Assessing the significance of focal activations using their spatial extent

Acute effects of different types of cannabis on young adult and adolescent resting-state brain networks

Adolescence is a time of rapid neurodevelopment and the endocannabinoid system is particularly prone to change during this time. Cannabis is a commonly used drug with a particularly high prevalence of use among adolescents. The two predominant phytocannabinoids are Delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), which affect the endocannabinoid system. It is unknown whether this period of rapid development makes adolescents more or less vulnerable to the effects of cannabis on brain-network connectivity, and whether CBD may attenuate the effects of THC. Using fMRI, we explored the impact of vaporized cannabis (placebo, THC: 8 mg/75 kg, THC + CBD: 8 mg/75 kg THC & 24 mg/75 kg CBD) on resting-state networks in groups of semi-regular cannabis users (usage frequency between 0.5 and 3 days/week), consisting of 22 adolescents (16-17 years) and 24 young adults (26-29 years) matched for cannabis use frequency. Cannabis caused reductions in within-network connectivity in the default mode (F[2,88] = 3.97, P = 0.022, η² = 0.018), executive control (F[2,88] = 18.62, P < 0.001, η² = 0.123), salience (F[2,88] = 12.12, P < 0.001, η² = 0.076), hippocampal (F[2,88] = 14.65, P < 0.001, η² = 0.087), and limbic striatal (F[2,88] = 16.19, P < 0.001, η² = 0.102) networks compared to placebo. Whole-brain analysis showed cannabis significantly disrupted functional connectivity with cortical regions and the executive control, salience, hippocampal, and limbic striatal networks compared to placebo. CBD did not counteract THC's effects and further reduced connectivity both within networks and the whole brain. While age-related differences were observed, there were no interactions between age group and cannabis treatment in any brain network. Overall, these results challenge the assumption that CBD can make cannabis safer, as CBD did not attenuate THC effects (and in some cases potentiated them); furthermore, they show that cannabis causes similar disruption to resting-state connectivity in the adolescent and adult brain.

High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry

BACKGROUND

Brain region segmentation and morphometry in humanized apolipoprotein E (APOE) mouse models with a human NOS2 background (HN) contribute to Alzheimer's disease (AD) research by demonstrating how various risk factors affect the brain. Photon-counting detector (PCD) micro-CT provides faster scan times than MRI, with superior contrast and spatial resolution to energy-integrating detector (EID) micro-CT. This paper presents a pipeline for mouse brain imaging, segmentation, and morphometry from PCD micro-CT.

METHODS

We used brains of 26 mice from 3 genotypes (APOE22HN, APOE33HN, APOE44HN). The pipeline included PCD and EID micro-CT scanning, hybrid (PCD and EID) iterative reconstruction, and brain region segmentation using the Small Animal Multivariate Brain Analysis (SAMBA) tool. We applied SAMBA to transfer brain region labels from our new PCD CT atlas to individual PCD brains via diffeomorphic registration. Region-based and voxel-based analyses were used for comparisons by genotype and sex.

RESULTS

Together, PCD and EID scanning take ~5 hours to produce images with a voxel size of 22 μm, which is faster than MRI protocols for mouse brain morphometry with voxel size above 40 μm. Hybrid iterative reconstruction generates PCD images with minimal artifacts and higher spatial resolution and contrast than EID images. Our PCD atlas is qualitatively and quantitatively similar to the prior MRI atlas and successfully transfers labels to PCD brains in SAMBA. Male and female mice had significant volume differences in 26 regions, including parts of the entorhinal cortex and cingulate cortex. APOE22HN brains were larger than APOE44HN brains in clusters from the hippocampus, a region where atrophy is associated with AD.

CONCLUSIONS

This work establishes a pipeline for mouse brain analysis using PCD CT, from staining to imaging and labeling brain images. Our results validate the effectiveness of the approach, setting a foundation for research on AD mouse models while reducing scanning durations.

Restoring bottom-up communication in brain-heart interplay after trauma-focused psychotherapy in breast cancer patients with post-traumatic stress disorder

BACKGROUND

The psychological impact of breast cancer (BC) is substantial, with a significant number of patients (up to 32 %) experiencing post-traumatic stress disorder (PTSD). Exploring the emotional aspects of PTSD through the functional brain-heart interplay (BHI) offers valuable insights into the condition. BHI examines the functional interactions between cortical and sympathovagal dynamics. This study aims to investigate changes in functional directional BHI after trauma-focused (TF) psychotherapy, specifically Eye Movement Desensitization and Reprocessing (EMDR), in comparison to treatment as usual (TAU) among BC patients with PTSD. To our knowledge, this study represents the first examination of such changes.

METHODS

We enrolled thirty BC patients who met the criteria for a PTSD diagnosis, with fourteen receiving EMDR and fifteen receiving TAU over a two- to three-month period. We analyzed changes in the emotional response during a script-driven imagery setting. Quantification of the functional interplay between EEG and sympathovagal dynamics was achieved using the synthetic data generation model (SDG) on electroencephalographic (EEG) and heartbeat series. Our focus was on the difference in the BHI index extracted at baseline and post-treatment.

RESULTS

We found statistically significant higher coupling in the heart-to-brain direction in patients treated with EMDR compared to controls. This suggests that the flow of information from the autonomic nervous system to the central nervous system is restored following EMDR-induced recovery from PTSD. Furthermore, we observed a significant correlation between improvements in PTSD symptoms and an increase in functional BHI after EMDR treatment.

CONCLUSIONS

TF psychotherapy, particularly EMDR, appears to facilitate the restoration of the bottom-up flow of interoceptive information, which is dysfunctional in patients with PTSD. The application of BHI analysis to the study of PTSD not only aids in identifying biomarkers of the disorder but also enhances our understanding of the changes brought about by TF treatments.

2.5-Year changes of connectivity dynamism are relevant for physical and cognitive deterioration in multiple sclerosis

BACKGROUND

In MS, functional connectivity (FC) dynamism may influence disease evolution.

OBJECTIVES

The objective is to assess time-varying functional connectivity (TVFC) changes over time at 2.5-year follow-up in MS patients according to physical and cognitive worsening.

METHODS

We collected 3T magnetic resonance imaging (MRI) for TVFC assessment (performed using sliding-window analysis of centrality) and clinical evaluations at baseline and 2.5-year follow-up from 28 healthy controls and 129 MS patients. Of these, 79 underwent baseline and follow-up neuropsychological assessment. At 2.5 years, physical/cognitive worsening was defined according to disability/neuropsychological score changes.

RESULTS

At follow-up, 25/129 (19.3%) MS patients worsened physically and 14/79 (17.7%) worsened cognitively. At baseline, MS patients showed reduced TVFC versus controls. At 2.5-year follow-up, no TVFC changes were detected in controls. Conversely, TVFC decreased over time in parieto-temporal regions in stable MS patients and in default-mode network in worsened MS. In physically worsened MS, basal ganglia TVFC reductions were also found. Reduced TVFC over time in the putamen in physically worsened and reduced TVFC in the precuneus in cognitively worsened were significant versus stable MS.

DISCUSSION

At 2.5-year follow-up, default-mode network TVFC reductions were found in worsening MS. Moreover, reduced deep gray matter TVFC characterized physically worsened patients, whereas precuneus involvement characterized cognitively worsened MS patients.

Spatial nonstationarity of image noise in widefield optical imaging and its effects on cluster-based inference for resting-state functional connectivity

BACKGROUND

Resting-state functional connectivity (RSFC) analysis with widefield optical imaging (WOI) is a potentially powerful tool to develop imaging biomarkers in mouse models of disease before translating them to human neuroimaging with functional magnetic resonance imaging (fMRI). The delineation of such biomarkers depends on rigorous statistical analysis. However, statistical understanding of WOI data is limited. In particular, cluster-based analysis of neuroimaging data depends on assumptions of spatial stationarity (i.e., that the distribution of cluster sizes under the null is equal at all brain locations). Whether actual data deviate from this assumption has not previously been examined in WOI.

NEW METHOD

In this manuscript, we characterize the effects of spatial nonstationarity in WOI RSFC data and adapt a "two-pass" technique from fMRI to correct cluster sizes and mitigate spatial bias, both parametrically and nonparametrically. These methods are tested on multi-institutional data.

RESULTS AND COMPARISON WITH EXISTING METHODS

We find that spatial nonstationarity has a substantial effect on inference in WOI RSFC data with false positives much more likely at some brain regions than others. This pattern of bias varies between imaging systems, contrasts, and mouse ages, all of which could affect experimental reproducibility if not accounted for.

CONCLUSIONS

Both parametric and nonparametric corrections for nonstationarity result in significant improvements in spatial bias. The proposed methods are simple to implement and will improve the robustness of inference in optical neuroimaging data.

Associations between antipsychotics-induced weight gain and brain networks of impulsivity

Given the unpredictable rapid onset and ubiquitous consequences of weight gain induced by antipsychotics, there is a pressing need to get insights into the underlying processes at the brain system level that will allow stratification of "at risk" patients. The pathophysiological hypothesis at hand is focused on brain networks governing impulsivity that are modulated by neuro-inflammatory processes. To this aim, we investigated brain anatomy and functional connectivity in patients with early psychosis (median age: 23 years, IQR = 21-27) using anthropometric data and magnetic resonance imaging acquired one month to one year after initiation of AP medication. Our analyses included 19 patients with high and rapid weight gain (i.e., ≥5% from baseline weight after one month) and 23 patients with low weight gain (i.e., <5% from baseline weight after one month). We replicated our analyses in young (26 years, IQR = 22-33, N = 102) and middle-aged (56 years, IQR = 51-62, N = 875) healthy individuals from the general population. In early psychosis patients, higher weight gain was associated with poor impulse control score (β = 1.35; P = 0.03). Here, the observed brain differences comprised nodes of impulsivity networks - reduced frontal lobe grey matter volume (Pcorrected = 0.007) and higher striatal volume (Pcorrected = 0.048) paralleled by disruption of fronto-striatal functional connectivity (R = -0.32; P = 0.04). Weight gain was associated with the inflammatory biomarker plasminogen activator inhibitor-1 (β = 4.9, P = 0.002). There was no significant association between increased BMI or weight gain and brain anatomy characteristics in both cohorts of young and middle-aged healthy individuals. Our findings support the notion of weight gain in treated psychotic patients associated with poor impulse control, impulsivity-related brain networks and chronic inflammation.

Integrative neuro-cardiovascular dynamics in response to test anxiety: A brain-heart axis study

Test anxiety (TA), a recognized form of social anxiety, is the most prominent cause of anxiety among students and, if left unmanaged, can escalate to psychiatric disorders. TA profoundly impacts both central and autonomic nervous systems, presenting as a dual manifestation of cognitive and autonomic components. While limited studies have explored the physiological underpinnings of TA, none have directly investigated the intricate interplay between the CNS and ANS in this context. In this study, we introduce a non-invasive, integrated neuro-cardiovascular approach to comprehensively characterize the physiological responses of 27 healthy subjects subjected to test anxiety induced via a simulated exam scenario. Our experimental findings highlight that an isolated analysis of electroencephalographic and heart rate variability data fails to capture the intricate information provided by a brain-heart axis assessment, which incorporates an analysis of the dynamic interaction between the brain and heart. With respect to resting state, the simulated examination induced a decrease in the neural control onto heartbeat dynamics at all frequencies, while the studying condition induced a decrease in the ascending heart-to-brain interplay at EEG oscillations up to 12Hz. This underscores the significance of adopting a multisystem perspective in understanding the complex and especially functional directional mechanisms underlying test anxiety.

Influence of transient emotional episodes on affective and cognitive theory of mind

Our emotions may influence how we interact with others. Previous studies have shown an important role of emotion induction in generating empathic reactions towards others' affect. However, it remains unclear whether (and to which extent) our own emotions can influence the ability to infer people's mental states, a process associated with Theory of Mind (ToM) and implicated in the representation of both cognitive (e.g. beliefs and intentions) and affective conditions. We engaged 59 participants in two emotion-induction experiments where they saw joyful, neutral and fearful clips. Subsequently, they were asked to infer other individuals' joy, fear (affective ToM) or beliefs (cognitive ToM) from verbal scenarios. Using functional magnetic resonance imaging, we found that brain activity in the superior temporal gyrus, precuneus and sensorimotor cortices were modulated by the preceding emotional induction, with lower response when the to-be-inferred emotion was incongruent with the one induced in the observer (affective ToM). Instead, we found no effect of emotion induction on the appraisal of people's beliefs (cognitive ToM). These findings are consistent with embodied accounts of affective ToM, whereby our own emotions alter the engagement of key brain regions for social cognition, depending on the compatibility between one's own and others' affect.

Response inhibition impairment related to altered frontal-striatal functional connectivity in insomnia disorder: A pilot and non-clinical study

BACKGROUND

It is not clear whether and how insomnia disorder (ID) impairs response inhibition ability. Fronto-striatal functional connectivity (FC) plays a critical role in response inhibition and is found be abnormal in patients with ID. In this study, we examined whether insomnia symptoms impair response inhibition in a large non-clinical sample and whether impaired response inhibition is related to abnormal fronto-striatal FC.

METHODS

One hundred and fifteen young ID patients and 160 age and sex-matched healthy controls (HC) underwent resting-state functional magnetic response imaging scans and performed the stop-signal task (SST). Performance of SST, Gray Matter Volumes (GMVs), and connections of brain regions related to fronto-striatal circuits was compared between groups. Further examined the association between response inhibition impairment and fronto-striatal FC.

RESULTS

The behavioral results showed that patients with ID had significantly longer stop-signal reaction time (SSRT) compared with the HC, reflecting the impaired response inhibition among IDs. Brain imaging results showed IDs had decreased GMVs of the Right Superior Frontal (SFG) and left Supplementary Motor area (SMA). Seed-based FC results showed that compared to HC, the ID showed decreased FC between left SMA and left Paracentral lobule, left SMA and right SMA, and right SFG and right Orbital Middle Frontal gyrus, and increased FC between right SFG and right putamen. Meanwhile, the FC between right SFG and putamen was positively correlated with SSRT in IDs.

CONCLUSIONS

The current study found significantly impaired response inhibition among ID and this impairment may be related to abnormal fronto-striatal FC in ID.

A priori free spectral unmixing with periodic absorbance changes: application for auto-calibrated intraoperative functional brain mapping

Spectral unmixing designates techniques that allow to decompose measured spectra into linear or non-linear combination of spectra of all targets (endmembers). This technique was initially developed for satellite applications, but it is now also widely used in biomedical applications. However, several drawbacks limit the use of these techniques with standard optical devices like RGB cameras. The devices need to be calibrated and a a priori on the observed scene is often necessary. We propose a new method for estimating endmembers and their proportion automatically and without calibration of the acquisition device based on near separable non-negative matrix factorization. This method estimates the endmembers on spectra of absorbance changes presenting periodic events. This is very common in in vivo biomedical and medical optical imaging where hemodynamics dominate the absorbance fluctuations. We applied the method for identifying functional brain areas during neurosurgery using four different RGB cameras (an industrial camera, a smartphone and two surgical microscopes). Results obtained with the auto-calibration method were consistent with the intraoperative gold standards. Endmembers estimated with the auto-calibration method were similar to the calibrated endmembers used in the modified Beer-Lambert law. The similarity was particularly strong when both cardiac and respiratory periodic events were considered. This work can allow a widespread use of spectral imaging in the industrial or medical field.

Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics

APOE allelic variation is critical in brain aging and Alzheimer's disease (AD). The APOE2 allele associated with cognitive resilience and neuroprotection against AD remains understudied. We employed a multipronged approach to characterize the transition from middle to old age in mice with APOE2 allele, using behavioral assessments, image-derived morphometry and diffusion metrics, structural connectomics, and blood transcriptomics. We used sparse multiple canonical correlation analyses (SMCCA) for integrative modeling, and graph neural network predictions. Our results revealed brain sub-networks associated with biological traits, cognitive markers, and gene expression. The cingulate cortex emerged as a critical region, demonstrating age-associated atrophy and diffusion changes, with higher fractional anisotropy in males and middle-aged subjects. Somatosensory and olfactory regions were consistently highlighted, indicating age-related atrophy and sex differences. The hippocampus exhibited significant volumetric changes with age, with differences between males and females in CA3 and CA1 regions. SMCCA underscored changes in the cingulate cortex, somatosensory cortex, olfactory regions, and hippocampus in relation to cognition and blood-based gene expression. Our integrative modeling in aging APOE2 carriers revealed a central role for changes in gene pathways involved in localization and the negative regulation of cellular processes. Our results support an important role of the immune system and response to stress. This integrative approach offers novel insights into the complex interplay among brain connectivity, aging, and sex. Our study provides a foundation for understanding the impact of APOE2 allele on brain aging, the potential for detecting associated changes in blood markers, and revealing novel therapeutic intervention targets.

Evaluation of resampling-based inference for topological features of neuroimages

Many recent studies have demonstrated the inflated type 1 error rate of the original Gaussian random field (GRF) methods for inference of neuroimages and identified resampling (permutation and bootstrapping) methods that have better performance. There has been no evaluation of resampling procedures when using robust (sandwich) statistical images with different topological features (TF) used for neuroimaging inference. Here, we consider estimation of distributions TFs of a statistical image and evaluate resampling procedures that can be used when exchangeability is violated. We compare the methods using realistic simulations and study sex differences in life-span age-related changes in gray matter volume in the Nathan Kline Institute Rockland sample. We find that our proposed wild bootstrap and the commonly used permutation procedure perform well in sample sizes above 50 under realistic simulations with heteroskedasticity. The Rademacher wild bootstrap has fewer assumptions than the permutation and performs similarly in samples of 100 or more, so is valid in a broader range of conditions. We also evaluate the GRF-based pTFCE method and show that it has inflated error rates in samples less than 200. Our R package, pbj , is available on Github and allows the user to reproducibly implement various resampling-based group level neuroimage analyses.

Failure to breathe persists without air hunger or alarm following amygdala seizures

Postictal apnea is thought to be a major cause of sudden unexpected death in epilepsy (SUDEP). However, the mechanisms underlying postictal apnea are unknown. To understand causes of postictal apnea, we used a multimodal approach to study brain mechanisms of breathing control in 20 patients (ranging from pediatric to adult) undergoing intracranial electroencephalography for intractable epilepsy. Our results indicate that amygdala seizures can cause postictal apnea. Moreover, we identified a distinct region within the amygdala where electrical stimulation was sufficient to reproduce prolonged breathing loss persisting well beyond the end of stimulation. The persistent apnea was resistant to rising CO2 levels, and air hunger failed to occur, suggesting impaired CO2 chemosensitivity. Using es-fMRI, a potentially novel approach combining electrical stimulation with functional MRI, we found that amygdala stimulation altered blood oxygen level-dependent (BOLD) activity in the pons/medulla and ventral insula. Together, these findings suggest that seizure activity in a focal subregion of the amygdala is sufficient to suppress breathing and air hunger for prolonged periods of time in the postictal period, likely via brainstem and insula sites involved in chemosensation and interoception. They further provide insights into SUDEP, may help identify those at greatest risk, and may lead to treatments to prevent SUDEP.

Longitudinal stability of individual brain plasticity patterns in blindness

The primary visual cortex (V1) in individuals born blind is engaged in a wide spectrum of tasks and sensory modalities, including audition, touch, language, and memory. This widespread involvement raises questions regarding the constancy of its role and whether it might exhibit flexibility in its function over time, connecting to diverse network functions in response to task-specific demands. This would suggest that reorganized V1 takes on a role similar to cognitive multiple-demand system regions. Alternatively, it is possible that the varying patterns of plasticity observed in the blind V1 can be attributed to individual factors, whereby different blind individuals recruit V1 for different functions, highlighting the immense idiosyncrasy of plasticity. In support of this second account, we have recently shown that V1 functional connectivity varies greatly across blind individuals. But do these represent stable individual patterns of plasticity or merely instantaneous changes, for a multiple-demand system now inhabiting V1? Here we tested if individual connectivity patterns from the visual cortex of blind individuals are stable over time. We show that over two years, fMRI functional connectivity from the primary visual cortex is unique and highly stable in a small sample of repeatedly sampled congenitally blind individuals. Further, using multivoxel pattern analysis, we demonstrate that the unique reorganization patterns of these individuals allow decoding of participant identity. Together with recent evidence for substantial individual differences in visual cortex connectivity, this indicates there may be a consistent role for the visual cortex in blindness, which may differ for each individual. Further, it suggests that the variability in visual reorganization in blindness across individuals could be used to seek stable neuromarkers for sight rehabilitation and assistive approaches.

Charting Aging Trajectories of Knee Cartilage Thickness for Early Osteoarthritis Risk Prediction: An MRI Study from the Osteoarthritis Initiative Cohort

Knee osteoarthritis (OA), a prevalent joint disease in the U.S., poses challenges in terms of predicting of its early progression. Although high-resolution knee magnetic resonance imaging (MRI) facilitates more precise OA diagnosis, the heterogeneous and multifactorial aspects of OA pathology remain significant obstacles for prognosis. MRI-based scoring systems, while standardizing OA assessment, are both time-consuming and labor-intensive. Current AI technologies facilitate knee OA risk scoring and progression prediction, but these often focus on the symptomatic phase of OA, bypassing initial-stage OA prediction. Moreover, their reliance on complex algorithms can hinder clinical interpretation. To this end, we make this effort to construct a computationally efficient, easily-interpretable, and state-of-the-art approach aiding in the radiographic OA (rOA) auto-classification and prediction of the incidence and progression, by contrasting an individual's cartilage thickness with a similar demographic in the rOA-free cohort. To better visualize, we have developed the toolset for both prediction and local visualization. A movie demonstrating different subtypes of dynamic changes in local centile scores during rOA progression is available at https://tli3.github.io/KneeOA/. Specifically, we constructed age-BMI-dependent reference charts for knee OA cartilage thickness, based on MRI scans from 957 radiographic OA (rOA)-free individuals from the Osteoarthritis Initiative cohort. Then we extracted local and global centiles by contrasting an individual's cartilage thickness to the rOA-free cohort with a similar age and BMI. Using traditional boosting approaches with our centile-based features, we obtain rOA classification of KLG ≤ 1 versus KLG = 2 (AUC = 0.95, F1 = 0.89), KLG ≤ 1 versus KLG ≥ 2 (AUC = 0.90, F1 = 0.82) and prediction of KLG2 progression (AUC = 0.98, F1 = 0.94), rOA incidence (KLG increasing from < 2 to ≥ 2; AUC = 0.81, F1 = 0.69) and rOA initial transition (KLG from 0 to 1; AUC = 0.64, F1 = 0.65) within a future 48-month period. Such performance in classifying KLG ≥ 2 matches that of deep learning methods in recent literature. Furthermore, its clinical interpretation suggests that cartilage changes, such as thickening in lateral femoral and anterior femoral regions and thinning in lateral tibial regions, may serve as indicators for prediction of rOA incidence and early progression. Meanwhile, cartilage thickening in the posterior medial and posterior lateral femoral regions, coupled with a reduction in the central medial femoral region, may signify initial phases of rOA transition.

Neuroimaging of social motivation during winning and losing: Associations with social anhedonia across the psychosis spectrum

BACKGROUND

Individuals with psychosis spectrum disorders (PSD) have difficulty developing social relationships. This difficulty may reflect reduced response to social feedback involving functional alterations in brain regions that support the social motivation system: ventral striatum, orbital frontal cortex, insula, dorsal anterior cingulate cortex, and amygdala. Whether these alterations span PSD is unknown.

METHODS

71 individuals with PSD, 27 unaffected siblings, and 37 control participants completed a team-based fMRI task. After each trial, participants received performance feedback paired with the expressive face of a teammate or opponent. A 2 × 2 (win versus loss outcome x teammate versus opponent) repeated measures ANOVA by group was performed on activation in the five key regions of interest during receipt of feedback.

RESULTS

Across groups, three social motivation regions, ventral striatum, orbital frontal cortex, and amygdala, showed sensitivity to feedback (significant main effect of outcome), with greater activation during win versus loss trials, regardless of whether the feedback was from a teammate or opponent. In PSD, ventral striatum and orbital frontal cortex activation to win feedback was negatively correlated with social anhedonia scores.

CONCLUSIONS

Patterns of neural activation during social feedback were similar in PSD, their unaffected siblings, and healthy controls. Across the psychosis spectrum, activity in key social motivation regions during social feedback was associated with individual differences in social anhedonia.

Intraoperative identification of functional brain areas with RGB imaging using statistical parametric mapping: Simulation and clinical studies

Complementary technique to preoperative fMRI and electrical brain stimulation (EBS) for glioma resection could improve dramatically the surgical procedure and patient care. Intraoperative RGB optical imaging is a technique for localizing functional areas of the human cerebral cortex that can be used during neurosurgical procedures. However, it still lacks robustness to be used with neurosurgical microscopes as a clinical standard. In particular, a robust quantification of biomarkers of brain functionality is needed to assist neurosurgeons. We propose a methodology to evaluate and optimize intraoperative identification of brain functional areas by RGB imaging. This consist in a numerical 3D brain model based on Monte Carlo simulations to evaluate intraoperative optical setups for identifying functional brain areas. We also adapted fMRI Statistical Parametric Mapping technique to identify functional brain areas in RGB videos acquired for 12 patients. Simulation and experimental results were consistent and showed that the intraoperative identification of functional brain areas is possible with RGB imaging using deoxygenated hemoglobin contrast. Optical functional identifications were consistent with those provided by EBS and preoperative fMRI. We also demonstrated that a halogen lighting may be particularity adapted for functional optical imaging. We showed that an RGB camera combined with a quantitative modeling of brain hemodynamics biomarkers can evaluate in a robust way the functional areas during neurosurgery and serve as a tool of choice to complement EBS and fMRI.

Associations between regular cannabis use and brain resting-state functional connectivity in adolescents and adults

BACKGROUND/AIM

Cannabis use is highly prevalent in adolescents; however, little is known about its effects on adolescent brain function.

METHOD

Resting-state functional magnetic resonance imaging was used in matched groups of regular cannabis users (N = 70, 35 adolescents: 16-17 years old, 35 adults: 26-29 years old) and non-regular-using controls (N = 70, 35 adolescents/35 adults). Pre-registered analyses examined the connectivity of seven major cortical and sub-cortical brain networks (default mode network, executive control network (ECN), salience network, hippocampal network and three striatal networks) using seed-based analysis methods with cross-sectional comparisons between user groups and age groups.

RESULTS

The regular cannabis use group (across both age groups), relative to controls, showed localised increases in connectivity only in the ECN analysis. All networks showed localised connectivity differences based on age group, with the adolescents generally showing weaker connectivity than adults, consistent with the developmental effects. Mean connectivity across entire network regions of interest (ROIs) was also significantly decreased in the ECN in adolescents. However, there were no significant interactions found between age group and user group in any of the seed-based or ROI analyses. There were also no associations found between cannabis use frequency and any of the derived connectivity measures.

CONCLUSION

Regular cannabis use is associated with changes in connectivity of the ECN, which may reflect allostatic or compensatory changes in response to regular cannabis intoxication. However, these associations were not significantly different in adolescents compared to adults.

Changes in resting-state functional MRI connectivity during and after transcranial direct current stimulation in healthy adults

Introduction

Transcranial direct current stimulation (tDCS) applied over the dorsolateral prefrontal cortex (DLPFC) at rest can influence behaviors. However, its mechanisms remain poorly understood. This study examined the effect of a single session of tDCS over the bilateral DLPFC on resting-state functional connectivity using fMRI (rs-fcMRI) during and after stimulation in healthy adults. We also investigated whether baseline rs-fcMRI predicted tDCS-induced changes in rs-fcMRI.

Methods

This was a randomized, sham-controlled, double-blind, crossover study. We delivered tDCS for 30 min at 1 mA with the anode and cathode over the left and right DLPFC, respectively. We used seed-based analyses to measure tDCS-induced effects on whole-brain rs-fcMRI using a 3 (before, during, after stimulation) × 2 (active, sham stimulation) ANOVA.

Results

There were four significant Time × Stimulation interactions on the connectivity scores with the left DLPFC seed (under the anode electrode) and no interactions for the right DLPFC seed (under the cathode electrode). tDCS changed rs-fcMRI between the left DLPFC seed and parieto-occipital, parietal, parieto-occipitotemporal, and frontal clusters during and after stimulation, as compared to sham. Furthermore, rs-fcMRI prior to stimulation predicted some of these tDCS-induced changes in rs-fcMRI during and after stimulation. For instance, rs-fcMRI of the fronto-parietooccipital network predicted changes observed after active stimulation, rs-fcMRI of the fronto-parietal network predicted changes during active stimulation, whereas rs-fcMRI of the fronto-parieto-occipitotemporal and the frontal networks predicted changes both during and after active stimulation.

Discussion

Our findings reveal that tDCS modulated rs-fcMRI both during and after stimulation mainly in regions distal, but also in those proximal to the area under the anode electrode, which were predicted by rs-fcMRI prior to tDCS. It might be worth considering rs-fcMRI to optimize response to tDCS.

Social-coalitional trait is related to coping capacity with mortality threat: association with leadership and a reduced parietal response to mortality salience

Introduction

Coping with mortality threat, a psychological threat unique to humans and distinct from general emotional distress, is traditionally characterized by immediate suppression and prolonged worldview defense within the framework of the influential terror management theory (TMT). Views regarding the personality-trait concepts for this coping capacity diverge: some favor a broad definition based on general psychological attitudes (e.g., hardiness), while others prefer a narrow definition linked to interpersonal attitudes related to social coalition (e.g., attachment style and self-transcendence).

Methods

Using functional MRI, we presented healthy older participants with death-related words and explored correlations between the neural responses to mortality threat and the factor scores of the Power to Live questionnaire, which measures eight resilience-related psychobehavioral traits.

Results

We observed a significant association between the factor score and a neural response only for leadership; individuals with a high leadership score exhibited reduced neural response to mortality salience in the right inferior parietal lobule.

Discussion

Within the TMT framework, our findings align with the concept of the immediate suppression of death-thought accessibility associated with a secure attachment style, a trait conceptually linked to leadership. These findings highlight the unique role for the narrowly defined social-coalitional trait during the immediate stage of the coping process with mortality salience, in contrast to the broadly defined resilience-related personality traits associated with a prolonged worldview defense process. The deterioration of this coping process could constitute a distinct aspect of psychopathology, separate from dysfunction in general emotion regulation.

Acute neural effects of fluoxetine on emotional regulation in depressed adolescents

BACKGROUND

Adolescent major depressive disorder (MDD) is associated with disrupted processing of emotional stimuli and difficulties in cognitive reappraisal. Little is known however about how current pharmacotherapies act to modulate the neural mechanisms underlying these key processes. The current study therefore investigated the neural effects of fluoxetine on emotional reactivity and cognitive reappraisal in adolescent depression.

METHODS

Thirty-one adolescents with MDD were randomised to acute fluoxetine (10 mg) or placebo. Seventeen healthy adolescents were also recruited but did not receive any treatment for ethical reasons. During functional magnetic resonance imaging (fMRI), participants viewed aversive images and were asked to either experience naturally the emotional state elicited ('Maintain') or to reinterpret the content of the pictures to reduce negative affect ('Reappraise'). Significant activations were identified using whole-brain analysis.

RESULTS

No significant group differences were seen when comparing Reappraise and Maintain conditions. However, when compared to healthy controls, depressed adolescents on placebo showed reduced visual activation to aversive pictures irrespective of the condition. The depressed adolescent group on fluoxetine showed the opposite pattern, i.e. increased visuo-cerebellar activity in response to aversive pictures, when compared to depressed adolescents on placebo.

CONCLUSIONS

These data suggest that depression in adolescence may be associated with reduced visual processing of aversive imagery and that fluoxetine may act to reduce avoidance of such cues. This could reflect a key mechanism whereby depressed adolescents engage with negative cues previously avoided. Future research combining fMRI with eye-tracking is nonetheless needed to further clarify these effects.

Altered brain connectivity in Long Covid during cognitive exertion: a pilot study

Introduction

Debilitating Long-Covid symptoms occur frequently after SARS-COVID-19 infection.

Methods

Functional MRI was acquired in 10 Long Covid (LCov) and 13 healthy controls (HC) with a 7 Tesla scanner during a cognitive (Stroop color-word) task. BOLD time series were computed for 7 salience and 4 default-mode network hubs, 2 hippocampus and 7 brainstem regions (ROIs). Connectivity was characterized by the correlation coefficient between each pair of ROI BOLD time series. We tested for HC versus LCov differences in connectivity between each pair of the 20 regions (ROI-to-ROI) and between each ROI and the rest of the brain (ROI-to-voxel). For LCov, we also performed regressions of ROI-to-ROI connectivity with clinical scores.

Results

Two ROI-to-ROI connectivities differed between HC and LCov. Both involved the brainstem rostral medulla, one connection to the midbrain, another to a DM network hub. Both were stronger in LCov than HC. ROI-to-voxel analysis detected multiple other regions where LCov connectivity differed from HC located in all major lobes. Most, but not all connections, were weaker in LCov than HC. LCov, but not HC connectivity, was correlated with clinical scores for disability and autonomic function and involved brainstem ROI.

Discussion

Multiple connectivity differences and clinical correlations involved brainstem ROIs. Stronger connectivity in LCov between the medulla and midbrain may reflect a compensatory response. This brainstem circuit regulates cortical arousal, autonomic function and the sleep-wake cycle. In contrast, this circuit exhibited weaker connectivity in ME/CFS. LCov connectivity regressions with disability and autonomic scores were consistent with altered brainstem connectivity in LCov.

Complex Brain-Heart Mapping in Mental and Physical Stress

OBJECTIVE

The central and autonomic nervous systems are deemed complex dynamic systems, wherein each system as a whole shows features that the individual system sub-components do not. They also continuously interact to maintain body homeostasis and appropriate react to endogenous and exogenous stimuli. Such interactions are comprehensively referred to functional brain-heart interplay (BHI). Nevertheless, it remains uncertain whether this interaction also exhibits complex characteristics, that is, whether the dynamics of the entire nervous system inherently demonstrate complex behavior, or if such complexity is solely a trait of the central and autonomic systems. Here, we performed complexity mapping of the BHI dynamics under mental and physical stress conditions.

METHODS AND PROCEDURES

Electroencephalographic and heart rate variability series were obtained from 56 healthy individuals performing mental arithmetic or cold-pressure tasks, and physiological series were properly combined to derive directional BHI series, whose complexity was quantified through fuzzy entropy.

RESULTS

The experimental results showed that BHI complexity is mainly modulated in the efferent functional direction from the brain to the heart, and mainly targets vagal oscillations during mental stress and sympathovagal oscillations during physical stress.

CONCLUSION

We conclude that the complexity of BHI mapping may provide insightful information on the dynamics of both central and autonomic activity, as well as on their continuous interaction.

CLINICAL IMPACT

This research enhances our comprehension of the reciprocal interactions between central and autonomic systems, potentially paving the way for more accurate diagnoses and targeted treatments of cardiovascular, neurological, and psychiatric disorders.

Comprehensive evaluation of harmonization on functional brain imaging for multisite data-fusion

To embrace big-data neuroimaging, harmonizing the site effect in resting-state functional magnetic resonance imaging (R-fMRI) data fusion is a fundamental challenge. A comprehensive evaluation of potentially effective harmonization strategies, particularly with specifically collected data, has been scarce, especially for R-fMRI metrics. Here, we comprehensively assess harmonization strategies from multiple perspectives, including tests on residual site effect, individual identification, test-retest reliability, and replicability of group-level statistical results, on widely used R-fMRI metrics across various datasets, including data obtained from participants with repetitive measures at different scanners. For individual identifiability (i.e., whether the same subject could be identified across R-fMRI data scanned across different sites), we found that, while most methods decreased site effects, the Subsampling Maximum-mean-distance based distribution shift correction Algorithm (SMA) and parametric unadjusted CovBat outperformed linear regression models, linear mixed models, ComBat series and invariant conditional variational auto-encoder in clustering accuracy. Test-retest reliability was better for SMA and parametric adjusted CovBat than unadjusted ComBat series and parametric unadjusted CovBat in the number of overlapped voxels. At the same time, SMA was superior to the latter in replicability in terms of the Dice coefficient and the scale of brain areas showing sex differences reproducibly observed across datasets. Furthermore, SMA better detected reproducible sex differences of ALFF under the site-sex confounded situation. Moreover, we designed experiments to identify the best target site features to optimize SMA identifiability, test-retest reliability, and stability. We noted both sample size and distribution of the target site matter and introduced a heuristic formula for selecting the target site. In addition to providing practical guidelines, this work can inform continuing improvements and innovations in harmonizing methodologies for big R-fMRI data.

Functional MRI reveals brain-wide actions of thalamically-initiated oscillatory activities on associative memory consolidation

As a key oscillatory activity in the brain, thalamic spindle activities are long believed to support memory consolidation. However, their propagation characteristics and causal actions at systems level remain unclear. Using functional MRI (fMRI) and electrophysiology recordings in male rats, we found that optogenetically-evoked somatosensory thalamic spindle-like activities targeted numerous sensorimotor (cortex, thalamus, brainstem and basal ganglia) and non-sensorimotor limbic regions (cortex, amygdala, and hippocampus) in a stimulation frequency- and length-dependent manner. Thalamic stimulation at slow spindle frequency (8 Hz) and long spindle length (3 s) evoked the most robust brain-wide cross-modal activities. Behaviorally, evoking these global cross-modal activities during memory consolidation improved visual-somatosensory associative memory performance. More importantly, parallel visual fMRI experiments uncovered response potentiation in brain-wide sensorimotor and limbic integrative regions, especially superior colliculus, periaqueductal gray, and insular, retrosplenial and frontal cortices. Our study directly reveals that thalamic spindle activities propagate in a spatiotemporally specific manner and that they consolidate associative memory by strengthening multi-target memory representation.

Deciphering Functional Connectivity Differences Between Motor Imagery and Execution of Target-Oriented Grasping

This study aimed to delineate overlapping and distinctive functional connectivity in visual motor imagery, kinesthetic motor imagery, and motor execution of target-oriented grasping action of the right hand. Functional magnetic resonance imaging data were obtained from 18 right-handed healthy individuals during each condition. Seed-based connectivity and multi-voxel pattern analyses were employed after selecting seed regions with the left primary motor cortex and supplementary motor area. There was equivalent seed-based connectivity during the three conditions in the bilateral frontoparietal and temporal areas. When the seed region was the left primary motor cortex, increased connectivity was observed in the left cuneus and superior frontal area during visual and kinesthetic motor imageries, respectively, compared with that during motor execution. Multi-voxel pattern analyses revealed that each condition was differentiated by spatially distributed connectivity patterns of the left primary motor cortex within the right cerebellum VI, cerebellum crus II, and left lingual area. When the seed region was the left supplementary motor area, the connectivity patterns within the right putamen, thalamus, cerebellar areas IV-V, and left superior parietal lobule were significantly classified above chance level across the three conditions. The present findings improve our understanding of the spatial representation of functional connectivity and its specific patterns among motor imagery and motor execution. The strength and fine-grained connectivity patterns of the brain areas can discriminate between motor imagery and motor execution.

Geometry-derived statistical significance: A probabilistic framework for detecting true positive findings in MRI data

INTRODUCTION

The false discovery rate (FDR) procedure does not incorporate the geometry of the random field and requires high statistical power at each voxel, a requirement not satisfied by the limited number of participants in imaging studies. Topological FDR, threshold free cluster enhancement (TFCE), and probabilistic TFCE improve statistical power by incorporating local geometry. However, topological FDR requires specifying a cluster defining threshold and TFCE requires specifying transformation weights.

METHODS

Geometry-derived statistical significance (GDSS) procedure overcomes these limitations by combining voxelwise p-values for the test statistic with the probabilities computed from the local geometry for the random field, thereby providing substantially greater statistical power than the procedures currently used to control for multiple comparisons. We use synthetic data and real-world data to compare its performance against the performance of these other, previously developed procedures.

RESULTS

GDSS provided substantially greater statistical power relative to the comparator procedures, which was less variable to the number of participants. GDSS was more conservative than TFCE: that is, it rejected null hypotheses at voxels with much higher effect sizes than TFCE. Our experiments also showed that the Cohen's D effect size decreases as the number of participants increases. Therefore, sample size calculations from small studies may underestimate the participants required in larger studies. Our findings also suggest effect size maps should be presented along with p-value maps for correct interpretation of findings.

CONCLUSIONS

GDSS compared with the other procedures provides considerably greater statistical power for detecting true positives while limiting false positives, especially in small sized (<40 participants) imaging cohorts.

Transient disruption of functional connectivity and depression of neural fluctuations in a mouse model of acute septic encephalopathy

Septic encephalopathy leads to major and costly burdens for a large percentage of admitted hospital patients. Elderly patients are at an increased risk, especially those with dementia. Current treatments are aimed at sedation to combat mental status changes and are not aimed at the underlying cause of encephalopathy. Indeed, the underlying pathology linking together peripheral infection and altered neural function has not been established, largely because good, acutely accessible readouts of encephalopathy in animal models do not exist. Behavioral testing in animals lasts multiple days, outlasting the time frame of acute encephalopathy. Here, we propose optical fluorescent imaging of neural functional connectivity (FC) as a readout of encephalopathy in a mouse model of acute sepsis. Imaging and basic behavioral assessment were performed at baseline, Hr8, Hr24, and Hr72 following injection of either lipopolysaccharide or phosphate buffered saline. Neural FC strength decreased at Hr8 and returned to baseline by Hr72 in motor, somatosensory, parietal, and visual cortical regions. Additionally, neural fluctuations transiently declined at Hr8 and returned to baseline by Hr72. Both FC strength and fluctuation tone correlated with neuroscore indicating this imaging methodology is a sensitive and acute readout of encephalopathy.

Automatic adaptive emotion regulation is associated with lower emotion-related activation in the frontoparietal cortex and other cortical regions with multi-componential organization

Although some researchers consider automatic adaptive emotion regulation to be an automatized strategy whereas others consider it to be implicit disengagement of deliberative process, to date, its neural correlates have been poorly investigated. In addition, the valence specificity of automatic adaptive emotion regulation and levels of activation relative to the neutral condition are controversial; the former is relevant to the attribution of resilient emotion regulation to positivity bias or emotional stability, and the latter to determining whether regulation is based on emotion-specific or emotion-non-specific processes. In this functional magnetic resonance imaging (fMRI) study, we presented positive and negative emotional pictures to healthy young participants and investigated the neural correlates of automatic adaptive emotion regulation in spontaneous emotional response. A significant negative trait effect (i.e., regression coefficient) on activation was identified both for positive and negative emotional responses in various cortical regions. A cluster analysis identified three clusters among these regions based on the valence specificity of the trait effect and level of activation relative to neutral stimuli. Cluster 1 included regions in the sensorimotor cortex characterized by negative emotion-specific decreases in activation relative to neutral stimuli in adaptive individuals. Cluster 2 included several cortical regions including the bilateral dorsal executive network, anterior cingulate, and inferior frontal gyrus, which were characterized by valence-independent decreases in activation in adaptive individuals. Cluster 3 included the bilateral ventrolateral and dorsomedial prefrontal cortices, right insula, and other posterior regions, which were characterized by increased activation for negative stimuli in non-adaptive individuals. These findings support the assumption that automatic adaptive emotion regulation involves the implicit disengagement of deliberative process and suggest the relevance of different cortical networks to the potential emotion- and valence-specificity of adaptive regulation.

Functional magnetic resonance imaging of headache: Issues, best-practices, and new directions, a narrative review

OBJECTIVE

To ensure readers are informed consumers of functional magnetic resonance imaging (fMRI) research in headache, to outline ongoing challenges in this area of research, and to describe potential considerations when asked to collaborate on fMRI research in headache, as well as to suggest future directions for improvement in the field.

BACKGROUND

Functional MRI has played a key role in understanding headache pathophysiology, and mapping networks involved with headache-related brain activity have the potential to identify intervention targets. Some investigators have also begun to explore its use for diagnosis.

METHODS/RESULTS

The manuscript is a narrative review of the current best practices in fMRI in headache research, including guidelines on transparency and reproducibility. It also contains an outline of the fundamentals of MRI theory, task-related study design, resting-state functional connectivity, relevant statistics and power analysis, image preprocessing, and other considerations essential to the field.

CONCLUSION

Best practices to increase reproducibility include methods transparency, eliminating error, using a priori hypotheses and power calculations, using standardized instruments and diagnostic criteria, and developing large-scale, publicly available datasets.

Correlates of poor insight: A comparative fMRI and sMRI study in obsessive-compulsive disorder and schizo-obsessive disorder

BACKGROUND

Despite the several researches on the correlates of insight in psychosis, less is known regarding the specificity of disease diagnosis on the relationship between insight and the correlates. The current study sought to explore the effects of insight and disease diagnosis on those in patients with obsessive-compulsive disorder (OCD) and patients with schizo-obsessive disorder (SOD).

METHODS

We evaluated clinical symptoms and neurocognitions among 111 patients (including 41 OCD with good insight, 40 OCD with poor insight, 14 SOD with good insight and 16 SOD with poor insight. Gray matter volume and spontaneous neural activity were also examined by analyzing the voxel-based morphometry and amplitude of low frequency fluctuation (ALFF), respectively.

RESULTS

Interactive effects of insight and diagnosis was found on working memory and the gray matter volume in right superior and middle temporal gyrus. Main effect of insight was found on working and visual memory, compulsion and obsession, and ALFF in right middle and superior occipital cortex. Main effect of diagnosis was found on severity of compulsion, relative verbal IQ, executive function, verbal and visual memory, working memory and ALFF in precuneus, medial superior frontal gyrus, anterior cingulate and paracingulate gyri, and inferior parietal, postcentral gyrus, paracentral lobule.

CONCLUSIONS

As a common feature in mental disorders, insight has its own special influence on neurocognition and possible structural/functional alterations in brain, and the influence is partly dependent of disease diagnosis.

Open-source statistical and data processing tools for wide-field optical imaging data in mice

Significance

Wide-field optical imaging (WOI) can produce concurrent hemodynamic and cell-specific calcium recordings across the entire cerebral cortex in animal models. There have been multiple studies using WOI to image mouse models with various environmental or genetic manipulations to understand various diseases. Despite the utility of pursuing mouse WOI alongside human functional magnetic resonance imaging (fMRI), and the multitude of analysis toolboxes in the fMRI literature, there is not an available open-source, user-friendly data processing and statistical analysis toolbox for WOI data.

Aim

To assemble a MATLAB toolbox for processing WOI data, as described and adapted to combine techniques from multiple WOI groups and fMRI.

Approach

We outline our MATLAB toolbox on GitHub with multiple data analysis packages and translate a commonly used statistical approach from the fMRI literature to the WOI data. To illustrate the utility of our MATLAB toolbox, we demonstrate the ability of the processing and analysis framework to detect a well-established deficit in a mouse model of stroke and plot activation areas during an electrical paw stimulus experiment.

Results

Our processing toolbox and statistical methods isolate a somatosensory-based deficit 3 days following photothrombotic stroke and cleanly localize sensory stimulus activations.

Conclusions

The toolbox presented here details an open-source, user-friendly compilation of WOI processing tools with statistical methods to apply to any biological question investigated with WOI techniques.

Controlling the familywise error rate in widefield optical neuroimaging of functional connectivity in mice

SIGNIFICANCE

Statistical inference in functional neuroimaging is complicated by the multiple testing problem and spatial autocorrelation. Common methods in functional magnetic resonance imaging to control the familywise error rate (FWER) include random field theory (RFT) and permutation testing. The ability of these methods to control the FWER in optical neuroimaging has not been evaluated.

AIM

We attempt to control the FWER in optical intrinsic signal imaging resting-state functional connectivity using both RFT and permutation inference at a nominal value of 0.05. The FWER was derived using a mass empirical analysis of real data in which the null is known to be true.

APPROACH

Data from normal mice were repeatedly divided into two groups, and differences between functional connectivity maps were calculated with pixel-wise t -tests. As the null hypothesis was always true, all positives were false positives.

RESULTS

Gaussian RFT resulted in a higher than expected FWER with either cluster-based (0.15) or pixel-based (0.62) methods. t -distribution RFT could achieve FWERs of 0.05 (cluster-based or pixel-based). Permutation inference always controlled the FWER.

CONCLUSIONS

RFT can lead to highly inflated FWERs. Although t -distribution RFT can be accurate, it is sensitive to statistical assumptions. Permutation inference is robust to statistical errors and accurately controls the FWER.

A Voxel-Based Morphometric Study of Gray Matter in Specific Phobia

The objective of this study was to analyze the neurostructural abnormalities of brain areas responsible for the acquisition and maintenance of fear in small animal phobia by comparing gray matter volume (GMV) in individuals with phobia and non-fearful controls. Structural magnetic resonance imaging was obtained from 62 adults (79% female) assigned to one of two groups: 31 were diagnosed with small animal phobia and 31 were non-fearful controls. To investigate structural alterations, a whole-brain voxel-based morphometry analysis was conducted to compare the GMV of the brain areas involved in fear between both groups. The results indicated that individuals with a small animal specific phobia showed smaller GMV in cortical regions, such as the orbitofrontal (OFC) and medial frontal cortex, and greater GMV in the putamen than non-fearful controls. These brain areas are responsible for avoidant behavior (putamen) and emotional regulation processes or inhibitory control (prefrontal cortex (PFC)), which might suggest a greater vulnerability of phobic individuals to acquiring non-adaptive conditioned responses and emotional dysregulation. The findings provide preliminary support for the involvement of structural deficits in OFC and medial frontal cortex in phobia, contributing to clarify the neurobiological substrates for phobias.

Functional MRI study of feedback-based reinforcement learning in depression

Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may alter activity in frontal and limbic structures that are key to learning. Although reward and decision-making have been examined in MDD, the effects of depression on associative learning is less well studied. We investigated whether depressive symptoms would be related to abnormalities in learning-related brain activity as measured by functional magnetic resonance imaging (fMRI). Also, we explored whether melancholic and atypical features were associated with altered brain activity. We conducted MRI scans on a 4T Varian MRI system in 10 individuals with MDD and 10 healthy subjects. We examined event-related brain activation during feedback-based learning task using Analysis of Functional NeuroImages (AFNI) for image processing and statistical analysis. We observed that MDD patients exhibited reduced activation in visual cortex but increased activation in cingulate and insular regions compared to healthy participants. Also, in relation to features of depressive subtypes, we observed that levels of activation in striatal, thalamic, and precuneus regions were negatively correlated with atypical characteristics. These results suggest that the effects of MDD change the neural circuitry underlying associative learning, and these effects may depend upon subtype features of MDD.

GeoSPM: Geostatistical parametric mapping for medicine

The characteristics and determinants of health and disease are often organized in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial relations. Drawing on statistical parametric mapping, a framework for topological inference well established in the realm of neuroimaging, we propose and validate an approach to the spatial analysis of diverse clinical data-GeoSPM-based on differential geometry and random field theory. We evaluate GeoSPM across an extensive array of synthetic simulations encompassing diverse spatial relationships, sampling, and corruption by noise, and demonstrate its application on large-scale data from UK Biobank. GeoSPM is readily interpretable, can be implemented with ease by non-specialists, enables flexible modeling of complex spatial relations, exhibits robustness to noise and under-sampling, offers principled criteria of statistical significance, and is through computational efficiency readily scalable to large datasets. We provide a complete, open-source software implementation.

Prenatal exposure to air pollution is associated with altered brain structure, function, and metabolism in childhood

BACKGROUND

Prenatal exposure to air pollution disrupts cognitive, emotional, and behavioral development. The brain disturbances associated with prenatal air pollution are largely unknown.

METHODS

In this prospective cohort study, we estimated prenatal exposures to fine particulate matter (PM_2.5 ) and polycyclic aromatic hydrocarbons (PAH), and then assessed their associations with measures of brain anatomy, tissue microstructure, neurometabolites, and blood flow in 332 youth, 6-14 years old. We then assessed how those brain disturbances were associated with measures of intelligence, ADHD and anxiety symptoms, and socialization.

RESULTS

Both exposures were associated with thinning of dorsal parietal cortices and thickening of postero-inferior and mesial wall cortices. They were associated with smaller white matter volumes, reduced organization in white matter of the internal capsule and frontal lobe, higher metabolite concentrations in frontal cortex, reduced cortical blood flow, and greater microstructural organization in subcortical gray matter nuclei. Associations were stronger for PM_2.5 in boys and PAH in girls. Youth with low exposure accounted for most significant associations of ADHD, anxiety, socialization, and intelligence measures with cortical thickness and white matter volumes, whereas it appears that high exposures generally disrupted these neurotypical brain-behavior associations, likely because strong exposure-related effects increased the variances of these brain measures.

CONCLUSIONS

The commonality of effects across exposures suggests PM_2.5 and PAH disrupt brain development through one or more common molecular pathways, such as inflammation or oxidative stress. Progressively higher exposures were associated with greater disruptions in local volumes, tissue organization, metabolite concentrations, and blood flow throughout cortical and subcortical brain regions and the white matter pathways interconnecting them. Together these affected regions comprise cortico-striato-thalamo-cortical circuits, which support the regulation of thought, emotion, and behavior.

Face shape processing via visual-to-auditory sensory substitution activates regions within the face processing networks in the absence of visual experience

Previous evidence suggests that visual experience is crucial for the emergence and tuning of the typical neural system for face recognition. To challenge this conclusion, we trained congenitally blind adults to recognize faces via visual-to-auditory sensory-substitution (SDD). Our results showed a preference for trained faces over other SSD-conveyed visual categories in the fusiform gyrus and in other known face-responsive-regions of the deprived ventral visual stream. We also observed a parametric modulation in the same cortical regions, for face orientation (upright vs. inverted) and face novelty (trained vs. untrained). Our results strengthen the conclusion that there is a predisposition for sensory-independent and computation-specific processing in specific cortical regions that can be retained in life-long sensory deprivation, independently of previous perceptual experience. They also highlight that if the right training is provided, such cortical preference maintains its tuning to what were considered visual-specific face features.

Improvement in prefrontal thalamic connectivity during the early course of the illness in recent-onset psychosis: a 12-month longitudinal follow-up resting-state fMRI study

BACKGROUND

Previous research in resting-state functional magnetic resonance imaging (rs-fMRI) has shown a mixed pattern of disrupted thalamocortical connectivity in psychosis. The clinical meaning of these findings and their stability over time remains unclear. We aimed to study thalamocortical connectivity longitudinally over a 1-year period in participants with recent-onset psychosis.

METHODS

To this purpose, 129 individuals with recent-onset psychosis and 87 controls were clinically evaluated and scanned using rs-fMRI. Among them, 43 patients and 40 controls were re-scanned and re-evaluated 12 months later. Functional connectivity between the thalamus and the rest of the brain was calculated using a seed to voxel approach, and then compared between groups and correlated with clinical features cross-sectionally and longitudinally.

RESULTS

At baseline, participants with recent-onset psychosis showed increased connectivity (compared to controls) between the thalamus and somatosensory and temporal regions (k = 653, T = 5.712), as well as decreased connectivity between the thalamus and left cerebellum and right prefrontal cortex (PFC; k = 201, T = -4.700). Longitudinal analyses revealed increased connectivity over time in recent-onset psychosis (relative to controls) in the right middle frontal gyrus.

CONCLUSIONS

Our results support the concept of abnormal thalamic connectivity as a core feature in psychosis. In agreement with a non-degenerative model of illness in which functional changes occur early in development and do not deteriorate over time, no evidence of progressive deterioration of connectivity during early psychosis was observed. Indeed, regionally increased connectivity between thalamus and PFC was observed.

Clinical Usefulness of Simultaneous Electroencephalography and Functional Magnetic Resonance Imaging in Children With Focal Epilepsy

Background and Purpose

The current study analyzed the interictal epileptiform discharge (IED)-related hemodynamic response and aimed to determine the clinical usefulness of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) in defining the epileptogenic zone (EZ) in children with focal epilepsy.

Methods

Patients with focal epilepsy showing IEDs on conventional EEG were evaluated using EEG-fMRI. Statistical analyses were performed using the times of spike as events modeled with multiple hemodynamic response functions. The area showing the most significant t-value for blood-oxygen-level-dependent (BOLD) changes was compared with the presumed EZ. Moreover, BOLD responses between -9 and +9 s around the spike times were analyzed to track the hemodynamic response patterns over time.

Results

Half (n=13) of 26 EEG-fMRI investigations of 19 patients were successful. Two patients showed 2 different types of spikes, resulting in 15 analyses. The maximum BOLD response was concordant with the EZ in 11 (73.3%) of the 15 analyses. In 10 (66.7%) analyses, the BOLD response localized the EZs more specifically. Focal BOLD responses in the EZs occurred before IEDs in 11 analyses and were often widespread after IEDs. Hemodynamic response patterns were consistent in the same epilepsy syndrome or when repeating the investigation in the same patients.

Conclusions

EEG-fMRI can provide additional information for localizing the EZ in children with focal epilepsy, and also reveal the pathogenesis of pediatric epilepsy by evaluating the patterns in the hemodynamic response across time windows of IEDs.

Hemispheric dissociations in regions supporting auditory sentence comprehension in older adults

We investigated how the aging brain copes with acoustic and syntactic challenges during spoken language comprehension. Thirty-eight healthy adults aged 54 - 80 years (M = 66 years) participated in an fMRI experiment wherein listeners indicated the gender of an agent in short spoken sentences that varied in syntactic complexity (object-relative vs subject-relative center-embedded clause structures) and acoustic richness (high vs low spectral detail, but all intelligible). We found widespread activity throughout a bilateral frontotemporal network during successful sentence comprehension. Consistent with prior reports, bilateral inferior frontal gyrus and left posterior superior temporal gyrus were more active in response to object-relative sentences than to subject-relative sentences. Moreover, several regions were significantly correlated with individual differences in task performance: Activity in right frontoparietal cortex and left cerebellum (Crus I & II) showed a negative correlation with overall comprehension. By contrast, left frontotemporal areas and right cerebellum (Lobule VII) showed a negative correlation with accuracy specifically for syntactically complex sentences. In addition, laterality analyses confirmed a lack of hemispheric lateralization in activity evoked by sentence stimuli in older adults. Importantly, we found different hemispheric roles, with a left-lateralized core language network supporting syntactic operations, and right-hemisphere regions coming into play to aid in general cognitive demands during spoken sentence processing. Together our findings support the view that high levels of language comprehension in older adults are maintained by a close interplay between a core left hemisphere language network and additional neural resources in the contralateral hemisphere.

Representational Coding of Overt and Covert Orienting of Visuospatial Attention in the Frontoparietal Network

Orienting of visuospatial attention refers to reallocation of attentional focus from one target or location to another and can occur either with (overt) or without (covert) eye movement. Although it has been demonstrated that both types of orienting commonly involve frontal and parietal brain regions as the frontoparietal network (FPN), the underlying representational coding of these two types of orienting remains unclear. In this functional magnetic resonance imaging study, participants performed a task that elicited overt and covert orienting to endogenously or exogenously cued targets with eye-tracking to monitor eye movement. Although the FPN was commonly activated for both overt and covert orienting, multivariate patterns of the activation of voxels in the FPN accurately predicted whether eye movements were involved or not during orienting. These overt- and covert-preferred voxels were topologically distributed as distinct and interlaced clusters in a millimeter scale. Inclusion of the two types of clusters predicted orienting type more accurately than one type of clusters alone. These findings suggest that overt and covert orienting are represented by interdependent functional clusters of neuronal populations in regions of the FPN, which might reflect a generalizable principle in the nervous system for functional organization of closely associated processes.

CLEAN: Leveraging spatial autocorrelation in neuroimaging data in clusterwise inference

While clusterwise inference is a popular approach in neuroimaging that improves sensitivity, current methods do not account for explicit spatial autocorrelations because most use univariate test statistics to construct cluster-extent statistics. Failure to account for such dependencies could result in decreased reproducibility. To address methodological and computational challenges, we propose a new powerful and fast statistical method called CLEAN (Clusterwise inference Leveraging spatial Autocorrelations in Neuroimaging). CLEAN computes multivariate test statistics by modelling brain-wise spatial autocorrelations, constructs cluster-extent test statistics, and applies a refitting-free resampling approach to control false positives. We validate CLEAN using simulations and applications to the Human Connectome Project. This novel method provides a new direction in neuroimaging that paces with advances in high-resolution MRI data which contains a substantial amount of spatial autocorrelation.

Complexity Modulation in functional Brain-Heart Interplay series driven by Emotional Stimuli: an early study using Fuzzy Entropy

Increasing attention has recently been devoted to the multidisciplinary investigation of functional brain-heart interplay (BHI), which has provided meaningful insights in neuroscience and clinical domains including cardiology, neurology, clinical psychology, and psychiatry. While neural (brain) and heartbeat series show high nonlinear and complex dynamics, a complexity analysis on BHI series has not been performed yet. To this end, in this preliminary study, we investigate BHI complexity modulation in 17 healthy subjects undergoing a 3-minute resting state and emotional elicitation through standardized image slideshow. Electroencephalographic and heart rate variability series were the inputs of an adhoc BHI model, which provides directional (from-heart-to-brain and from-brain-to-heart) estimates at different frequency bands. A Fuzzy entropy analysis was performed channel-wise on the model output for the two experimental conditions. Results suggest that BHI complexity increases in the emotional elicitation phase with respect to a resting state, especially in the functional direction from the heart to the brain. We conclude that BHI complexity may be a viable computational tool to characterize neurophysiological and pathological states under different experimental conditions.

Meta-analysis of human prediction error for incentives, perception, cognition, and action

Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, there is still much to learn. Here, we leverage the wealth of human PE data acquired in the functional neuroimaging setting in service of a deeper understanding, using an MKDA (multi-level kernel-based density) meta-analysis. Studies were identified with Google Scholar, and we included studies with healthy adult participants that reported activation coordinates corresponding to PEs published between 1999-2018. Across 264 PE studies that have focused on reward, punishment, action, cognition, and perception, consistent with domain-general theoretical models of prediction error we found midbrain PE signals during cognitive and reward learning tasks, and an insula PE signal for perceptual, social, cognitive, and reward prediction errors. There was evidence for domain-specific error signals--in the visual hierarchy during visual perception, and the dorsomedial prefrontal cortex during social inference. We assessed bias following prior neuroimaging meta-analyses and used family-wise error correction for multiple comparisons. This organization of computation by region will be invaluable in building and testing mechanistic models of cognitive function and dysfunction in machines, humans, and other animals. Limitations include small sample sizes and ROI masking in some included studies, which we addressed by weighting each study by sample size, and directly comparing whole brain vs. ROI-based results.

Neurofilament light in plasma is a potential biomarker of central nervous system involvement in systemic lupus erythematosus

BACKGROUND

Neuropsychiatric manifestations (NP) are common in systemic lupus erythematosus (SLE). However, the pathophysiological mechanisms are not completely understood. Neurofilament light protein (NfL) is part of the neuronal cytoskeleton. Increased NfL concentrations, reflecting neurodegeneration, is observed in cerebrospinal fluid (CSF) in several neurodegenerative and neuroinflammatory conditions. We aimed to explore if plasma NfL could serve as a biomarker for central nervous system (CNS) involvement in SLE.

METHODS

Sixty-seven patients with SLE underwent neurological examination; 52 underwent lumbar puncture, while 62 underwent cerebral magnetic resonance imaging (MRI). We measured selected auto-antibodies and other laboratory variables postulated to have roles in NP pathophysiology in the blood and/or CSF. We used SPM12 software for MRI voxel-based morphometry.

RESULTS

Age-adjusted linear regression analyses revealed increased plasma NfL concentrations with increasing creatinine (β = 0.01, p < 0.001) and Q-albumin (β = 0.07, p = 0.008). We observed higher plasma NfL concentrations in patients with a history of seizures (β = 0.57, p = 0.014), impaired motor function (β = 0.36, p = 0.008), increasing disease activity (β = 0.04, p = 0.008), and organ damage (β = 0.10, p = 0.002). Voxel-based morphometry suggested an association between increasing plasma NfL concentrations and the loss of cerebral white matter in the corpus callosum and hippocampal gray matter.

CONCLUSION

Increased plasma NfL concentrations were associated with some abnormal neurological, cognitive, and neuroimaging findings. However, plasma NfL was also influenced by other factors, such as damage accrual, creatinine, and Q-albumin, thereby obscuring the interpretation of how plasma NfL reflects CNS involvement. Taken together, NfL in CSF seems a better marker of neuronal injury than plasma NfL in patients with SLE.

Learning under social versus nonsocial uncertainty: A meta-analytic approach

Much of the uncertainty that clouds our understanding of the world springs from the covert values and intentions held by other people. Thus, it is plausible that specialized mechanisms that compute learning signals under uncertainty of exclusively social origin operate in the brain. To test this hypothesis, we scoured academic databases for neuroimaging studies involving learning under uncertainty, and performed a meta‐analysis of brain activation maps that compared learning in the face of social versus nonsocial uncertainty. Although most of the brain activations associated with learning error signals were shared between social and nonsocial conditions, we found some evidence for functional segregation of error signals of exclusively social origin during learning in limited regions of ventrolateral prefrontal cortex and insula. This suggests that most behavioral adaptations to navigate social environments are reused from frontal and subcortical areas processing generic value representation and learning, but that a specialized circuitry might have evolved in prefrontal regions to deal with social context representation and strategic action.