fMRI Acquisition Research Articles

High-Resolution Oscillating Steady-State fMRI Using Patch-Tensor Low-Rank Reconstruction.

The goals of fMRI acquisition include high spatial and temporal resolutions with a high signal to noise ratio (SNR). Oscillating Steady-State Imaging (OSSI) is a new fMRI acquisition method that provides large oscillating signals with the potential for high SNR, but does so at the expense of spatial and temporal resolutions. The unique oscillation pattern of OSSI images makes it well suited for high-dimensional modeling. We propose a patch-tensor low-rank model to exploit the local spatial-temporal low-rankness of OSSI images. We also develop a practical sparse sampling scheme with improved sampling incoherence for OSSI. With an alternating direction method of multipliers (ADMM) based algorithm, we improve OSSI spatial and temporal resolutions with a factor of 12 acquisition acceleration and 1.3 mm isotropic spatial resolution in prospectively undersampled experiments. The proposed model yields high temporal SNR with more activation than other low-rank methods. Compared to the standard grad- ient echo (GRE) imaging with the same spatial-temporal resolution, 3D OSSI tensor model reconstruction demonstrates 2 times higher temporal SNR with 2 times more functional activation.

Frontoparietal network activity during model-based reinforcement learning updates is reduced among adolescents with severe sexual abuse

Trauma and trauma-related disorders are characterized by impaired learning processes, including reinforcement learning (RL). Identifying which aspects of learning are altered by trauma is critical endeavor, as this may reveal key mechanisms of impairment and potential intervention targets. There are at least two types of RL that have been delineated using computational modeling: model-free and model-based RL. Although these RL processes differentially predict decision-making behavior, most research has examined the impact of trauma on model-free RL. Currently unclear whether model-based RL, which involves building abstract and nuanced representations of stimulus-outcome relationships, is impaired among individuals with a history of trauma. The present study sought to test the hypothesis of impaired model-based RL among adolescent females exposed to assaultive trauma. Participants (n = 60; 29 without a history of assault and 31 with a history of assault with and without PTSD) completed a three-arm bandit task during fMRI acquisition. Two computational models compared the degree to which participants’ task behavior fit the use of a model-free versus model-based RL strategy. Although a history of assaultive trauma did not predict poorer model-based RL, greater sexual abuse severity predicted less use of model-based compared to model-free RL. Additionally, severe sexual abuse predicted less left frontoparietal network encoding of model-based RL updates. Altered model-based RL, which supports goal-directed behavior, may be an important route through which clinical impairment emerges among individuals with a history of severe sexual abuse and should be examined further in future studies.

A Neuroimaging Preparation Protocol Tailored for Autism.

This paper describes the key basic elements required for a successful multi-parametric MRI data acquisition in awake children with autism. The procedure was designed by taking into account methodological challenges arising from the acquisition of Resting State fMRI (RS fMRI) data, and factors such as cost, time, and staff availability. The ultimate aim was to prepare an imaging preparation protocol with high transferability to the whole autism spectrum, adaptable for use in a multi-site research with multiple time points. As part of a randomized pharmaco-intervention study, 31 children aged 4-10 years with Neurofibromatosis 1 and autism underwent MR imaging at baseline and end of intervention. The protocol consisted of tailored habituation instructions including gradual exposure to scanner noise, a social stories booklet, positive incentive strategies, and Play Therapy support. Success rate for initial acquisition was 71% for GABA+ MR spectroscopy at either location, 87% for perfusion, and 67% for diffusion assessment, and 71% for RS fMRI. Qualitative data indicated that 84% parents found the habituation protocol helpful. LAY SUMMARY: Here we describe a protocol for brain Magnetic Resonance Imaging (MRI) tailored for children with ASD to help reduce stress and avoid sedation during scanning. This procedure can make advanced medical imaging more accessible and promote a better MRI experience for families of children with ASD.

Interrelations between dopamine and serotonin producing sites and regions of the default mode network.

Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level‐dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5‐HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top‐down information flow in the resting‐state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5‐HT. We found that latencies range from milliseconds to seconds with high inter‐subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.

New acquisition techniques and their prospects for the achievable resolution of fMRI.

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

Postsynaptic activity of inhibitory neurons evokes hemodynamic fMRI responses

Functional MRI responses are localized to the synaptic sites of evoked inhibitory neurons, but it is unknown whether, or by what mechanisms, these neurons initiate functional hyperemia. Here, the neuronal origins of these hemodynamic responses were investigated by fMRI or local field potential and blood flow measurements during topical application of pharmacological agents when GABAergic granule cells in the rat olfactory bulb were synaptically targeted. First, to examine if postsynaptic activation of these inhibitory neurons was required for neurovascular coupling, we applied an NMDA receptor antagonist during cerebral blood volume-weighted fMRI acquisition and found that responses below the drug application site (up to ~1.5 mm) significantly decreased within ~30 min. Similarly, large decreases in granule cell postsynaptic activities and blood flow responses were observed when AMPA or NMDA receptor antagonists were applied. Second, inhibition of nitric oxide synthase preferentially decreased the initial, fast component of the blood flow response, while inhibitors of astrocyte-specific glutamate transporters and vasoactive intestinal peptide receptors did not decrease blood flow responses. Third, inhibition of GABA release with a presynaptic GABAB receptor agonist caused less reduction of neuronal and blood flow responses compared to the postsynaptic glutamate receptor antagonists. In conclusion, local hyperemia by synaptically-evoked inhibitory neurons was primarily driven by their postsynaptic activities, possibly through NMDA receptor-dependent calcium signaling that was not wholly dependent on nitric oxide.

Rotated spiral RARE for high spatial and temporal resolution volumetric arterial spin labeling acquisition

BackgroundArterial Spin Labeling (ASL) MRI can provide quantitative images that are sensitive to both time averaged blood flow and its temporal fluctuations. 3D image acquisitions for ASL are desirable because they are more readily compatible with background suppression to reduce noise, can reduce signal loss and distortion, and provide uniform flow sensitivity across the brain. However, single-shot 3D acquisition for maximal temporal resolution typically involves degradation of image quality through blurring or noise amplification by parallel imaging. Here, we report a new approach to accelerate a common stack of spirals 3D image acquisition by pseudo golden-angle rotation and compressed sensing reconstruction without any degradation of time averaged blood flow images. Methods28 healthy volunteers were imaged at 3T with background-suppressed unbalanced pseudo-continuous ASL combined with a pseudo golden-angle Stack-of-Spirals 3D RARE readout. A fully-sampled perfusion-weighted volume was reconstructed by 3D non-uniform Fast Fourier Transform (nuFFT) followed by sum-of-squares combination of the 32 individual channels. Coil sensitivities were estimated followed by reconstruction of the 39 single-shot volumes using an L1-wavelet Compressed-Sensing reconstruction. Finally, brain connectivity analyses were performed in regions where BOLD signal suffers from low signal-to-noise ratio and susceptibility artifacts. ResultsImage quality, assessed with a non-reference 3D blurring metric, of full time averaged blood flow was comparable to a conventional interleaved acquisition. The temporal resolution provided by the acceleration enabled identification and quantification of resting-state networks even in inferior regions such as the amygdala and inferior frontal lobes, where susceptibility artifacts can degrade conventional resting-state fMRI acquisitions. ConclusionThis approach can provide measures of blood flow modulations and resting-state networks for free within any research or clinical protocol employing ASL for resting blood flow.

Re-imagining fMRI for awake behaving infants

Thousands of functional magnetic resonance imaging (fMRI) studies have provided important insight into the human brain. However, only a handful of these studies tested infants while they were awake, because of the significant and unique methodological challenges involved. We report our efforts to address these challenges, with the goal of creating methods for awake infant fMRI that can reveal the inner workings of the developing, preverbal mind. We use these methods to collect and analyze two fMRI datasets obtained from infants during cognitive tasks, released publicly with this paper. In these datasets, we explore and evaluate data quantity and quality, task-evoked activity, and preprocessing decisions. We disseminate these methods by sharing two software packages that integrate infant-friendly cognitive tasks and eye-gaze monitoring with fMRI acquisition and analysis. These resources make fMRI a feasible and accessible technique for cognitive neuroscience in awake and behaving human infants.

SLIMM: Slice localization integrated MRI monitoring

Functional MRI (fMRI) is extremely challenging to perform in subjects who move because subject motion disrupts blood oxygenation level dependent (BOLD) signal measurement. It has become common to use retrospective framewise motion detection and censoring in fMRI studies to eliminate artifacts arising from motion. Data censoring results in significant loss of data and statistical power unless the data acquisition is extended to acquire more data not corrupted by motion. Acquiring more data than is necessary leads to longer than necessary scan duration, which is more expensive and may lead to additional subject non-compliance. Therefore, it is well established that real-time prospective motion monitoring is crucial to ensure data quality and reduce imaging costs. In addition, real-time monitoring of motion allows for feedback to the operator and the subject during the acquisition, to enable intervention to reduce the subject motion. The most widely used form of motion monitoring for fMRI is based on volume-to-volume registration (VVR), which quantifies motion as the misalignment between subsequent volumes. However, motion is not constrained to occur only at the boundaries of volume acquisition, but instead may occur at any time. Consequently, each slice of an fMRI acquisition may be displaced by motion, and assessment of whole volume to volume motion may be insensitive to both intra-volume and inter-volume motion that is revealed by displacement of the slices. We developed the first slice-by-slice self-navigated motion monitoring system for fMRI by developing a real-time slice-to-volume registration (SVR) algorithm. Our real-time SVR algorithm, which is the core of the system, uses a local image patch-based matching criterion along with a Levenberg-Marquardt optimizer, all accelerated via symmetric multi-processing, with interleaved and simultaneous multi-slice acquisition schemes. Extensive experimental results on real motion data demonstrated that our fast motion monitoring system, named Slice Localization Integrated MRI Monitoring (SLIMM), provides more accurate motion measurements than a VVR based approach. Therefore, SLIMM offers improved online motion monitoring which is particularly important in fMRI for challenging patient populations. Real-time motion monitoring is crucial for online data quality control and assurance, for enabling feedback to the subject and the operator to act to mitigate motion, and in adaptive acquisition strategies that aim to ensure enough data of sufficient quality is acquired without acquiring excess data.

Resting State Cortico-Limbic Functional Connectivity and Dispositional Use of Emotion Regulation Strategies: A Replication and Extension Study.

Neuroimaging functional connectivity analyses have shown that the negative coupling between the amygdala and cortical regions is linked to better emotion regulation (ER) in experimental task settings. However, less is known about the neural correlates of ER traits or dispositions. The present study aimed to: (1) replicate the findings of differential cortico-limbic coupling during resting-state depending on the dispositional use of emotion regulation strategies. Furthermore, the study aimed to: (2) extend prior findings by examining whether differences in cortico-limbic coupling during resting-state predict experiential and neuronal ER success in a standard ER task. To this end, N = 107 healthy adults completed the Emotion Regulation Questionnaire (ERQ), underwent an 8-min resting-state fMRI acquisition, and completed a reappraisal task during fMRI. Functional connectivity maps of basolateral and centromedial amygdala nuclei were estimated with a seed-based approach regarding associations with regions of the prefrontal cortex and were then correlated with ERQ scores as well as experiential and neuronal ER success. All hypotheses and the analysis plan are preregistered at https://osf.io/8wsgu. Opposed to prior findings, we were not able to replicate a correlation of dispositional ER strategy use with functional connectivity between the amygdala and PFC regions (p > 0.05, FWE-corrected). Furthermore, there was no association of experiential and neuronal reappraisal success with functional connectivity between amygdala and insula as well as PFC (p > 0.05, FWE-corrected). The present preregistered study calls into question the reported association between individual differences in resting-state cortico-limbic connectivity and dispositional use of ER strategies. However, ongoing advances in functional brain imaging and distributed network approaches may leverage the identification of reliable functional connectivity patterns that underlie successful emotion regulation.

The neural basis of metacognitive monitoring during arithmetic in the developing brain.

In contrast to a substantial body of research on the neural basis of cognitive performance in several academic domains, less is known about how the brain generates metacognitive (MC) awareness of such performance. The existing work on the neurobiological underpinnings of metacognition has almost exclusively been done in adults and has largely focused on lower level cognitive processing domains, such as perceptual decision‐making. Extending this body of evidence, we investigated MC monitoring by asking children to solve arithmetic problems, an educationally relevant higher‐order process, while providing concurrent MC reports during fMRI acquisition. Results are reported on 50 primary school children aged 9–10 years old. The current study is the first to demonstrate that brain activity during MC monitoring, relative to the control task, increased in the left inferior frontal gyrus in children. This brain activity further correlated with children's arithmetic development over a 3‐year time period. These data are in line with the frequently suggested, yet never empirically tested, hypothesis that activity in the prefrontal cortex during arithmetic is related to the higher‐order process of MC monitoring.

Neural and behavioral correlates of inhibitory control in youths with varying levels of irritability

BackgroundIrritability, a relatively lowered threshold for anger, is prevalent in typically and atypically developing youths. Inhibitory control, the ability to suppress behaviors counter to goals, is essential for regulating emotions, including anger. Understanding how irritability relates to behavioral and neural markers of inhibitory control may inform interventions. MethodsYouths (N=52; mean age=13.78) completed a Flanker task on an iPad to measure behavioral correlates of inhibitory control; a subsample (n=19; mean age=13.21) additionally completed a similar task while undergoing fMRI acquisition to evaluate inhibitory control on a neural level. Irritability was measured using the Affective Reactivity Index. Associations between irritability and inhibitory control were evaluated behaviorally (via Pearson correlations), and neurally (via ANCOVAs with whole-brain activation and amygdala connectivity). ResultsfMRI results indicated that higher levels of irritability were associated with aberrant activation (in middle frontal gyrus, amygdala/parahippocampal gyrus, anterior cingulate, lentiform nucleus/striatum) and left amygdala connectivity (with middle temporal gyrus, parahippocampal gyrus, posterior cingulate, fusiform gyrus, and thalamus). Behavioral results were mixed. LimitationsLongitudinal studies are needed to characterize changes in neural circuitry and delineate whether the brain profiles precede or are a consequence of symptoms. Larger samples powered to examine multiple irritability-related symptom dimensions will be necessary to elucidate shared vs. disorder-specific irritability mechanisms. ConclusionsFindings suggest that pediatric irritability may be related to neural processes involving inhibitory control. Further, findings underscore the importance of neuroimaging in investigating symptom dimensions such as irritability, as neuroimaging may be more sensitive in detecting underlying abnormalities compared to behavioral data alone.

Concurrent electrophysiological and hemodynamic measurements of evoked neural oscillations in human visual cortex using sparsely interleaved fast fMRI and EEG

Electroencephalography (EEG) concurrently collected with functional magnetic resonance imaging (fMRI) is heavily distorted by the repetitive gradient coil switching during the fMRI acquisition. The performance of the typical template-based gradient artifact suppression method can be suboptimal because the artifact changes over time. Gradient artifact residuals also impede the subsequent suppression of ballistocardiography artifacts.Here we propose recording continuous EEG with temporally sparse fast fMRI (fast fMRI-EEG) to minimize the EEG artifacts caused by MRI gradient coil switching without significantly compromising the field-of-view and spatiotemporal resolution of fMRI. Using simultaneous multi-slice inverse imaging to achieve whole-brain fMRI with isotropic 5-mm resolution in 0.1 ​s, and performing these acquisitions once every 2 ​s, we have 95% of the duty cycle available to record EEG with substantially less gradient artifact. We found that the standard deviation of EEG signals over the entire acquisition period in fast fMRI-EEG was reduced to 54% of that in conventional concurrent echo-planar imaging (EPI) and EEG recordings (EPI-EEG) across participants. When measuring 15-Hz steady-state visual evoked potentials (SSVEPs), the baseline-normalized oscillatory neural response in fast fMRI-EEG was 2.5-fold of that in EPI-EEG. The functional MRI responses associated with the SSVEP delineated by EPI and fast fMRI were similar in the spatial distribution, the elicited waveform, and detection power. Sparsely interleaved fast fMRI-EEG provides high-quality EEG without substantially compromising the quality of fMRI in evoked response measurements, and has the potential utility for applications where the onset of the target stimulus cannot be precisely determined, such as epilepsy.

Neuroplasticity and brain reorganization associated with positive outcomes of multidisciplinary rehabilitation in progressive multiple sclerosis: A fMRI study

BackgroundMultiple sclerosis (MS) is characterized by a range of symptoms, including motor, sensorimotor and cognitive impairments, that limit the quality of life. A multidisciplinary rehabilitation approach in people affected by multiple sclerosis was recently reported to improve the functional abilities of MS patients in daily activities. The purpose of the study was to assess the effect of multidisciplinary rehabilitation on the whole brain of MS patients by means of functional magnetic resonance imaging (fMRI). MethodsThirty individuals affected by MS (49.9 ± 12.1 years; disease duration: 16.0 ± 8.5 years) with a medium-high severity of disease were enrolled. The fMRI examination assessed a range of action-related tasks involving passive movement, mental simulation of action and miming of action triggered by external stimuli, such as object photography. The three tasks were performed using each arm separately. The fMRI acquisitions were performed at T1 (inclusion in the study), T2 (3 months later, at the start of rehabilitation) and T3 (after 3 months of multidisciplinary rehabilitation). ResultsThe fMRI results revealed a significant reduction in the activity of brain areas related to task-specific networks as well as the activation of cerebral regions not usually involved in task-specific related network, such as the medial prefrontal area. ConclusionsThe effectiveness of multidisciplinary rehabilitation on activity and participation has been established in previous studies. Our study sheds new light on the effect of such treatment on brain reorganization.

Vascular physiology drives functional brain networks

We present the first evidence for vascular regulation driving fMRI signals in specific functional brain networks. Using concurrent neuronal and vascular stimuli, we collected 30 BOLD fMRI datasets in 10 healthy individuals: a working memory task, flashing checkerboard stimulus, and CO2 inhalation challenge were delivered in concurrent but orthogonal paradigms. The resulting imaging data were averaged together and decomposed using independent component analysis, and three “neuronal networks” were identified as demonstrating maximum temporal correlation with the neuronal stimulus paradigms: Default Mode Network, Task Positive Network, and Visual Network. For each of these, we observed a second network component with high spatial overlap. Using dual regression in the original 30 datasets, we extracted the time-series associated with these network pairs and calculated the percent of variance explained by the neuronal or vascular stimuli using a normalized R2 parameter. In each pairing, one network was dominated by the appropriate neuronal stimulus, and the other was dominated by the vascular stimulus as represented by the end-tidal CO2 time-series recorded in each scan. We acquired a second dataset in 8 of the original participants, where no CO2 challenge was delivered and CO2 levels fluctuated naturally with breathing variations. Although splitting of functional networks was not robust in these data, performing dual regression with the network maps from the original analysis in this new dataset successfully replicated our observations. Thus, in addition to responding to localized metabolic changes, the brain’s vasculature may be regulated in a coordinated manner that mimics (and potentially supports) specific functional brain networks. Multi-modal imaging and advances in fMRI acquisition and analysis could facilitate further study of the dual nature of functional brain networks. It will be critical to understand network-specific vascular function, and the behavior of a coupled vascular-neural network, in future studies of brain pathology.

Association of Different Types of Externalizing Conditions With Head Motion (HM) During fMRI Acquisition

Association of Different Types of Externalizing Conditions With Head Motion (HM) During fMRI Acquisition

Functional, anatomical and diffusion tensor MRI study of radiology expertise.

BackgroundRepeated practice to acquire expertise could result in the structural and functional changes in relevant brain circuits as a result of long-term potentiation, neurogenesis, glial genesis, and remodeling.PurposeThe goal of this study is to use task fMRI to study the brain of expert radiologists performing a diagnosis task where a series of medical images were presented during fMRI acquisition for 12s and participants were asked to choose a diagnosis. Structural and diffusion-tensor MRI were also acquired.MethodsRadiologists (N = 12, 11M, 38.2±10.3 years old) and non-radiologists (N = 17, 15M, 30.6±5.5 years old) were recruited with informed consent. Medical images were presented for 12 s and three multiple choices were displayed and the participants were asked to choose a diagnosis. fMRI, structural and diffusion-tensor MRI were acquired. fMRI analysis used FSL to determine differences in fMRI responses between groups. Voxel-wise analysis was performed to determine if subcortical volume, cortical thickness and fractional anisotropy differed between groups. Correction for multiple comparisons used false discovery rate.ResultsRadiologists showed overall lower task-related brain activation than non-radiologists. Radiologists showed significantly lower activation in the left lateral occipital cortex, left superior parietal lobule, occipital pole, right superior frontal and precentral gyri, lingual gyrus, and the left intraparietal sulcus (p<0.05). There were no significant differences between groups in cortical thickness, subcortical volume and fractional anisotropy (p>0.05).ConclusionsRadiologists and non-radiologists had no significant difference in structural metrics. However, in diagnosis tasks, radiologists showed markedly lower task-related brain activations overall as well as a number of high-order visual and non-visual brain regions than non-radiologists. Some brain circuits appear to be uniquely associated with differential-diagnosis paradigm expertise that are not involved in simpler object-recognition cases. Improved understanding of the brain circuitry involved in acquisition of expertise might be used to design optimal training paradigms.

Presurgical Localization of the Primary Sensorimotor Cortex in Gliomas

PurposeFunctional magnetic resonance imaging (fMRI) has an established role in neurosurgical planning; however, ambiguity surrounds the comparative value of resting and task-based fMRI relative to anatomical localization of the sensorimotor cortex. This study was carried out to determine: 1) how often fMRI adds to prediction of motor risks beyond expert neuroradiological review, 2) success rates of presurgical resting and task-based sensorimotor mapping, and 3) the impact of accelerated resting fMRI acquisitions on network detectability.MethodsData were collected at 2 centers from 71 patients with a primary brain tumor (31 women; mean age 41.9 ± 13.9 years) and 14 healthy individuals (6 women; mean age 37.9 ± 12.7 years). Preoperative 3T MRI included anatomical scans and resting fMRI using unaccelerated (TR = 3.5 s), intermediate (TR = 1.56 s) or high temporal resolution (TR = 0.72 s) sequences. Task fMRI finger tapping data were acquired in 45 patients. Group differences in fMRI reproducibility, spatial overlap and success frequencies were assessed with t‑tests and χ2-tests.ResultsRadiological review identified the central sulcus in 98.6% (70/71) patients. Task-fMRI succeeded in 100% (45/45). Resting fMRI failed to identify a sensorimotor network in up to 10 patients; it succeeded in 97.9% (47/48) of accelerated fMRIs, compared to only 60.9% (14/23) of unaccelerated fMRIs (chi(2) = 17.84, p < 0.001). Of the patients 12 experienced postoperative deterioration, largely predicted by anatomical proximity to the central sulcus.ConclusionThe use of fMRI in patients with residual or intact presurgical motor function added value to uncertain anatomical localization in just a single peri-Rolandic glioma case. Resting fMRI showed high correspondence to task localization when acquired with accelerated sequences but offered limited success at standard acquisitions.

Attention shifting in the context of emotional faces: Disentangling neural mechanisms of irritability from anxiety.

Irritability predicts concurrent and prospective psychiatric disorders across the lifespan. Anxiety commonly co-occurs with irritability, and such comorbidity complicates care. Understanding the mechanisms of comorbid traits is necessary to inform treatment decisions. This study aimed to disentangle neural mechanisms of irritability from anxiety in the context of attentional shifting toward and away from emotional faces in youths from treatment-seeking families. Youths (N = 45), mean age = 14.01 years (standard deviation = 1.89) completed a dot-probe task during functional magnetic resonance imaging acquisition. Whole-brain activation analyses evaluated the effect of irritability on neural reactivity in the context of varying attentional shifting toward and away from emotional faces, both depending on and above and beyond anxiety (i.e., with anxiety as [a] a moderator and [b] a covariate, respectively). Higher irritability levels related to distinct task-related patterns of cuneus activation, depending on comorbid anxiety levels. Increased irritability also related to distinct task-related patterns of parietal, temporal, occipital, and cerebellar activation, controlling for anxiety. Overall, youths with higher levels of irritability evinced more pronounced fluctuations in neural reactivity across task conditions. The present study contributes to a literature delineating the unique and shared neural mechanisms of overlapping symptom dimensions, which will be necessary to ultimately build a brain- and behavior-based nosology that forms the basis for more targeted and effective treatments.

Improved motion correction for functional MRI using an omnibus regression model.

Head motion during functional Magnetic Resonance Imaging acquisition can significantly contaminate the neural signal and introduce spurious, distance-dependent changes in signal correlations. This can heavily confound studies of development, aging, and disease. Previous approaches to suppress head motion artifacts have involved sequential regression of nuisance covariates, but this has been shown to reintroduce artifacts. We propose a new motion correction pipeline using an omnibus regression model that avoids this problem by simultaneously regressing out multiple artifacts using the best performing algorithms to estimate each artifact. We quantitatively evaluate its motion artifact suppression performance against sequential regression pipelines using a large heterogeneous dataset (n=151) which includes high-motion subjects and multiple disease phenotypes. The proposed concatenated regression pipeline significantly reduces the association between head motion and functional connectivity while significantly outperforming the traditional sequential regression pipelines in eliminating distance-dependent head motion artifacts.