Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI

Reciprocal causation relationship between rumination thinking and sleep quality: a resting-state fMRI study

Rumination thinking is a type of negative repetitive thinking, a tendency to constantly focus on the causes, consequences and other aspects of negative events, which has implications for a variety of psychiatric disorders. Previous studies have confirmed a strong association between rumination thinking and poor sleep or insomnia, but the direction of causality between the two is not entirely clear. This study examined the relationship between rumination thinking and sleep quality using a longitudinal approach and resting-state functional MRI data. Participants were 373 university students (males: n = 84, 18.67 ± 0.76 years old) who completed questionnaires at two time points (T1 and T2) and had resting-state MRI data collected. The results of the cross-lagged model analysis revealed a bidirectional causal relationship between rumination thinking and sleep quality. Additionally, the functional connectivity (FC) of the precuneus and lingual gyrus was found to be negatively correlated with rumination thinking and sleep quality. Furthermore, mediation analysis showed that rumination thinking at T1 fully mediated the relationship between FC of the precuneus-lingual and sleep quality at T2. These findings suggest that rumination thinking and sleep quality are causally related in a bidirectional manner and that the FC of the precuneus and lingual gyrus may serve as the neural basis for rumination thinking to predict sleep quality. Overall, this study provides new insights for enhancing sleep quality and promoting overall health.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-025-10223-3.

Developmental patterns of white matter functional networks in neonates

In recent years, the development of neonatal brain networks has become a research focus, with traditional studies primarily emphasizing gray matter (GM) functional networks. This study systematically explores the developmental characteristics of white matter (WM) functional networks in neonates. Utilizing data from the third release of the Developing Human Connectome Project (dHCP), we analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from 730 full-term and 157 preterm neonates. We successfully identified ten large-scale WM functional networks and validated their correspondence with established WM fiber tracts using diffusion tensor imaging (DTI). We examined WM functional networks from two dimensions: network functional connectivity and spontaneous activity, incorporating four factors: preterm birth status, age, sex, and hemispheric differences. The results indicate that WM network functional connectivity significantly increases with age, with preterm infants exhibiting lower connectivity than full-term infants, whereas no significant differences were observed between sexes or hemispheres. Regarding spontaneous activity, preterm infants showed lower amplitude in the low-frequency range, whereas in the high-frequency range, their amplitude distribution was more unstable and dispersed. Additionally, certain differences in spontaneous activity were observed between hemispheres and sexes. These findings provide novel insights into the early development of neonatal brain networks and hold significant implications for clinical interventions and treatment strategies for preterm infants.

Multi-Metric Approach for the Comparison of Denoising Techniques for Resting-State fMRI

Despite the increasing use of resting-state functional magnetic resonance imaging (rs-fMRI) data for studying the spontaneous functional interactions within the brain, the achievement of robust results is often hampered by insufficient data quality and by poor knowledge of the most effective denoising methods. The present study aims to define an appropriate denoising strategy for rs-fMRI data by proposing a robust framework for the quantitative and comprehensive comparison of the performance of multiple pipelines made available by the newly proposed HALFpipe software. This will ultimately contribute to standardizing rs-fMRI preprocessing and denoising steps. Fifty-three participants took part in the study by undergoing a rs-fMRI session. Synthetic rs-fMRI data from one subject were also generated. Nine different denoising pipelines were applied in parallel to the minimally preprocessed fMRI data. The comparison was conducted by computing previously proposed and novel metrics that quantify the degree of artifact removal, signal enhancement, and resting-state network identifiability. A summary performance index, accounting for both noise removal and information preservation, was proposed. The results confirm the performance heterogeneity of different denoising pipelines across the different quality metrics. In both real and synthetic data, the summary performance index favored the denoising strategy including the regression of mean signals from white matter and cerebrospinal fluid brain areas and global signal. This pipeline resulted in the best compromise between artifact removal and preservation of the information on resting-state networks. Our study provided useful methodological tools and key information on the effectiveness of multiple denoising strategies for rs-fMRI data. Besides providing a robust comparison approach that could be adapted to other fMRI studies, a suitable denoising pipeline for rs-fMRI data was identified, which could be used to improve the reproducibility of rs-fMRI findings.

Left Ventral Caudate Functional Connectivity Mediates the Relationship Between Habitual Responding and Alcohol Use

Preclinical studies posit that habitual behaviour is an important mechanism in the development of alcohol use disorder (AUD), but human findings are unclear. The goals of this study were to test a behavioural measure of habit formation, the Slips of Action Task (SOAT), in humans and identify brain-based mechanisms explaining the relationship between habit and alcohol use. Thirty-six participants (63.9% female, mean age = 30.58, SD = 9.73, 69.4% White, 83.3% Not Hispanic/Latino) who endorsed heavy drinking completed self-report measures, the SOAT (lower scores = higher habit formation), a 2.5-h intravenous alcohol self-administration session, and a resting-state functional magnetic resonance imaging scan. Three seed regions-bilateral ventral caudate, nucleus accumbens and dorsal caudate-were assessed for significant whole brain functional connectivity (FC) associations with SOAT (cluster-level pFWE < 0.05 at a cluster-forming threshold p = 0.001). Two clusters survived Bonferroni correction (cluster pFWE = 0.008): FC between the left ventral caudate and the left middle frontal gyrus correlated negatively, while FC between the left NAc and the right central operculum correlated positively, with SOAT score. SOAT score was unrelated to drinking outcomes; however, there was a significant indirect relationship between SOAT and average drinks per drinking day through FC between the left ventral caudate and the left middle frontal gyrus. A similar trend seen with cumulative work for alcohol fell short of significance. Habit formation's relationship with alcohol use may function through neuroadaptations in the ventral caudate. More work is needed to better characterize objective habit formation in the human alcohol laboratory with additional laboratory-, alcohol-specific, imaging- and ambulatory-based alcohol use metrics.

Characterizing the distribution of neural and non-neural components in multi-echo EPI data across echo times based on tensor-ICA

Multi-echo echo-planar imaging (ME-EPI) acquires images at multiple echo times (TEs), enabling the differentiation of BOLD and non-BOLD fluctuations through TE-dependent analysis of transverse relaxation time and initial intensity. Decomposing ME-EPI in tensor space is a promising approach to characterize the distribution of changes across TEs (TE patterns) directly and aid the classification of components by providing information from an additional domain. In this study, the tensorial extension of independent component analysis (tensor-ICA) is used to characterize the TE patterns of neural and non-neural components in ME-EPI data. With the constraints of independent spatial maps, an ME-EPI dataset was decomposed into spatial, temporal, and TE domains to understand the TE patterns of noise or signal-related independent components. Our analysis revealed three distinct groups of components based on their TE patterns. Motion-related and other non-BOLD origin components followed decreased TE patterns. While the long-TE-peak components showed a large overlay on grey matter and signal patterns, the components that peaked at short TEs reflected noise that may be related to the vascular system, respiration, or cardiac pulsation, amongst others. Accordingly, removing short-TE peak components as part of a denoising strategy significantly improved quality control metrics and revealed clearer, more interpretable activation patterns compared to non-denoised data. To our knowledge, this work is the first application of decomposing ME-EPI in a tensor way. Our findings demonstrate that tensor-ICA is efficient in decomposing ME-EPI and characterizing the neural and non-neural TE patterns aiding in classifying components which is important for denoising fMRI data.

Network segregation during episodic memory shows age-invariant relations with memory performance from 7 to 82 years

Lower episodic memory capability, as seen in development and aging compared with younger adulthood, may partly depend on lower brain network segregation. Here, our objective was twofold: (1) test this hypothesis using within- and between-network functional connectivity (FC) during episodic memory encoding and retrieval, in two independent samples (n = 734, age 7-82 years). (2) Assess associations with age and the ability to predict memory comparing task-general FC and memory-modulated FC. In a multiverse-inspired approach, we performed tests across multiple analytic choices. Results showed that relationships differed based on these analytic choices and were mainly present in the largest dataset,. Significant relationships indicated that (i) memory-modulated FC predicted memory performance and associated with memory in an age-invariant manner. (ii) In line with the so-called neural dedifferentiation view, task-general FC showed lower segregation with higher age in adults which was associated with worse memory performance. In development, although there were only weak signs of a neural differentiation, that is, gradually higher segregation with higher age, we observed similar lower segregation-worse memory relationships. This age-invariant relationships between FC and episodic memory suggest that network segregation is pivotal for memory across the healthy lifespan.

Sex differences in Cingulo-Opercular activation during risky decision-making in youth with externalizing disorders

BACKGROUND

Risky decision-making deficits predict unsafe behaviors, but sex differences in decision-making are underexplored in high-risk youth with externalizing disorders. While boys with externalizing pathology are more likely to make risky decisions, it remains unclear how these patterns manifest in girls, whose brains may process risks differently. Our study investigates sex differences in risky decision-making neurobiological activation among at-risk adolescents to identify sex-specific vulnerabilities for risky behaviors.

METHOD

168 adolescents divided into four groups of 81 externalizing males, 39 externalizing females, 33 control males, and 15 control females completed a risky decision-making task, the Balloon Analog Risk Task, during functional magnetic resonance imaging.

RESULTS

Our primary finding was that externalizing males showed greater activation in the right dorsomedial prefrontal cortex/dorsal anterior cingulate cortex as the chance of a balloon explosion increased while making riskier choices over safer choices, compared to all other groups.

CONCLUSIONS

These findings highlight key sex differences in the neurobiology of risky decision-making in youth with externalizing psychopathology within the cingulo-opercular network. With this network's involvement in cognitive control and impulse inhibition-functions critical for managing risky behaviors-understanding its role in the interaction between sex and externalizing disorders is crucial for targeted, sex-specific interventions preventing risky behaviors.

Brain activity associated with emotion regulation predicts individual differences in working memory ability

Previous behavioral research has found that working memory is associated with emotion regulation efficacy. However, there has been mixed evidence as to whether the neural mechanisms between emotion regulation and working memory overlap. The present study tested the prediction that individual differences on the working memory subtest of the Weschler Adult Intelligence Scale (WAIS-IV) could be predicted from the pattern of brain activity produced during emotion regulation in regions typically associated with working memory, such as the dorsal lateral prefrontal cortex (dlPFC). A total of 101 participants completed an emotion regulation fMRI task in which they either viewed or reappraised negative images. Participants also completed working memory test outside the scanner. A whole brain covariate analysis contrasting the reappraise negative and view negative BOLD response found that activity in the right dlPFC positively related to working memory ability. Moreover, a multivoxel pattern analysis approach using tenfold cross-validated support vector regression in regions-of-interest associated with working memory, including bilateral dlPFC, demonstrated that we could predict individual differences in working memory ability from the pattern of activity associated with emotion regulation. These findings support the idea that emotion regulation shares underlying cognitive processes and neural mechanisms with working memory, particularly in the dlPFC.

Frontostriatal Networks Undergo Functional Specialization During Adolescence that Follows a Ventral-Dorsal Gradient: Developmental Trajectories and Longitudinal Associations

Seminal studies in animal neuroscience demonstrate that frontostriatal circuits exhibit a ventral-dorsal functional gradient to integrate neural functions related to reward processing and cognitive control. Prominent neurodevelopmental models posit that heightened reward-seeking and risk-taking during adolescence result from maturational imbalances between frontostriatal neural systems underlying reward processing and cognitive control. The present study investigated whether the development of ventral (VS) and dorsal (DS) striatal resting-state connectivity (rsFC) networks along this proposed functional gradient relates to putative imbalances between reward and executive systems posited by a dual neural systems theory of adolescent development. 163 participants aged 11-25 years (54% female, 90% white) underwent resting scans at baseline and biennially thereafter, yielding 339 scans across four assessment waves. We observed developmental increases in VS rsFC with brain areas implicated in reward processing (e.g., subgenual cingulate gyrus and medial orbitofrontal cortex) and concurrent decreases with areas implicated in executive function (e.g., ventrolateral and dorsolateral prefrontal cortices). DS rsFC exhibited the opposite pattern. More rapid developmental increases in VS rsFC with reward areas were associated with developmental improvements in reward-based decision making, whereas increases in DS rsFC with executive function areas were associated with improved executive function, though each network exhibited some crossover in function. Collectively, these findings suggest that typical adolescent neurodevelopment is characterized by a divergence in ventral and dorsal frontostriatal connectivity that may relate to developmental improvements in affective decision-making and executive function.Significance Statement Anatomical studies in nonhuman primates demonstrate that frontostriatal circuits are essential for integration of neural functions underlying reward processing and cognition, with human neuroimaging studies linking alterations in these circuits to psychopathology. The present study characterized the developmental trajectories of frontostriatal resting state networks from childhood to young adulthood. We demonstrate that ventral and dorsal aspects of the striatum exhibit distinct age-related changes that predicted developmental improvements in reward-related decision making and executive function. These results highlight that adolescence is characterized by distinct changes in frontostriatal networks that may relate to normative increases in risk-taking. Atypical developmental trajectories of frontostriatal networks may contribute to adolescent-onset psychopathology.

Tangent space functional reconfigurations in individuals at risk for alcohol use disorder

Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are, nevertheless, scarce. Here, we present a principled mathematical framework to quantify brain functional reconfiguration when engaging and disengaging from a stop signal task (SST). We apply tangent space projection (a Riemannian geometry mapping technique) to transform the functional connectomes (FCs) of 54 participants and quantify functional reconfiguration using the correlation distance of the resulting tangent-FCs. Our goal was to compare functional reconfigurations in individuals at risk for alcohol use disorder (AUD). We hypothesized that functional reconfigurations when transitioning to/from a task would be influenced by family history of AUD (FHA) and other AUD risk factors. Multilinear regression models showed that engaging and disengaging functional reconfiguration were associated with FHA and recent drinking. When engaging in the SST after a rest condition, functional reconfiguration was negatively associated with recent drinking, while functional reconfiguration when disengaging from the SST was negatively associated with FHA. In both models, several other factors contributed to the functional reconfiguration. This study demonstrates that tangent-FCs can characterize task-induced functional reconfiguration and that it is related to AUD risk.

fMRI Activation in Sensorimotor Regions at 6 Weeks After Anterior Cruciate Ligament Reconstruction

BACKGROUND

Brain activity during knee movements is altered throughout the sensorimotor network after anterior cruciate ligament reconstruction (ACLR). Patients at 2 to 5 years after surgery appear to require greater neural activity to perform basic knee movement patterns, but it is unclear if brain activity differences within sensorimotor regions are present early after surgery. It is also unknown whether uninvolved knee movements elicit similar or unique activity compared with involved knee movements.

PURPOSE

To examine brain activity in sensorimotor regions during involved and uninvolved knee movements in patients at 6 weeks after ACLR compared with control participants.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

A total of 15 patients who underwent ACLR (mean age, 21.9 ± 4.3 years [range, 17-29 years]; 8 female) and 15 control participants performed 30-second blocks of repeated knee flexion and extension, followed by 30 seconds of rest, during functional magnetic resonance imaging. Regions of interest included the right and left primary motor cortex (M1), right and left primary somatosensory cortex (S1), supplementary motor area (SMA), precuneus, and lingual gyrus. Activity from task-relevant voxels (move > rest) was extracted, and generalized estimating equations evaluated the main effect of group and group-by-limb interaction. Effect sizes were calculated using the Cohen d.

RESULTS

Reduced brain activity during knee flexion and extension was observed in the ACLR group in the ipsilateral M1 and S1, contralateral S1, SMA, and precuneus during movements of the involved and uninvolved knees. There were no group-by-limb interaction effects, indicating no significant differences between the involved knee and uninvolved knee in the ACLR group. Medium to large effect sizes were identified for between-group differences in all regions.

CONCLUSION

At 6 weeks after ACLR, patients exhibited bilateral reductions in brain activity during knee movements in multiple sensorimotor regions. These identified regions are associated with motor planning, motor execution, somatosensory function, and sensorimotor integration. These data indicate that ACLR affected sensorimotor brain activity in both limbs during the early postoperative phase of rehabilitation.

The role of human intraparietal sulcus in evidence accumulation revealed by EEG and model-informed fMRI: IPS accumulates evidence during decision-making

Sequential sampling models propose that the repeated sampling of sensory information is a fundamental component of perceptual decision-making. Electroencephalographic investigations in humans have demonstrated motor-independent representations of evidence accumulation, but such observations have seldom been made in neuroimaging studies exploring the neuroanatomical origins of evidence accumulation. Here, we aimed to reveal the neuroanatomical locus of sensory evidence accumulation in the human brain by regressing an electrophysiological marker of evidence accumulation (centroparietal positivity, CPP) against changes in blood oxygen level-dependent (BOLD) signal during perceptual decision-making. Our cross-modal imaging approach revealed a cluster within left intraparietal sulcus (IPS), located within putative lateral intraparietal area (region hIP3), for which BOLD signals scaled in relation to the slope of the CPP. Furthermore, the drift rate parameter of a drift diffusion model parametrically modulated BOLD activity within an overlapping region of left IPS. In contrast, parametric modulation by reaction time revealed a distributed fronto-parietal network, demonstrating the utility of our approach for isolating a discrete neuroanatomical locus of evidence accumulation. Together, our findings provide strong support for intraparietal sulcus involvement in the accumulation of sensory evidence during human perceptual decision-making.

Measuring the effects of motion corruption in fetal fMRI

Irregular and unpredictable fetal movement is the most common cause of artifacts in in utero functional magnetic resonance imaging (fMRI), affecting analysis and limiting our understanding of early functional brain development. The accurate detection of corrupted functional connectivity (FC) resulting from motion artifacts or preprocessing, instead of neural activity, is a prerequisite for reliable and valid analysis of FC and early brain development. Approaches to address this problem in adult data are of limited utility in fetal fMRI. In this study, we evaluate a novel technique for robust computational assessment of motion artifacts, and the quantitative comparison of regression models for artifact removal in fetal FC analysis. It exploits the association between dynamic FC and non-stationarity of fetal movement, to detect residual noise. To validate our motion artifact detection technique in detail, we used a parametric generative model for neural events and fMRI blood oxygenation level-dependent (BOLD) signal. We conducted a systematic evaluation of 11 commonly used regression models in a sample of 70 fetuses with gestational age of 19-39 weeks. Results demonstrate that the proposed method has better accuracy in identifying corrupted FC compared to methods designed for adults. The technique, suggests that censoring, global signal regression and anatomical component-based regression models are the most effective models for compensating motion. The benchmarking technique, and the generative model for realistic fetal fMRI BOLD enables investigators conducting in utero fMRI analysis to effectively quantify the impact of fetal motion and evaluate alternative regression strategies for mitigating this impact. The code is publicly available at: https://github.com/cirmuw/fetalfMRIproc.

Peripherally acting anti-CGRP monoclonal antibodies attenuate cortical resting-state connectivity in migraine patients

BACKGROUND

In about half of migraine patients, anti-calcitonin gene-related peptide monoclonal antibodies reduce monthly migraine days by >50%. In these patients, this class of drugs may change cortical functions by decreasing nociceptive afferent barrage. This prospective study investigated functional connectivity changes in treatment responders after three-month treatment with galcanezumab.

METHODS

Resting-state functional magnetic resonance imaging data were acquired for patients with high-frequency episodic or chronic migraine (N = 36) before and after treatment. Of these, 19 patients were classified as treatment responders (≥50% reduction in monthly migraine days) and 17 were considered non-responders (<50% reduction). Functional connectivity across cortical regions was assessed using a region-of-interest (ROI)-to-ROI analysis approach.

RESULTS

At baseline, there were no significant differences between treatment responders and treatment non-responders. In the treatment responder group, reduced functional connectivity was observed after treatment between regions of the primary somatosensory and motor cortices, insula, and several occipital and temporo-occipital areas (within the visual network). In contrast, no such changes were seen in the non-responder group.

CONCLUSION

These findings suggest that even a relatively short period of reduced nociceptive signals may be sufficient to initiate a cortical recovery process in which its resting hyperexcitable mode shifts to a less excitable state.

Neural Activity for Uninvolved Knee Motor Control After ACL Reconstruction Differs from Healthy Controls

Recovery from anterior cruciate ligament reconstruction (ACLR) induces bilateral functional and physiological adaptations. Neurophysiologic measures of motor control have focused on the involved knee joint, limiting understanding regarding the extent of bilateral neural adaptations. Therefore, the aim of this study was to investigate differences in neural activity during uninvolved-limb motor control after ACLR compared to healthy controls.

METHODS

Fifteen participants with left ACLR (8 female and 7 male, 21.53 ± 2.7 years, 173.22 ± 10.0 cm, 72.15 ± 16.1 kg, Tegner 7.40 ± 1.1, 43.33 ± 33.1 mo. post-surgery, 2 patellar tendon, and 13 hamstring) and 15 matched controls (8 female, 23.33 ± 2.7 years, 174.92 ± 9.7 cm, 72.14 ± 15.4 kg, Tegner 7.33 ± 1.0) participated. Neural activity was evaluated using functional magnetic resonance imaging on a 3T Siemens Magnetom scanner during four 30-s cycles of a right (uninvolved) knee flexion-extension task paced with a metronome (1.2 Hz) and was completed interspersed with 30 s of rest. A significance threshold of p < 0.05 was used for all analyses, cluster corrected for multiple comparisons, and z-thresholds of >3.1 (subject level), and >2.3 (group level).

RESULTS

The ACLR group had greater neural activity in one statistically significant cluster corresponding to the left middle frontal gyrus (MFG) (834 voxels, z = 3.81, p < 0.01 multiple comparisons corrected) compared to controls.

CONCLUSIONS

These data indicate a potential contribution to uninvolved-knee neuromuscular deficits after injury and support the limitations of using the uninvolved side as a clinical reference. Uninvolved knee motor control after ACLR may require greater cognitive demand. Clinicians should be aware that the uninvolved limb might also demonstrate whole brain alterations limiting clinical inference from functional symmetry.

Motor Signature Differences Between Autism Spectrum Disorder and Developmental Coordination Disorder, and Their Neural Mechanisms

Autism spectrum disorder (ASD) and Developmental Coordination Disorder (DCD) are distinct clinical groups with overlapping motor features. We attempted to (1) differentiate children with ASD from those with DCD, and from those typically developing (TD) (ages 8-17; 18 ASD, 16 DCD, 20 TD) using a 5-min coloring game on a smart tablet and (2) identify neural correlates of these differences. We utilized standardized behavioral motor assessments (e.g. fine motor, gross motor, and balance skills) and video recordings of a smart tablet task to capture any visible motor, behavioral, posture, or engagement differences. We employed machine learning analytics of motor kinematics during a 5-min coloring game on a smart tablet. Imaging data was captured using functional magnetic resonance imaging (fMRI) during action production tasks. While subject-rated motor assessments could not differentiate the two clinical groups, machine learning computational analysis provided good predictive discrimination: between TD and ASD (76% accuracy), TD and DCD (78% accuracy), and ASD and DCD (71% accuracy). Two kinematic markers which strongly drove categorization were significantly correlated with cerebellar activity. Findings demonstrate unique neuromotor patterns between ASD and DCD relate to cerebellar function and present a promising route for computational techniques in early identification. These are promising preliminary results that warrant replication with larger samples.

Negative valence in Obsessive-Compulsive Disorder: A worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium

OBJECTIVE

Obsessive-compulsive disorder (OCD) is associated with altered brain function related to processing of negative emotions. To investigate neural correlates of negative valence in OCD, we pooled fMRI data of 633 individuals with OCD and 453 healthy controls from 16 studies using different negatively-valenced tasks across the ENIGMA-OCD Working-Group.

METHODS

Participant data were processed uniformly using HALFpipe, to extract voxelwise participant-level statistical images of one common first-level contrast: negative vs. neutral stimuli. In pre-registered analyses, parameter estimates were entered into Bayesian multilevel models to examine whole-brain and regional effects of OCD and its clinically relevant features - symptom severity, age of onset, and medication status.

RESULTS

We provided a proof-of-concept that participant-level data can be combined across several task paradigms and observed one common task activation pattern across individuals with OCD and controls that encompasses fronto-limbic and visual areas implicated in negative valence. Compared to controls, individuals with OCD showed very strong evidence of weaker activation of the bilateral occipital cortex (P+<0.001) and adjacent visual processing regions during negative valence processing that was related to greater OCD severity, late-onset of disease and an unmedicated status. Individuals with OCD also showed stronger activation in the orbitofrontal, subgenual anterior cingulate and ventromedial prefrontal cortex (all P+<0.1) that was related to greater OCD severity and late onset.

CONCLUSION

In the first mega-analysis of this kind, we replicate previous findings of stronger ventral prefrontal activation in OCD during negative valence processing and highlight the lateral occipital cortex as an important region implicated in altered negative valence processing.

Brain activity during working memory in patients with autoimmune Addison's disease

Autoimmune Addison's disease (AAD) is treated with daily oral hormone replacements for cortisol and aldosterone. The current treatment is sub-optimal, and frequently results in supra- and infra-physiological cortisol levels that might negatively affect the brain and cognitive functioning. It is currently unclear if the brains of these patients need to be better protected. The present study investigates brain function during working memory in young adults with AAD compared to healthy controls. All participants (56 AAD (33 females), 62 controls (39 females), 19-43 years), underwent MRI brain scanning while performing a visuo-spatial and verbal working memory task. No main group differences in accuracy, reaction time or brain activity during the tasks were found. These findings suggest that patients perform equal to controls, and achieve similar levels of brain activity during working memory. However, variations in the patient population may have confounded this outcome. Controlled studies on larger cohorts are therefore needed to confirm these findings and test if having AAD affects the brain on the long term.

Resting State Functional Networks in Gliomas: Validation With Direct Electric Stimulation Using a New Tool for Planning Brain Resections

BACKGROUND AND OBJECTIVES

Precise mapping of functional networks in patients with brain tumor is essential for tailoring personalized treatment strategies. Resting-state functional MRI (rs-fMRI) offers an alternative to task-based fMRI, capable of capturing multiple networks within a single acquisition, without necessitating task engagement. This study demonstrates a strong concordance between preoperative rs-fMRI maps and the gold standard intraoperative direct electric stimulation (DES) mapping during awake surgery.

METHODS

We conducted an analysis involving 28 patients with glioma who underwent awake surgery with DES mapping. A total of 100 DES recordings were collected to map sensorimotor (SMN), language (LANG), visual (VIS), and speech articulation cognitive domains. Preoperative rs-fMRI maps were generated using an updated version of the ReStNeuMap software, specifically designed for rs-fMRI data preprocessing and automatic detection of 7 resting-state networks (SMN, LANG, VIS, speech articulation, default mode, frontoparietal, and visuospatial). To evaluate the agreement between these networks and those mapped with invasive cortical mapping, we computed patient-specific distances between them and intraoperative DES recordings.

RESULTS

Automatically detected preoperative functional networks exhibited excellent agreement with intraoperative DES recordings. When we spatially compared DES points with their corresponding networks, we found that SMN, VIS, and speech articulatory DES points fell within the corresponding network (median distance = 0 mm), whereas for LANG a median distance of 1.6 mm was reported.

CONCLUSION

Our findings show the remarkable consistency between key functional networks mapped noninvasively using presurgical rs-fMRI and invasive cortical mapping. This evidence highlights the utility of rs-fMRI for personalized presurgical planning, particularly in scenarios where awake surgery with DES is not feasible to protect eloquent areas during tumor resection. We have made the updated tool for automated functional network estimation publicly available, facilitating broader utilization of rs-fMRI mapping in various clinical contexts, including presurgical planning, functional reorganization over follow-up periods, and informing future treatments such as radiotherapy.

Relationship between central autonomic effective connectivity and heart rate variability: A Resting-state fMRI dynamic causal modeling study

The central autonomic network (CAN) serves as a regulatory hub with top-down regulatory control and integration of bottom-up physiological feedback via the autonomic nervous system. Heart rate variability (HRV)-the time variance of the heart's beat-to-beat intervals-is an index of the CAN's affective and behavioral regulatory capacity. Although neural functional connectivities that are associated with HRV and CAN have been well studied, no published report to date has studied effective (directional) connectivities (EC) that are associated with HRV and CAN. Better understanding of neural EC in the brain has the potential to improve our understanding of how the CAN sub-regions regulate HRV. To begin to address this knowledge gap, we employed resting-state functional magnetic resonance imaging and dynamic causal modeling (DCM) with parametric empirical Bayes analyses in 34 healthy adults (19 females; mean age= 32.68 years [SD= 14.09], age range 18-68 years) to examine the bottom-up and top-down neural circuits associated with HRV. Throughout the whole brain, we identified 12 regions associated with HRV. DCM analyses revealed that the ECs from the right amygdala to the anterior cingulate cortex and to the ventrolateral prefrontal cortex had a negative linear relationship with HRV and a positive linear relationship with heart rate. These findings suggest that ECs from the amygdala to the prefrontal cortex may represent a neural circuit associated with regulation of cardiodynamics.

COVID-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study

Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting-state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in ECdelta (i.e., the difference in EC values pre- and post-COVID-19) and Volumetricdelta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that ECdelta significantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in Volumetricdelta between groups (p = 0.041). The reduced ECdelta in the left amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.

The Role of Cerebellum and Basal Ganglia Functional Connectivity in Altered Voluntary Movement Execution in Essential Tremor

Substantial evidence highlights the role of the cerebellum in the pathophysiology of tremor in essential tremor (ET), although its potential involvement in altered movement execution in this condition remains unclear. This study aims to explore potential correlations between the cerebellum and basal ganglia functional connectivity and voluntary movement execution abnormalities in ET, objectively assessed with kinematic techniques. A total of 20 patients diagnosed with ET and 18 healthy subjects were enrolled in this study. Tremor and repetitive finger tapping were recorded using an optoelectronic kinematic system. All participants underwent comprehensive 3T-MRI examinations, including 3D-T1 and blood-oxygen-level dependent (BOLD) sequences during resting state. Morphometric analysis was conducted on the 3D-T1 images, while a seed-based analysis was performed to investigate the resting-state functional connectivity (rsFC) of dorsal and ventral portions of the dentate nucleus and the external and internal segments of the globus pallidus. Finally, potential correlations between rsFC alterations in patients and clinical as well as kinematic scores were assessed. Finger tapping movements were slower in ET than in healthy subjects. Compared to healthy subjects, patients with ET exhibited altered FC of both dentate and globus pallidus with cerebellar, basal ganglia, and cortical areas. Interestingly, both dentate and pallidal FC exhibited positive correlations with movement velocity in patients, differently from that we observed in healthy subjects, indicating the higher the FC, the faster the finger tapping. The findings of this study indicate the possible role of both cerebellum and basal ganglia in the pathophysiology of altered voluntary movement execution in patients with ET.

Longitudinal development of resting-state functional connectivity in adolescents with and without internalizing disorders

Longitudinal studies using resting-state functional magnetic resonance imaging (rs-fMRI) focused on adolescent internalizing psychopathology are scarce and have mostly investigated standardized treatment effects on functional connectivity (FC) of the full amygdala. The role of amygdala subregions and large resting-state networks had yet to be elucidated, and treatment is in practice often personalized. Here, longitudinal FC development of amygdala subregions and whole-brain networks are investigated in a clinically representative sample. Treatment-naïve adolescents with clinical depression and comorbid anxiety who started care-as-usual (n = 23; INT) and healthy controls (n = 24; HC) participated in rs-fMRI scans and questionnaires at baseline (before treatment) and after three months. Changes between and within groups over time in FC of the laterobasal amygdala (LBA), centromedial amygdala (CMA) and whole-brain networks derived from independent component analysis (ICA) were investigated. Groups differed significantly in FC development of the right LBA to the postcentral gyrus and the left LBA to the frontal pole. Within INT, FC to the frontal pole and postcentral gyrus changed over time while changes in FC of the right LBA were also linked to symptom change. No significant interactions were observed when considering FC from CMA bilateral seeds or within ICA-derived networks. Results in this cohort suggest divergent longitudinal development of FC from bilateral LBA subregions in adolescents with internalizing disorders compared to healthy peers, possibly reflecting nonspecific treatment effects. Moreover, associations were found with symptom change. These results highlight the importance of differentiation of amygdala subregions in neuroimaging research in adolescents.

Transdiagnostic Symptom Domains are Associated with Head Motion During Multimodal Imaging in Children

Background

Head motion is a challenge for neuroimaging research in developmental populations. However, it is unclear how transdiagnostic symptom domains including attention, disruptive behavior (e.g., externalizing behavior), and internalizing problems are linked to scanner motion in children, particularly across structural and functional MRI. The current study examined whether transdiagnostic domains of attention, disruptive behavior, and internalizing symptoms are associated with scanner motion in children during multimodal imaging.

Methods

In a sample of 9,045 children aged 9-10 years in the Adolescent Brain Cognitive Development (ABCD) Study, logistic regression and linear mixed-effects models were used to examine associations between motion and behavior. Motion was indexed using ABCD Study quality control metrics and mean framewise displacement for the following: T1-weighted structural, resting-state fMRI, diffusion MRI, Stop-Signal Task, Monetary Incentive Delay task, and Emotional n-Back task. The Child Behavior Checklist was used as a continuous measure of symptom severity.

Results

Greater attention and disruptive behavior problem severity was associated with a lower likelihood of passing motion quality control across several imaging modalities. In contrast, increased internalizing severity was associated with a higher likelihood of passing motion quality control. Increased attention and disruptive behavior problem severity was also associated with increased mean motion, whereas increased internalizing problem severity was associated with decreased mean motion.

Conclusion

Transdiagnostic domains emerged as predictors of motion in youths. These findings have implications for advancing development of generalizable and robust brain-based biomarkers, computational approaches for mitigating motion effects, and enhancing accessibility of imaging protocols for children with varying symptom severities.

Structural and functional connectivity in relation to executive functions in antipsychotic-naïve patients with first episode schizophrenia and levels of glutamatergic metabolites

Patients with schizophrenia exhibit structural and functional dysconnectivity but the relationship to the well-documented cognitive impairments is less clear. This study investigates associations between structural and functional connectivity and executive functions in antipsychotic-naïve patients experiencing schizophrenia. Sixty-four patients with schizophrenia and 95 matched controls underwent cognitive testing, diffusion weighted imaging and resting state functional magnetic resonance imaging. In the primary analyses, groupwise interactions between structural connectivity as measured by fixel-based analyses and executive functions were investigated using multivariate linear regression analyses. For significant structural connections, secondary analyses examined whether functional connectivity and associations with executive functions also differed for the two groups. In group comparisons, patients exhibited cognitive impairments across all executive functions compared to controls (p < 0.001), but no group difference were observed in the fixel-based measures. Primary analyses revealed a groupwise interaction between planning abilities and fixel-based measures in the left anterior thalamic radiation (p = 0.004), as well as interactions between cognitive flexibility and fixel-based measures in the isthmus of corpus callosum and cingulum (p = 0.049). Secondary analyses revealed increased functional connectivity between grey matter regions connected by the left anterior thalamic radiation (left thalamus with pars opercularis p = 0.018, and pars orbitalis p = 0.003) in patients compared to controls. Moreover, a groupwise interaction was observed between cognitive flexibility and functional connectivity between contralateral regions connected by the isthmus (precuneus p = 0.028, postcentral p = 0.012), all p-values corrected for multiple comparisons. We conclude that structural and functional connectivity appear to associate with executive functions differently in antipsychotic-naïve patients with schizophrenia compared to controls.

The role of functional emotion circuits in distinct dimensions of psychopathology in youth

Several mental disorders emerge during childhood or adolescence and are often characterized by socioemotional difficulties, including alterations in emotion perception. Emotional facial expressions are processed in discrete functional brain modules whose connectivity patterns encode emotion categories, but the involvement of these neural circuits in psychopathology in youth is poorly understood. This study examined the associations between activation and functional connectivity patterns in emotion circuits and psychopathology during development. We used task-based fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC, N = 1221, 8-23 years) and conducted generalized psycho-physiological interaction (gPPI) analyses. Measures of psychopathology were derived from an independent component analysis of questionnaire data. The results showed positive associations between identifying fearful, sad, and angry faces and depressive symptoms, and a negative relationship between sadness recognition and positive psychosis symptoms. We found a positive main effect of depressive symptoms on BOLD activation in regions overlapping with the default mode network, while individuals reporting higher levels of norm-violating behavior exhibited emotion-specific lower functional connectivity within regions of the salience network and between modules that overlapped with the salience and default mode network. Our findings illustrate the relevance of functional connectivity patterns underlying emotion processing for behavioral problems in children and adolescents.

Imbalanced temporal states of cortical blood-oxygen-level-dependent signal variability during rest in episodic migraine

BACKGROUND

Migraine has been associated with functional brain changes including altered connectivity and activity both during and between headache attacks. Recent studies established that the variability of the blood-oxygen-level-dependent (BOLD) signal is an important attribute of brain activity, which has so far been understudied in migraine. In this study, we investigate how time-varying measures of BOLD variability change interictally in episodic migraine patients.

METHODS

Two independent resting state functional MRI datasets acquired on 3T (discovery cohort) and 1.5T MRI scanners (replication cohort) including 99 episodic migraine patients (n3T = 42, n1.5T=57) and 78 healthy controls (n3T = 46, n1.5T=32) were analyzed in this cross-sectional study. A framework using time-varying measures of BOLD variability was applied to derive BOLD variability states. Descriptors of BOLD variability states such as dwell time and fractional occupancy were calculated, then compared between migraine patients and healthy controls using Mann-Whitney U-tests. Spearman's rank correlation was calculated to test associations with clinical parameters.

RESULTS

Resting-state activity was characterized by states of high and low BOLD signal variability. Migraine patients in the discovery cohort spent more time in the low variability state (mean dwell time: p = 0.014, median dwell time: p = 0.022, maximum dwell time: p = 0.013, fractional occupancy: p = 0.013) and less time in the high variability state (mean dwell time: p = 0.021, median dwell time: p = 0.021, maximum dwell time: p = 0.025, fractional occupancy: p = 0.013). Higher uptime of the low variability state was associated with greater disability as measured by MIDAS scores (maximum dwell time: R = 0.45, p = 0.007; fractional occupancy: R = 0.36, p = 0.035). Similar results were observed in the replication cohort.

CONCLUSION

Episodic migraine patients spend more time in a state of low BOLD variability during rest in headache-free periods, which is associated with greater disability. BOLD variability states show potential as a replicable functional imaging marker in episodic migraine.

Differences in spatiotemporal brain network dynamics of Montessori and traditionally schooled students

Across development, experience has a strong impact on the way we think and adapt. School experience affects academic and social-emotional outcomes, yet whether differences in pedagogical experience modulate underlying brain network development is still unknown. In this study, we compared the brain network dynamics of students with different pedagogical backgrounds. Specifically, we characterized the diversity and stability of brain activity at rest by combining both resting-state fMRI and diffusion-weighted structural imaging data of 87 4-18 years old students experiencing either the Montessori pedagogy (i.e., student-led, trial-and-error pedagogy) or the traditional pedagogy (i.e., teacher-led, test-based pedagogy). Our results revealed spatiotemporal brain dynamics differences between students as a function of schooling experience at the whole-brain level. Students from Montessori schools showed overall higher functional integration (higher system diversity) and neural stability (lower spatiotemporal diversity) compared to traditionally schooled students. Higher integration was explained mainly through the cerebellar (CBL) functional network. In contrast, higher temporal stability was observed in the ventral attention, dorsal attention, somatomotor, frontoparietal, and CBL functional networks. This study suggests a form of experience-dependent dynamic functional connectivity plasticity, in learning-related networks.

Multivariate association between psychosocial environment, behaviors, and brain functional networks in adolescent depression

BACKGROUND

Adolescent depression shows high clinical heterogeneity. Brain functional networks serve as a powerful tool for investigating neural mechanisms underlying depression profiles. A key challenge is to characterize how variation in brain functional organization links to behavioral features and psychosocial environmental influences.

METHODS

We recruited 80 adolescents with major depressive disorder (MDD) and 42 healthy controls (HCs). First, we estimated the differences in functional connectivity of resting-state networks (RSN) between the two groups. Then, we used sparse canonical correlation analysis to characterize patterns of associations between RSN connectivity and symptoms, cognition, and psychosocial environmental factors in MDD adolescents. Clustering analysis was applied to stratify patients into homogenous subtypes according to these brain-behavior-environment associations.

RESULTS

MDD adolescents showed significantly hyperconnectivity between the ventral attention and cingulo-opercular networks compared with HCs. We identified one reliable pattern of covariation between RSN connectivity and clinical/environmental features in MDD adolescents. In this pattern, psychosocial factors, especially the interpersonal and family relationships, were major contributors to variation in connectivity of salience, cingulo-opercular, ventral attention, subcortical and somatosensory-motor networks. Based on this association, we categorized patients into two subgroups which showed different environment and symptoms characteristics, and distinct connectivity alterations. These differences were covered up when the patients were taken as a whole group.

CONCLUSION

This study identified the environmental exposures associated with specific functional networks in MDD youths. Our findings emphasize the importance of the psychosocial context in assessing brain function alterations in adolescent depression and have the potential to promote targeted treatment and precise prevention.

Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism

Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network - an early-emerging neural network involved in orienting attention to the most salient aspects of one's internal and external environment - may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.

Motor performance and functional connectivity between the posterior cingulate cortex and supplementary motor cortex in bipolar and unipolar depression

Although implicated in unsuccessful treatment, psychomotor deficits and their neurobiological underpinnings in bipolar (BD) and unipolar (UD) depression remain poorly investigated. Here, we hypothesized that motor performance deficits in depressed patients would relate to basal functional coupling of the hand primary motor cortex (M1) and the posterior cingulate cortex (PCC) with the supplementary motor area (SMA). We performed a longitudinal, naturalistic study in BD, UD and matched healthy controls comprising of two resting-state functional MRI measurements five weeks apart and accompanying assessments of motor performance using a finger tapping task (FTT). A subject-specific seed-based analysis describing functional connectivity between PCC-SMA as well as M1-SMA was conducted. The basal relationships with motor performance were investigated using linear regression models and all measures were compared across groups. Performance in FTT was impaired in BD in comparison to HC in both sessions. Behavioral performance across groups correlated significantly with resting state functional coupling of PCC-SMA, but not of M1-SMA regions. This relationship was partially reflected in a reduced PCC-SMA connectivity in BD vs HC in the second session. Exploratory evaluation of large-scale networks coupling (SMN-DMN) exhibited no correlation to motor performance. Our results shed new light on the association between the degree of disruption in the SMA-PCC anticorrelation and the level of motor impairment in BD.

Functional connectivity of the sensorimotor cerebellum in autism: associations with sensory over-responsivity

The cerebellum has been consistently shown to be atypical in autism spectrum disorder (ASD). However, despite its known role in sensorimotor function, there is limited research on its association with sensory over-responsivity (SOR), a common and impairing feature of ASD. Thus, this study sought to examine functional connectivity of the sensorimotor cerebellum in ASD compared to typically developing (TD) youth and investigate whether cerebellar connectivity is associated with SOR. Resting-state functional connectivity of the sensorimotor cerebellum was examined in 54 ASD and 43 TD youth aged 8-18 years. Using a seed-based approach, connectivity of each sensorimotor cerebellar region (defined as lobules I-IV, V-VI and VIIIA&B) with the whole brain was examined in ASD compared to TD youth, and correlated with parent-reported SOR severity. Across all participants, the sensorimotor cerebellum was functionally connected with sensorimotor and visual regions, though the three seed regions showed distinct connectivity with limbic and higher-order sensory regions. ASD youth showed differences in connectivity including atypical connectivity within the cerebellum and increased connectivity with hippocampus and thalamus compared to TD youth. More severe SOR was associated with stronger connectivity with cortical regions involved in sensory and motor processes and weaker connectivity with cognitive and socio-emotional regions, particularly prefrontal cortex. These results suggest that atypical cerebellum function in ASD may play a role in sensory challenges in autism.

Continuous evaluation of denoising strategies in resting-state fMRI connectivity using fMRIPrep and Nilearn

Reducing contributions from non-neuronal sources is a crucial step in functional magnetic resonance imaging (fMRI) connectivity analyses. Many viable strategies for denoising fMRI are used in the literature, and practitioners rely on denoising benchmarks for guidance in the selection of an appropriate choice for their study. However, fMRI denoising software is an ever-evolving field, and the benchmarks can quickly become obsolete as the techniques or implementations change. In this work, we present a denoising benchmark featuring a range of denoising strategies, datasets and evaluation metrics for connectivity analyses, based on the popular fMRIprep software. The benchmark prototypes an implementation of a reproducible framework, where the provided Jupyter Book enables readers to reproduce or modify the figures on the Neurolibre reproducible preprint server (https://neurolibre.org/). We demonstrate how such a reproducible benchmark can be used for continuous evaluation of research software, by comparing two versions of the fMRIprep. Most of the benchmark results were consistent with prior literature. Scrubbing, a technique which excludes time points with excessive motion, combined with global signal regression, is generally effective at noise removal. Scrubbing was generally effective, but is incompatible with statistical analyses requiring the continuous sampling of brain signal, for which a simpler strategy, using motion parameters, average activity in select brain compartments, and global signal regression, is preferred. Importantly, we found that certain denoising strategies behave inconsistently across datasets and/or versions of fMRIPrep, or had a different behavior than in previously published benchmarks. This work will hopefully provide useful guidelines for the fMRIprep users community, and highlight the importance of continuous evaluation of research methods.

Increased Resting-State Functional Connectivity in Patients With Autoimmune Addison Disease

CONTEXT

Individuals with autoimmune Addison disease (AAD) take replacement medication for the lack of adrenal-derived glucocorticoid (GC) and mineralocorticoid hormones from diagnosis. The brain is highly sensitive to these hormones, but the consequence of having AAD for brain health has not been widely addressed.

OBJECTIVE

The present study compared resting-state functional connectivity (rs-fc) of the brain between individuals with AAD and healthy controls.

METHODS

Fifty-seven patients with AAD (33 female) and 69 healthy controls (39 female), aged 19 to 43 years were scanned with 3-T magnetic resonance imaging (MRI).

RESULTS

Independent component and subsequent dual regression analyses revealed that individuals with AAD had stronger rs-fc compared to controls in 3 networks: the bilateral orbitofrontal cortex (OFC), the left medial visual and left posterior default mode network. A higher GC replacement dose was associated with stronger rs-fc in a small part of the left OFC in patients. We did not find any clear associations between rs-fc and executive functions or mental fatigue.

CONCLUSION

Our results suggest that having AAD affects the baseline functional organization of the brain and that current treatment strategies of AAD may be one risk factor.

Testing the sensitivity of diagnosis-derived patterns in functional brain networks to symptom burden in a Norwegian youth sample

Aberrant brain network development represents a putative aetiological component in mental disorders, which typically emerge during childhood and adolescence. Previous studies have identified resting-state functional connectivity (RSFC) patterns reflecting psychopathology, but the generalisability to other samples and politico-cultural contexts has not been established. We investigated whether a previously identified cross-diagnostic case-control and autism spectrum disorder (ASD)-specific pattern of RSFC (discovery sample; aged 5-21 from New York City, USA; n = 1666) could be validated in a Norwegian convenience-based youth sample (validation sample; aged 9-25 from Oslo, Norway; n = 531). As a test of generalisability, we investigated if these diagnosis-derived RSFC patterns were sensitive to levels of symptom burden in both samples, based on an independent measure of symptom burden. Both the cross-diagnostic and ASD-specific RSFC pattern were validated across samples. Connectivity patterns were significantly associated with thematically appropriate symptom dimensions in the discovery sample. In the validation sample, the ASD-specific RSFC pattern showed a weak, inverse relationship with symptoms of conduct problems, hyperactivity and prosociality, while the cross-diagnostic pattern was not significantly linked to symptoms. Diagnosis-derived connectivity patterns in a developmental clinical US sample were validated in a convenience sample of Norwegian youth, however, they were not associated with mental health symptoms.

Optimizing the measurement of sample entropy in resting-state fMRI data

Introduction

The complexity of brain signals may hold clues to understand brain-based disorders. Sample entropy, an index that captures the predictability of a signal, is a promising tool to measure signal complexity. However, measurement of sample entropy from fMRI signals has its challenges, and numerous questions regarding preprocessing and parameter selection require research to advance the potential impact of this method. For one example, entropy may be highly sensitive to the effects of motion, yet standard approaches to addressing motion (e.g., scrubbing) may be unsuitable for entropy measurement. For another, the parameters used to calculate entropy need to be defined by the properties of data being analyzed, an issue that has frequently been ignored in fMRI research. The current work sought to rigorously address these issues and to create methods that could be used to advance this field.

Methods

We developed and tested a novel windowing approach to select and concatenate (ignoring connecting volumes) low-motion windows in fMRI data to reduce the impact of motion on sample entropy estimates. We created utilities (implementing autoregressive models and a grid search function) to facilitate selection of the matching length m parameter and the error tolerance r parameter. We developed an approach to apply these methods at every grayordinate of the brain, creating a whole-brain dense entropy map. These methods and tools have been integrated into a publicly available R package ("powseR"). We demonstrate these methods using data from the ABCD study. After applying the windowing procedure to allow sample entropy calculation on the lowest-motion windows from runs 1 and 2 (combined) and those from runs 3 and 4 (combined), we identified the optimal m and r parameters for these data. To confirm the impact of the windowing procedure, we compared entropy values and their relationship with motion when entropy was calculated using the full set of data vs. those calculated using the windowing procedure. We then assessed reproducibility of sample entropy calculations using the windowed procedure by calculating the intraclass correlation between the earlier and later entropy measurements at every grayordinate.

Results

When applying these optimized methods to the ABCD data (from the subset of individuals who had enough windows of continuous "usable" volumes), we found that the novel windowing procedure successfully mitigated the large inverse correlation between entropy values and head motion seen when using a standard approach. Furthermore, using the windowed approach, entropy values calculated early in the scan (runs 1 and 2) are largely reproducible when measured later in the scan (runs 3 and 4), although there is some regional variability in reproducibility.

Discussion

We developed an optimized approach to measuring sample entropy that addresses concerns about motion and that can be applied across datasets through user-identified adaptations that allow the method to be tailored to the dataset at hand. We offer preliminary results regarding reproducibility. We also include recommendations for fMRI data acquisition to optimize sample entropy measurement and considerations for the field.

Distinct functional subnetworks of cognitive domains in older adults with minor cognitive deficits

Although past research has established a relationship between functional connectivity and cognitive function, less is known about which cognitive domains are associated with which specific functional networks. This study investigated associations between functional connectivity and global cognitive function and performance in the domains of memory, executive function and psychomotor speed in 166 older adults aged 75-91 years (mean = 80.3 ± 3.8) with minor cognitive deficits (Mini-Mental State Examination scores between 21 and 27). Functional connectivity was assessed within 10 standard large-scale resting-state networks and on a finer spatial resolution between 300 nodes in a functional connectivity matrix. No domain-specific associations with mean functional connectivity within large-scale resting-state networks were found. Node-level analysis revealed that associations between functional connectivity and cognitive performance differed across cognitive functions in strength, location and direction. Specific subnetworks of functional connections were found for each cognitive domain in which higher connectivity between some nodes but lower connectivity between other nodes were related to better cognitive performance. Our findings add to a growing body of literature showing differential sensitivity of functional connections to specific cognitive functions and may be a valuable resource for hypothesis generation of future studies aiming to investigate specific cognitive dysfunction with resting-state functional connectivity in people with beginning cognitive deficits.

Comparing data-driven physiological denoising approaches for resting-state fMRI: implications for the study of aging

Introduction

Physiological nuisance contributions by cardiac and respiratory signals have a significant impact on resting-state fMRI data quality. As these physiological signals are often not recorded, data-driven denoising methods are commonly used to estimate and remove physiological noise from fMRI data. To investigate the efficacy of these denoising methods, one of the first steps is to accurately capture the cardiac and respiratory signals, which requires acquiring fMRI data with high temporal resolution.

Methods

In this study, we used such high-temporal resolution fMRI data to evaluate the effectiveness of several data-driven denoising methods, including global-signal regression (GSR), white matter and cerebrospinal fluid regression (WM-CSF), anatomical (aCompCor) and temporal CompCor (tCompCor), ICA-AROMA. Our analysis focused on the consequence of changes in low-frequency, cardiac and respiratory signal power, as well as age-related differences in terms of functional connectivity (fcMRI).

Results

Our results confirm that the ICA-AROMA and GSR removed the most physiological noise but also more low-frequency signals. These methods are also associated with substantially lower age-related fcMRI differences. On the other hand, aCompCor and tCompCor appear to be better at removing high-frequency physiological signals but not low-frequency signal power. These methods are also associated with relatively higher age-related fcMRI differences, whether driven by neuronal signal or residual artifact. These results were reproduced in data downsampled to represent conventional fMRI sampling frequency. Lastly, methods differ in performance depending on the age group.

Discussion

While this study cautions direct comparisons of fcMRI results based on different denoising methods in the study of aging, it also enhances the understanding of different denoising methods in broader fcMRI applications.

Neuro-environmental interactions: a time sensitive matter

Introduction

The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI).

Methods

We implemented an interpretable XGBoost-shapley additive explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages, 13-25 years) enrolled in the public health impact of metals exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, copper, nickel, and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood, and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex.

Results

Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated (p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics.

Discussion

Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

Developmental shift in testosterone influence on prefrontal emotion control

A paradox of testosterone effects is seen in adolescents versus adults in social emotional approach-avoidance behavior. During adolescence, high testosterone levels are associated with increased anterior prefrontal (aPFC) involvement in emotion control, whereas during adulthood this neuro-endocrine relation is reversed. Rodent work shows that, during puberty, testosterone transitions from a neuro-developmental to a social-sexual activating hormone. In this study, we explored whether this functional transition is also present in human adolescents and young adults. Using a prospective longitudinal design, we investigated the role of testosterone on neural control of social emotional behavior during the transitions from middle to late adolescence and into young adulthood. Seventy-one individuals (tested at ages 14, 17, and 20 years) performed an fMRI-adapted approach-avoidance (AA) task involving automatic and controlled actions in response to social emotional stimuli. In line with predictions from animal models, the effect of testosterone on aPFC engagement decreased between middle and late adolescence, and shifted into an activational role by young adulthood-impeding neural control of emotions. This change in testosterone function was accompanied by increased testosterone-modulated amygdala reactivity. These findings qualify the testosterone-dependent maturation of the prefrontal-amygdala circuit supporting emotion control during the transition from middle adolescence into young adulthood.

Multilayer meta-matching: translating phenotypic prediction models from multiple datasets to small data

Resting-state functional connectivity (RSFC) is widely used to predict phenotypic traits in individuals. Large sample sizes can significantly improve prediction accuracies. However, for studies of certain clinical populations or focused neuroscience inquiries, small-scale datasets often remain a necessity. We have previously proposed a "meta-matching" approach to translate prediction models from large datasets to predict new phenotypes in small datasets. We demonstrated large improvement of meta-matching over classical kernel ridge regression (KRR) when translating models from a single source dataset (UK Biobank) to the Human Connectome Project Young Adults (HCP-YA) dataset. In the current study, we propose two meta-matching variants ("meta-matching with dataset stacking" and "multilayer meta-matching") to translate models from multiple source datasets across disparate sample sizes to predict new phenotypes in small target datasets. We evaluate both approaches by translating models trained from five source datasets (with sample sizes ranging from 862 participants to 36,834 participants) to predict phenotypes in the HCP-YA and HCP-Aging datasets. We find that multilayer meta-matching modestly outperforms meta-matching with dataset stacking. Both meta-matching variants perform better than the original "meta-matching with stacking" approach trained only on the UK Biobank. All meta-matching variants outperform classical KRR and transfer learning by a large margin. In fact, KRR is better than classical transfer learning when less than 50 participants are available for finetuning, suggesting the difficulty of classical transfer learning in the very small sample regime. The multilayer meta-matching model is publicly available at GITHUB_LINK.

Disruptions of Hierarchical Cortical Organization in Early Psychosis and Schizophrenia

BACKGROUND

The cerebral cortex is organized hierarchically along an axis that spans unimodal sensorimotor to transmodal association areas. This hierarchy is often characterized using low-dimensional embeddings, termed gradients, of interregional functional coupling estimates measured with resting-state functional magnetic resonance imaging. Such analyses may offer insights into the pathophysiology of schizophrenia, which has been frequently linked to dysfunctional interactions between association and sensorimotor areas.

METHODS

To examine disruptions of hierarchical cortical function across distinct stages of psychosis, we applied diffusion map embedding to 2 independent functional magnetic resonance imaging datasets: one comprising 114 patients with early psychosis and 48 control participants, and the other comprising 50 patients with established schizophrenia and 121 control participants. Then, we analyzed the primary sensorimotor-to-association and secondary visual-to-sensorimotor gradients of each participant in both datasets.

RESULTS

There were no significant differences in regional gradient scores between patients with early psychosis and control participants. Patients with established schizophrenia showed significant differences in the secondary, but not primary, gradient compared with control participants. Gradient differences in schizophrenia were characterized by lower within-network dispersion in the dorsal attention (false discovery rate [FDR]-corrected p [pFDR] < .001), visual (pFDR = .003), frontoparietal (pFDR = .018), and limbic (pFDR = .020) networks and lower between-network dispersion between the visual network and other networks (pFDR < .001).

CONCLUSIONS

These findings indicate that differences in cortical hierarchical function occur along the secondary visual-to-sensorimotor axis rather than the primary sensorimotor-to-association axis as previously thought. The absence of differences in early psychosis suggests that visual-sensorimotor abnormalities may emerge as the illness progresses.

Neighborhood poverty during childhood prospectively predicts adolescent functional brain network architecture

Family poverty has been associated with altered brain structure, function, and connectivity in youth. However, few studies have examined how disadvantage within the broader neighborhood may influence functional brain network organization. The present study leveraged a longitudinal community sample of 538 twins living in low-income neighborhoods to evaluate the prospective association between exposure to neighborhood poverty during childhood (6-10 y) with functional network architecture during adolescence (8-19 y). Using resting-state and task-based fMRI, we generated two latent measures that captured intrinsic brain organization across the whole-brain and network levels - network segregation and network segregation-integration balance. While age was positively associated with network segregation and network balance overall across the sample, these associations were moderated by exposure to neighborhood poverty. Specifically, these positive associations were observed only in youth from more, but not less, disadvantaged neighborhoods. Moreover, greater exposure to neighborhood poverty predicted reduced network segregation and network balance in early, but not middle or late, adolescence. These effects were detected both across the whole-brain system as well as specific functional networks, including fronto-parietal, default mode, salience, and subcortical systems. These findings indicate that where children live may exert long-reaching effects on the organization and development of the adolescent brain.

Denoising task-related fMRI: Balancing noise reduction against signal loss

Preprocessing fMRI data requires striking a fine balance between conserving signals of interest and removing noise. Typical steps of preprocessing include motion correction, slice timing correction, spatial smoothing, and high-pass filtering. However, these standard steps do not remove many sources of noise. Thus, noise-reduction techniques, for example, CompCor, FIX, and ICA-AROMA have been developed to further improve the ability to draw meaningful conclusions from the data. The ability of these techniques to minimize noise while conserving signals of interest has been tested almost exclusively in resting-state fMRI and, only rarely, in task-related fMRI. Application of noise-reduction techniques to task-related fMRI is particularly important given that such procedures have been shown to reduce false positive rates. Little remains known about the impact of these techniques on the retention of signal in tasks that may be associated with systemic physiological changes. In this paper, we compared two ICA-based, that is FIX and ICA-AROMA, two CompCor-based noise-reduction techniques, that is aCompCor, and tCompCor, and standard preprocessing using a large (n = 101) fMRI dataset including noxious heat and non-noxious auditory stimulation. Results show that preprocessing using FIX performs optimally for data obtained using noxious heat, conserving more signals than CompCor-based techniques and ICA-AROMA, while removing only slightly less noise. Similarly, for data obtained during non-noxious auditory stimulation, FIX noise-reduction technique before analysis with a covariate of interest outperforms the other techniques. These results indicate that FIX might be the most appropriate technique to achieve the balance between conserving signals of interest and removing noise during task-related fMRI.

A randomized controlled trial investigating the effect of liraglutide on self-reported liking and neural responses to food stimuli in participants with obesity

BACKGROUND/OBJECTIVES

Obesity is a complex condition and the mechanisms involved in weight gain and loss are not fully understood. Liraglutide, a GLP-1 receptor agonist, has been demonstrated to successfully promote weight loss in patients with obesity (OB). Yet, it is unclear whether the observed weight loss is driven by an alteration of food liking. Here we investigated the effects of liraglutide on food liking and the cerebral correlates of liking in OB.

SUBJECTS/METHODS

This study was a randomized, single-center, double-blind, placebo-controlled, parallel group, prospective clinical trial. 73 participants with OB and without diabetes following a multidisciplinary weight loss program, were randomly assigned (1:1) to receive liraglutide 3.0 mg (37.40 ± 11.18 years old, BMI = 35.89 ± 3.01 kg) or a placebo (40.04 ± 14.10 years old, BMI = 34.88 ± 2.87 kg) subcutaneously once daily for 16 weeks.

INTERVENTIONS/METHODS

We investigated liking during food consumption. Participants reported their hedonic experience while consuming a high-calorie food (milkshake) and a tasteless solution. The solutions were administered inside the scanner with a Magnetic Resonance Imaging (MRI)-compatible gustometer to assess neural responses during consumption. The same procedure was repeated during the pre- and post-intervention sessions.

RESULTS

None of the effects involving the intervention factor reached significance when comparing liking between the pre- and post-intervention sessions or groups. Liking during food reward consumption was associated with the activation of the ventromedial prefrontal cortex (vmPFC) and the amygdala. The liraglutide group lost more weight (BMI post-pre = -3.19 ± 1.28 kg/m2) than the placebo group (BMI post-pre = -0.60 ± 1.26 kg/m2).

CONCLUSIONS

These results suggest that liraglutide leads to weight loss without self-report or neural evidence supporting a concomitant reduction of food liking in participants with OB.

The virtual aging brain: Causal inference supports interhemispheric dedifferentiation in healthy aging

The mechanisms of cognitive decline and its variability during healthy aging are not fully understood, but have been associated with reorganization of white matter tracts and functional brain networks. Here, we built a brain network modeling framework to infer the causal link between structural connectivity and functional architecture and the consequent cognitive decline in aging. By applying in-silico interhemispheric degradation of structural connectivity, we reproduced the process of functional dedifferentiation during aging. Thereby, we found the global modulation of brain dynamics by structural connectivity to increase with age, which was steeper in older adults with poor cognitive performance. We validated our causal hypothesis via a deep-learning Bayesian approach. Our results might be the first mechanistic demonstration of dedifferentiation during aging leading to cognitive decline.

Organization of sensorimotor activity in anterior cruciate ligament reconstructed individuals: an fMRI conjunction analysis

Introduction

Anterior cruciate ligament reconstruction (ACLR) is characterized by persistent involved limb functional deficits that persist for years despite rehabilitation. Previous research provides evidence of both peripheral and central nervous system adaptations following ACLR. However, no study has compared functional organization of the brain for involved limb motor control relative to the uninvolved limb and healthy controls. The purpose of this study was to examine sensorimotor cortex and cerebellar functional activity overlap and non-overlap during a knee motor control task between groups (ACLR and control), and to determine cortical organization of involved and uninvolved limb movement between groups.

Methods

Eighteen participants with left knee ACLR and 18 control participants performed a knee flexion/extension motor control task during functional magnetic resonance imaging (fMRI). A conjunction analysis was conducted to determine the degree of overlap in brain activity for involved and uninvolved limb knee motor control between groups.

Results

The ACLR group had a statistically higher mean percent signal change in the sensorimotor cortex for the involved > uninvolved contrast compared to the control group. Brain activity between groups statistically overlapped in sensorimotor regions of the cortex and cerebellum for both group contrasts: involved > uninvolved and uninvolved > involved. Relative to the control group, the ACLR group uniquely activated superior parietal regions (precuneus, lateral occipital cortex) for involved limb motor control. Additionally, for involved limb motor control, the ACLR group displayed a medial and superior shift in peak voxel location in frontal regions; for parietal regions, the ACLR group had a more posterior and superior peak voxel location relative to the control group.

Conclusion

ACLR may result in unique activation of the sensorimotor cortex via a cortically driven sensory integration strategy to maintain involved limb motor control. The ACLR group's unique brain activity was independent of strength, self-reported knee function, and time from surgery.

Neuroimaging and behavioral evidence that violent video games exert no negative effect on human empathy for pain and emotional reactivity to violence

Influential accounts claim that violent video games (VVGs) decrease players' emotional empathy by desensitizing them to both virtual and real-life violence. However, scientific evidence for this claim is inconclusive and controversially debated. To assess the causal effect of VVGs on the behavioral and neural correlates of empathy and emotional reactivity to violence, we conducted a prospective experimental study using functional magnetic resonance imaging (fMRI). We recruited 89 male participants without prior VVG experience. Over the course of two weeks, participants played either a highly violent video game or a non-violent version of the same game. Before and after this period, participants completed an fMRI experiment with paradigms measuring their empathy for pain and emotional reactivity to violent images. Applying a Bayesian analysis approach throughout enabled us to find substantial evidence for the absence of an effect of VVGs on the behavioral and neural correlates of empathy. Moreover, participants in the VVG group were not desensitized to images of real-world violence. These results imply that short and controlled exposure to VVGs does not numb empathy nor the responses to real-world violence. We discuss the implications of our findings regarding the potential and limitations of experimental research on the causal effects of VVGs. While VVGs might not have a discernible effect on the investigated subpopulation within our carefully controlled experimental setting, our results cannot preclude that effects could be found in settings with higher ecological validity, in vulnerable subpopulations, or after more extensive VVG play.

Epigenetic aging and PTSD outcomes in the immediate aftermath of trauma

BACKGROUND

Psychological trauma exposure and posttraumatic stress disorder (PTSD) have been associated with advanced epigenetic age. However, whether epigenetic aging measured at the time of trauma predicts the subsequent development of PTSD outcomes is unknown. Moreover, the neural substrates underlying posttraumatic outcomes associated with epigenetic aging are unclear.

METHODS

We examined a multi-ancestry cohort of women and men (n = 289) who presented to the emergency department (ED) after trauma. Blood DNA was collected at ED presentation, and EPIC DNA methylation arrays were used to assess four widely used metrics of epigenetic aging (HorvathAge, HannumAge, PhenoAge, and GrimAge). PTSD symptoms were evaluated longitudinally at the time of ED presentation and over the ensuing 6 months. Structural and functional neuroimaging was performed 2 weeks after trauma.

RESULTS

After covariate adjustment and correction for multiple comparisons, advanced ED GrimAge predicted increased risk for 6-month probable PTSD diagnosis. Secondary analyses suggested that the prediction of PTSD by GrimAge was driven by worse trajectories for intrusive memories and nightmares. Advanced ED GrimAge was also associated with reduced volume of the whole amygdala and specific amygdala subregions, including the cortico-amygdaloid transition and the cortical and accessory basal nuclei.

CONCLUSIONS

Our findings shed new light on the relation between biological aging and trauma-related phenotypes, suggesting that GrimAge measured at the time of trauma predicts PTSD trajectories and is associated with relevant brain alterations. Furthering these findings has the potential to enhance early prevention and treatment of posttraumatic psychiatric sequelae.