Search

Background: Therapeutic administration of psychedelic drugs has shown significant potential in historical accounts and in recent clinical trials in the treatment of depression and other mood disorders. A recent randomized double-blind phase-IIb study demonstrated the safety and efficacy of COMP360, COMPASS Pathways’ proprietary synthetic formulation of psilocybin, in participants with treatment resistant depression. While promising, the treatment works for a portion of the population and early prediction of outcome is a key objective.Methods: Transcripts were made from audio recordings of the psychological support session between participant and therapist one day post COMP360 administration. A zero-shot machine learning classifier based on the BART large language model was used to compute two-dimensional sentiment (valence and arousal) for the participant and therapist from the transcript. These scores, combined with the Emotional Breakthrough Index (EBI) and treatment arm were used to predict treatment outcome as measured by MADRS scores. Code and data are available at https://github.com/compasspathways/Sentiment2DResults: Two multinomial logistic regression models were fit to predict responder status at week 3 and through week 12. Cross-validation of these models resulted in 85% and 88% accuracy and AUC values of 88% and 85%.Conclusions: A machine learning algorithm using NLP and EBI accurately predicts long term patient response, allowing rapid prognostication of personalized response to psilocybin treatment and insight into therapeutic model optimization. Further research is required to understand if language data from earlier stages in the therapeutic process hold similar predictive power.

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, post-concussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/treatment interventions. Progress in overcoming these limitations has been challenging, because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large scale (n = 5,000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for one year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.

Importance Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings. Objectives To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended. Design, setting, and participants This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020. Main outcomes and measures Percentage of children with IFs in each category and prevalence of specific IFs. Results A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387). Conclusions and relevance Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.

Background Recent advancements in simultaneous multi-slice (SMS) imaging techniques have enabled whole-brain resting-state fMRI (rs-fMRI) scanning at sub-second temporal resolution, providing spectral ranges much wider than the typically used range of 0.01–0.1 Hz. However, the advantages of this accelerated acquisition for rs-fMRI have not been evaluated. New method In this study, we used SMS Echo Planar Imaging (EPI) to probe whole-brain functional connectivity with a short repetition time (TR = 350 ms) and compared it with standard EPI with a longer TR of 2000 ms. We determined the effect of scan length and investigated the temporal filtration strategies that optimize results based on metrics of signal-noise separation and test-retest reliability using both seed-based and independent component analysis (ICA). Results We found that use of either the entire frequency range of 0.01–1.4 Hz or the entire frequency range with the exclusion of typical cardiac and respiratory frequency values tended to provide the best functional connectivity maps. Comparison with existing methods We found that the SMS-acquired rs-fMRI scans had improved the signal-noise separation, while preserving the same level of test-retest reliability compared to conventional EPI, and enabled the detection of reliable functional connectivity networks with scan times as short as 3 min. Conclusions Our findings suggest that whole-brain rs-fMRI studies may benefit from the increased temporal resolution enabled by the SMS-EPI acquisition, leading to drastic scan time reductions, which in turn should enable the more widespread use of rs-fMRI in clinical research protocols.

Previous studies attempting to quantify white matter (WM) microstructure in individuals with fragile X syndrome (FXS) have produced inconsistent findings, most likely due to the various control groups employed, differing analysis methods, and failure to examine for potential motion artifact. In addition, analyses have heretofore lacked sufficient specificity to provide regional information. In this study, we used Automated Fiber-tract Quantification (AFQ) to identify specific regions of aberrant WM microstructure along WM tracts in patients with FXS that differed from controls who were matched on age, IQ and degree of autistic symptoms. Participants were 20 patients with FXS, aged 10 to 23 years, and 20 matched controls. Using Automated Fiber-tract Quantification (AFQ), we created Tract Profiles of fractional anisotropy and mean diffusivity along 18 major WM fascicles. We found that fractional anisotropy was significantly increased in the left and right inferior longitudinal fasciculus (ILF), right uncinate fasciculus, and left cingulum hippocampus in individuals with FXS compared to controls. Conversely, mean diffusivity was significantly decreased in the right ILF in patients with FXS compared to controls. Age was significantly negatively associated with MD values across both groups in 11 tracts. Taken together, these findings indicate that FXS results in abnormal WM microstructure in specific regions of the ILF and uncinate fasciculus, most likely caused by inefficient synaptic pruning as a result of decreased or absent Fragile X Mental Retardation Protein (FMRP). Longitudinal studies are needed to confirm these findings., Highlights • We quantified regions of aberrant WM microstructure in patients with fragile X syndrome. • FXS patients were compared to controls matched on age and symptom characteristics. • Fractional anisotropy was increased in sections of the right uncinate in patients with FXS. • Mean diffusivity was significantly decreased in sections of the right ILF in patients with FXS. • FXS results in abnormal WM microstructure in specific regions of the ILF and uncinate fasciculus.

Here, we describe a quantitative neuroimaging method to estimate the macromolecular tissue volume (MTV), a fundamental measure of brain anatomy. By making measurements over a range of field strengths and scan parameters, we tested the key assumptions and the robustness of the method. The measurements confirm that a consistent quantitative estimate of MTV can be obtained across a range of scanners. MTV estimates are sufficiently precise to enable a comparison between data obtained from an individual subject with control population data. We describe two applications. First, we show that MTV estimates can be combined with T1 and diffusion measurements to augment our understanding of the tissue properties. Second, we show that MTV provides a sensitive measure of disease status in individual patients with multiple sclerosis. The MTV maps are obtained using short clinically appropriate scans that can reveal how tissue changes influence behavior and cognition.

Frontostriatal circuits have been implicated in reward learning, and emerging findings suggest that frontal white matter structural integrity and probabilistic reward learning are reduced in older age. This cross-sectional study examined whether age differences in frontostriatal white matter integrity could account for age differences in reward learning in a community life span sample of human adults. By combining diffusion tensor imaging with a probabilistic reward learning task, we found that older age was associated with decreased reward learning and decreased white matter integrity in specific pathways running from the thalamus to the medial prefrontal cortex and from the medial prefrontal cortex to the ventral striatum. Further, white matter integrity in these thalamocorticostriatal paths could statistically account for age differences in learning. These findings suggest that the integrity of frontostriatal white matter pathways critically supports reward learning. The findings also raise the possibility that interventions that bolster frontostriatal integrity might improve reward learning and decision making.

SummaryA century of neurology and neuroscience shows that seeing words depends on ventral occipital-temporal (VOT) circuitry. Typically, reading is learned using high-contrast line-contour words. We explored whether a specific VOT region, the visual word form area (VWFA), learns to see only these words or recognizes words independent of the specific shape-defining visual features. Word forms were created using atypical features (motion-dots, luminance-dots) whose statistical properties control word-visibility. We measured fMRI responses as word form visibility varied, and we used TMS to interfere with neural processing in specific cortical circuits, while subjects performed a lexical decision task. For all features, VWFA responses increased with word-visibility and correlated with performance. TMS applied to motion-specialized area hMT+ disrupted reading performance for motion-dots, but not line-contours or luminance-dots. A quantitative model describes feature-convergence in the VWFA and relates VWFA responses to behavioral performance. These findings suggest how visual feature-tolerance in the reading network arises through signal convergence from feature-specialized cortical areas.

Diffusion tensor imaging (DTI) data differ from most medical images in that values at each voxel are not scalars, but 3 × 3 symmetric positive definite matrices called diffusion tensors (DTs). The anatomic characteristics of the tissue at each voxel are reflected by the DT eigenvalues and eigenvectors. In this article we consider the problem of testing whether the means of two groups of DT images are equal at each voxel in terms of the DT’s eigenvalues, eigenvectors, or both. Because eigendecompositions are highly nonlinear, existing likelihood ratio statistics (LRTs) for testing differences in eigenvalues or eigenvectors of means of Gaussian symmetric matrices assume an orthogonally invariant covariance structure between the matrix entries. While retaining the form of the LRTs, we derive new approximations to their true distributions when the covariance between the DT entries is arbitrary and possibly different between the two groups. The approximate distributions are those of similar LRT statistics computed on the tangent space to the parameter manifold at the true value of the parameter, but plugging in an estimate for the point of application of the tangent space. The resulting distributions, which are weighted sums of chi-squared distributions, are further approximated by scaled chi-squared distributions by matching the first two moments. For validity of the Gaussian model, the positive definite constraints on the DT are removed via a matrix log transformation, although this is not crucial asymptotically. Voxelwise application of the test statistics leads to a multiple-testing problem, which is solved by false discovery rate inference. The foregoing methods are illustrated in a DTI group comparison of boys versus girls.

Resting-state functional connectivity magnetic resonance imaging (fcMRI) studies constitute a growing proportion of functional brain imaging publications. This approach detects temporal correlations in spontaneous blood oxygen level-dependent (BOLD) signal oscillations while subjects rest quietly in the scanner. Although distinct resting-state networks related to vision, language, executive processing, and other sensory and cognitive domains have been identified, considerable skepticism remains as to whether resting-state functional connectivity maps reflect neural connectivity or simply track BOLD signal correlations driven by nonneural artifact. Here we combine diffusion tensor imaging (DTI) tractography with resting-state fcMRI to test the hypothesis that resting-state functional connectivity reflects structural connectivity. These 2 modalities were used to investigate connectivity within the default mode network, a set of brain regions--including medial prefrontal cortex (MPFC), medial temporal lobes (MTLs), and posterior cingulate cortex (PCC)/retropslenial cortex (RSC)--implicated in episodic memory processing. Using seed regions from the functional connectivity maps, the DTI analysis revealed robust structural connections between the MTLs and the retrosplenial cortex whereas tracts from the MPFC contacted the PCC (just rostral to the RSC). The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks.

The development of skilled reading requires efficient communication between distributed brain regions. By using diffusion tensor imaging, we assessed the interhemispheric connections in a group of children with a wide range of reading abilities. We segmented the callosal fibers into regions based on their likely cortical projection zones, and we measured diffusion properties in these segmented regions. Phonological awareness (a key factor in reading acquisition) was positively correlated with diffusivity perpendicular to the main axis of the callosal fibers that connect the temporal lobes. These results could be explained by several physiological properties. For example, good readers may have fewer but larger axons connecting left and right temporal lobes, or their axon membranes in these regions may be more permeable than the membranes of poor readers. These measurements are consistent with previous work suggesting that good readers have reduced interhemispheric connectivity and are better at processing rapidly changing visual and auditory stimuli.

Skilled reading requires mapping of visual text to sound and meaning. Because reading relies on neural systems spread across the brain, a full understanding of this cognitive ability involves the identification of pathways that communicate information between these processing regions. In the past few years, diffusion tensor imaging has been used to identify correlations between white matter properties and reading skills in adults and children. White matter differences have been found in left temporo-parietal areas and in posterior callosal tracts. We review these findings and relate them to possible pathways that are important for various aspects of reading. We describe how the results from diffusion tensor imaging can be integrated with functional results in good and poor readers.

Purpose. Many behavioral studies have found impaired perception of dynamic visual stimuli in dyslexia and several neuroimaging studies have found reduced activation of the human motion area MT in dyslexia. These results are often interpreted as a magnocellular (MC) deficit in dyslexia. It has also been claimed that colored filters can help dyslexics to read. One defining feature of the MC-pathway is a greater weight for L-cone input than M-cone input, and at most very weak S-cone input. We measured the subjective speed matches between L-, M-, and S-cone isolating stimuli in good and poor readers. Methods. Subjects performed a speed-matching task with drifting cone-isolating stimuli to find the point of subjective equality between two drifting patterns. Such a task is known to activate cortical area MT, presumably via the MC-pathway. Results. L- to M-cone speed-match ratios were negatively correlated with single-word (r 0.46) and irregular-word reading (r 0.56) but not with non-word reading. Conclusions. Results suggest that relative L-cone sensitivity within the MC-pathway may limit orthographic reading performance. (Optom Vis Sci 2007;84:229–236)

Individuals with Autism Spectrum Disorder (ASD) have social and communication deficits and difficulties regulating emotions. The brain bases of these socio-affective deficits are not yet clear, but one candidate is structural connectivity in the left uncinate fasciculus, which connects limbic temporal and frontal areas thought to be involved in socio-affective processing. In this study, we assessed white matter structure in the left and right uncinate fasciculus in 18 high-functioning individuals with ASD and 18 group-matched typically developing (TD) controls using Diffusion Tensor Imaging. To test specificity of the associations, we also examined the association between both uncinate fasciculi and restricted and repetitive behaviors. Compared to TD individuals, individuals with ASD had significantly lower fractional anisotropy (FA) in the left and right uncinate. Group status significantly moderated the association between left uncinate and socio-affective deficits, indicating that within the ASD group, FA was associated with socio-affective deficits: Individuals with ASD with lower FA in the left uncinate had significantly more social and emotion regulation deficits. There was no association with restricted and repetitive behaviors. This study provides evidence that the left uncinate may play a critical role in socio-affective skills in individuals with ASD.

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders., Large-scale, multimodal phenotypic characterisation is a valuable tool to explore brain function. Poldrack et al. collect and relate MRI, psychological, physiological, metabolic and gene expression data from a single human over an 18 month period, providing a rich resource for future studies.

[This corrects the article DOI: 10.1186/s13229-015-0005-4.].

The extent of motion processing deficits and M/dorsal pathway involvement in amblyopia is unclear. Fellow eye performance was assessed in amblyopic children for motion-defined (MD) form, global motion, and maximum displacement (Dmax) tasks. Group performance on MD form was significantly worse in amblyopic children than in control children. Global motion deficits were significantly related to residual binocular function. Abnormally elevated Dmax thresholds were most prevalent in children with anisometropia. Our findings from these three uncorrelated tasks implicate involvement of binocular motion-sensitive mechanisms in the neural deficits of amblyopic children with strabismic, anisometropic, and aniso-strabismic etiologies.

Diffusion tensor imaging (DTI) and fiber tracking (FT) were used to measure the occipital lobe fiber tracts connecting the two hemispheres in individual human subjects. These tracts are important for normal vision. Also, damage to portions of these tracts is associated with alexia. To assess the reliability of the DTI-FT measurements, occipital-callosal projections were estimated from each subject's left and right hemispheres independently. The left and right estimates converged onto the same positions within the splenium. We further characterized the properties of the estimated occipital-callosal fiber tracts by combining them with functional MRI. We used functional MRI to identify visual field maps in cortex and labeled fibers by the cortical functional response at the fiber endpoint. This labeling reveals a regular organization of the fibers within the splenium. The dorsal visual maps (dorsal V3, V3A, V3B, V7) send projections through a large band in the middle of the splenium, whereas ventral visual maps (ventral V3, V4) send projections through the inferior-anterior corner of the splenium. The agreement between the independent left/right estimates, further supported by previous descriptions of homologous tracts in macaque, validates the DTI-FT methods. However, a principal limitation of these methods is low sensitivity: a large number of fiber tracts that connect homotopic regions of ventral and lateral visual cortex were undetected. We conclude that most of the estimated tracts are real and can be localized with a precision of 1-2 mm, but many tracts are missed because of data and algorithm limitations.

We describe the location and general properties of nine human visual field maps. The cortical location of each map, as well as many examples of the eccentricity and angular representations within these maps, are shown in a series of images that summarize a large set of functional MRI data. The organization and properties of these maps are compared and contrasted with descriptions by other investigators. We hypothesize that the human visual field maps are arranged in several clusters, each comprising a group of maps that share a common foveal representation and semicircular eccentricity map. The spatial organization of these clusters suggests that the perceptual processing within each cluster serves related functions.

Background Abnormalities in the corpus callosum have been reported in individuals with autism spectrum disorder (ASD), but few studies have evaluated young children. Sex differences in callosal organization and diffusion characteristics have also not been evaluated fully in ASD. Methods Structural and diffusion-weighted images were acquired in 139 preschool-aged children with ASD (112 males/27 females) and 82 typically developing (TD) controls (53 males/29 females). Longitudinal scanning at two additional annual time points was carried out in a subset of these participants. Callosal organization was evaluated using two approaches: 1) diffusion tensor imaging (DTI) tractography to define subregions based on cortical projection zones and 2) as a comparison to previous studies, midsagittal area analysis using Witelson subdivisions. Diffusion measures of callosal fibers were also evaluated. Results Analyses of cortical projection zone subregions revealed sex differences in the patterns of altered callosal organization. Relative to their sex-specific TD counterparts, both males and females with ASD had smaller regions dedicated to fibers projecting to superior frontal cortex, but patterns differed in callosal subregions projecting to other parts of frontal cortex. While males with ASD had a smaller callosal region dedicated to the orbitofrontal cortex, females with ASD had a smaller callosal region dedicated to the anterior frontal cortex. There were also sex differences in diffusion properties of callosal fibers. While no alterations were observed in males with ASD relative to TD males, mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were all increased in females with ASD relative to TD females. Analyses of Witelson subdivisions revealed a decrease in midsagittal area of the corpus callosum in both males and females with ASD but no regional differences in specific subdivisions. Longitudinal analyses revealed no diagnostic or sex differences in the growth rate or change in diffusion measures of the corpus callosum from 3 to 5 years of age. Conclusions There are sex differences in the pattern of altered corpus callosum neuroanatomy in preschool-aged children with ASD. Electronic supplementary material The online version of this article (doi:10.1186/s13229-015-0005-4) contains supplementary material, which is available to authorized users.

© 2015 Elsevier Ireland Ltd. The fornix is the primary subcortical output fiber system of the hippocampal formation. In children with 22q11.2 deletion syndrome (22q11.2DS), hippocampal volume reduction has been commonly reported, but few studies as yet have evaluated the integrity of the fornix. Therefore, we investigated the fornix of 45 school-aged children with 22q11.2DS and 38 matched typically developing (TD) children. Probabilistic diffusion tensor imaging (DTI) tractography was used to reconstruct the body of the fornix in each child[U+05F3]s brain native space. Compared with children, significantly lower fractional anisotropy (FA) and higher radial diffusivity (RD) was observed bilaterally in the body of the fornix in children with 22q11.2DS. Irregularities were especially prominent in the posterior aspect of the fornix where it emerges from the hippocampus. Smaller volumes of the hippocampal formations were also found in the 22q11.2DS group. The reduced hippocampal volumes were correlated with lower fornix FA and higher fornix RD in the right hemisphere. Our findings provide neuroanatomical evidence of disrupted hippocampal connectivity in children with 22q11.2DS, which may help to further understand the biological basis of spatial impairments, affective regulation, and other factors related to the ultra-high risk for schizophrenia in this population.

We performed a series of functional magnetic resonance imaging experiments to divide the human MT+ complex into subregions that may be identified as homologs to a pair of macaque motion-responsive visual areas: the middle temporal area (MT) and the medial superior temporal area (MST). Using stimuli designed to tease apart differences in retinotopic organization and receptive field size, we established a double dissociation between two distinct MT+ subregions in 8 of the 10 hemispheres studied. The first subregion exhibited retinotopic organization but did not respond to peripheral ipsilateral stimulation, indicative of smaller receptive fields. Conversely, the second subregion within MT+ did not demonstrate retinotopic organization but did respond to peripheral stimuli in both the ipsilateral and contralateral visual hemifields, indicative of larger receptive fields. We tentatively identify these subregions as the human homologues of macaque MT and MST, respectively. Putative human MT and MST were typically located on the posterior/ventral and anterior/dorsal banks of a dorsal/posterior limb of the inferior temporal sulcus, similar to their relative positions in the macaque superior temporal sulcus.

Two patterns of appropriately filtered acoustic white noise can be binaurally fused by the human auditory system to extract pitch and location information that is not available to either ear alone. This phenomenon is called dichotic pitch. Here we present a new method for generating more effective and useful dichotic pitch stimuli. These novel stimuli allow the psychophysical assessment of dichotic pitch detection thresholds. We show that dichotic pitch detection is significantly impaired in individuals with developmental dyslexia, as compared to average readers. These results suggest a low-level auditory deficit associated with dyslexia and also demonstrate the potential value of our new dichotic pitch stimuli for assessment of auditory processing.

In task-based functional magnetic resonance imaging (fMRI), researchers seek to measure fMRI signals related to a given task or condition. In many circumstances, measuring this signal of interest is limited by noise. In this study, we present GLMdenoise, a technique that improves signal-to-noise ratio (SNR) by entering noise regressors into a general linear model (GLM) analysis of fMRI data. The noise regressors are derived by conducting an initial model fit to determine voxels unrelated to the experimental paradigm, performing principal components analysis (PCA) on the time-series of these voxels, and using cross-validation to select the optimal number of principal components to use as noise regressors. Due to the use of data resampling, GLMdenoise requires and is best suited for datasets involving multiple runs (where conditions repeat across runs). We show that GLMdenoise consistently improves cross-validation accuracy of GLM estimates on a variety of event-related experimental datasets and is accompanied by substantial gains in SNR. To promote practical application of methods, we provide MATLAB code implementing GLMdenoise. Furthermore, to help compare GLMdenoise to other denoising methods, we present the Denoise Benchmark (DNB), a public database and architecture for evaluating denoising methods. The DNB consists of the datasets described in this paper, a code framework that enables automatic evaluation of a denoising method, and implementations of several denoising methods, including GLMdenoise, the use of motion parameters as noise regressors, ICA-based denoising, and RETROICOR/RVHRCOR. Using the DNB, we find that GLMdenoise performs best out of all of the denoising methods we tested.

We tested whether linear structural models of the mechanisms underlying flicker sensitivity could reproduce the variance-covariance matrix of temporal contrast sensitivity data. Monocular sensitivities to frequencies between 2.5 and 45 Hz were measured for 124 subjects, ages 18–88 yr. Exploratory factor analyses revealed that both a two-mechanism and a three-mechanism model could adequately account for the data. Furthermore, confirmatory factor analyses and full structural equation models, using age as an explanatory variable, supported both models, with the three-factor model giving a somewhat better representation of the data. Parsimony favors the two-mechanism model. But patterns of loss associated with pre-exudative age-related maculopathy are more easily understood in terms of three underlying mechanisms.

The presence of a photopigment (melanopsin) within certain retinal ganglion cells was a surprising and significant discovery. This pigment is routinely described as “nonvisual” to highlight its signaling role in pupil dilation and circadian rhythms. Here we asked whether light absorbed by melanopsin can be seen by healthy human subjects. To answer this requires delivering intense (above rod saturation), well-controlled lights using four independent primaries. We collected detection thresholds to many four-primary stimuli. Threshold measurements in the fovea are explained by trichromatic theory, with no need to invoke a fourth photopigment. In the periphery, where melanopsin is present, threshold measurements deviate from trichromatic theory; at high photopic levels, sensitivity is explained by absorptions in four, not three, photopigment classes. We consider a series of hypotheses to explain the tetrasensitivity at high photopic levels in the human peripheral field. The most likely hypothesis is that in healthy human subjects melanopsin absorptions influence visibility.

White matter tissue properties are highly correlated with reading proficiency; we would like to have a model that relates the dynamics of an individual’s white matter development to their acquisition of skilled reading. The development of cerebral white matter involves multiple biological processes, and the balance between these processes differs between individuals. Cross-sectional measures of white matter mask the interplay between these processes and their connection to an individual’s cognitive development. Hence, we performed a longitudinal study to measure white-matter development (diffusion-weighted imaging) and reading development (behavioral testing) in individual children (age 7–15 y). The pattern of white-matter development differed significantly among children. In the left arcuate and left inferior longitudinal fasciculus, children with above-average reading skills initially had low fractional anisotropy (FA) that increased over the 3-y period, whereas children with below-average reading skills had higher initial FA that declined over time. We describe a dual-process model of white matter development comprising biological processes with opposing effects on FA, such as axonal myelination and pruning, to explain the pattern of results.

Tractography based on diffusion weighted imaging (DWI) data is a method for identifying the major white matter fascicles (tracts) in the living human brain. The health of these tracts is an important factor underlying many cognitive and neurological disorders. In vivo, tissue properties may vary systematically along each tract for several reasons: different populations of axons enter and exit the tract, and disease can strike at local positions within the tract. Hence quantifying and understanding diffusion measures along each fiber tract (Tract Profile) may reveal new insights into white matter development, function, and disease that are not obvious from mean measures of that tract. We demonstrate several novel findings related to Tract Profiles in the brains of typically developing children and children at risk for white matter injury secondary to preterm birth. First, fractional anisotropy (FA) values vary substantially within a tract but the Tract FA Profile is consistent across subjects. Thus, Tract Profiles contain far more information than mean diffusion measures. Second, developmental changes in FA occur at specific positions within the Tract Profile, rather than along the entire tract. Third, Tract Profiles can be used to compare white matter properties of individual patients to standardized Tract Profiles of a healthy population to elucidate unique features of that patient's clinical condition. Fourth, Tract Profiles can be used to evaluate the association between white matter properties and behavioral outcomes. Specifically, in the preterm group reading ability is positively correlated with FA measured at specific locations on the left arcuate and left superior longitudinal fasciculus and the magnitude of the correlation varies significantly along the Tract Profiles. We introduce open source software for automated fiber-tract quantification (AFQ) that measures Tract Profiles of MRI parameters for 18 white matter tracts. With further validation, AFQ Tract Profiles have potential for informing clinical management and decision-making.