Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling.

Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.

Indirect structural changes and reduced controllability after temporal lobe epilepsy resection.

OBJECTIVE: To understand the potential behavioral and cognitive effects of mesial temporal resection for temporal lobe epilepsy (TLE) a method is required to characterize network-wide functional alterations caused by a discrete structural disconnection. The objective of this study was to investigate network-wide alterations in brain dynamics of patients with TLE before and after surgical resection of the seizure focus using average regional controllability (ARC), a measure of the ability of a node to influence network dynamics. METHODS: Diffusion-weighted imaging (DWI) data were acquired in 27 patients with drug-resistant unilateral mesial TLE who underwent selective amygdalohippocampectomy. Imaging data were acquired before and after surgery and a presurgical and postsurgical structural connectome was generated from whole-brain tractography. Edge-wise strength, node strength, and node ARC were compared before and after surgery. Direct and indirect edge-wise strength changes were identified using patient-specific simulated resections. Direct edges were defined as primary edges disconnected by the resection zone itself. Indirect edges were secondary measured edge strength changes. Changes in node strength and ARC were then related to both direct and indirect edge changes. RESULTS: We found nodes with significant postsurgical changes in both node strength and ARC surrounding the resection zone (paired t tests, p < .05, Bonferroni corrected). ARC identified additional postsurgical changes in nodes outside of the resection zone within the ipsilateral occipital lobe, which were associated with indirect edge-wise strength changes of the postsurgical network (Fisher's exact test, p < .001). These indirect edge-wise changes were facilitated through the "hub" nodes including the thalamus, putamen, insula, and precuneus. SIGNIFICANCE: Discrete network disconnection from TLE resection results in widespread structural and functional changes not predicted by disconnection alone. These can be well characterized by dynamic controllability measures such as ARC and may be useful for investigating changes in brain function that may contribute to seizure recurrence and behavioral or cognitive changes after surgery.

Modulation of hippocampal activity in schizophrenia with levetiracetam: a randomized, double-blind, cross-over, placebo-controlled trial.

Hippocampal hyperactivity is a novel pharmacological target in the treatment of schizophrenia. We hypothesized that levetiracetam (LEV), a drug binding to the synaptic vesicle glycoprotein 2 A, normalizes hippocampal activity in persons with schizophrenia and can be measured using neuroimaging methods. Thirty healthy control participants and 30 patients with schizophrenia (28 treated with antipsychotic drugs), were randomly assigned to a double-blind, cross-over trial to receive a single administration of 500 mg oral LEV or placebo during two study visits. At each visit, we assessed hippocampal function using resting state fractional amplitude of low frequency fluctuations (fALFF), cerebral blood flow (CBF) with arterial spin labeling, and hippocampal blood-oxygen-level-dependent (BOLD) signal during a scene processing task. After placebo treatment, we found significant elevations in hippocampal fALFF in patients with schizophrenia, consistent with hippocampal hyperactivity. Additionally, hippocampal fALFF in patients with schizophrenia after LEV treatment did not significantly differ from healthy control participants receiving placebo, suggesting that LEV may normalize hippocampal hyperactivity. In contrast to our fALFF findings, we did not detect significant group differences or an effect of LEV treatment on hippocampal CBF. In the context of no significant group difference in BOLD signal, we found that hippocampal recruitment during scene processing is enhanced by LEV more significantly in schizophrenia. We conclude that pharmacological modulation of hippocampal hyperactivity in schizophrenia can be studied with some neuroimaging methods, but not others. Additional studies in different cohorts, employing alternate neuroimaging methods and study designs, are needed to establish levetiracetam as a treatment for schizophrenia.

Paramagnetic rim lesions and the central vein sign: Characterizing multiple sclerosis imaging markers.

BACKGROUND AND PURPOSE: Paramagnetic rims and the central vein sign (CVS) are proposed imaging markers of multiple sclerosis (MS) lesions. Using 7 tesla magnetic resonance imaging, we aimed to: (1) characterize the appearance of paramagnetic rim lesions (PRLs); (2) assess whether PRLs and the CVS are associated with higher levels of MS pathology; and (3) compare the characteristics between subjects with and without PRLs in early MS. METHODS: Prospective study of 32 treatment-naïve subjects around the time of diagnosis who were assessed for the presence of PRLs and the CVS. Comparisons of lesion volume and macromolecular pool size ratio (PSR) index, a proxy of myelin integrity, between PRLs and non-PRLs, and CVS-positive and CVS-negative lesions were carried out. Differences in clinical/demographic characteristics between patients with PRLs and those without were tested. RESULTS: Fifteen subjects had ≥1 PRL for a total of 36 PRLs, of which two-thirds had a full rim. PRLs predicted a larger lesion size and decreased PSR signal. Lesion volume and presence of cervical spine lesions were significantly different between subjects with PRLs and those without, although neither remained significant after adjusting for multiple comparisons. One hundred and eighty-one lesions with CVS were identified with no differences between CVS-positive and CVS-negative lesions in volume (p = .27) and PSR values (p = .62). CONCLUSIONS: PRLs, but not CVS-positive lesions, are larger and have lower myelin integrity. Our findings indicate that PRLs are associated with higher levels of lesion-specific pathology prior to the start of disease-modifying therapy.

Differences in temporal profile of brain responses by pleasantness of somatosensory stimulation in autistic individuals.

Purpose/Aim. Autistic individuals may show either hyper- or hypo- responsiveness to touch compared to non-autistic individuals. These behavioural responses depend on perceptual and evaluative mechanisms, which unfold sequentially and thus can be distinguished by exploring the timing of neural responses. In this study, we examined neural response timing to pleasant, unpleasant, and affectively neutral textures, to determine whether these perceptual versus evaluative subprocesses differ in autism and how each subprocess contributes to behavioural responses.Materials and Methods. Our sample included n = 13 autistic and n = 14 non-autistic adults who completed functional magnetic resonance imaging. We analysed early, intermediate, and late phases of the tactile response, derived from studies of noxious tactile stimulation, to three different textures.Results. The autistic group showed distinct differences from the non-autistic group to each of the textures, showing earlier, somatosensory differences in response to the pleasantly and unpleasantly rated textures and later, frontomotor differences in response to the neutrally rated texture. Further, reduced early phase response to the pleasant texture correlated with increased sensory seeking behaviour.Conclusions. While preliminary, these results suggest distinct patterns between autistic and non-autistic individuals in how the neural response to touch unfolds and its correspondence with the perceived pleasantness of tactile experience. The findings suggest perceptual differences in response to affectively charged textures and evaluative differences in response to neutral, ambiguous textures. These temporal properties may inform future studies of tactile processing in autism, lending a better understanding of how individuals differ in their sensory experiences across contexts.

Detecting macromolecular differences of the CSF in low disability multiple sclerosis using quantitative MT MRI at 3T.

Background: Imaging investigation of cerebrospinal fluid (CSF) in multiple sclerosis (MS) is understudied. Development of noninvasive methods to detect pathological CSF changes would have a profound effect on MS diagnosis and would offer insight into MS pathophysiology and mechanisms of neurological impairment. Objective: We propose magnetization transfer (MT) MRI as a tool to detect macromolecular changes in spinal CSF. Methods: MT and quantitative MT (qMT) data were acquired in the cervical region in 27 people with relapsing-remitting multiple sclerosis (pwRRMS) and 38 age and sex-matched healthy controls (HCs). MT ratio (MTR), the B1, B0, and R1 corrected qMT-derived pool size ratio (PSR) were quantified in the spinal cord and CSF of each group. Results: Both CSF MTR and CSF qMT-derived PSR were significantly increased in pwRRMS compared to HC (p = 0.027 and p = 0.020, respectively). CSF PSR of pwRRMS was correlated to Expanded Disability Status Scale Scores (p = 0.045, R = 0.352). Conclusion: Our findings demonstrate increased CSF macromolecular content in pwRRMS and link CSF macromolecular content with clinical impairment. This highlights the potential role of CSF in processing products of demyelination.

Seasonal variations of functional connectivity of human brains.

Seasonal variations have long been observed in various aspects of human life. While there is an abundance of research that has characterized seasonality effects in, for example, cognition, mood, and behavior, including studies of underlying biophysical mechanisms, direct measurements of seasonal variations of brain functional activities have not gained wide attention. We have quantified seasonal effects on functional connectivity as derived from MRI scans. A cohort of healthy human subjects was divided into four groups based on the seasons of their scanning dates as documented in the image database of the Human Connectome Project. Sinusoidal functions were used as regressors to determine whether there were significant seasonal variations in measures of brain activities. We began with the analysis of seasonal variations of the fractional amplitudes of low frequency fluctuations of regional functional signals, followed by the seasonal variations of functional connectivity in both global- and network-level. Furthermore, relevant environmental factors, including average temperature and daylength, were found to be significantly associated with brain functional activities, which may explain how the observed seasonal fluctuations arise. Finally, topological properties of the brain functional network also showed significant variations across seasons. All the observations accumulated revealed seasonality effects of human brain activities in a resting-state, which may have important practical implications for neuroimaging research.

Detection of resting-state functional connectivity in the lumbar spinal cord with 3T MRI.

Functional MRI (fMRI) of the spinal cord is an expanding area of research with potential to investigate neuronal activity in the central nervous system. We aimed to characterize the functional connectivity features of the human lumbar spinal cord using resting-state fMRI (rs-fMRI) at 3T, using region-based and data-driven analysis approaches. A 3D multi-shot gradient echo resting-state blood oxygenation level dependent-sensitive rs-fMRI protocol was implemented in 26 healthy participants. Average temporal signal-to-noise ratio in the gray matter was 16.35 ± 4.79 after denoising. Evidence of synchronous signal fluctuations in the ventral and dorsal horns with their contralateral counterparts was observed in representative participants using interactive, exploratory seed-based correlations. Group-wise average in-slice Pearson's correlations were 0.43 ± 0.17 between ventral horns, and 0.48 ± 0.16 between dorsal horns. Group spatial independent component analysis (ICA) was used to identify areas of coherent activity¸ and revealed components within the gray matter corresponding to anatomical regions. Lower-dimensionality ICA revealed bilateral components corresponding to ventral and dorsal networks. Additional separate ICAs were run on two subsets of the participant group, yielding two sets of components that showed visual consistency and moderate spatial overlap. This work shows feasibility of rs-fMRI to probe the functional features and organization of the lumbar spinal cord.

Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study.

Background: Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years. Methods: We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model. Results: Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration. Conclusions: These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.

Increased microglia activation in late non-central nervous system cancer survivors links to chronic systemic symptomatology.

Prolonged inflammatory expression within the central nervous system (CNS) is recognized by the brain as a molecular signal of "sickness", that has knock-on effects to the blood-brain barrier, brain-spinal barrier, blood-cerebrospinal fluid barrier, neuro-axonal structures, neurotransmitter activity, synaptic plasticity, neuroendocrine function, and resultant systemic symptomatology. It is concurred that the inflammatory process associated with cancer and cancer treatments underline systemic symptoms present in a large portion of survivors, although this concept is largely theoretical from disparate and indirect evidence and/or clinical anecdotal reports. We conducted a proof-of-concept study to link for the first time late non-CNS cancer survivors presenting chronic systemic symptoms and the presence of centralized inflammation, or neuroinflammation, using TSPO-binding PET tracer [11 C]-PBR28 to visualize microglial activation. We compared PBR28 SUVR in 10 non-CNS cancer survivors and 10 matched healthy controls. Our data revealed (1) microglial activation was significantly higher in caudate, temporal, and occipital regions in late non-central nervous system/CNS cancer survivors compared to healthy controls; (2) increased neuroinflammation in cancer survivors was not accompanied by significant differences in plasma cytokine markers of peripheral inflammation; (3) increased neuroinflammation was not accompanied by reduced fractional anisotropy, suggesting intact white matter microstructural integrity, a marker of neurovascular fiber tract organization; and (4) the presentation of chronic systemic symptoms in cancer survivors was significantly connected with microglial activation. We present the first data empirically supporting the concept of a peripheral-to-centralized inflammatory response in non-CNS cancer survivors, specifically those previously afflicted with head and neck cancer. Following resolution of the initial peripheral inflammation from the cancer/its treatments, in some cases damage/toxification to the central nervous system occurs, ensuing chronic systemic symptoms.

Automatic Preprocessing Pipeline for White Matter Functional Analyses of Large-Scale Databases.

Recently, increasing evidence suggests that fMRI signals in white matter (WM), conventionally ignored as nuisance, are robustly detectable using appropriate processing methods and are related to neural activity, while changes in WM with aging and degeneration are also well documented. These findings suggest variations in patterns of BOLD signals in WM should be investigated. However, existing fMRI analysis tools, which were designed for processing gray matter signals, are not well suited for large-scale processing of WM signals in fMRI data. We developed an automatic pipeline for high-performance preprocessing of fMRI images with emphasis on quantifying changes in BOLD signals in WM in an aging population. At the image processing level, the pipeline integrated existing software modules with fine parameter tunings and modifications to better extract weaker WM signals. The preprocessing results primarily included whole-brain time-courses, functional connectivity, maps and tissue masks in a common space. At the job execution level, this pipeline exploited a local XNAT to store datasets and results, while using DAX tool to automatic distribute batch jobs that run on high-performance computing clusters. Through the pipeline, 5,034 fMRI/T1 scans were preprocessed. The intraclass correlation coefficient (ICC) of test-retest experiment based on the preprocessed data is 0.52 - 0.86 (N=1000), indicating a high reliability of our pipeline, comparable to previously reported ICC in gray matter experiments. This preprocessing pipeline highly facilitates our future analyses on WM functional alterations in aging and may be of benefit to a larger community interested in WM fMRI studies.

Mapping the Impact of Approximate Gradient Nonlinearity Fields Correction on Tractography.

Nonlinear gradients impact diffusion weighted MRI by introducing spatial variation in estimated diffusion tensors. Recent studies have shown that increasing signal-to-noise ratios and the use of ultra-strong gradients may lead to clinically significant impacts on analyses due to these nonlinear gradients in microstructural measures. These effects can potentially bias tractography results and cause misinterpretation of data. Herein, we characterize the impact of an "approximate" gradient nonlinearity correction technique in tractography using empirically derived gradient nonlinear fields. This technique scales the diffusion signal by the change in magnitude due to the gradient nonlinearities, without concomitant correction of gradient direction errors. The impact of this correction on tractography is assessed through white matter bundle segmentation and connectomics via bundle-wise volume, fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity, primary eigenvector, and length; as well as the modularity, global efficiency, and characteristic path length connectomics graph measures. We investigate the differences between (1) these measures directly and (2) the within session variability of these measures before and after approximate correction in 61 subjects from the MASiVar pediatric reproducibility dataset. We find approximate correction results is little to no differences on the population level, but large differences on the subject-specific level for both the measures directly and their within session variability. Thus, this study suggests though approximate correction of gradient nonlinearities may not change tractography findings on the population level, subject-specific interpretations may exhibit large fluctuations. A limitation is the lack of comparison with the empirical voxel-wise gradient table correction.

Cerebellar Effects on Abnormal Psychomotor Function Are Mediated by Processing Speed in Psychosis Spectrum.

Psychomotor disturbance has been identified as a key feature of psychotic disorders, with motor signs observed in upwards of 66% of unmedicated, first-episode patients. Aberrations in the cerebellum have been directly linked to sensorimotor processing deficits including processing speed, which may underly psychomotor disturbance in psychosis, though these brain-behavior-symptom relationships are unclear, in part due to within-diagnosis heterogeneity across these levels of analysis. In 339 psychosis patients (242 schizophrenia-spectrum, 97 bipolar with psychotic features) and 217 controls, we evaluated the relationship between cerebellar grey matter volume in the Yeo sensorimotor network and psychomotor disturbance (mannerisms and posturing, retardation, excitement of the Positive and Negative Syndrome Scale [PANSS]), as mediated by processing speed (assessed via the SCIP). Models included intracranial volume, age, sex, and chlorpromazine equivalents as covariates. We observed significant mediation by processing speed, with a small positive effect of the cerebellum on processing speed (ß = 0.172, p = 0.029, d = 0.24) and a medium negative effect of processing speed on psychomotor disturbance (ß = -0.254, p < 0.001, d = 0.60), with acceptable specificity and sensitivity suggesting this model is robust against unmeasured confounding. The current findings suggest a critical role of cerebellar circuitry in a well-established sensorimotor aberration in psychosis (processing speed) and the presentation of related psychomotor phenotypes within psychosis. Establishing such relationships is critical for intervention research, such as TMS. Future work will employ more dimensional measures of psychomotor disturbance and cognitive processes to capture normative and aberrant brain-behavior-symptom relationships and may also determine the magnitude of these relationships within subtypes of psychosis (e.g., disorganized behavior, catatonia).

Sound Level Changes the Auditory Cortical Activation Detected with Functional Near-Infrared Spectroscopy.

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is a viable non-invasive technique for functional neuroimaging in the cochlear implant (CI) population; however, the effects of acoustic stimulus features on the fNIRS signal have not been thoroughly examined. This study examined the effect of stimulus level on fNIRS responses in adults with normal hearing or bilateral CIs. We hypothesized that fNIRS responses would correlate with both stimulus level and subjective loudness ratings, but that the correlation would be weaker with CIs due to the compression of acoustic input to electric output. METHODS: Thirteen adults with bilateral CIs and 16 with normal hearing (NH) completed the study. Signal-correlated noise, a speech-shaped noise modulated by the temporal envelope of speech stimuli, was used to determine the effect of stimulus level in an unintelligible speech-like stimulus between the range of soft to loud speech. Cortical activity in the left hemisphere was recorded. RESULTS: Results indicated a positive correlation of cortical activation in the left superior temporal gyrus with stimulus level in both NH and CI listeners with an additional correlation between cortical activity and perceived loudness for the CI group. The results are consistent with the literature and our hypothesis. CONCLUSIONS: These results support the potential of fNIRS to examine auditory stimulus level effects at a group level and the importance of controlling for stimulus level and loudness in speech recognition studies. Further research is needed to better understand cortical activation patterns for speech recognition as a function of both stimulus presentation level and perceived loudness.

Functional alterations in bipartite network of white and grey matters during aging.

The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22-96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

Structural disconnection relates to functional changes after temporal lobe epilepsy surgery.

Epilepsy surgery consists of surgical resection of the epileptic focus and is recommended for patients with drug-resistant focal epilepsy. However, focal brain lesions can lead to effects in distant brain regions. Similarly, the focal resection in temporal lobe epilepsy surgery has been shown to lead to functional changes distant from the resection. Here we hypothesize that there are changes in brain function caused by temporal lobe epilepsy surgery in regions distant from the resection that are due to their structural disconnection from the resected epileptic focus. Therefore, the goal of this study was to localize changes in brain function caused by temporal lobe epilepsy surgery and relate them to the disconnection from the resected epileptic focus. This study takes advantage of the unique opportunity that epilepsy surgery provides to investigate the effects of focal disconnections on brain function in humans, which has implications in epilepsy and broader neuroscience. Changes in brain function from pre- to post-epilepsy surgery were quantified in a group of temporal lobe epilepsy patients (n = 36) using a measure of resting state functional MRI activity fluctuations. We identified regions with significant functional MRI changes that had high structural connectivity to the resected region in healthy controls (n = 96) and patients based on diffusion MRI. The structural disconnection from the resected epileptic focus was then estimated using presurgical diffusion MRI and related to the functional MRI changes from pre- to post-surgery in these regions. Functional MRI activity fluctuations increased from pre- to post-surgery in temporal lobe epilepsy in the two regions most highly structurally connected to the resected epileptic focus in healthy controls and patients-the thalamus and the fusiform gyrus ipsilateral to the side of surgery (PFWE < 0.05). Broader surgeries led to larger functional MRI changes in the thalamus than more selective surgeries (P < 0.05), but no other clinical variables were related to functional MRI changes in either the thalamus or fusiform. The magnitude of the functional MRI changes in both the thalamus and fusiform increased with a higher estimated structural disconnection from the resected epileptic focus when controlling for the type of surgery (P < 0.05). These results suggest that the structural disconnection from the resected epileptic focus may contribute to the functional changes seen after epilepsy surgery. Broadly, this study provides a novel link between focal disconnections in the structural brain network and downstream effects on function in distant brain regions.

Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging.

In diffusion weighted MRI (DW-MRI), hardware nonlinearities lead to spatial variations in the orientation and magnitude of diffusion weighting. While the correction of these spatial distortions has been well established for analyses of DW-MRI, the existing voxel-wise empirical correction for gradient nonlinearities requires reimplementation of existing models, as the resultant gradients vary by voxel. Herein, we propose a two-step signal approximation after voxel-wise correction of gradient nonlinearity effects in DW-MRI. The proposed technique (1) scales the diffusion signal and (2) resamples the gradient orientations. This results in uniform gradients across the corrected image and provides the key advantage of seamless integration into current diffusion workflows. We investigated the validity of our technique by fitting a multi-compartment neurite orientation dispersion and density imaging (NODDI) model to the empirical correction and proposed approximation in five subjects from the MASiVar pediatric dataset. We evaluated intra-cellular volume fraction (iVF), CSF volume fraction (cVF), and orientation dispersion index (ODI) from NODDI. The Cohen's d of iVF, cVF and ODI between the techniques was <0.2 indicating the proposed technique does not exhibit significant differences from the voxel-wise correction technique. Our two-step signal approximation is an efficient representation of the voxel-wise gradient table correction. Using this approximation, correction of gradient nonlinearities can be easily incorporated into existing diffusion preprocessing pipelines and is implemented in "PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images".

Neural Correlates of Audiovisual Speech Processing in Autistic and Non-Autistic Youth.

Autistic youth demonstrate differences in processing multisensory information, particularly in temporal processing of multisensory speech. Extensive research has identified several key brain regions for multisensory speech processing in non-autistic adults, including the superior temporal sulcus (STS) and insula, but it is unclear to what extent these regions are involved in temporal processing of multisensory speech in autistic youth. As a first step in exploring the neural substrates of multisensory temporal processing in this clinical population, we employed functional magnetic resonance imaging (fMRI) with a simultaneity-judgment audiovisual speech task. Eighteen autistic youth and a comparison group of 20 non-autistic youth matched on chronological age, biological sex, and gender participated. Results extend prior findings from studies of non-autistic adults, with non-autistic youth demonstrating responses in several similar regions as previously implicated in adult temporal processing of multisensory speech. Autistic youth demonstrated responses in fewer of the multisensory regions identified in adult studies; responses were limited to visual and motor cortices. Group responses in the middle temporal gyrus significantly interacted with age; younger autistic individuals showed reduced MTG responses whereas older individuals showed comparable MTG responses relative to non-autistic controls. Across groups, responses in the precuneus covaried with task accuracy, and anterior temporal and insula responses covaried with nonverbal IQ. These preliminary findings suggest possible differences in neural mechanisms of audiovisual processing in autistic youth while highlighting the need to consider participant characteristics in future, larger-scale studies exploring the neural basis of multisensory function in autism.

Mapping the impact of nonlinear gradient fields with noise on diffusion MRI.

In diffusion MRI, gradient nonlinearities cause spatial variations in the magnitude and direction of diffusion gradients. Studies have shown artifacts from these distortions can results in biased diffusion tensor information and tractography. Here, we investigate the impact of gradient nonlinearity correction in the presence of noise. We introduced empirically derived gradient nonlinear fields at different signal-to-noise ratio (SNR) levels in two experiments: tensor field simulation and simulation of the brain. For each experiment, this work compares two techniques empirically: voxel-wise gradient table correction and approximate correction by scaling the signal directly. The impact was assessed through diffusion metrics including mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and principal eigen vector (V1). The study shows (1) the correction of gradient nonlinearities will not lead to substantively incorrect estimation of diffusion metrics in a linear system, (2) gradient nonlinearity correction does not interact adversely with noise, (3) nonlinearity correction suppresses the impact of nonlinearities in typical SNR data, (4) for SNR below 30, the performance of both the gradient nonlinearity correction techniques were similar, and (5) larger impacts are seen in regions where the gradient nonlinearities are distinct. Thus, this study suggests that there were greater beneficial effects than adverse effects due to the correction of nonlinearities. Additionally, correction of nonlinearities is recommended when region of interests are in areas with pronounced nonlinearities.

Anterior hippocampal dysfunction in early psychosis: a 2-year follow-up study.

BACKGROUND: Cross-sectional studies indicate that hippocampal function is abnormal across stages of psychosis. Neural theories of psychosis pathophysiology suggest that dysfunction worsens with illness stage. Here, we test the hypothesis that hippocampal function is impaired in the early stage of psychosis and declines further over the next 2 years. METHODS: We measured hippocampal function over 2 years using a scene processing task in 147 participants (76 individuals in the early stage of a non-affective psychotic disorder and 71 demographically similar healthy control individuals). Two-year follow-up was completed in 97 individuals (50 early psychosis, 47 healthy control). Voxelwise longitudinal analysis of activation in response to scenes was carried out within a hippocampal region of interest to test for group differences at baseline and a group by time interaction. RESULTS: At baseline, we observed lower anterior hippocampal activation in the early psychosis group relative to the healthy control group. Contrary to our hypothesis, hippocampal activation remained consistent and did not show the predicted decline over 2 years in the early psychosis group. Healthy controls showed a modest reduction in hippocampal activation after 2 years. CONCLUSIONS: The results of this study suggest that hippocampal dysfunction in early psychosis does not worsen over 2 years and highlight the need for longer-term longitudinal studies.