Life-Span Development of Brain Network Integration Assessed with Phase Lag Index Connectivity and Minimum Spanning Tree Graphs.

Graph analysis of electroencephalography (EEG) has previously revealed developmental increases in connectivity between distant brain areas and a decrease in randomness and increased integration in the brain network with concurrent increased modularity. Comparisons of graph parameters across age groups, however, may be confounded with network degree distributions. In this study, we analyzed graph parameters from minimum spanning tree (MST) graphs and compared their developmental trajectories to those of graph parameters based on full graphs published previously. MST graphs are constructed by selecting only the strongest available connections avoiding loops, resulting in a backbone graph that is thought to reflect the major qualitative properties of the network, while allowing a better comparison across age groups by avoiding the degree of distribution confound. EEG was recorded in a large (n = 1500) population-based sample aged 5-71 years. Connectivity was assessed using phase lag index to reduce effects of volume conduction. Connectivity in the MST graph increased significantly from childhood to adolescence, continuing to grow nonsignificantly into adulthood, and decreasing significantly about 57 years of age. Leaf number, degree, degree correlation, and maximum centrality from the MST graph indicated a pattern of increased integration and decreased randomness from childhood into early adulthood. The observed development in network topology suggested that maturation at the neuronal level is aimed to increase connectivity as well as increase integration of the brain network. We confirm that brain network connectivity shows quantitative changes across the life span and additionally demonstrate parallel qualitative changes in the connectivity pattern.

Using fMRI to Investigate Memory in Young Children Born Small for Gestational Age.

OBJECTIVES: Intrauterine growth restriction (IUGR) can lead to infants being born small for gestational age (SGA). SGA is associated with differences in brain anatomy and impaired cognition. We investigated learning and memory in children born SGA using neuropsychological testing and functional Magnetic Resonance Imaging (fMRI). STUDY DESIGN: 18 children born appropriate for gestational age (AGA) and 34 SGA born children (18 with and 16 without postnatal catch-up growth) participated in this study. All children were between 4 and 7 years old. Cognitive functioning was assessed by IQ and memory testing (Digit/Word Span and Location Learning). A newly developed fMRI picture encoding task was completed by all children in order to assess brain regions involved in memory processes. RESULTS: Neuropsychological testing demonstrated that SGA children had IQ's within the normal range but lower than in AGA and poorer performances across measures of memory. Using fMRI, we observed memory related activity in posterior parahippocampal gyrus as well as the hippocampus proper. Additionally, activation was seen bilaterally in the prefrontal gyrus. Children born SGA showed less activation in the left parahippocampal region compared to AGA. CONCLUSIONS: This is the first fMRI study demonstrating different brain activation patterns in 4-7 year old children born SGA, suggesting that intrauterine growth restriction continues to affect neural functioning in children later-on.

Increased power of resting-state gamma oscillations in autism spectrum disorder detected by routine electroencephalography.

Experimental studies suggest that increased resting-state power of gamma oscillations is associated with autism spectrum disorder (ASD). To extend the clinical applicability of this finding, we retrospectively investigated routine electroencephalography (EEG) recordings of 19 patients with ASD and 19 age- and gender-matched controls. Relative resting-state condition gamma spectral power was variable, but on average significantly increased in children with ASD. This effect remained when excluding electrodes associated with myogenic gamma activity. These findings further indicate that increased resting-state gamma activity characterizes a subset of ASD and may also be detected by routine EEG as a clinically accessible and well-tolerated investigation.

Cortical information flow during inferences of agency.

Building on the recent finding that agency experiences do not merely rely on sensorimotor information but also on cognitive cues, this exploratory study uses electroencephalographic recordings to examine functional connectivity during agency inference processing in a setting where action and outcome are independent. Participants completed a computerized task in which they pressed a button followed by one of two color words (red or blue) and rated their experienced agency over producing the color. Before executing the action, a matching or mismatching color word was pre-activated by explicitly instructing participants to produce the color (goal condition) or by briefly presenting the color word (prime condition). In both conditions, experienced agency was higher in matching vs. mismatching trials. Furthermore, increased electroencephalography (EEG)-based connectivity strength was observed between parietal and frontal nodes and within the (pre)frontal cortex when color-outcomes matched with goals and participants reported high agency. This pattern of increased connectivity was not identified in trials where outcomes were pre-activated through primes. These results suggest that different connections are involved in the experience and in the loss of agency, as well as in inferences of agency resulting from different types of pre-activation. Moreover, the findings provide novel support for the involvement of a fronto-parietal network in agency inferences.

Resting-State Oscillatory Activity in Children Born Small for Gestational Age: An MEG Study.

Growth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG) in 4- to 7-year-old children to test if children born small for gestational age (SGA) show deviations in resting-state brain oscillatory activity. Children born SGA with postnatally spontaneous catch-up growth [SGA+; six boys, seven girls; mean age 6.3 year (SD = 0.9)] and children born appropriate for gestational age [AGA; seven boys, three girls; mean age 6.0 year (SD = 1.2)] participated in a resting-state MEG study. We calculated absolute and relative power spectra and used non-parametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At the time of MEG investigation, SGA+ children showed significantly lower head circumference (HC) and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth.

Disrupted functional brain networks in autistic toddlers.

Communication and integration of information between brain regions plays a key role in healthy brain function. Conversely, disruption in brain communication may lead to cognitive and behavioral problems. Autism is a neurodevelopmental disorder that is characterized by impaired social interactions and aberrant basic information processing. Aberrant brain connectivity patterns have indeed been hypothesized to be a key neural underpinning of autism. In this study, graph analytical tools are used to explore the possible deviant functional brain network organization in autism at a very early stage of brain development. Electroencephalography (EEG) recordings in 12 toddlers with autism (mean age 3.5 years) and 19 control subjects were used to assess interregional functional brain connectivity, with functional brain networks constructed at the level of temporal synchronization between brain regions underlying the EEG electrodes. Children with autism showed a significantly increased normalized path length and reduced normalized clustering, suggesting a reduced global communication capacity already during early brain development. In addition, whole brain connectivity was found to be significantly reduced in these young patients suggesting an overall under-connectivity of functional brain networks in autism. Our findings support the hypothesis of abnormal neural communication in autism, with deviating effects already present at the early stages of brain development.

Growing trees in child brains: graph theoretical analysis of electroencephalography-derived minimum spanning tree in 5- and 7-year-old children reflects brain maturation.

The child brain is a small-world network, which is hypothesized to change toward more ordered configurations with development. In graph theoretical studies, comparing network topologies under different conditions remains a critical point. Constructing a minimum spanning tree (MST) might present a solution, since it does not require setting a threshold and uses a fixed number of nodes and edges. In this study, the MST method is introduced to examine developmental changes in functional brain network topology in young children. Resting-state electroencephalography was recorded from 227 children twice at 5 and 7 years of age. Synchronization likelihood (SL) weighted matrices were calculated in three different frequency bands from which MSTs were constructed, which represent constructs of the most important routes for information flow in a network. From these trees, several parameters were calculated to characterize developmental change in network organization. The MST diameter and eccentricity significantly increased, while the leaf number and hierarchy significantly decreased in the alpha band with development. Boys showed significant higher leaf number, betweenness, degree and hierarchy and significant lower SL, diameter, and eccentricity than girls in the theta band. The developmental changes indicate a shift toward more decentralized line-like trees, which supports the previously hypothesized increase toward regularity of brain networks with development. Additionally, girls showed more line-like decentralized configurations, which is consistent with the view that girls are ahead of boys in brain development. MST provides an elegant method sensitive to capture subtle developmental changes in network organization without the bias of network comparison.

The brain matures with stronger functional connectivity and decreased randomness of its network.

We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years) by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998) graph parameters C (local clustering) and L (global path length) for alpha (~10 Hz), beta (~20 Hz), and theta (~4 Hz) oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ~50 yrs). Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ~18 yrs). Older age (55+) was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05), while path length was related to both white matter (alpha: max. r = 38, p<001) and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001) volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain.

Resting-state networks in awake five- to eight-year old children.

During the first 6-7 years of life children undergo a period of major neurocognitive development. Higher-order cognitive functions such as executive control of attention, encoding and retrieving of stored information and goal-directed behavior are present but less developed compared to older individuals. There is only very limited information from functional magnetic resonance imaging (fMRI) studies about the level of organization of functional networks in children in the early school period. In this study we perform continuous resting-state functional connectivity MRI in 5- to 8-year-old children in an awake state to identify and characterize resting-state networks (RSNs). Temporal concatenation independent component analysis (ICA) approach was applied to analyze the data. We identified 14 components consisting of regions known to be involved in visual and auditory processing, motor function, attention control, memory, and the default mode network (DMN). Most networks, in particular those supporting basic motor function and sensory related processing, had a robust functional organization similar to mature adult patterns. In contrast, the DMN and other RSNs involved in higher-order cognitive functions had immature characteristics, revealing incomplete and fragmented patterns indicating less developed functional connectivity. We therefore conclude that the DMN and other RSNs involved in higher order cognitive functioning are detectable, yet in an immature state, at an age when these cognitive abilities are mastered.

Global and regional differences in brain anatomy of young children born small for gestational age.

In children who are born small for gestational age (SGA), an adverse intrauterine environment has led to underdevelopment of both the body and the brain. The delay in body growth is (partially) restored during the first two years in a majority of these children. In addition to a negative influence on these physical parameters, decreased levels of intelligence and cognitive impairments have been described in children born SGA. In this study, we used magnetic resonance imaging to examine brain anatomy in 4- to 7-year-old SGA children with and without complete bodily catch-up growth and compared them to healthy children born appropriate for gestational age. Our findings demonstrate that these children strongly differ on brain organisation when compared with healthy controls relating to both global and regional anatomical differences. Children born SGA displayed reduced cerebral and cerebellar grey and white matter volumes, smaller volumes of subcortical structures and reduced cortical surface area. Regional differences in prefrontal cortical thickness suggest a different development of the cerebral cortex. SGA children with bodily catch-up growth constitute an intermediate between those children without catch-up growth and healthy controls. Therefore, bodily catch-up growth in children born SGA does not implicate full catch-up growth of the brain.

Brain volume changes after withdrawal of atypical antipsychotics in patients with first-episode schizophrenia.

The influence of antipsychotic medication on brain morphology in schizophrenia may confound interpretation of brain changes over time. We aimed to assess the effect of discontinuation of atypical antipsychotic medication on change in brain volume in patients. Sixteen remitted, stable patients with first-episode schizophrenia, schizoaffective or schizophreniform disorder and 20 healthy controls were included. Two magnetic resonance imaging brain scans were obtained from all subjects with a 1-year interval. The patients either discontinued (n = 8) their atypical antipsychotic medication (olanzapine, risperidone, or quetiapine) or did not (n = 8) discontinue during the follow-up period. Intracranial volume and volumes of total brain, cerebral gray and white matter, cerebellum, third and lateral ventricle, nucleus caudatus, nucleus accumbens, and putamen were obtained. Multiple linear regression analyses were used to assess main effects for group (patient-control) and discontinuation (yes-no) for brain volume (change) while correcting for age, sex, and intracranial volume. Decrease in cerebral gray matter and caudate nucleus volume over time was significantly more pronounced in patients relative to controls. Our data suggest decreases in the nucleus accumbens and putamen volumes during the interval in patients who discontinued antipsychotic medication, whereas increases were found in patients who continued their antipsychotics. We confirmed earlier findings of excessive gray matter volume decrements in patients with schizophrenia compared with normal controls. We found evidence suggestive of decreasing volumes of the putamen and nucleus accumbens over time after discontinuation of medication. This might suggest that discontinuation reverses effects of atypical medication.

Network analysis of resting state EEG in the developing young brain: structure comes with maturation.

During childhood, brain structure and function changes substantially. Recently, graph theory has been introduced to model connectivity in the brain. Small-world networks, such as the brain, combine optimal properties of both ordered and random networks, i.e., high clustering and short path lengths. We used graph theoretical concepts to examine changes in functional brain networks during normal development in young children. Resting-state eyes-closed electroencephalography (EEG) was recorded (14 channels) from 227 children twice at 5 and 7 years of age. Synchronization likelihood (SL) was calculated in three different frequency bands and between each pair of electrodes to obtain SL-weighted graphs. Mean normalized clustering index, average path length and weight dispersion were calculated to characterize network organization. Repeated measures analysis of variance tested for time and gender effects. For all frequency bands mean SL decreased from 5 to 7 years. Clustering coefficient increased in the alpha band. Path length increased in all frequency bands. Mean normalized weight dispersion decreased in beta band. Girls showed higher synchronization for all frequency bands and a higher mean clustering in alpha and beta bands. The overall decrease in functional connectivity (SL) might reflect pruning of unused synapses and preservation of strong connections resulting in more cost-effective networks. Accordingly, we found increases in average clustering and path length and decreased weight dispersion indicating that normal brain maturation is characterized by a shift from random to more organized small-world functional networks. This developmental process is influenced by gender differences early in development.

Preparing children with a mock scanner training protocol results in high quality structural and functional MRI scans.

We evaluated the use of a mock scanner training protocol as an alternative for sedation and for preparing young children for (functional) magnetic resonance imaging (MRI). Children with severe mental retardation or developmental disorders were excluded. A group of 90 children (median age 6.5 years, range 3.65-14.5 years) participated in this study. Children were referred to the actual MRI investigation only when they passed the training. We assessed the pass rate of the mock scanner training sessions. In addition, the quality of both structural and functional MRI (fMRI) scans was rated on a semi-quantitative scale. The overall pass rate of the mock scanner training sessions was 85/90. Structural scans of diagnostic quality were obtained in 81/90 children, and fMRI scans with sufficient quality for further analysis were obtained in 30/43 of the children. Even in children under 7 years of age, who are generally sedated, the success rate of structural scans with diagnostic quality was 53/60. FMRI scans with sufficient quality were obtained in 23/36 of the children in this younger age group. The association between age and proportion of children with fMRI scans of sufficient quality was not statistically significant. We conclude that a mock MRI scanner training protocol can be useful to prepare children for a diagnostic MRI scan. It may reduce the need for sedation in young children undergoing MRI. Our protocol is also effective in preparing young children to participate in fMRI investigations.

Function of striatum beyond inhibition and execution of motor responses.

We used functional magnetic resonance imaging (fMRI) to study the role of the striatum in inhibitory motor control. Subjects had to refrain from responding to designated items (STOP trials) within a similar series of motor stimuli. Striatal activation was increased significantly compared to that when responding to all targets within a series of motor stimuli, indicating that the striatum is more active when inhibitory motor control over responses is required. The likelihood of a STOP trial was varied parametrically by varying the number of GO trials before a STOP trial. We could thus measure the effect of expecting a STOP trial on the fMRI response in the striatum. We show for the first time in humans that the striatum becomes more active when the likelihood of inhibiting a planned motor response increases. Our findings suggest that the striatum is critically involved in inhibitory motor control, most likely by controlling the execution of planned motor responses.