Fairy Tales versus Facts: Genre Matters to the Developing Brain.

Neurobiological studies of discourse comprehension have almost exclusively focused on narrative comprehension. However, successful engagement in modern society, particularly in educational settings, also requires comprehension with an aim to learn new information (i.e., "expository comprehension"). Despite its prevalence, no studies to date have neurobiologically characterized expository comprehension as compared with narrative. In the current study, we used functional magnetic resonance imaging in typically developing children to test whether different genres require specialized brain networks. In addition to expected activations in language and comprehension areas in the default mode network (DMN), expository comprehension required significantly greater activation in the frontoparietal control network (FPN) than narrative comprehension, and relied significantly less on posterior regions in the DMN. Functional connectivity analysis revealed that, compared with narrative, the FPN robustly correlated with the DMN, and this inter-network communication was higher with increased reading expertise. These findings suggest that, relative to narrative comprehension, expository comprehension shows (1) a unique configuration of the DMN, potentially to support non-social comprehension processes, and (2) increased utilization of top-down regions to help support goal-directed comprehension processes in the DMN. More generally, our findings reveal that different types of discourse-level comprehension place diverse neural demands on the developing brain.

Applying a network framework to the neurobiology of reading and dyslexia.

BACKGROUND: There is a substantial literature on the neurobiology of reading and dyslexia. Differences are often described in terms of individual regions or individual cognitive processes. However, there is a growing appreciation that the brain areas subserving reading are nested within larger functional systems, and new network analysis methods may provide greater insight into how reading difficulty arises. Yet, relatively few studies have adopted a principled network-based approach (e.g., connectomics) to studying reading. In this study, we combine data from previous reading literature, connectomics studies, and original data to investigate the relationship between network architecture and reading. METHODS: First, we detailed the distribution of reading-related areas across many resting-state networks using meta-analytic data from NeuroSynth. Then, we tested whether individual differences in modularity, the brain's tendency to segregate into resting-state networks, are related to reading skill. Finally, we determined whether brain areas that function atypically in dyslexia, as identified by previous meta-analyses, tend to be concentrated in hub regions. RESULTS: We found that most resting-state networks contributed to the reading network, including those subserving domain-general cognitive skills such as attention and executive function. There was also a positive relationship between the global modularity of an individual's brain network and reading skill, with the visual, default mode and cingulo-opercular networks showing the highest correlations. Brain areas implicated in dyslexia were also significantly more likely to have a higher participation coefficient (connect to multiple resting-state networks) than other areas. CONCLUSIONS: These results contribute to the growing literature on the relationship between reading and brain network architecture. They suggest that an efficient network organization, i.e., one in which brain areas form cohesive resting-state networks, is important for skilled reading, and that dyslexia can be characterized by abnormal functioning of hub regions that map information between multiple systems. Overall, use of a connectomics framework opens up new possibilities for investigating reading difficulty, especially its commonalities across other neurodevelopmental disorders.

Voxel-wise detection of functional networks in white matter.

Functional magnetic resonance imaging (fMRI) depicts neural activity in the brain indirectly by measuring blood oxygenation level dependent (BOLD) signals. The majority of fMRI studies have focused on detecting cortical activity in gray matter (GM), but whether functional BOLD signal changes also arise in white matter (WM), and whether neural activities trigger hemodynamic changes in WM similarly to GM, remain controversial, particularly in light of the much lower vascular density in WM. However, BOLD effects in WM are readily detected under hypercapnic challenges, and the number of reports supporting reliable detections of stimulus-induced activations in WM continues to grow. Rather than assume a particular hemodynamic response function, we used a voxel-by-voxel analysis of frequency spectra in WM to detect WM activations under visual stimulation, whose locations were validated with fiber tractography using diffusion tensor imaging (DTI). We demonstrate that specific WM regions are robustly activated in response to visual stimulation, and that regional distributions of WM activation are consistent with fiber pathways reconstructed using DTI. We further examined the variation in the concordance between WM activation and fiber density in groups of different sample sizes, and compared the signal profiles of BOLD time series between resting state and visual stimulation conditions in activated GM as well as activated and non-activated WM regions. Our findings confirm that BOLD signal variations in WM are modulated by neural activity and are detectable with conventional fMRI using appropriate methods, thus offering the potential of expanding functional connectivity measurements throughout the brain.

Detection of synchronous brain activity in white matter tracts at rest and under functional loading.

Functional MRI based on blood oxygenation level-dependent (BOLD) contrast is well established as a neuroimaging technique for detecting neural activity in the cortex of the human brain. While detection and characterization of BOLD signals, as well as their electrophysiological and hemodynamic/metabolic origins, have been extensively studied in gray matter (GM), the detection and interpretation of BOLD signals in white matter (WM) remain controversial. We have previously observed that BOLD signals in a resting state reveal structure-specific anisotropic temporal correlations in WM and that external stimuli alter these correlations and permit visualization of task-specific fiber pathways, suggesting variations in WM BOLD signals are related to neural activity. In this study, we provide further strong evidence that BOLD signals in WM reflect neural activities both in a resting state and under functional loading. We demonstrate that BOLD signal waveforms in stimulus-relevant WM pathways are synchronous with the applied stimuli but with various degrees of time delay and that signals in WM pathways exhibit clear task specificity. Furthermore, resting-state signal fluctuations in WM tracts show significant correlations with specific parcellated GM volumes. These observations support the notion that neural activities are encoded in WM circuits similarly to cortical responses.

Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation.

Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead-lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC-IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC-IPL SC at one time point positively predicted future changes in RLPFC-IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability.SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation (functional connectivity, FC), and reasoning ability in a large longitudinal sample of subjects 6-22 years of age. We found that greater frontoparietal SC in childhood predicts future increases in both FC and reasoning ability, demonstrating the importance of white matter development during childhood for subsequent brain and cognitive functioning.

Functional connectivity and activity of white matter in somatosensory pathways under tactile stimulations.

Functional MRI has proven to be effective in detecting neural activity in brain cortices on the basis of blood oxygenation level dependent (BOLD) contrast, but has relatively poor sensitivity for detecting neural activity in white matter. To demonstrate that BOLD signals in white matter are detectable and contain information on neural activity, we stimulated the somatosensory system and examined distributions of BOLD signals in related white matter pathways. The temporal correlation profiles and frequency contents of BOLD signals were compared between stimulation and resting conditions, and between relevant white matter fibers and background regions, as well as between left and right side stimulations. Quantitative analyses show that, overall, MR signals from white matter fiber bundles in the somatosensory system exhibited significantly greater temporal correlations with the primary sensory cortex and greater signal power during tactile stimulations than in a resting state, and were stronger than corresponding measurements for background white matter both during stimulations and in a resting state. The temporal correlation and signal power under stimulation were found to be twice those observed from the same bundle in a resting state, and bore clear relations with the side of stimuli. These indicate that BOLD signals in white matter fibers encode neural activity related to their functional roles connecting cortical volumes, which are detectable with appropriate methods.

Comprehending text versus reading words in young readers with varying reading ability: distinct patterns of functional connectivity from common processing hubs.

Skilled reading depends on recognizing words efficiently in isolation (word-level processing; WL) and extracting meaning from text (discourse-level processing; DL); deficiencies in either result in poor reading. FMRI has revealed consistent overlapping networks in word and passage reading, as well as unique regions for DL processing; however, less is known about how WL and DL processes interact. Here we examined functional connectivity from seed regions derived from where BOLD signal overlapped during word and passage reading in 38 adolescents ranging in reading ability, hypothesizing that even though certain regions support word- and higher-level language, connectivity patterns from overlapping regions would be task modulated. Results indeed revealed that the left-lateralized semantic and working memory (WM) seed regions showed task-dependent functional connectivity patterns: during DL processes, semantic and WM nodes all correlated with the left angular gyrus, a region implicated in semantic memory/coherence building. In contrast, during WL, these nodes coordinated with a traditional WL area (left occipitotemporal region). In addition, these WL and DL findings were modulated by decoding and comprehension abilities, respectively, with poorer abilities correlating with decreased connectivity. Findings indicate that key regions may uniquely contribute to multiple levels of reading; we speculate that these connectivity patterns may be especially salient for reading outcomes and intervention response.

Visualizing functional pathways in the human brain using correlation tensors and magnetic resonance imaging.

Functional magnetic resonance imaging usually detects changes in blood oxygenation level dependent (BOLD) signals from T2*-sensitive acquisitions, and is most effective in detecting activity in brain cortex which is irrigated by rich vasculature to meet high metabolic demands. We recently demonstrated that MRI signals from T2*-sensitive acquisitions in a resting state exhibit structure-specific temporal correlations along white matter tracts. In this report we validate our preliminary findings and introduce spatio-temporal functional correlation tensors to characterize the directional preferences of temporal correlations in MRI signals acquired at rest. The results bear a remarkable similarity to data obtained by diffusion tensor imaging but without any diffusion-encoding gradients. Just as in gray matter, temporal correlations in resting state signals may reflect intrinsic synchronizations of neural activity in white matter. Here we demonstrate that functional correlation tensors are able to visualize long range white matter tracts as well as short range sub-cortical fibers imaged at rest, and that evoked functional activities alter these structures and enhance the visualization of relevant neural circuitry. Furthermore, we explore the biophysical mechanisms underlying these phenomena by comparing pulse sequences, which suggest that white matter signal variations are consistent with hemodynamic (BOLD) changes associated with neural activity. These results suggest new ways to evaluate MRI signal changes within white matter.