The ASA's statement on p-values: context, process, and purpose

Good summary and interesting background on the ASA's statement on p-values.

Let’s be clear. Nothing in the ASA statement is new. Statisticians and others have been sounding the alarm about these matters for decades, to little avail. We hoped that a statement from the world’s largest professional association of statisticians would open a fresh discussion and draw renewed and vigorous attention to changing the practice of science with regards to the use of statistical inference.

Task-free MRI predicts individual differences in brain activity during task performance

Nice use of resting state and HCP data.

When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.


Factors affecting characterization and localization of interindividual differences in functional connectivity using MRI

Much recent attention has been paid to quantifying anatomic and functional neuroimaging on the individual subject level. For optimal individual subject characterization, specific acquisition and analysis features need to be identified that maximize interindividual variability while concomitantly minimizing intra-subject variability. We delineate the effect of various acquisition parameters (length of acquisition, sampling frequency) and analysis methods (time course extraction, region of interest parcellation, and thresholding of connectivity-derived network graphs) on characterizing individual subject differentiation. We utilize a non-parametric statistical metric that quantifies the degree to which a parameter set allows this individual subject differentiation by both maximizing interindividual variance and minimizing intra-individual variance. We apply this metric to analysis of four publicly available test-retest resting-state fMRI (rs-fMRI) data sets. We find that for the question of maximizing individual differentiation, (i) for increasing sampling, there is a relative tradeoff between increased sampling frequency and increased acquisition time; (ii) for the sizes of the interrogated data sets, only 3-4 min of acquisition time was sufficient to maximally differentiate each subject with an algorithm that utilized no a priori information regarding subject identification; and (iii) brain regions that most contribute to this individual subject characterization lie in the default mode, attention, and executive control networks. These findings may guide optimal rs-fMRI experiment design and may elucidate the neural bases for subject-to-subject differences


Exploring the Early Organization and Maturation of Linguistic Pathways in the Human Infant Brain

Linguistic processing is based on a close collaboration between temporal and frontal regions connected by two pathways: the “dorsal” and “ventral pathways” (assumed to support phonological and semantic processing, respectively, in adults). We investigated here the development of these pathways at the onset of language acquisition, during the first post-natal weeks, using cross-sectional diffusion imaging in 21 healthy infants (6–22 weeks of age) and 17 young adults. We compared the bundle organization and microstructure at these two ages using tractography and original clustering analyses of diffusion tensor imaging parameters. We observed structural similarities between both groups, especially concerning the dorsal/ventral pathway segregation and the arcuate fasciculus asymmetry. We further highlighted the developmental tempos of the linguistic bundles: The ventral pathway maturation was more advanced than the dorsal pathway maturation, but the latter catches up during the first post-natal months. Its fast development during this period might relate to the learning of speech cross-modal representations and to the first combinatorial analyses of the speech input.

Overview of molecular fMRI

Comprehensive analysis of brain function depends on understanding the dynamics of diverse neural signaling processes over large tissue volumes in intact animals and humans. Most existing approaches to measuring brain signaling suffer from limited tissue penetration, poor resolution, or lack of specificity for well-defined neural events. Here we discuss a new brain activity mapping method that overcomes some of these problems by combining MRI with contrast agents sensitive to neural signaling. The goal of this “molecular fMRI” approach is to permit noninvasive whole-brain neuroimaging with specificity and resolution approaching current optical neuroimaging methods. In this article, we describe the context and need for molecular fMRI as well as the state of the technology today. We explain how major types of MRI probes work and how they can be sensitized to neurobiological processes, such as neurotransmitter release, calcium signaling, and gene expression changes. We comment both on past work in the field and on challenges and promising avenues for future development.


White-matter diffusion fMRI of mouse optic nerve

Non-invasive assessment of white-matter functionality in the nervous system would be a valuable basic neuroscience and clinical diagnostic tool. Using standard MRI techniques, a visual-stimulus-induced 27% decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC⊥) is demonstrated for C57BL/6 mouse optic nerve in vivo. No change in ADC|| (diffusion parallel to the optic nerve fibers) was observed during visual stimulation. The stimulus-induced changes are completely reversible. A possible vascular contribution was sought by carrying out the ADC⊥ measurements in hypercapnic mice with and without visual stimulus. Similar effects were seen in room-air-breathing and hypercapnic animals. The in vivo stimulus-induced ADC⊥ decreases are roughly similar to literature reports for ex vivo rat optic nerve preparations under conditions of osmotic swelling. The experimental results strongly suggest that osmotic after-effects of nerve impulses through the axonal fibers are responsible for the observed ADC decrease.


Provoking relationship between pupil diameter and global hemodynamic signal in mice

Imaging techniques such as fMRI seek to estimate neural signals in local brain regions through measurements of hemodynamic activity. However, hemodynamic activity is accompanied by large vascular fluctuations of unclear significance. To characterize these fluctuations and their impact on estimates of neural signals, we used optical imaging in visual cortex of awake mice. We found that hemodynamic activity can be expressed as the sum of two components, one local and one global. The local component reflected presumed neural signals driven by visual stimuli in the appropriate retinotopic region. The global component constituted large fluctuations shared by larger cortical regions, which extend beyond visual cortex. These fluctuations varied from trial to trial, but they did not constitute noise: they correlated with pupil diameter, suggesting that they reflect variations in arousal or alertness. Distinguishing local and global contributions to hemodynamic activity may help understand neurovascular coupling and interpret measurements of hemodynamic responses.

Trade-off between angular and spatial resolutions in in vivo fiber tractography

Tractography is becoming an increasingly popular method to reconstruct white matter connections in vivo. The diffusion MRI data that tractography is based on requires a high angular resolution to resolve crossing fibers whereas high spatial resolution is required to distinguish kissing from crossing fibers. However, scan time increases with increasing spatial and angular resolutions, which can become infeasible in clinical settings. Here we investigated the trade-off between spatial and angular resolutions to determine which of these factors is most worth investing scan time in. We created a unique diffusion MRI dataset with 1.0 mm isotropic resolution and a high angular resolution (100 directions) using an advanced 3D diffusion-weighted multi-slab EPI acquisition. This dataset was reconstructed to create subsets of lower angular (75, 50, and 25 directions) and lower spatial (1.5, 2.0, and 2.5 mm) resolution. Using all subsets, we investigated the effects of angular and spatial resolutions in three fiber bundles—the corticospinal tract, arcuate fasciculus and corpus callosum—by analyzing the volumetric bundle overlap and anatomical correspondence between tracts. Our results indicate that the subsets of 25 and 50 directions provided inferior tract reconstructions compared with the datasets with 75 and 100 directions. Datasets with spatial resolutions of 1.0, 1.5, and 2.0 mm were comparable, while the lowest resolution (2.5 mm) datasets had discernible inferior quality. In conclusion, we found that angular resolution appeared to be more influential than spatial resolution in improving tractography results. Spatial resolutions higher than 2.0 mm only appear to benefit multi-fiber tractography methods if this is not at the cost of decreased angular resolution.


Measurement of oxygen extraction fraction (OEF): A model for use with hypercapnic and hyperoxic calibration

Several techniques have been proposed to estimate relative changes in cerebral metabolic rate of oxygen consumption (CMRO2) by exploiting combined BOLD fMRI and cerebral blood flow data in conjunction with hypercapnic or hyperoxic respiratory challenges. More recently, methods based on respiratory challenges that include both hypercapnia and hyperoxia have been developed to assess absolute CMRO2, an important parameter for understanding brain energetics. In this paper, we empirically optimize a previously presented “original calibration model” relating BOLD and blood flow signals specifically for the estimation of oxygen extraction fraction (OEF) and absolute CMRO2.

To do so, we have created a set of synthetic BOLD signals using a detailed BOLD signal model to reproduce experiments incorporating hypercapnic and hyperoxic respiratory challenges at 3 T. A wide range of physiological conditions was simulated by varying input parameter values (baseline cerebral blood volume (CBV0), baseline cerebral blood flow (CBF0), baseline oxygen extraction fraction (OEF0) and hematocrit (Hct)).

From the optimization of the calibration model for estimation of OEF and practical considerations of hypercapnic and hyperoxic respiratory challenges, a new “simplified calibration model” is established which reduces the complexity of the original calibration model by substituting the standard parameters α and β with a single parameter θ. The optimal value of θ is determined (θ = 0.06) across a range of experimental respiratory challenges. The simplified calibration model gives estimates of OEF0 and absolute CMRO2 closer to the true values used to simulate the experimental data compared to those estimated using the original model incorporating literature values of α and β. Finally, an error propagation analysis demonstrates the susceptibility of the original and simplified calibration models to measurement errors and potential violations in the underlying assumptions of isometabolism. We conclude that using the simplified calibration model results in a reduced bias in OEF0 estimates across a wide range of potential respiratory challenge experimental designs.


A perceived social partner alters the neural processing of speech

Mounting evidence suggests that social interaction changes how communicative behaviors (e.g., spoken language, gaze) are processed, but the precise neural bases by which social-interactive context may alter communication remain unknown. Various perspectives suggest that live interactions are more rewarding, more attention-grabbing, or require increased mentalizing—thinking about the thoughts of others. Dissociating between these possibilities is difficult because most extant neuroimaging paradigms examining social interaction have not directly compared live paradigms to conventional “offline” (or recorded) paradigms. We developed a novel fMRI paradigm to assess whether and how an interactive context changes the processing of speech matched in content and vocal characteristics. Participants listened to short vignettes—which contained no reference to people or mental states—believing that some vignettes were prerecorded and that others were presented over a real-time audio-feed by a live social partner. In actuality, all speech was prerecorded. Simply believing that speech was live increased activation in each participant’s own mentalizing regions, defined using a functional localizer. Contrasting live to recorded speech did not reveal significant differences in attention or reward regions. Further, higher levels of autistic-like traits were associated with altered neural specialization for live interaction. These results suggest that humans engage in ongoing mentalizing about social partners, even when such mentalizing is not explicitly required, illustrating how social context shapes social cognition. Understanding communication in social context has important implications for typical and atypical social processing, especially for disorders like autism where social difficulties are more acute in live interaction.


Transcranial magnetic stimulation (TMS) inhibits cortical dendrites | eLife

Nice rat study on the effects of TMS.

One of the leading approaches to non-invasively treat a variety of brain disorders is transcranial magnetic stimulation (TMS). However, despite its clinical prevalence, very little is known about the action of TMS at the cellular level let alone what effect it might have at the subcellular level (e.g. dendrites). Here, we examine the effect of single-pulse TMS on dendritic activity in layer 5 pyramidal neurons of the somatosensory cortex using an optical fiber imaging approach. We find that TMS causes GABAB-mediated inhibition of sensory-evoked dendritic Ca2+ activity. We conclude that TMS directly activates fibers within the upper cortical layers that leads to the activation of dendrite-targeting inhibitory neurons which in turn suppress dendritic Ca2+ activity. This result implies a specificity of TMS at the dendritic level that could in principle be exploited for investigating these structures non-invasively.

New tissue priors for improved classification of subcortical brain structures on MRI

Despite the constant improvement of algorithms for automated brain tissue classification, the accurate delineation of subcortical structures using magnetic resonance images (MRI) data remains challenging. The main difficulties arise from the low gray-white matter contrast of iron rich areas in T1-weighted (T1w) MRI data and from the lack of adequate priors for basal ganglia and thalamus. The most recent attempts to obtain such priors were based on cohorts with limited size that included subjects in a narrow age range, failing to account for age-related gray-white matter contrast changes. Aiming to improve the anatomical plausibility of automated brain tissue classification from T1w data, we have created new tissue probability maps for subcortical gray matter regions. Supported by atlas-derived spatial information, raters manually labeled subcortical structures in a cohort of healthy subjects using magnetization transfer saturation and R2* MRI maps, which feature optimal gray-white matter contrast in these areas. After assessment of inter-rater variability, the new tissue priors were tested on T1w data within the framework of voxel-based morphometry. The automated detection of gray matter in subcortical areas with our new probability maps was more anatomically plausible compared to the one derived with currently available priors. We provide evidence that the improved delineation compensates age-related bias in the segmentation of iron rich subcortical regions. The new tissue priors, allowing robust detection of basal ganglia and thalamus, have the potential to enhance the sensitivity of voxel-based morphometry in both healthy and diseased brains.


Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI

While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among “good quality” structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects' tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion—even at levels which do not manifest in visible motion artifact—can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans.

Locus Coeruleus: From Global Projection System to Adaptive Regulation of Behavior

The brainstem nucleus locus coeruleus (LC) is a major source of norepinephrine (NE) projections throughout the CNS. This important property was masked in very early studies by the inability to visualize endogenous monoamines. The development of monoamine histofluorescence methods by Swedish scientists led to a plethora of studies, including a paper published in Brain Research by Loizou in 1969. That paper was highly cited (making it a focal point for the 50th anniversary issue of this journal), and helped to spark a large and continuing set of investigations to further refine our understating of the LC-NE system and its contribution to brain function and behavior. This paper very briefly reviews the ensuing advances in anatomical, physiological and behavioral aspects of the LC-NE system. Although its projections are ubiquitously present throughout the CNS, recent studies find surprising specificity within the organizational and operational domains of LC neurons. These and other findings lead us to expect that future work will unmask additional features of the LC-NE system and its roles in normative and pathological brain and behavioral processes.


Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography

While histological studies and conventional magnetic resonance imaging (MRI) investigations have elucidated the trajectory of structural changes in the developing brain, less is known regarding early functional cerebral development. Recent investigations have demonstrated that resting-state functional connectivity MRI (fcMRI) can identify networks of functional cerebral connections in infants. However, technical and logistical challenges frequently limit the ability to perform MRI scans early or repeatedly in neonates, particularly in those at greatest risk for adverse neurodevelopmental outcomes. High-density diffuse optical tomography (HD-DOT), a portable imaging modality, potentially enables early continuous and quantitative monitoring of brain function in infants. We introduce an HD-DOT imaging system that combines advancements in cap design, ergonomics, and data analysis methods to allow bedside mapping of functional brain development in infants. In a cohort of healthy, full-term neonates scanned within the first days of life, HD-DOT results demonstrate strong congruence with those obtained using co-registered, subject-matched fcMRI and reflect patterns of typical brain development. These findings represent a transformative advance in functional neuroimaging in infants, and introduce HD-DOT as a powerful and practical method for quantitative mapping of early functional brain development in normal and high-risk neonates.