Data-driven MRI analysis reveals fitness-related functional change in default mode network and cognition following an exercise intervention.

Previous research has indicated that cardiorespiratory fitness (CRF) is structurally and functionally neuroprotective in older adults. However, questions remain regarding the mechanistic role of CRF on cognitive and brain health. The purposes of this study were to investigate if higher pre-intervention CRF was associated with greater change in functional brain connectivity during an exercise intervention and to determine if the magnitude of change in connectivity was related to better post-intervention cognitive performance. The sample included low-active older adults (n = 139) who completed a 6-month exercise intervention and underwent neuropsychological testing, functional neuroimaging, and CRF testing before and after the intervention. A data-driven multi-voxel pattern analysis was performed on resting-state MRI scans to determine changes in whole-brain patterns of connectivity from pre- to post-intervention as a function of pre-intervention CRF. Results revealed a positive correlation between pre-intervention CRF and changes in functional connectivity in the precentral gyrus. Using the precentral gyrus as a seed, analyses indicated that CRF-related connectivity changes within the precentral gyrus were derived from increased correlation strength within clusters located in the Dorsal Attention Network (DAN) and increased anti-correlation strength within clusters located in the Default Mode Network (DMN). Exploratory analysis demonstrated that connectivity change between the precentral gyrus seed and DMN clusters were associated with improved post-intervention performance on perceptual speed tasks. These findings suggest that in a sample of low-active and mostly lower-fit older adults, even subtle individual differences in CRF may influence the relationship between functional connectivity and aspects of cognition following a 6-month exercise intervention.

Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production.

A fronto-temporal brain network has long been implicated in language comprehension. However, this network's role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across 3 functional magnetic resonance imaging experiments that rely on robust individual-subject analyses, we characterize the language network's response to high-level production demands. We report 3 novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions-within or outside the language network-that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.

Brain-wide connectome inferences using functional connectivity MultiVariate Pattern Analyses (fc-MVPA).

Current functional Magnetic Resonance Imaging technology is able to resolve billions of individual functional connections characterizing the human connectome. Classical statistical inferential procedures attempting to make valid inferences across this many measures from a reduced set of observations and from a limited number of subjects can be severely underpowered for any but the largest effect sizes. This manuscript discusses fc-MVPA (functional connectivity Multivariate Pattern Analysis), a novel method using multivariate pattern analysis techniques in the context of brain-wide connectome inferences. The theory behind fc-MVPA is presented, and several of its key concepts are illustrated through examples from a publicly available resting state dataset, including an analysis of gender differences across the entire functional connectome. Finally, Monte Carlo simulations are used to demonstrate the validity and sensitivity of this method. In addition to offering powerful whole-brain inferences, fc-MVPA also provides a meaningful characterization of the heterogeneity in functional connectivity across subjects.

Mindfulness training preserves sustained attention and resting state anticorrelation between default-mode network and dorsolateral prefrontal cortex: A randomized controlled trial.

Mindfulness training can enhance cognitive control, but the neural mechanisms underlying such enhancement in children are unknown. Here, we conducted a randomized controlled trial (RCT) with sixth graders (mean age 11.76 years) to examine the impact of 8 weeks of school-based mindfulness training, relative to coding training as an active control, on sustained attention and associated resting-state functional brain connectivity. At baseline, better performance on a sustained-attention task correlated with greater anticorrelation between the default mode network (DMN) and right dorsolateral prefrontal cortex (DLPFC), a key node of the central executive network. Following the interventions, children in the mindfulness group preserved their sustained-attention performance (i.e., fewer lapses of attention) and preserved DMN-DLPFC anticorrelation compared to children in the active control group, who exhibited declines in both sustained attention and DMN-DLPFC anticorrelation. Further, change in sustained-attention performance correlated with change in DMN-DLPFC anticorrelation only within the mindfulness group. These findings provide the first causal link between mindfulness training and both sustained attention and associated neural plasticity. Administered as a part of sixth graders' school schedule, this RCT supports the beneficial effects of school-based mindfulness training on cognitive control.

Anomalous morphology in left hemisphere motor and premotor cortex of children who stutter.

Stuttering is a neurodevelopmental disorder that affects the smooth flow of speech production. Stuttering onset occurs during a dynamic period of development when children first start learning to formulate sentences. Although most children grow out of stuttering naturally, ∼1% of all children develop persistent stuttering that can lead to significant psychosocial consequences throughout one's life. To date, few studies have examined neural bases of stuttering in children who stutter, and even fewer have examined the basis for natural recovery versus persistence of stuttering. Here we report the first study to conduct surface-based analysis of the brain morphometric measures in children who stutter. We used FreeSurfer to extract cortical size and shape measures from structural MRI scans collected from the initial year of a longitudinal study involving 70 children (36 stuttering, 34 controls) in the 3-10-year range. The stuttering group was further divided into two groups: persistent and recovered, based on their later longitudinal visits that allowed determination of their eventual clinical outcome. A region of interest analysis that focused on the left hemisphere speech network and a whole-brain exploratory analysis were conducted to examine group differences and group × age interaction effects. We found that the persistent group could be differentiated from the control and recovered groups by reduced cortical thickness in left motor and lateral premotor cortical regions. The recovered group showed an age-related decrease in local gyrification in the left medial premotor cortex (supplementary motor area and and pre-supplementary motor area). These results provide strong evidence of a primary deficit in the left hemisphere speech network, specifically involving lateral premotor cortex and primary motor cortex, in persistent developmental stuttering. Results further point to a possible compensatory mechanism involving left medial premotor cortex in those who recover from childhood stuttering.

Surface electromyographic control of a novel phonemic interface for speech synthesis.

Many individuals with minimal movement capabilities use AAC to communicate. These individuals require both an interface with which to construct a message (e.g., a grid of letters) and an input modality with which to select targets. This study evaluated the interaction of two such systems: (a) an input modality using surface electromyography (sEMG) of spared facial musculature, and (b) an onscreen interface from which users select phonemic targets. These systems were evaluated in two experiments: (a) participants without motor impairments used the systems during a series of eight training sessions, and (b) one individual who uses AAC used the systems for two sessions. Both the phonemic interface and the electromyographic cursor show promise for future AAC applications.

Evidence for planning and motor subtypes of stuttering based on resting state functional connectivity.

We tested the hypothesis, generated from the Gradient Order Directions Into Velocities of Articulators (GODIVA) model, that adults who stutter (AWS) may comprise subtypes based on differing connectivity within the cortico-basal ganglia planning or motor loop. Resting state functional connectivity from 91 AWS and 79 controls was measured for all GODIVA model connections. Based on a principal components analysis, two connections accounted for most of the connectivity variability in AWS: left thalamus - left posterior inferior frontal sulcus (planning loop component) and left supplementary motor area - left ventral premotor cortex (motor loop component). A k-means clustering algorithm using the two connections revealed three clusters of AWS. Cluster 1 was significantly different from controls in both connections; Cluster 2 was significantly different in only the planning loop; and Cluster 3 was significantly different in only the motor loop. These findings suggest the presence of planning and motor subtypes of stuttering.

Precision fMRI reveals that the language network exhibits adult-like left-hemispheric lateralization by 4 years of age.

Left hemisphere damage in adulthood often leads to linguistic deficits, but many cases of early damage leave linguistic processing preserved, and a functional language system can develop in the right hemisphere. To explain this early apparent equipotentiality of the two hemispheres for language, some have proposed that the language system is bilateral during early development and only becomes left-lateralized with age. We examined language lateralization using functional magnetic resonance imaging with two large pediatric cohorts (total n=273 children ages 4-16; n=107 adults). Strong, adult-level left-hemispheric lateralization (in activation volume and response magnitude) was evident by age 4. Thus, although the right hemisphere can take over language function in some cases of early brain damage, and although some features of the language system do show protracted development (magnitude of language response and strength of inter-regional correlations in the language network), the left-hemisphere bias for language is robustly present by 4 years of age. These results call for alternative accounts of early equipotentiality of the two hemispheres for language.

Functional connectivity MRI quality control procedures in CONN.

Quality control (QC) for functional connectivity magnetic resonance imaging (FC-MRI) is critical to ensure the validity of neuroimaging studies. Noise confounds are common in MRI data and, if not accounted for, may introduce biases in functional measures affecting the validity, replicability, and interpretation of FC-MRI study results. Although FC-MRI analysis rests on the assumption of adequate data processing, QC is underutilized and not systematically reported. Here, we describe a quality control pipeline for the visual and automated evaluation of MRI data implemented as part of the CONN toolbox. We analyzed publicly available resting state MRI data (N = 139 from 7 MRI sites) from the FMRI Open QC Project. Preprocessing steps included realignment, unwarp, normalization, segmentation, outlier identification, and smoothing. Data denoising was performed based on the combination of scrubbing, motion regression, and aCompCor - a principal component characterization of noise from minimally eroded masks of white matter and of cerebrospinal fluid tissues. Participant-level QC procedures included visual inspection of raw-level data and of representative images after each preprocessing step for each run, as well as the computation of automated descriptive QC measures such as average framewise displacement, average global signal change, prevalence of outlier scans, MNI to anatomical and functional overlap, anatomical to functional overlap, residual BOLD timeseries variability, effective degrees of freedom, and global correlation strength. Dataset-level QC procedures included the evaluation of inter-subject variability in the distributions of edge connectivity in a 1,000-node graph (FC distribution displays), and the estimation of residual associations across participants between functional connectivity strength and potential noise indicators such as participant's head motion and prevalence of outlier scans (QC-FC analyses). QC procedures are demonstrated on the reference dataset with an emphasis on visualization, and general recommendations for best practices are discussed in the context of functional connectivity and other fMRI analysis. We hope this work contributes toward the dissemination and standardization of QC testing performance reporting among peers and in scientific journals.

Auditory feedback control in adults who stutter during metronome-paced speech I. Timing Perturbation.

PURPOSE: This study determined whether adults who stutter (AWS) exhibit deficits in responding to an auditory feedback timing perturbation, and whether external timing cues, which increase fluency, attenuate any disruptions due to altered temporal auditory feedback. METHODS: Fifteen AWS and sixteen adults who do not stutter (ANS) read aloud a multisyllabic sentence either with normal pacing or with each syllable paced at the rate of a metronome. On random trials, an auditory feedback timing perturbation was applied, and timing responses were compared between groups and pacing conditions. RESULTS: Both groups responded to the timing perturbation by delaying subsequent syllable boundaries, and there were no significant differences between groups in either pacing condition. Furthermore, no response differences were found between normally paced and metronome-paced conditions. CONCLUSION: These findings are interpreted as showing that 1) AWS respond normally to pure timing perturbations, and 2) metronome-paced speech has no effect on online speech timing control as assessed in the present experiment.

A comparison of structural morphometry in children and adults with persistent developmental stuttering.

This cross-sectional study aimed to differentiate earlier occurring neuroanatomical differences that may reflect core deficits in stuttering versus changes associated with a longer duration of stuttering by analysing structural morphometry in a large sample of children and adults who stutter and age-matched controls. Whole-brain T1-weighted structural scans were obtained from 166 individuals who stutter (74 children, 92 adults; ages 3-58) and 191 controls (92 children, 99 adults; ages 3-53) from eight prior studies in our laboratories. Mean size and gyrification measures were extracted using FreeSurfer software for each cortical region of interest. FreeSurfer software was also used to generate subcortical volumes for regions in the automatic subcortical segmentation. For cortical analyses, separate ANOVA analyses of size (surface area, cortical thickness) and gyrification (local gyrification index) measures were conducted to test for a main effect of diagnosis (stuttering, control) and the interaction of diagnosis-group with age-group (children, adults) across cortical regions. Cortical analyses were first conducted across a set of regions that comprise the speech network and then in a second whole-brain analysis. Next, separate ANOVA analyses of volume were conducted across subcortical regions in each hemisphere. False discovery rate corrections were applied for all analyses. Additionally, we tested for correlations between structural morphometry and stuttering severity. Analyses revealed thinner cortex in children who stutter compared with controls in several key speech-planning regions, with significant correlations between cortical thickness and stuttering severity. These differences in cortical size were not present in adults who stutter, who instead showed reduced gyrification in the right inferior frontal gyrus. Findings suggest that early cortical anomalies in key speech planning regions may be associated with stuttering onset. Persistent stuttering into adulthood may result from network-level dysfunction instead of focal differences in cortical morphometry. Adults who stutter may also have a more heterogeneous neural presentation than children who stutter due to their unique lived experiences.

Improving the study of brain-behavior relationships by revisiting basic assumptions.

Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidence from human brain imaging and the study of non-human animals that calls each foundational assumption into question. We then consider the opportunities for a robust science of brain-behavior relationships that await if scientists ground their research efforts in revised assumptions supported by current empirical evidence.

Do Not Cut Off Your Tail: A Mega-Analysis of Responses to Auditory Perturbation Experiments.

PURPOSE: The practice of removing "following" responses from speech perturbation analyses is increasingly common, despite no clear evidence as to whether these responses represent a unique response type. This study aimed to determine if the distribution of responses to auditory perturbation paradigms represents a bimodal distribution, consisting of two distinct response types, or a unimodal distribution. METHOD: This mega-analysis pooled data from 22 previous studies to examine the distribution and magnitude of responses to auditory perturbations across four tasks: adaptive pitch, adaptive formant, reflexive pitch, and reflexive formant. Data included at least 150 unique participants for each task, with studies comprising younger adult, older adult, and Parkinson's disease populations. A Silverman's unimodality test followed by a smoothed bootstrap resampling technique was performed for each task to evaluate the number of modes in each distribution. Wilcoxon signed-ranks tests were also performed for each distribution to confirm significant compensation in response to the perturbation. RESULTS: Modality analyses were not significant (p > .05) for any group or task, indicating unimodal distributions. Our analyses also confirmed compensatory reflexive responses to pitch and formant perturbations across all groups, as well as adaptive responses to sustained formant perturbations. However, analyses of sustained pitch perturbations only revealed evidence of adaptation in studies with younger adults. CONCLUSION: The demonstration of a clear unimodal distribution across all tasks suggests that following responses do not represent a distinct response pattern, but rather the tail of a unimodal distribution. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24282676.

Subject-specific functional localizers increase sensitivity and functional resolution of multi-subject analyses.

One important goal of cognitive neuroscience is to discover and explain properties common to all human brains. The traditional solution for comparing functional activations across brains in fMRI is to align each individual brain to a template brain in a Cartesian coordinate system (e.g., the Montreal Neurological Institute template). However, inter-individual anatomical variability leads to decreases in sensitivity (ability to detect a significant activation when it is present) and functional resolution (ability to discriminate spatially adjacent but functionally different neural responses) in group analyses. Subject-specific functional localizers have been previously argued to increase the sensitivity and functional resolution of fMRI analyses in the presence of inter-subject variability in the locations of functional activations (e.g., Brett et al., 2002; Fedorenko and Kanwisher, 2009, 2011; Fedorenko et al., 2010; Kanwisher et al., 1997; Saxe et al., 2006). In the current paper we quantify this dependence of sensitivity and functional resolution on functional variability across subjects in order to illustrate the highly detrimental effects of this variability on traditional group analyses. We show that analyses that use subject-specific functional localizers usually outperform traditional group-based methods in both sensitivity and functional resolution, even when the same total amount of data is used for each analysis. We further discuss how the subject-specific functional localization approach, which has traditionally only been considered in the context of ROI-based analyses, can be extended to whole-brain voxel-based analyses. We conclude that subject-specific functional localizers are particularly well suited for investigating questions of functional specialization in the brain. An SPM toolbox that can perform all of the analyses described in this paper is publicly available, and the analyses can be applied retroactively to any dataset, provided that multiple runs were acquired per subject, even if no explicit "localizer" task was included.

Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia.

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness.

Auditory feedback control in adults who stutter during metronome-paced speech II. Formant Perturbation.

PURPOSE: Prior work has shown that Adults who stutter (AWS) have reduced and delayed responses to auditory feedback perturbations. This study aimed to determine whether external timing cues, which increase fluency, resolve auditory feedback processing disruptions. METHODS: Fifteen AWS and sixteen adults who do not stutter (ANS) read aloud a multisyllabic sentence either with natural stress and timing or with each syllable paced at the rate of a metronome. On random trials, an auditory feedback formant perturbation was applied, and formant responses were compared between groups and pacing conditions. RESULTS: During normally paced speech, ANS showed a significant compensatory response to the perturbation by the end of the perturbed vowel, while AWS did not. In the metronome-paced condition, which significantly reduced the disfluency rate, the opposite was true: AWS showed a significant response by the end of the vowel, while ANS did not. CONCLUSION: These findings indicate a potential link between the reduction in stuttering found during metronome-paced speech and changes in auditory motor integration in AWS.

Quantitatively characterizing reflexive responses to pitch perturbations.

Background: Reflexive pitch perturbation experiments are commonly used to investigate the neural mechanisms underlying vocal motor control. In these experiments, the fundamental frequency-the acoustic correlate of pitch-of a speech signal is shifted unexpectedly and played back to the speaker via headphones in near real-time. In response to the shift, speakers increase or decrease their fundamental frequency in the direction opposing the shift so that their perceived pitch is closer to what they intended. The goal of the current work is to develop a quantitative model of responses to reflexive perturbations that can be interpreted in terms of the physiological mechanisms underlying the response and that captures both group-mean data and individual subject responses. Methods: A model framework was established that allowed the specification of several models based on Proportional-Integral-Derivative and State-Space/Directions Into Velocities of Articulators (DIVA) model classes. The performance of 19 models was compared in fitting experimental data from two published studies. The models were evaluated in terms of their ability to capture both population-level responses and individual differences in sensorimotor control processes. Results: A three-parameter DIVA model performed best when fitting group-mean data from both studies; this model is equivalent to a single-rate state-space model and a first-order low pass filter model. The same model also provided stable estimates of parameters across samples from individual subject data and performed among the best models to differentiate between subjects. The three parameters correspond to gains in the auditory feedback controller's response to a perceived error, the delay of this response, and the gain of the somatosensory feedback controller's "resistance" to this correction. Excellent fits were also obtained from a four-parameter model with an additional auditory velocity error term; this model was better able to capture multi-component reflexive responses seen in some individual subjects. Conclusion: Our results demonstrate the stereotyped nature of an individual's responses to pitch perturbations. Further, we identified a model that captures population responses to pitch perturbations and characterizes individual differences in a stable manner with parameters that relate to underlying motor control capabilities. Future work will evaluate the model in characterizing responses from individuals with communication disorders.

Increased Intra-Subject Variability of Neural Activity During Speech Production in People with Autism Spectrum Disorder.

Background: Communication difficulties are a core deficit in many people with autism spectrum disorder (ASD). The current study evaluated neural activation in participants with ASD and neurotypical (NT) controls during a speech production task. Methods: Neural activities of participants with ASD (N = 15, M = 16.7 years, language abilities ranged from low verbal abilities to verbally fluent) and NT controls (N = 12, M = 17.1 years) was examined using functional magnetic resonance imaging with a sparse-sampling paradigm. Results: There were no differences between the ASD and NT groups in average speech activation or inter-subject run-to-run variability in speech activation. Intra-subject run-to-run neural variability was greater in the ASD group and was positively correlated with autism severity in cortical areas associated with speech. Conclusions: These findings highlight the importance of understanding intra-subject neural variability in participants with ASD.

Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior.

Sedentary behaviors are increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths worldwide. Understanding the mechanistic predictors of sedentary behaviors will improve future intervention development and precision medicine approaches. It has been posited that humans have an innate attraction towards effort minimization and that inhibitory control is required to overcome this prepotent disposition. Consequently, we hypothesized that individual differences in the functional connectivity of brain regions implicated in inhibitory control and physical effort decision making at the beginning of an exercise intervention in older adults would predict the change in time spent sedentary over the course of that intervention. In 143 healthy, low-active older adults participating in a 6-month aerobic exercise intervention (with three conditions: walking, dance, stretching), we aimed to use baseline neuroimaging (resting state functional connectivity of two a priori defined seed regions), and baseline accelerometer measures of time spent sedentary to predict future pre-post changes in objectively measured time spent sedentary in daily life over the 6-month intervention. Our results demonstrated that functional connectivity between (1) the anterior cingulate cortex and the supplementary motor area and (2) the right anterior insula and the left temporoparietal/temporooccipital junction, predicted changes in time spent sedentary in the walking group. Functional connectivity of these brain regions did not predict changes in time spent sedentary in the dance nor stretch and tone conditions, but baseline time spent sedentary was predictive in these conditions. Our results add important knowledge toward understanding mechanistic associations underlying complex out-of-session sedentary behaviors within a walking intervention setting in older adults.

Probabilistic atlas for the language network based on precision fMRI data from >800 individuals.

Two analytic traditions characterize fMRI language research. One relies on averaging activations across individuals. This approach has limitations: because of inter-individual variability in the locations of language areas, any given voxel/vertex in a common brain space is part of the language network in some individuals but in others, may belong to a distinct network. An alternative approach relies on identifying language areas in each individual using a functional 'localizer'. Because of its greater sensitivity, functional resolution, and interpretability, functional localization is gaining popularity, but it is not always feasible, and cannot be applied retroactively to past studies. To bridge these disjoint approaches, we created a probabilistic functional atlas using fMRI data for an extensively validated language localizer in 806 individuals. This atlas enables estimating the probability that any given location in a common space belongs to the language network, and thus can help interpret group-level activation peaks and lesion locations, or select voxels/electrodes for analysis. More meaningful comparisons of findings across studies should increase robustness and replicability in language research.