Clinical and radiological characterization of novel FIG4-related combined system disease with neuropathy.

Variants in the FIG4 gene, which encodes a phosphatidylinositol-3,5-bisphosphatase lead to obstruction of endocytic trafficking, causing accumulation of enlarged vesicles in murine peripheral neurons and fibroblasts. Bi-allelic pathogenic variants in FIG4 are associated with neurological disorders including Charcot-Marie-Tooth disease type-4J (CMT4J) and Yunis-Varón syndrome (YVS). We present four probands from three unrelated families, all homozygous for a recurrent FIG4 missense variant c.506A>C p.(Tyr169Ser), with a novel phenotype involving features of both CMT4J and YVS. Three presented with infant-onset dystonia and one with hypotonia. All have depressed lower limb reflexes and distal muscle weakness, two have nerve conduction studies (NCS) consistent with severe sensorimotor demyelinating peripheral neuropathy and one had NCS showing patchy intermediate/mildly reduced motor conduction velocities. All have cognitive impairment and three have swallowing difficulties. MRI showed cerebellar atrophy and bilateral T2 hyperintense medullary swellings in all patients. These children represent a novel clinicoradiological phenotype and suggest that phenotypes associated with FIG4 missense variants do not neatly fall into previously described diagnoses but can present with variable features. Analysis of this gene should be considered in patients with central and peripheral neurological signs and medullary radiological changes, providing earlier diagnosis and informing reproductive choices.

Ultra-High-Field fMRI Reveals a Role for the Subiculum in Scene Perceptual Discrimination.

Recent "representational" accounts suggest a key role for the hippocampus in complex scene perception. Due to limitations in scanner field strength, however, the functional neuroanatomy of hippocampal-dependent scene perception is unknown. Here, we applied 7 T high-resolution functional magnetic resonance imaging (fMRI) alongside a perceptual oddity task, modified from nonhuman primate studies. This task requires subjects to discriminate highly similar scenes, faces, or objects from multiple viewpoints, and has revealed selective impairments during scene discrimination following hippocampal lesions. Region-of-interest analyses identified a preferential response in the subiculum subfield of the hippocampus during scene, but not face or object, discriminations. Notably, this effect was in the anteromedial subiculum and was not modulated by whether scenes were subsequently remembered or forgotten. These results highlight the value of ultra-high-field fMRI in generating more refined, anatomically informed, functional accounts of hippocampal contributions to cognition, and a unique role for the human subiculum in discrimination of complex scenes from different viewpoints.SIGNIFICANCE STATEMENT There is increasing evidence that the human hippocampus supports functions beyond just episodic memory, with human lesion studies suggesting a contribution to the perceptual processing of navigationally relevant, complex scenes. While the hippocampus itself contains several small, functionally distinct subfields, examining the role of these in scene processing has been previously limited by scanner field strength. By applying ultra-high-resolution 7 T fMRI, we delineated the functional contribution of individual hippocampal subfields during a perceptual discrimination task for scenes, faces, and objects. This demonstrated that the discrimination of scenes, relative to faces and objects, recruits the anterior subicular region of the hippocampus, regardless of whether scenes were subsequently remembered or forgotten.

Impact of time-of-day on brain morphometric measures derived from T1-weighted magnetic resonance imaging.

Measures of brain morphometry derived from T1-weighted (T1W) magnetic resonance imaging (MRI) are widely used to elucidate the relation between brain structure and function. However, the computation of T1W morphometric measures can be confounded by subject-related factors such as head motion and level of hydration. A recent study reported subtle yet significant changes in brain volume from morning to evening in a large group of patient populations as well as in healthy elderly individuals. In addition, there is a growing recognition that factors such as circadian rhythm can impact MRI measures of brain function and structure. Here, we provide a comprehensive assessment of the impact of time-of-day (TOD) on widely used measures of brain morphometry in a group of 19 healthy young adults. Our results show that (a) even in a small group of healthy adult volunteers, a highly significant reduction in apparent brain volume, from morning to evening, could be detected; (b) the apparent volume of all three major tissue compartments - gray matter, white matter, and cerebrospinal fluid - were influenced by TOD, and the magnitude of the TOD effect varied across the tissue compartments; (c) measures of cortical thickness, cortical surface area, and gray matter density computed with widely used neuroimaging software suites (i.e., FreeSurfer, FSL-VBM) were all affected by TOD, while other measures, such as curvature indices and sulcal depth, were not; and (d) the effect of TOD appeared to have a greater impact on morphometric measures of the frontal and temporal lobe than on other major lobes of the brain. Our results suggest that the TOD effect is a physiological phenomenon and that controlling for the effect of TOD is crucial for proper interpretation of apparent structural differences measured with T1W morphometry.

Multi-modal characterization of rapid anterior hippocampal volume increase associated with aerobic exercise.

The hippocampus has been shown to demonstrate a remarkable degree of plasticity in response to a variety of tasks and experiences. For example, the size of the human hippocampus has been shown to increase in response to aerobic exercise. However, it is currently unknown what underlies these changes. Here we scanned sedentary, young to middle-aged human adults before and after a six-week exercise intervention using nine different neuroimaging measures of brain structure, vasculature, and diffusion. We then tested two different hypotheses regarding the nature of the underlying changes in the tissue. Surprisingly, we found no evidence of a vascular change as has been previously reported. Rather, the pattern of changes is better explained by an increase in myelination. Finally, we show that hippocampal volume increase is temporary, returning to baseline after an additional six weeks without aerobic exercise. This is the first demonstration of a change in hippocampal volume in early to middle adulthood suggesting that hippocampal volume is modulated by aerobic exercise throughout the lifespan rather than only in the presence of age related atrophy. It is also the first demonstration of hippocampal volume change over a period of only six weeks, suggesting that gross morphometric hippocampal plasticity occurs faster than previously thought.

The organization of dorsal frontal cortex in humans and macaques.

The human dorsal frontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. Here we used diffusion-weighted magnetic resonance imaging (DW-MRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of dorsal frontal cortex in the two species. Using DW-MRI tractography-based parcellation, we identified 10 dorsal frontal regions lying between the human inferior frontal sulcus and cingulate cortex. Patterns of functional coupling between each area and the rest of the brain were then estimated with fMRI and compared with functional coupling patterns in macaques. Areas in human medial frontal cortex, including areas associated with high-level social cognitive processes such as theory of mind, showed a surprising degree of similarity in their functional coupling patterns with the frontal pole, medial prefrontal, and dorsal prefrontal convexity in the macaque. We failed to find evidence for "new" regions in human medial frontal cortex. On the lateral surface, comparison of functional coupling patterns suggested correspondences in anatomical organization distinct from those that are widely assumed. A human region sometimes referred to as lateral frontal pole more closely resembled area 46, rather than the frontal pole, of the macaque. Overall the pattern of results suggest important similarities in frontal cortex organization in humans and other primates, even in the case of regions thought to carry out uniquely human functions. The patterns of interspecies correspondences are not, however, always those that are widely assumed.

Gray matter volume is associated with rate of subsequent skill learning after a long term training intervention.

The ability to predict learning performance from brain imaging data has implications for selecting individuals for training or rehabilitation interventions. Here, we used structural MRI to test whether baseline variations in gray matter (GM) volume correlated with subsequent performance after a long-term training of a complex whole-body task. 44 naïve participants were scanned before undertaking daily juggling practice for 6weeks, following either a high intensity or a low intensity training regime. To assess performance across the training period participants' practice sessions were filmed. Greater GM volume in medial occipito-parietal areas at baseline correlated with steeper learning slopes. We also tested whether practice time or performance outcomes modulated the degree of structural brain change detected between the baseline scan and additional scans performed immediately after training and following a further 4weeks without training. Participants with better performance had higher increases in GM volume during the period following training (i.e., between scans 2 and 3) in dorsal parietal cortex and M1. When contrasting brain changes between the practice intensity groups, we did not find any straightforward effects of practice time though practice modulated the relationship between performance and GM volume change in dorsolateral prefrontal cortex. These results suggest that practice time and performance modulate the degree of structural brain change evoked by long-term training regimes.

Reliability and predictability of phenotype information from functional connectivity in large imaging datasets.

One of the central objectives of contemporary neuroimaging research is to create predictive models that can disentangle the connection between patterns of functional connectivity across the entire brain and various behavioral traits. Previous studies have shown that models trained to predict behavioral features from the individual's functional connectivity have modest to poor performance. In this study, we trained models that predict observable individual traits (phenotypes) and their corresponding singular value decomposition (SVD) representations - herein referred to as latent phenotypes from resting state functional connectivity. For this task, we predicted phenotypes in two large neuroimaging datasets: the Human Connectome Project (HCP) and the Philadelphia Neurodevelopmental Cohort (PNC). We illustrate the importance of regressing out confounds, which could significantly influence phenotype prediction. Our findings reveal that both phenotypes and their corresponding latent phenotypes yield similar predictive performance. Interestingly, only the first five latent phenotypes were reliably identified, and using just these reliable phenotypes for predicting phenotypes yielded a similar performance to using all latent phenotypes. This suggests that the predictable information is present in the first latent phenotypes, allowing the remainder to be filtered out without any harm in performance. This study sheds light on the intricate relationship between functional connectivity and the predictability and reliability of phenotypic information, with potential implications for enhancing predictive modeling in the realm of neuroimaging research.

A bimodal taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients.

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (n = 34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bimodal distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex, and complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (n = 228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

A highly replicable decline in mood during rest and simple tasks.

Does our mood change as time passes? This question is central to behavioural and affective science, yet it remains largely unexamined. To investigate, we intermixed subjective momentary mood ratings into repetitive psychology paradigms. Here we demonstrate that task and rest periods lowered participants' mood, an effect we call 'Mood Drift Over Time'. This finding was replicated in 19 cohorts totalling 28,482 adult and adolescent participants. The drift was relatively large (-13.8% after 7.3 min of rest, Cohen's d = 0.574) and was consistent across cohorts. Behaviour was also impacted: participants were less likely to gamble in a task that followed a rest period. Importantly, the drift slope was inversely related to reward sensitivity. We show that accounting for time using a linear term significantly improves the fit of a computational model of mood. Our work provides conceptual and methodological reasons for researchers to account for time's effects when studying mood and behaviour.

A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients.

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

The positive-negative mode link between brain connectivity, demographics and behaviour: a pre-registered replication of Smith et al. (2015).

In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to mental health disorders. Recently, a family of data-driven analyses have provided such reliable measures when applied to large, population-level datasets. In the current pre-registered replication study, we show that the canonical correlation analysis (CCA) methods previously developed using resting-state magnetic resonance imaging functional connectivity and subject measures (SMs) of cognition and behaviour from healthy adults are also effective in measuring well-being (a 'positive-negative axis') in an independent developmental dataset. Our replication was successful in two out of three of our pre-registered criteria, such that a primary CCA mode's weights displayed a significant positive relationship and explained a significant amount of variance in both functional connectivity and SMs. The only criterion that was not successful was that compared to other modes the magnitude of variance explained by the primary CCA mode was smaller than predicted, a result that could indicate a developmental trajectory of a primary mode. This replication establishes a signature neurotypical relationship between connectivity and phenotype, opening new avenues of research in neuroscience with clear clinical applications.

The NIMH intramural healthy volunteer dataset: A comprehensive MEG, MRI, and behavioral resource.

The NIMH Healthy Research Volunteer Dataset is a collection of phenotypic data characterizing healthy research volunteers using clinical assessments such as assays of blood and urine, mental health assessments, diagnostic and dimensional measures of mental health, cognitive and neuropsychological functioning, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG). In addition, blood samples of healthy volunteers are banked for future analyses. All data collected in this protocol are broadly shared in the OpenNeuro repository, in the Brain Imaging Data Structure (BIDS) format. In addition, task paradigms and basic pre-processing scripts are shared on GitHub. There are currently few open access MEG datasets, and multimodal neuroimaging datasets are even more rare. Due to its depth of characterization of a healthy population in terms of brain health, this dataset may contribute to a wide array of secondary investigations of non-clinical and clinical research questions.

Extranodal lymphoma from head to toe: part 1, the head and spine.

OBJECTIVE: Lymphoma can affect virtually every tissue in the body, producing a variety of imaging appearances. In this article, the extranodal manifestations of lymphoma in the head and spine are illustrated and the imaging features that aid in diagnosis are reviewed. CONCLUSION: Knowledge of the imaging appearances of extranodal lymphoma can aid in the differential diagnosis of mass lesions encountered in tissues throughout the body on different imaging modalities.

Extranodal lymphoma from head to toe: part 2, the trunk and extremities.

OBJECTIVE: Lymphoma can affect virtually every tissue in the body, producing a variety of imaging appearances. In this article, the extranodal manifestations of this disease in the trunk and extremities are illustrated and the imaging features that aid in the diagnosis are reviewed. CONCLUSION: Knowledge of the imaging appearances of extranodal lymphoma can aid the differential diagnosis of mass lesions encountered in tissues throughout the body on different imaging modalities.

The fornix in health and disease: an imaging review.

The fornix is a discrete white matter tract bundle that is critical for normal cognitive functioning. Although clearly visualized at magnetic resonance imaging, its involvement in pathologic processes is often overlooked. Certain disease processes show a predilection for involvement of the fornix; in other pathologic conditions, its involvement is a rare but recognized finding. As part of the Papez circuit, it is critical in formation of memory, with damage or disease resulting in anterograde amnesia. Many different pathologic conditions can affect the fornix. Midline tumors such as gliomas or lymphoma can infiltrate it. As part of the limbic system, it may be affected by herpes simplex encephalitis. Involvement by inflammatory conditions such as multiple sclerosis may illustrate its importance in global cognitive function. An appreciation of forniceal atrophy may aid in assessment of mesial temporal sclerosis. Metabolic conditions such as Wernicke encephalopathy have been reported to involve it. The original discoveries of its role in memory arose from surgical trauma, but as a midline structure, it is susceptible to the shearing forces of diffuse axonal injury. Infarction of the fornix is rare but can result in acute amnesic syndromes. Its role in degenerative conditions such as Alzheimer disease and psychiatric conditions such as schizophrenia is a topic of research interest. Recognition of involvement of the fornix by various pathologic processes may aid in explaining the troubling clinical symptoms of amnesia.

Functional but not structural changes associated with learning: an exploration of longitudinal voxel-based morphometry (VBM).

Voxel-Based Morphometry (VBM) has been used for several years to study differences in brain structure between populations. Recently, a longitudinal version of VBM has been used to show changes in gray matter associated with relatively short periods of training. In the present study we use fMRI and three different standard implementations of longitudinal VBM: SPM2, FSL, and SPM5 to assess functional and structural changes associated with a simple learning task. Behavioral and fMRI data clearly showed a significant learning effect. However, initially positive VBM results were found to be inconsistent across minor perturbations of the analysis technique and ultimately proved to be artifactual. When alignment biases were controlled for and recommended statistical procedures were used, no significant changes in grey matter density were found. This work, initially intended to show structural and functional changes with learning, rather demonstrates some of the potential pitfalls of existing longitudinal VBM methods and prescribes that these tools be applied and interpreted with extreme caution.

Knowing What You Know in Brain Segmentation Using Bayesian Deep Neural Networks.

In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours. The network was trained and evaluated on a large dataset (n = 11,480), obtained by combining data from more than a hundred different sites, and also evaluated on another completely held-out dataset (n = 418). The network was trained using a novel spike-and-slab dropout-based variational inference approach. We show that, on these datasets, the proposed Bayesian DNN outperforms previously proposed methods, in terms of the similarity between the segmentation predictions and the FreeSurfer labels, and the usefulness of the estimate uncertainty of these predictions. In particular, we demonstrated that the prediction uncertainty of this network at each voxel is a good indicator of whether the network has made an error and that the uncertainty across the whole brain can predict the manual quality control ratings of a scan. The proposed Bayesian DNN method should be applicable to any new network architecture for addressing the segmentation problem.

Crowdsourced MRI quality metrics and expert quality annotations for training of humans and machines.

The neuroimaging community is steering towards increasingly large sample sizes, which are highly heterogeneous because they can only be acquired by multi-site consortia. The visual assessment of every imaging scan is a necessary quality control step, yet arduous and time-consuming. A sizeable body of evidence shows that images of low quality are a source of variability that may be comparable to the effect size under study. We present the MRIQC Web-API, an open crowdsourced database that collects image quality metrics extracted from MR images and corresponding manual assessments by experts. The database is rapidly growing, and currently contains over 100,000 records of image quality metrics of functional and anatomical MRIs of the human brain, and over 200 expert ratings. The resource is designed for researchers to share image quality metrics and annotations that can readily be reused in training human experts and machine learning algorithms. The ultimate goal of the database is to allow the development of fully automated quality control tools that outperform expert ratings in identifying subpar images.

Hippocampal Functional Dynamics Are Clinically Implicated in Autoimmune Encephalitis With Faciobrachial Dystonic Seizures.

This is the first study to investigate functional brain activity in patients affected by autoimmune encephalitis with faciobrancial dystonic seizures (FBDS). Multimodal 3T MRI scans, including structural neuroimaging (T1-weighted, diffusion weighted) and functional neuroimaging (scene-encoding task known to activate hippocampal regions), were performed. This case series analysis included eight patients treated for autoimmune encephalitis with FBDS, scanned during the convalescent phase of their condition (median 1.1 years post-onset), and eight healthy volunteers. Compared to controls, 50% of patients showed abnormal hippocampal activity during scene-encoding relative to familiar scene-viewing. Higher peak FBDS frequency was significantly related to lower hippocampal activity during scene-encoding (p = 0.02), though not to markers of hippocampal microstructure (mean diffusivity, p = 0.3) or atrophy (normalized volume, p = 0.4). During scene-encoding, stronger within-medial temporal lobe (MTL) functional connectivity correlated with poorer Addenbrooke's Cognitive Examination-Revised memory score (p = 0.03). These findings suggest that in autoimmune encephalitis, frequent seizures may have a long-term impact on hippocampal activity, beyond that of structural damage. These observations also suggest a potential approach to determine on-going MTL performance in this condition to guide long-term management and future clinical trials.

A very simple, re-executable neuroimaging publication.

Reproducible research is a key element of the scientific process. Re-executability of neuroimaging workflows that lead to the conclusions arrived at in the literature has not yet been sufficiently addressed and adopted by the neuroimaging community. In this paper, we document a set of procedures, which include supplemental additions to a manuscript, that unambiguously define the data, workflow, execution environment and results of a neuroimaging analysis, in order to generate a verifiable re-executable publication. Re-executability provides a starting point for examination of the generalizability and reproducibility of a given finding.