An executive-functions-based reading training enhances sensory-motor systems integration during reading fluency in children with dyslexia.

The Simple View of Reading model suggests that intact language processing and word decoding lead to proficient reading comprehension, with recent studies pointing at executive functions as an important component contributing to reading proficiency. Here, we aimed to determine the underlying mechanism(s) for these changes. Participants include 120 8- to 12-year-old children (n = 55 with dyslexia, n = 65 typical readers) trained on an executive functions-based reading program, including pre/postfunctional MRI and behavioral data collection. Across groups, improved word reading was related to stronger functional connections within executive functions and sensory networks. In children with dyslexia, faster and more accurate word reading was related to stronger functional connections within and between sensory networks. These results suggest greater synchronization of brain systems after the intervention, consistent with the "neural noise" hypothesis in children with dyslexia and support the consideration of including executive functions as part of the Simple View of Reading model.

Cognitive deficits and altered functional brain network organization in pediatric brain tumor patients.

Survivors of pediatric brain tumors experience significant cognitive deficits from their diagnosis and treatment. The exact mechanisms of cognitive injury are poorly understood, and validated predictors of long-term cognitive outcome are lacking. Resting state functional magnetic resonance imaging allows for the study of the spontaneous fluctuations in bulk neural activity, providing insight into brain organization and function. Here, we evaluated cognitive performance and functional network architecture in pediatric brain tumor patients. Forty-nine patients (7-18 years old) with a primary brain tumor diagnosis underwent resting state imaging during regularly scheduled clinical visits. All patients were tested with a battery of cognitive assessments. Extant data from 139 typically developing children were used as controls. We found that obtaining high-quality imaging data during routine clinical scanning was feasible. Functional network organization was significantly altered in patients, with the largest disruptions observed in patients who received propofol sedation. Awake patients demonstrated significant decreases in association network segregation compared to controls. Interestingly, there was no difference in the segregation of sensorimotor networks. With a median follow-up of 3.1 years, patients demonstrated cognitive deficits in multiple domains of executive function. Finally, there was a weak correlation between decreased default mode network segregation and poor picture vocabulary score. Future work with longer follow-up, longitudinal analyses, and a larger cohort will provide further insight into this potential predictor.

Probabilistic mapping of human functional brain networks identifies regions of high group consensus.

Many recent developments surrounding the functional network organization of the human brain have focused on data that have been averaged across groups of individuals. While such group-level approaches have shed considerable light on the brain's large-scale distributed systems, they conceal individual differences in network organization, which recent work has demonstrated to be common and widespread. This individual variability produces noise in group analyses, which may average together regions that are part of different functional systems across participants, limiting interpretability. However, cost and feasibility constraints may limit the possibility for individual-level mapping within studies. Here our goal was to leverage information about individual-level brain organization to probabilistically map common functional systems and identify locations of high inter-subject consensus for use in group analyses. We probabilistically mapped 14 functional networks in multiple datasets with relatively high amounts of data. All networks show "core" (high-probability) regions, but differ from one another in the extent of their higher-variability components. These patterns replicate well across four datasets with different participants and scanning parameters. We produced a set of high-probability regions of interest (ROIs) from these probabilistic maps; these and the probabilistic maps are made publicly available, together with a tool for querying the network membership probabilities associated with any given cortical location. These quantitative estimates and public tools may allow researchers to apply information about inter-subject consensus to their own fMRI studies, improving inferences about systems and their functional specializations.

Default-mode network streams for coupling to language and control systems.

The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained ∼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity.

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., 'motion' parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 â€‹Hz, here referred to as 'HF-motion'), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0-2.5 â€‹s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 â€‹s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants.

High-fidelity mapping of repetition-related changes in the parietal memory network.

fMRI studies of human memory have identified a "parietal memory network" (PMN) that displays distinct responses to novel and familiar stimuli, typically deactivating during initial encoding but robustly activating during retrieval. The small size of PMN regions, combined with their proximity to the neighboring default mode network, makes a targeted assessment of their responses in highly sampled subjects important for understanding information processing within the network. Here, we describe an experiment in which participants made semantic decisions about repeatedly-presented stimuli, assessing PMN BOLD responses as items transitioned from experimentally novel to repeated. Data are from the highly-sampled subjects in the Midnight Scan Club dataset, enabling a characterization of BOLD responses at both the group and single-subject level. Across all analyses, PMN regions deactivated in response to novel stimuli and displayed changes in BOLD activity across presentations, but did not significantly activate to repeated items. Results support only a portion of initially hypothesized effects, in particular suggesting that novelty-related deactivations may be less susceptible to attentional/task manipulations than are repetition-related activations within the network. This in turn suggests that novelty and familiarity may be processed as separable entities within the PMN.

Children Use Regions in the Visual Processing and Executive Function Networks during a Subsequent Memory Reading Task.

Memory encoding is a critical process for memory function, which is foundational for cognitive functioning including reading, and has been extensively studied using subsequent memory tasks. Research in adults using such tasks indicates the participation of visual and cognitive-control systems in remembered versus forgotten words. However, given the known developmental trajectories of these systems, the functional neuroanatomy of memory encoding in children may be different than in adults. We examined brain activation for silent word reading and checkerboard viewing during an event-related reading task in 8-12 year-old children. Results indicate greater activation for checkerboard viewing than lexical processing in early visual regions, as well as for lexical processing versus checkerboard viewing in regions in left sensorimotor mouth, cingulo-opercular and dorsal-attention networks. Greater activation for remembered than forgotten words was observed in bilateral visual system and left lateralized regions within the ventral- and dorsal-attention, cingulo-opercular and fronto-parietal networks. These findings suggest a relatively mature reliance on the cognitive-control system, but greater reliance on the visual system in children when viewing words subsequently remembered. The location of regions with greater activity for remembered words reinforces the involvement of the attention and cognitive-control systems in subsequent memory in reading.

Spatial and Temporal Organization of the Individual Human Cerebellum.

The cerebellum contains the majority of neurons in the human brain and is unique for its uniform cytoarchitecture, absence of aerobic glycolysis, and role in adaptive plasticity. Despite anatomical and physiological differences between the cerebellum and cerebral cortex, group-average functional connectivity studies have identified networks related to specific functions in both structures. Recently, precision functional mapping of individuals revealed that functional networks in the cerebral cortex exhibit measurable individual specificity. Using the highly sampled Midnight Scan Club (MSC) dataset, we found the cerebellum contains reliable, individual-specific network organization that is significantly more variable than the cerebral cortex. The frontoparietal network, thought to support adaptive control, was the only network overrepresented in the cerebellum compared to the cerebral cortex (2.3-fold). Temporally, all cerebellar resting state signals lagged behind the cerebral cortex (125-380 ms), supporting the hypothesis that the cerebellum engages in a domain-general function in the adaptive control of all cortical processes.

Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation.

The organization of human brain networks can be measured by capturing correlated brain activity with fMRI. There is considerable interest in understanding how brain networks vary across individuals or neuropsychiatric populations or are altered during the performance of specific behaviors. However, the plausibility and validity of such measurements is dependent on the extent to which functional networks are stable over time or are state dependent. We analyzed data from nine high-quality, highly sampled individuals to parse the magnitude and anatomical distribution of network variability across subjects, sessions, and tasks. Critically, we find that functional networks are dominated by common organizational principles and stable individual features, with substantially more modest contributions from task-state and day-to-day variability. Sources of variation were differentially distributed across the brain and differentially linked to intrinsic and task-evoked sources. We conclude that functional networks are suited to measuring stable individual characteristics, suggesting utility in personalized medicine.

Precision Functional Mapping of Individual Human Brains.

Human functional MRI (fMRI) research primarily focuses on analyzing data averaged across groups, which limits the detail, specificity, and clinical utility of fMRI resting-state functional connectivity (RSFC) and task-activation maps. To push our understanding of functional brain organization to the level of individual humans, we assembled a novel MRI dataset containing 5 hr of RSFC data, 6 hr of task fMRI, multiple structural MRIs, and neuropsychological tests from each of ten adults. Using these data, we generated ten high-fidelity, individual-specific functional connectomes. This individual-connectome approach revealed several new types of spatial and organizational variability in brain networks, including unique network features and topologies that corresponded with structural and task-derived brain features. We are releasing this highly sampled, individual-focused dataset as a resource for neuroscientists, and we propose precision individual connectomics as a model for future work examining the organization of healthy and diseased individual human brains.

Cognitive Training for Adults With Bothersome Tinnitus: A Randomized Clinical Trial.

Importance: Individuals with tinnitus have poorer working memory, slower processing speeds and reaction times, and deficiencies in selective attention, all of which interfere with readiness and performance. Brain Fitness Program-Tinnitus (BFP-T) is a cognitive training program specially designed to exploit neuroplasticity for preservation and expansion of cognitive health in adults with tinnitus. Objective: To evaluate the effect of the BFP-T on tinnitus. Design, Setting, and Participants: This open-label, intention-to-treat randomized clinical trial prescreened 191 patients with tinnitus and 64 healthy controls (HCs) from June 1, 2012, through October 31, 2013. Participants were 40 adults with bothersome tinnitus for more than 6 months and 20 age-matched HCs. Patients with tinnitus were randomized to a BFP-T or non-BFP-T control group. The BFP-T was completed online, and assessments were completed at Washington University School of Medicine. Interventions: Participants in the intervention group were required to complete the BFP-T online 1 hour per day 5 days per week for 8 weeks. Tinnitus assessment, neuroimaging, and cognitive testing were completed at baseline and 8 weeks later. The HCs underwent neuroimaging and cognitive assessments. Main Outcomes and Measures: The primary outcome measure was the change in Tinnitus Handicap Inventory (THI) score. Behavioral measures, neuroimaging, and cognitive tests were performed before and after the intervention. Results: A total of 40 patients with tinnitus and 20 HCs participated in the study (median [range] age, 56 [35-64] years in the BFP-T group, 52 [24-64] years in the non-BFP-T group, and 50 [30-64] years in the HC group; 13 [65%] in the BFP-T group, 14 [70%] in the non-BFP-T group, and 13 [65%] in the HC group were males; and 16 [80%] in the BFP-T group, 16 [80%] in the non-BFP-T group, and 15 [75%] in the HC group were white). There was a reduction in the THI score in the BFP-T group (median, 7; range, -16 to 64) and non-BFP-T group (median, 11; range, -6 to 26), but this reduction was not significantly different between the 2 groups (median difference, 0; 95% CI, -10 to 8). There was no difference in cognitive test scores and other behavioral measures. There was a significant difference between baseline and follow-up in functional connectivity in cognitive control regions in the BFP-T group but not in HCs or individuals with untreated tinnitus. Of the 20 patients in the BFP-T group, 10 (50%) self-reported improvement attributable to the intervention, and 6 (30%) reported to be much improved in the domains of tinnitus, memory, attention, and concentration. Conclusions and Relevance: These findings suggest that the computer-based cognitive training program is associated with self-reported changes in attention, memory, and perception of tinnitus. A possible mechanistic explanation for these changes could be neuroplastic changes in key brain systems involved in cognitive control. Cognitive training programs might have a role in the future treatment of patients with tinnitus. Trial Registration: clinicaltrials.gov Identifier: NCT01458821.

The Feasibility of Using Metacognitive Strategy Training to Improve Cognitive Performance and Neural Connectivity in Women with Chemotherapy-Induced Cognitive Impairment.

OBJECTIVE: To evaluate the feasibility and preliminary effect of metacognitive strategy training (MCST) on cognitive performance and on neural connectivity in the frontoparietal network in women with chemotherapy-induced cognitive impairment (CICI) following treatment for breast cancer. METHODS: A single-group pre/post study was conducted. After completing the baseline assessment battery and neuroimaging, the participants completed a 12-session MCST intervention. Following the completion of the intervention, the subjects completed the same assessment battery and neuroimaging as was completed at baseline within 4 weeks after the intervention. The key inclusion/exclusion criteria for this study were: completed chemotherapy for treatment of breast cancer, no other neurological or psychiatric diagnoses, self-reported CICI, and no contraindications to the use of MRI. RESULTS: MCST had a small-to-large positive effect on all primary (cognitive) and secondary (quality of life and psychosocial) behavioral outcome measures (r = -0.12 to -0.88). There was also a positive change in functional connectivity in a frontoparietal cognitive control network connection in 6 of the 10 subjects, which was correlated to changes in the behavioral measures. CONCLUSIONS: This study found that MCST was associated with a positive effect on cognitive performance and neural connectivity in women with CICI following treatment for breast cancer.

Unmasking Language Lateralization in Human Brain Intrinsic Activity.

Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal.

Cognitive impairment after chemotherapy related to atypical network architecture for executive control.

OBJECTIVES: A common complaint of cancer patients is the experience of cognitive difficulty during and after chemotherapy. We hypothesized that cognitive impairment may result from dysfunction in large-scale brain networks, particularly those involved in attentional control. METHODS: Using a case-control design, this study includes women with a history of invasive ductal or lobular triple-negative breast cancer who completed standard adjuvant chemotherapy within 2 years of study entry. Women who reported cognitive impairment by the Global Rating of Cognition question were considered to be cases (n = 15). Women who reported no cognitive impairment were considered to be controls (n = 13). All enrolled participants were eligible for MRI investigation and underwent resting-state functional connectivity MRI. RESULTS: Women who self-reported cognitive impairment were found to have disrupted resting-state functional connectivity, as measured by MRI, when compared to women who did not self-report cognitive impairment. These findings suggest that some women may be more sensitive to the standard treatments for breast cancer and that this increased sensitivity may result in functional connectivity alterations in the brain networks supporting attention and executive function. CONCLUSIONS: Neuroimaging analyses confirmed self-reported cognitive deficits in women with breast cancer treated with chemotherapy.

Diffusion tensor imaging in children with unilateral hearing loss: a pilot study.

OBJECTIVE: Language acquisition was assumed to proceed normally in children with unilateral hearing loss (UHL) since they have one functioning ear. However, children with UHL score poorly on speech-language tests and have higher rates of educational problems compared to normal hearing (NH) peers. Diffusion tensor imaging (DTI) is an imaging modality used to measure microstructural integrity of brain white matter. The purpose of this pilot study was to investigate differences in fractional anisotropy (FA) and mean diffusivity (MD) in hearing- and non-hearing-related structures in the brain between children with UHL and their NH siblings. STUDY DESIGN: Prospective observational cohort. SETTING: Academic medical center. SUBJECTS AND METHODS: Sixty one children were recruited, tested and imaged. Twenty nine children with severe-to-profound UHL were compared to 20 siblings with NH using IQ and oral language testing, and MRI with DTI. Twelve children had inadequate MRI data. Parents provided demographic data and indicated whether children had a need for an individualized educational program (IEP) or speech therapy (ST). DTI parameters were measured in auditory and non-auditory regions of interest (ROIs). Between-group comparisons were evaluated with non-parametric tests. RESULTS: Lower FA of left lateral lemniscus was observed for children with UHL compared to their NH siblings, as well as trends toward differences in other auditory and non-auditory regions. Correlation analyses showed associations between several DTI parameters and outcomes in children with UHL. Regression analyses revealed relationships between educational outcome variables and several DTI parameters, which may provide clinically useful information for guidance of speech therapy. DISCUSSION/CONCLUSION: Our data suggests that white matter microstructural patterns in several brain regions are preserved despite unilateral rather than bilateral auditory input which contrasts with findings in patients with bilateral hearing loss.

Allodynia and descending pain modulation in migraine: a resting state functional connectivity analysis.

OBJECTIVE: Most migraineurs develop cutaneous allodynia during migraines, and many have cutaneous sensitization between attacks. Atypical pain modulation via the descending pain system may contribute to this sensitization and allodynia. The objective of this study was to test the hypothesis that compared with non-allodynic migraineurs, allodynic migraineurs have atypical periaqueductal gray (PAG) and nucleus cuneiformis (NCF) resting-state functional connectivity (rs-fc) with other pain processing regions. DESIGN: Ten minutes resting-state blood-oxygen-level-dependent data were collected from 38 adult migraineurs and 20 controls. Seed-based analyses compared whole-brain rs-fc with PAG and with NCF in migraineurs with severe ictal allodynia (N = 8) to migraineurs with no ictal allodynia (N = 8). Correlations between the strength of functional connections that differed between severely allodynic and non-allodynic migraineurs with allodynia severity were determined for all migraineurs (N = 38). PAG and NCF rs-fc in all migraineurs was compared with rs-fc in controls. RESULTS: Migraineurs with severe allodynia had stronger PAG and NCF rs-fc to other brainstem, thalamic, insula and cerebellar regions that participate in discriminative pain processing, as well as to frontal and temporal regions implicated in higher order pain modulation. Evidence that these rs-fc differences were specific for allodynia included: 1) strong correlations between some rs-fc strengths and allodynia severity among all migraineurs; and 2) absence of overlap when comparing rs-fc differences in severely allodynic vs non-allodynic migraineurs with those in all migraineurs vs controls. CONCLUSION: Atypical rs-fc of brainstem descending modulatory pain regions with other brainstem and higher order pain-modulating regions is associated with migraine-related allodynia.

Atypical resting-state functional connectivity of affective pain regions in chronic migraine.

OBJECTIVE: Chronic migraineurs (CM) have painful intolerances to somatosensory, visual, olfactory, and auditory stimuli during and between migraine attacks. These intolerances are suggestive of atypical affective responses to potentially noxious stimuli. We hypothesized that atypical resting-state functional connectivity (rs-fc) of affective pain-processing brain regions may associate with these intolerances. This study compared rs-fc of affective pain-processing regions in CM with controls. METHODS: Twelve minutes of resting-state blood oxygenation level-dependent data were collected from 20 interictal adult CM and 20 controls. Rs-fc between 5 affective regions (anterior cingulate cortex, right/left anterior insula, and right/left amygdala) with the rest of the brain was determined. Functional connections consistently differing between CM and controls were identified using summary analyses. Correlations between number of migraine years and the strengths of functional connections that consistently differed between CM and controls were calculated. RESULTS: Functional connections with affective pain regions that differed in CM and controls included regions in anterior insula, amygdala, pulvinar, mediodorsal thalamus, middle temporal cortex, and periaqueductal gray. There were significant correlations between the number of years with CM and functional connectivity strength between the anterior insula with mediodorsal thalamus and anterior insula with periaqueductal gray. CONCLUSION: CM is associated with interictal atypical rs-fc of affective pain regions with pain-facilitating and pain-inhibiting regions that participate in sensory-discriminative, cognitive, and integrative domains of the pain experience. Atypical rs-fc with affective pain regions may relate to aberrant affective pain processing and atypical affective responses to painful stimuli characteristic of CM.

Parcellation in left lateral parietal cortex is similar in adults and children.

A key question in developmental neuroscience involves understanding how and when the cerebral cortex is partitioned into distinct functional areas. The present study used functional connectivity MRI mapping and graph theory to identify putative cortical areas and generate a parcellation scheme of left lateral parietal cortex (LLPC) in 7 to 10-year-old children and adults. Results indicated that a majority of putative LLPC areas could be matched across groups (mean distance between matched areas across age: 3.15 mm). Furthermore, the boundaries of children's putative LLPC areas respected the boundaries generated from the adults' parcellation scheme for a majority of children's areas (13/15). Consistent with prior research, matched LLPC areas showed age-related differences in functional connectivity strength with other brain regions. These results suggest that LLPC cortical parcellation and functional connectivity mature along different developmental trajectories, with adult-like boundaries between LLPC areas established in school-age children prior to adult-like functional connectivity.

Modulation of the brain's functional network architecture in the transition from wake to sleep.

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes.

Prediction of individual brain maturity using fMRI.

Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.