEG and fMRI results in 16 adolescents performing a three-phase verb generation task that involves repeating the auditorily presented concrete noun and generating verbs either overtly or covertly in response to the auditorily presented noun. MEG analysis was completed using a synthetic aperture magnetometry (SAM) technique, while the fMRI data were analyzed using the general linear model approach with random-effects. To quantify the agreement between the two modalities, we implemented voxel-wise concordance correlation coefficient (CCC) and identified the left inferior frontal gyrus and the bilateral motor cortex with high CCC values. At the group level, MEG and fMRI data showed spatial convergence in the left inferior frontal gyrus for covert or overt generation versus overt repetition, and the bilateral motor cortex when overt generation versus covert generation. These findings demonstrate the utility of the CCC as a quantitative measure of spatial convergence between two neuroimaging techniques.

Dynamics of large-scale cortical interactions at high gamma frequencies during word production: event related causality (ERC) analysis of human electrocorticography (ECoG)

Intracranial EEG studies in humans have shown that functional brain activation in a variety of functional-anatomic domains of human cortex is associated with an increase in power at a broad range of high gamma (>60Hz) frequencies. Although these electrophysiological responses are highly specific for the location and timing of cortical processing and in animal recordings are highly correlated with increased population firing rates, there has been little direct empirical evidence for causal interactions between different recording sites at high gamma frequencies. Such causal interactions are hypothesized to occur during cognitive tasks that activate multiple brain regions. To determine whether such causal interactions occur at high gamma frequencies and to investigate their functional significance, we used event-related causality (ERC) analysis to estimate the dynamics, directionality, and magnitude of event-related causal interactions using subdural electrocorticography (ECoG) recorded during two word production tasks: picture naming and auditory word repetition. A clinical subject who had normal hearing but was skilled in American Signed Language (ASL) provided a unique opportunity to test our hypothesis with reference to a predictable pattern of causal interactions, i.e. that language cortex interacts with different areas of sensorimotor cortex during spoken vs. signed responses. Our ERC analyses confirmed this prediction. During word production with spoken responses, perisylvian language sites had prominent causal interactions with mouth/tongue areas of motor cortex, and when responses were gestured in sign language, the most prominent interactions involved hand and arm areas of motor cortex. Furthermore, we found that the sites from which the most numerous and prominent causal interactions originated, i.e. sites with a pattern of ERC "divergence", were also sites where high gamma power increases were most prominent and where electrocortical stimulation mapping interfered with word production. These findings suggest that the number, strength and directionality of event-related causal interactions may help identify network nodes that are not only activated by a task but are critical to its performance.

Relationship between functional connectivity and sensory impairment: red flag or red herring?

Resting-state functional magnetic resonance imaging (fMRI) can be used to study the functional connectivity in the somatosensory system. However, the relationship between sensory network connectivity, sensory deficits, and structural abnormality remains poorly understood. Previously, we investigated the motor network in children with congenital hemiparesis due to middle cerebral artery strokes (MCA, n = 6) or periventricular lesions (PL, n = 8). In the present study, we validate the use of interleaved resting-state data from blocked fMRI designs to investigate the somatosensory network in these patients. The approach was validated by assessing the predicted "crossed-over" connectivity between the cerebral cortex and the cerebellum. Furthermore, the impact on the volume of gray-matter (GM) in primary (S1) and secondary (S2) somatosensory cortex on functional connectivity measures was investigated. We were able to replicate the well-known "crossed-over" pattern of functional connectivity between cerebral and cerebellar cortex. The MCA group displayed more sensory deficit and significantly reduced functional connectivity in the lesioned S2 (but not in lesioned S1) when compared with the PL group. However, when accounting for GM volume loss, this difference disappeared. This study demonstrates the applicability of analyzing resting-state connectivity in patients with brain lesions. Reductions of functional connectivity within the somatosensory network were associated with sensory deficits, but were fully explained by the underlying GM damage.

A cerebellar thalamic cortical circuit for error-related cognitive control

Error detection and behavioral adjustment are core components of cognitive control. Numerous studies have focused on the anterior cingulate cortex (ACC) as a critical locus of this executive function. Our previous work showed greater activation in the dorsal ACC and subcortical structures during error detection, and activation in the ventrolateral prefrontal cortex (VLPFC) during post-error slowing (PES) in a stop signal task (SST). However, the extent of error-related cortical or subcortical activation across subjects was not correlated with VLPFC activity during PES. So then, what causes VLPFC activation during PES? To address this question, we employed Granger causality mapping (GCM) and identified regions that Granger caused VLPFC activation in 54 adults performing the SST during fMRI. These brain regions, including the supplementary motor area (SMA), cerebellum, a pontine region, and medial thalamus, represent potential targets responding to errors in a way that could influence VLPFC activation. In confirmation of this hypothesis, the error-related activity of these regions correlated with VLPFC activation during PES, with the cerebellum showing the strongest association. The finding that cerebellar activation Granger causes prefrontal activity during behavioral adjustment supports a cerebellar function in cognitive control. Furthermore, multivariate GCA described the "flow of information" across these brain regions. Through connectivity with the thalamus and SMA, the cerebellum mediates error and post-error processing in accord with known anatomical projections. Taken together, these new findings highlight the role of the cerebello-thalamo-cortical pathway in an executive function that has heretofore largely been ascribed to the anterior cingulate-prefrontal cortical circuit.

Influences of brain development and ageing on cortical interactive networks

OBJECTIVE

To study the effect of brain development and ageing on the pattern of cortical interactive networks.

METHODS

By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years).

RESULTS

By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas.

CONCLUSIONS

The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing.

SIGNIFICANCE

Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing.

Quantifying auditory event-related responses in multichannel human intracranial recordings

Multichannel intracranial recordings are used increasingly to study the functional organization of human cortex. Intracranial recordings of event-related activity, or electrocorticography (ECoG), are based on high density electrode arrays implanted directly over cortex, combining good temporal and spatial resolution. Developing appropriate statistical methods for analyzing event-related responses in these high dimensional ECoG datasets remains a major challenge for clinical and systems neuroscience. We present a novel methodological framework that combines complementary, existing methods adapted for statistical analysis of auditory event-related responses in multichannel ECoG recordings. This analytic framework integrates single-channel (time-domain, time–frequency) and multichannel analyses of event-related ECoG activity to determine statistically significant evoked responses, induced spectral responses, and effective (causal) connectivity. Implementation of this quantitative approach is illustrated using multichannel ECoG data from recent studies of auditory processing in patients with epilepsy. Methods described include a time–frequency matching pursuit algorithm adapted for modeling brief, transient cortical spectral responses to sound, and a recently developed method for estimating effective connectivity using multivariate autoregressive modeling to measure brief event-related changes in multichannel functional interactions. A semi-automated spatial normalization method for comparing intracranial electrode locations across patients is also described. The individual methods presented are published and readily accessible. We discuss the benefits of integrating multiple complementary methods in a unified and comprehensive quantitative approach. Methodological considerations in the analysis of multichannel ECoG data, including corrections for multiple comparisons are discussed, as well as remaining challenges in the development of new statistical approaches.

Nonlinear connectivity by Granger causality

The communication among neuronal populations, reflected by transient synchronous activity, is the mechanism underlying the information processing in the brain. Although it is widely assumed that the interactions among those populations (i.e. functional connectivity) are highly nonlinear, the amount of nonlinear information transmission and its functional roles are not clear. The state of the art to understand the communication between brain systems are dynamic causal modeling (DCM) and Granger causality. While DCM models nonlinear couplings, Granger causality, which constitutes a major tool to reveal effective connectivity, and is widely used to analyze EEG/MEG data as well as fMRI signals, is usually applied in its linear version. In order to capture nonlinear interactions between even short and noisy time series, a few approaches have been proposed. We review them and focus on a recently proposed flexible approach has been recently proposed, consisting in the kernel version of Granger causality. We show the application of the proposed approach on EEG signals and fMRI data.

Evaluating the effective connectivity of resting state networks using conditional Granger causality

The human brain has been documented to be spatially organized in a finite set of specific coherent patterns, namely resting state networks (RSNs). The interactions among RSNs, being potentially dynamic and directional, may not be adequately captured by simple correlation or anticorrelation. In order to evaluate the possible effective connectivity within those RSNs, we applied a conditional Granger causality analysis (CGCA) to the RSNs retrieved by independent component analysis (ICA) from resting state functional magnetic resonance imaging (fMRI) data. Our analysis provided evidence for specific causal influences among the detected RSNs: default-mode, dorsal attention, core, central-executive, self-referential, somatosensory, visual, and auditory networks. In particular, we identified that self-referential and default-mode networks (DMNs) play distinct and crucial roles in the human brain functional architecture. Specifically, the former RSN exerted the strongest causal influence over the other RSNs, revealing a top-down modulation of self-referential mental activity (SRN) over sensory and cognitive processing. In quite contrast, the latter RSN was profoundly affected by the other RSNs, which may underlie an integration of information from primary function and higher level cognition networks, consistent with previous task-related studies. Overall, our results revealed the causal influences among these RSNs at different processing levels, and supplied information for a deeper understanding of the brain network dynamics.