Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI

Fast 3D fMRI acquisition with high spatial resolutions over a reduced FOV

PURPOSE

To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k-t 3D reduced FOV imaging (3D-rFOVI).

METHODS

Based on 3D gradient-echo EPI, k-t 3D-rFOVI used a 2D RF pulse to reduce the FOV in the in-plane phase-encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k-space region along the through-slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k-t 3D-rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k-t 3D-rFOVI and compare it with a commercial multiband EPI sequence.

RESULTS

The simulation data showed that k-t 3D-rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5-mm spatial resolution and 800-ms volume TR (TRvol), k-t 3D-rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k-t 3D-rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation.

CONCLUSIONS

k-t 3D-rFOVI can simultaneously achieve a high spatial resolution (1.5-mm isotropically) and short TRvol (480-ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume.

The effect of multiband sequences on statistical outcome measures in functional magnetic resonance imaging using a gustatory stimulus

Recent technical developments have led to the invention of multiband functional magnetic resonance imaging (fMRI) sequences that allow for faster sampling rates. However, some studies have highlighted problems with these sequences, leading to a decreased temporal signal-to-noise ratio (tSNR). In addition, this temporal noise may interfere with detecting reward-related responses in mesolimbic regions. The blood-oxygen-level-dependent signal utilized in the majority of fMRI measurements is relatively slow. Furthermore, the cerebral response to gustatory stimuli would also be relatively slow. Therefore, given the temporal noise issues with multiband sequences, it is unclear whether multiband sequences are necessary for fMRI studies using gustatory stimuli. We thus conducted an fMRI experiment using a gustatory stimulus to investigate the effects of multiband sequences and increased sampling rates on statistical outcome measures. A single-band sequence with a repetition time (TR) of 2 s of phantom fMRI data and gustatory fMRI data from the gustatory regions exhibited the highest tSNR, although the tSNR of this sequence of gustatory fMRI was not statistically different from tSNR of multiband sequences with a TR of 2 s in any of the selected region of interests. Conventional general linear model analysis of fMRI showed that single-band sequences are more advantageous than multiband sequences for detecting brain responses to gustatory stimuli in the primary gustatory cortex. In addition, a Bayesian data comparison showed that data derived from a single-band sequence with a TR of 2 s was optimal for inferring neuronal connectivity in gustatory processing. Therefore, a conventional single-band sequence with a TR of 2 s is more appropriate for fMRI with gustatory stimuli. Image acquisition sequences should be selected aligned with the study objectives and target brain regions.

Dynamic estimation of the attentional field from visual cortical activity

Navigating around the world, we must adaptively allocate attention to our surroundings based on anticipated future stimuli and events. This allocation of spatial attention boosts visuocortical representations at attended locations and locally enhances perception. Indeed, spatial attention has often been analogized to a "spotlight" shining on the item of relevance. Although the neural underpinnings of the locus of this attentional spotlight have been relatively well studied, less is known about the size of the spotlight: to what extent can the attentional field be broadened and narrowed in accordance with behavioral demands? In this study, we developed a paradigm for dynamically estimating the locus and spread of covert spatial attention, inferred from visuocortical activity using fMRI in humans. We measured BOLD activity in response to an annulus while participants (4 female, 4 male) used covert visual attention to determine whether more numbers or letters were present in a cued region of the annulus. Importantly, the width of the cued area was systematically varied, calling for different sizes of the attentional spotlight. The deployment of attention was associated with an increase in BOLD activity in corresponding retinotopic regions of visual areas V1-V3. By modeling the visuocortical attentional modulation, we could reliably recover the cued location, as well as a broadening of the attentional enhancement with wider attentional cues. This modeling approach offers a useful window into the dynamics of attention and spatial uncertainty.

Significance Statement

This study explores whether spatial attention can dynamically adapt by shifting and broadening the attentional field. While previous research has focused on the modulation of neural responses at attended locations, less is known about how the size of the attentional field is represented within visual cortex. Using fMRI, we developed a novel paradigm to estimate the spatial tuning of the attentional field and demonstrate that we were able to recover both the location as well as the width of the attentional field. Our findings offer new insights into the neural mechanisms underlying the deployment of spatial attention, contributing to a deeper understanding of how spatial attention supports visual perception.

Macrovascular blood flow and microvascular cerebrovascular reactivity are regionally coupled in adolescence

Cerebrovascular imaging assessments are particularly challenging in adolescent cohorts, where not all modalities are appropriate, and rapid brain maturation alters hemodynamics at both macro- and microvascular scales. In a preliminary sample of healthy adolescents (n=12, 8-25 years), we investigated relationships between 4D flow MRI-derived blood velocity and blood flow in bilateral anterior, middle, and posterior cerebral arteries and BOLD cerebrovascular reactivity in associated vascular territories. As hypothesized, higher velocities in large arteries are associated with an earlier response to a vasodilatory stimulus (cerebrovascular reactivity delay) in the downstream territory. Higher blood flow through these arteries is associated with a larger BOLD response to a vasodilatory stimulus (cerebrovascular reactivity amplitude) in the associated territory. These trends are consistent in a case study of adult moyamoya disease. In our small adolescent cohort, macrovascular-microvascular relationships for velocity/delay and flow/CVR change with age, though underlying mechanisms are unclear. Our work emphasizes the need to better characterize this key stage of human brain development, when cerebrovascular hemodynamics are changing, and standard imaging methods offer limited insight into these processes. We provide important normative data for future comparisons in pathology, where combining macro- and microvascular assessments may better help us prevent, stratify, and treat cerebrovascular disease.

Inhibitory mechanisms in the prefrontal-cortex differentially mediate Putamen activity during valence-based learning

Learning from appetitive and aversive stimuli involves interactions between the prefrontal cortex and subcortical structures. Preclinical and theoretical studies indicate that inhibition is essential in regulating the relevant neural circuitry. Here, we demonstrate that GABA, the main inhibitory neurotransmitter in the central nervous system, differentially affects how the dACC interacts with subcortical structures during appetitive and aversive learning in humans. Participants engaged in tasks involving appetitive and aversive learning, while using functional magnetic resonance spectroscopy (MRS) at 7T to track GABA concentrations in the dACC, alongside whole-brain fMRI scans to assess BOLD activation. During appetitive learning, dACC GABA concentrations were negatively correlated with learning performance and BOLD activity measured from the dACC and the Putamen. These correlations were absent during aversive learning, where dACC GABA concentrations negatively correlated with the connectivity between the dACC and the Putamen. Our results show that inhibition in the dACC mediates appetitive and aversive learning in humans through distinct mechanisms.

Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the study's core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

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.

POSE: POSition Encoding for accelerated quantitative MRI

Quantitative MRI utilizes multiple acquisitions with varying sequence parameters to sufficiently characterize a biophysical model of interest, resulting in undesirable scan times. Here we propose, validate and demonstrate a new general strategy for accelerating MRI using subvoxel shifting as a source of encoding called POSition Encoding (POSE). The POSE framework applies unique subvoxel shifts along the acquisition parameter dimension, thereby creating an extra source of encoding. Combining with a biophysical signal model of interest, accelerated and enhanced resolution maps of biophysical parameters are obtained. This has been validated and demonstrated through numerical Bloch equation simulations, phantom experiments and in vivo experiments using the variable flip angle signal model in 3D acquisitions as an application example. Monte Carlo simulations were performed using in vivo data to investigate our method's noise performance. POSE quantification results from numerical Bloch equation simulations of both a numerical phantom and realistic digital brain phantom concur well with the reference method, validating our method both theoretically and for realistic situations. NIST phantom experiment results show excellent overall agreement with the reference method, confirming our method's applicability for a wide range of T1 values. In vivo results not only exhibit good agreement with the reference method, but also show g-factors that significantly outperforms conventional parallel imaging methods with identical acceleration. Furthermore, our results show that POSE can be combined with parallel imaging to further accelerate while maintaining superior noise performance over parallel imaging that uses lower acceleration factors.

Fuzzy ripple artifact in high resolution fMRI: identification, cause, and mitigation

Purpose

High resolution fMRI is a rapidly growing research field focused on capturing functional signal changes across cortical layers. However, the data acquisition is limited by low spatial frequency EPI artifacts; termed here as Fuzzy Ripples. These artifacts limit the practical applicability of acquisition protocols with higher spatial resolution, faster acquisition speed, and they challenge imaging in lower brain areas.

Methods

We characterize Fuzzy Ripple artifacts across commonly used sequences and distinguish them from conventional EPI Nyquist ghosts, off-resonance effects, and GRAPPA artifacts. To investigate their origin, we employ dual polarity readouts.

Results

Our findings indicate that Fuzzy Ripples are primarily caused by readout-specific imperfections in k-space trajectories, which can be exacerbated by inductive coupling between third-order shims and readout gradients. We also find that these artifacts can be mitigated through complex-valued averaging of dual polarity EPI or by disconnecting the third-order shim coils.

Conclusion

The proposed mitigation strategies allow overcoming current limitations in layer-fMRI protocols: (1)Achieving resolutions beyond 0.8mm is feasible, and even at 3T, we achieved 0.53mm voxel functional connectivity mapping.(2)Sub-millimeter sampling acceleration can be increased to allow sub-second TRs and laminar whole brain protocols with up to GRAPPA 8.(3)Sub-millimeter fMRI is achievable in lower brain areas, including the cerebellum.

Global brain connectivity: Test-retest stability and association with biological and neurocognitive variables

BACKGROUND

Global brain connectivity (GBC) enables measuring brain regions' functional connectivity strength at rest by computing the average correlation between each brain voxel's time-series and that of all other voxels.

NEW METHOD

We used resting-state fMRI (rs-fMRI) data of young adult participants from the Human Connectome Project (HCP) dataset to explore the test-retest stability of GBC, the brain regions with higher or lower GBC, as well as the associations of this measure with age, sex, and fluid intelligence. GBC was computed by considering separately the positive and negative correlation coefficients (positive GBC and negative GBC).

RESULTS

Test-retest stability was higher for positive compared to negative GBC. Areas with higher GBC were located in the default mode network, insula, and visual areas, while regions with lower GBC were in subcortical regions, temporal cortex, and cerebellum. Higher age was related to global reduction of positive GBC. Males displayed higher positive GBC in the whole brain. Fluid intelligence was associated to increased positive GBC in fronto-parietal, occipital and temporal regions.

COMPARISON WITH EXISTING METHOD

Compared to previous works, this study adopted a larger sample size and tested GBC stability using data from different rs-fMRI sessions. Moreover, these associations were examined by testing positive and negative GBC separately.

CONCLUSIONS

Lower stability for negative compared to positive GBC suggests that negative correlations may reflect less stable couplings between brain regions. Our findings indicate a greater importance of positive compared to negative GBC for the associations of functional connectivity strength with biological and neurocognitive variables.

Insomnia-related brain functional correlates in first-episode drug-naïve major depressive disorder revealed by resting-state fMRI

Introduction

Insomnia is a common comorbidity symptom in major depressive disorder (MDD) patients. Abnormal brain activities have been observed in both MDD and insomnia patients, however, the central pathological mechanisms underlying the co-occurrence of insomnia in MDD patients are still unclear. This study aimed to explore the differences of spontaneous brain activity between MDD patients with and without insomnia, as well as patients with different level of insomnia.

Methods

A total of 88 first-episode drug-naïve MDD patients including 44 with insomnia (22 with high insomnia and 22 with low insomnia) and 44 without insomnia, as well as 44 healthy controls (HC), were enrolled in this study. The level of depression and insomnia were evaluated by HAMD-17, adjusted HAMD-17 and its sleep disturbance subscale in all subjects. Resting-state functional and structural magnetic resonance imaging data were acquired from all participants and then were preprocessed by the software of DPASF. Regional homogeneity (ReHo) values of brain regions were calculated by the software of REST and were compared. Finally, receiver operating characteristic (ROC) curves were conducted to determine the values of abnormal brain regions for identifying MDD patients with insomnia and evaluating the severity of insomnia.

Results

Analysis of variance showed that there were significant differences in ReHo values in the left middle frontal gyrus, left pallidum, right superior frontal gyrus, right medial superior frontal gyrus and right rectus gyrus among three groups. Compared with HC, MDD patients with insomnia showed increased ReHo values in the medial superior frontal gyrus, middle frontal gyrus, triangular inferior frontal gyrus, calcarine fissure and right medial superior frontal gyrus, medial orbital superior frontal gyrus, as well as decreased ReHo values in the left middle occipital gyrus, pallidum and right superior temporal gyrus, inferior temporal gyrus, middle cingulate gyrus, hippocampus, putamen. MDD patients without insomnia demonstrated increased ReHo values in the left middle frontal gyrus, orbital middle frontal gyrus, anterior cingulate gyrus and right triangular inferior frontal gyrus, as well as decreased ReHo values in the left rectus gyrus, postcentral gyrus and right rectus gyrus, fusiform gyrus, pallidum. In addition, MDD patients with insomnia had decreased ReHo values in the left insula when compared to those without insomnia. Moreover, MDD patients with high insomnia exhibited increased ReHo values in the right middle temporal gyrus, and decreased ReHo values in the left orbital superior frontal gyrus, lingual gyrus, right inferior parietal gyrus and postcentral gyrus compared to those with low insomnia. ROC analysis demonstrated that impaired brain region might be helpful for identifying MDD patients with insomnia and evaluating the severity of insomnia.

Conclusion

These findings suggested that MDD patients with insomnia had wider abnormalities of brain activities in the prefrontal-limbic circuits including increased activities in the prefrontal cortex, which might be the compensatory mechanism underlying insomnia in MDD. In addition, decreased activity of left insula might be associated with the occurrence of insomnia in MDD patients and decreased activities of the frontal-parietal network might cause more serious insomnia related to MDD.

SAD: semi-supervised automatic detection of BOLD activations in high temporal resolution fMRI data

OBJECTIVE

Despite the prevalent use of the general linear model (GLM) in fMRI data analysis, assuming a pre-defined hemodynamic response function (HRF) for all voxels can lead to reduced reliability and may distort the inferences derived from it. To overcome the necessity of presuming a specific model for the hemodynamic response, we introduce a semi-supervised automatic detection (SAD) method.

MATERIALS AND METHODS

The proposed SAD method employs a Bi-LSTM neural network to classify high temporal resolution fMRI data. Network training utilized an fMRI dataset with 75-ms temporal resolution in an iterative scheme. Classification performance was evaluated on a second fMRI dataset from the same participant, collected on a different day. Comparative analysis with the standard GLM approach was conducted to evaluate the cooperative effectiveness of the SAD method.

RESULTS

The SAD method performed well based on the classification scores: true-positive rate = 0.961, area under the receiver operating curve = 0.998, true-negative rate = 0.99, F1-score = 0.979, False-negative rate = 0.038, false-discovery rate = 0.002, false-positive rate = 0.002 at 75-ms temporal resolution.

CONCLUSION

SAD can detect hemodynamic responses at 75-ms temporal resolution without relying on a specific shape of an HRF. Future work could expand the use cases to include more participants and different fMRI paradigms.

Brain activation and aberrant effective connectivity in the mentalizing network of preadolescent children at familial high-risk of schizophrenia or bipolar disorder

INTRODUCTION

Schizophrenia and bipolar disorder are characterized by social cognitive impairments and recent research has identified alterations of the social brain. However, it is unknown whether familial high-risk of these disorders is associated with neurobiological alterations already present in childhood.

METHODS

As part of The Danish High Risk and Resilience Study - VIA 11, we examined children at familial high-risk of schizophrenia (FHR-SZ, n = 121, 50% females) or bipolar disorder (FHR-BP, n = 75, 47% females) and population-based controls (PBC, n = 128, 48% females). Using functional magnetic resonance imaging and dynamic causal modeling, we investigated brain activation and effective connectivity during the social cognition paradigm from the Human Connectome Project.

RESULTS

We found similar activation of the mentalizing network across groups, including visual area V5, dorsomedial prefrontal cortex (dmPFC), and posterior superior temporal sulcus (pSTS). Nonetheless, both familial high-risk groups showed aberrant brain connectivity in the form of increased feedforward connectivity from left V5 to pSTS compared with PBC. Children at FHR-SZ had reduced intrinsic connectivity in bilateral V5 relative to PBC, whereas children at FHR-BP showed increased reciprocal connectivity between left dmPFC and pSTS, increased intrinsic connectivity in right pSTS, and reduced feedforward connectivity from right pSTS to dmPFC compared with PBC.

CONCLUSIONS

Our results provide first-time evidence of aberrant brain connectivity in the mentalizing network of children at FHR-SZ or FHR-BP. Longitudinal research is warranted to clarify whether aberrant brain connectivity during mentalizing constitutes an endophenotype associated with the development of a mental disorder later in life.

Distinct functional connectivity patterns during naturalistic learning by adolescent first versus second language speakers

Spoken lessons (lectures) are commonly used in schools as a medium for conveying educational content. In adolescence, experience-expectant maturation of language and cognitive systems supports learning; however, little is known about whether or how learners' language experiences interact with this integration process during learning. We examined functional connectivity using fMRI in 38 Spanish-English bilingual (L1-Spanish) and English monolingual (L1-English) adolescents during a naturalistic science video lesson in English. Seed analyses including the left inferior frontal gyrus (pars opercularis) and posterior middle temporal gyrus showed that L1-Spanish adolescents, when learning in their second language (L2), displayed widespread bilateral functional connectivity throughout the cortex while L1-English adolescents displayed mostly left-lateralized connectivity with core language regions over the course of the science lesson. Furthermore, we identified functional seed connectivity associated with better learning outcomes for adolescents with diverse language backgrounds. Importantly, functional connectivity patterns in L1-Spanish adolescents while learning in English also correlate with their Spanish cloze reading. Findings suggest that functional networks associated with higher-order language processing and cognitive control are differentially engaged for L1 vs. L2 speakers while learning new information through spoken language.

Cortico-Cerebellar Monitoring of Speech Sequence Production

In a functional magnetic resonance imaging study, we examined speech error monitoring in a cortico-cerebellar network for two contrasts: (a) correct trials with high versus low articulatory error probability and (b) overtly committed errors versus correct trials. Engagement of the cognitive cerebellar region Crus I in both contrasts suggests that this region is involved in overarching performance monitoring. The activation of cerebellar motor regions (superior medial cerebellum, lobules VI and VIII) indicates the additional presence of a sensorimotor driven implementation of control. The combined pattern of pre-supplementary motor area (active across contrasts) and anterior cingulate cortex (only active in the contrast involving overt errors) activations suggests sensorimotor driven feedback monitoring in the medial frontal cortex, making use of proprioception and auditory feedback through overt errors. Differential temporal and parietal cortex activation across contrasts indicates involvement beyond sensorimotor driven feedback in line with speech production models that link these regions to auditory target processing and internal modeling-like mechanisms. These results highlight the presence of multiple, possibly hierarchically interdependent, mechanisms that support the optimizing of speech production.

From Maps to Models: A Survey on the Reliability of Small Studies of Task-Based fMRI

Task-based functional magnetic resonance imaging is a powerful tool for studying brain function, but neuroimaging research produces ongoing concerns regarding small-sample studies and how to interpret them. Although it is well understood that larger samples are preferable, many situations require researchers to make judgments from small studies, including reviewing the existing literature, analyzing pilot data, or assessing subsamples. Quantitative guidance on how to make these judgments remains scarce. To address this, we leverage the Human Connectome Project's Young Adult dataset to survey various analyses-from regional activation maps to predictive models. We find that, for some classic analyses such as detecting regional activation or cluster peak location, studies with as few as 40 subjects are adequate, although this depends crucially on effect sizes. For predictive modeling, similar sizes can be adequate for detecting whether features are predictable, but at least an order of magnitude more (at least hundreds) may be required for developing consistent predictions. These results offer valuable insights for designing and interpreting fMRI studies, emphasizing the importance of considering effect size, sample size, and analysis approach when assessing the reliability of findings. We hope that this survey serves as a reference for identifying which kinds of research questions can be reliably answered with small-scale studies.

Recurrent inhibition refines mental templates to optimize perceptual decisions

Translating sensory inputs to perceptual decisions relies on building internal representations of features critical for solving complex tasks. Yet, we still lack a mechanistic account of how the brain forms these mental templates of task-relevant features to optimize decision-making. Here, we provide evidence for recurrent inhibition: an experience-dependent plasticity mechanism that refines mental templates by enhancing γ-aminobutyric acid (GABA)-mediated (GABAergic) inhibition and recurrent processing in superficial visual cortex layers. We combine ultrahigh-field (7 T) functional magnetic resonance imaging at submillimeter resolution with magnetic resonance spectroscopy to investigate the fine-scale functional and neurochemical plasticity mechanisms for optimized perceptual decisions. We demonstrate that GABAergic inhibition increases following training on a visual (i.e., fine orientation) discrimination task, enhancing the discriminability of orientation representations in superficial visual cortex layers that are known to support recurrent processing. Modeling functional and neurochemical plasticity interactions reveals that recurrent inhibitory processing optimizes brain computations for perpetual decisions and adaptive behavior.

Altered brain perfusion and oxygen levels relate to sleepiness and attention in post-COVID syndrome

OBJECTIVE

Persisting neurological symptoms after COVID-19 affect up to 10% of patients and can manifest in fatigue and cognitive complaints. Based on recent evidence, we evaluated whether cerebral hemodynamic changes contribute to post-COVID syndrome (PCS).

METHODS

Using resting-state functional magnetic resonance imaging, we investigated brain perfusion and oxygen level estimates in 47 patients (44.4 ± 11.6 years; F:M = 38:9) and 47 individually matched healthy control participants. Group differences were calculated using two-sample t-tests. Multivariable linear regression was used for associations of each regional perfusion and oxygen level measure with cognition and sleepiness measures. Exploratory hazard ratios were calculated for each brain metric with clinical measures.

RESULTS

Patients presented with high levels of fatigue (79%) and daytime sleepiness (45%). We found widespread decreased brain oxygen levels, most evident in the white matter (false discovery rate adjusted-p-value (p-FDR) = 0.038) and cortical grey matter (p-FDR = 0.015). Brain perfusion did not differ between patients and healthy participants. However, delayed patient caudate nucleus perfusion was associated with better executive function (p-FDR = 0.008). Delayed perfusion in the cortical grey matter and hippocampus were associated with a reduced risk of daytime sleepiness (hazard ratio (HR) = 0.07, p = 0.037 and HR = 0.06, p = 0.034). Decreased putamen oxygen levels were associated with a reduced risk of poor cognitive outcome (HR = 0.22, p = 0.019). Meanwhile, lower thalamic oxygen levels were associated with a higher risk of cognitive fatigue (HR = 6.29, p = 0.017).

INTERPRETATION

Our findings of lower regional brain blood oxygen levels suggest increased cerebral metabolism in PCS, which potentially holds a compensatory function. These hemodynamic changes were related to symptom severity, possibly representing metabolic adaptations.

Exposure to multiple ambient air pollutants changes white matter microstructure during early adolescence with sex-specific differences

BACKGROUND

Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex.

METHODS

We investigate sex-stratified effects of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at ages 9-10 years on longitudinal patterns of white matter microstructure over a 2-year period. Diffusion-weighted imaging was collected on 3T MRI scanners for 8182 participants (1-2 scans per subject; 45% with two scans) from the Adolescent Brain Cognitive Development (ABCD) Study®. Restriction spectrum imaging was performed to quantify intracellular isotropic (RNI) and directional (RND) diffusion. Ensemble-based air pollution concentrations were assigned to each child's primary residential address. Multi-pollutant, sex-stratified linear mixed-effect models assessed associations between pollutants and RNI/RND with age over time, adjusting for sociodemographic factors.

RESULTS

Here we show higher PM2.5 exposure is associated with higher RND at age 9 in both sexes, with no significant effects of PM2.5 on RNI/RND change over time. Higher NO2 exposure is associated with higher RNI at age 9 in both sexes, as well as attenuating RNI over time in females. Higher O3 exposure is associated with differences in RND and RNI at age 9, as well as changes in RND and RNI over time in both sexes.

CONCLUSIONS

Criteria air pollutants influence patterns of white matter maturation between 9-13 years old, with some sex-specific differences in the magnitude and anatomical locations of affected tracts. This occurs at concentrations that are below current U.S. standards, suggesting exposure to low-level pollution during adolescence may have long-term consequences.

Characterizing white matter connectome abnormalities in patients with temporal lobe epilepsy using threshold-free network-based statistics

INTRODUCTION

Emerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study. Furthermore, we assessed whether aberrant white matter connections are differentially related to cognitive impairment and a history of focal-to-bilateral tonic-clonic (FBTC) seizures.

METHODS

Multi-shell connectome MRI data were preprocessed using the DESIGNER guidelines. The IIT Destrieux gray matter atlas was used to derive the 162 × 162 structural connectivity matrices (SCMs) using MRTrix3. ComBat data harmonization was applied to harmonize the SCMs from pre- and post-scanner upgrade acquisitions. Threshold-free network-based statistics were used for statistical analysis of the harmonized SCMs. Cognitive impairment status and FBTC seizure status were then correlated with these findings.

RESULTS

We employed connectome measurements from 142 subjects, including 92 patients with TLE (36 males, mean age = 40.1 ± 11.7 years) and 50 HCs (25 males, mean age = 32.6 ± 10.2 years). Our analysis revealed overall significant decreases in cross-sectional area (CSA) of the white matter tract in TLE group compared to controls, indicating decreased white matter tract integrity and connectivity abnormalities in addition to apparent differences in graph theoretic measures of connectivity and network-based statistics. Focal and generalized cognitive impaired TLE patients showcased higher trend-level abnormalities in the white matter connectome via decreased CSA than those with no cognitive impairment. Patients with a positive FBTC seizure history also showed trend-level findings of association via decreased CSA.

CONCLUSIONS

Widespread global aberrant white matter connectome changes were observed in TLE patients and characterized by seizure history and cognitive impairment, laying a foundation for future studies to expand on and validate the novel biomarkers and further elucidate TLE's impact on brain plasticity.

Psilocybin desynchronizes the human brain

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

Value of fractional-order calculus (FROC) model diffusion-weighted imaging combined with simultaneous multi-slice (SMS) acceleration technology for evaluating benign and malignant breast lesions

BACKGROUND

This study explores the diagnostic value of combining fractional-order calculus (FROC) diffusion-weighted model with simultaneous multi-slice (SMS) acceleration technology in distinguishing benign and malignant breast lesions.

METHODS

178 lesions (73 benign, 105 malignant) underwent magnetic resonance imaging with diffusion-weighted imaging using multiple b-values (14 b-values, highest 3000 s/mm2). Independent samples t-test or Mann-Whitney U test compared image quality scores, FROC model parameters (D,, ), and ADC values between two groups. Multivariate logistic regression analysis identified independent variables and constructed nomograms. Model discrimination ability was assessed with receiver operating characteristic (ROC) curve and calibration chart. Spearman correlation analysis and Bland-Altman plot evaluated parameter correlation and consistency.

RESULTS

Malignant lesions exhibited lower D, and ADC values than benign lesions (P < 0.05), with higher values (P < 0.05). In SSEPI-DWI and SMS-SSEPI-DWI sequences, the AUC and diagnostic accuracy of D value are maximal, with D value demonstrating the highest diagnostic sensitivity, while value exhibits the highest specificity. The D and combined model had the highest AUC and accuracy. D and ADC values showed high correlation between sequences, and moderate. Bland-Altman plot demonstrated unbiased parameter values.

CONCLUSION

SMS-SSEPI-DWI FROC model provides good image quality and lesion characteristic values within an acceptable time. It shows consistent diagnostic performance compared to SSEPI-DWI, particularly in D and values, and significantly reduces scanning time.

Structural and functional features characterizing the brains of individuals with higher controllability of motor imagery

Motor imagery is a higher-order cognitive brain function that mentally simulates movements without performing the actual physical one. Although motor imagery has attracted the interest of many researchers, and mental practice utilizing motor imagery has been widely used in sports training and post-stroke rehabilitation, neural bases that determine individual differences in motor imagery ability are not well understood. In this study, using controllability of motor imagery (CMI) test that can objectively evaluate individual ability to manipulate one's imaginary postures, we examined structural and functional features characterizing the brains of individuals with higher controllability of motor imagery, by analyzing T1-weighted structural MRI data obtained from 89 participants and functional MRI data obtained from 28 of 89 participants. The higher CMI test scorers had larger volume in the bilateral superior frontoparietal white matter regions. The CMI test activated the bilateral dorsal premotor cortex (PMD) and superior parietal lobule (SPL); specifically, the left PMD and/or the right SPL enhanced functional coupling with the visual body, somatosensory, and motor/kinesthetic areas in the higher scorers. Hence, controllability of motor imagery is higher for those who well-develop superior frontoparietal network, and for those whose this network accesses these sensory areas to predict the expected multisensory experiences during motor imagery. This study elucidated for the first time the structural and functional features characterizing the brains of individuals with higher controllability of motor imagery, and advanced understanding of individual differences in motor imagery ability.

Neural Correlates of Metacognition Impairment in Opioid Addiction

BACKGROUND

Individuals with substance use disorder show impaired self-awareness of ongoing behavior. This deficit suggests problems with metacognition, which has been operationalized in the cognitive neuroscience literature as the ability to monitor and evaluate the success of one's own cognition and behavior. However, the neural mechanisms of metacognition have not been characterized in a population with drug addiction.

METHODS

Community samples of participants with opioid use disorder (OUD) (n = 27) and healthy control participants (n = 29) performed a previously validated functional magnetic resonance imaging metacognition task (perceptual decision-making task along with confidence ratings of performance). Measures of recent drug use and addiction severity were also acquired.

RESULTS

Individuals with OUD had lower metacognitive sensitivity (i.e., disconnection between task performance and task-related confidence) than control individuals. Trial-by-trial analyses showed that this overall group difference was driven by (suboptimally) low confidence in participants with OUD during correct trials. In functional magnetic resonance imaging analyses, the task engaged an expected network of brain regions (e.g., rostrolateral prefrontal cortex and dorsal anterior cingulate/supplementary motor area, both previously linked to metacognition); group differences emerged in a large ventral anterior cluster that included the medial and lateral orbitofrontal cortex and striatum (higher activation in OUD). Trial-by-trial functional magnetic resonance imaging analyses showed group differences in rostrolateral prefrontal cortex activation, which further correlated with metacognitive behavior across all participants. Exploratory analyses suggested that the behavioral and neural group differences were exacerbated by recent illicit opioid use and unexplained by general cognition.

CONCLUSIONS

With confirmation and extension of these findings, metacognition and its associated neural circuits could become new, promising therapeutic targets in addiction.

Phenomena of hypo- and hyperconnectivity in basal ganglia-thalamo-cortical circuits linked to major depression: a 7T fMRI study

Major depressive disorder (MDD) typically manifests itself in depressed affect, anhedonia, low energy, and additional symptoms. Despite its high global prevalence, its pathophysiology still gives rise to questions. Current research places alterations in functional connectivity among MDD's most promising biomarkers. However, given the heterogeneity of previous findings, the use of higher-resolution imaging techniques, like ultra-high field (UHF) fMRI (≥7 Tesla, 7T), may offer greater specificity in delineating fundamental impairments. In this study, 7T UHF fMRI scans were conducted on 31 MDD patients and 27 age-gender matched healthy controls to exploratorily contrast cerebral resting-state functional connectivity patterns between both groups. The CONN toolbox was used to generate functional network connectivity (FNC) analysis based on the region of interest (ROI)-to-ROI correlations in order to enable the identification of clusters of significantly different connections. Correction for multiple comparisons was implemented at the cluster level using a false discovery rate (FDR). The analysis revealed three significant clusters differentiating MDD patients and healthy controls. In Clusters 1 and 2, MDD patients exhibited between-network hypoconnectivity in basal ganglia-cortical pathways as well as hyperconnectivity in thalamo-cortical pathways, including several individual ROI-to-ROI connections. In Cluster 3, they showed increased occipital interhemispheric within-network connectivity. These findings suggest that alterations in basal ganglia-thalamo-cortical circuits play a substantial role in the pathophysiology of MDD. Furthermore, they indicate potential MDD-related deficits relating to a combination of perception (vision, audition, and somatosensation) as well as more complex functions, especially social-emotional processing, modulation, and regulation. It is anticipated that these findings might further inform more accurate clinical procedures for addressing MDD.

A Novel Registration Framework for Aligning Longitudinal Infant Brain Tensor Images

Registering longitudinal infant brain images is challenging, as the infant brain undergoes rapid changes in size, shape and tissue contrast in the first months and years of life. Diffusion tensor images (DTI) have relatively consistent tissue properties over the course of infancy compared to commonly used T1 or T2- weighted images, presenting great potential for infant brain registration. Moreover, groupwise registration has been widely used in infant neuroimaging studies to reduce bias introduced by predefined atlases that may not be well representative of samples under study. To date, however, no methods have been developed for groupwise registration of tensor-based images. Here, we propose a novel registration approach to groupwise align longitudinal infant DTI images to a sample-specific common space. Longitudinal infant DTI images are first clustered into more homogenous subgroups based on image similarity using Louvain clustering. DTI scans are then aligned within each subgroup using standard tensor-based registration. The resulting images from all subgroups are then further aligned onto a sample-specific common space. Results show that our approach significantly improved registration accuracy both globally and locally compared to standard tensor-based registration and standard fractional anisotropy-based registration. Additionally, clustering based on image similarity yielded significantly higher registration accuracy compared to no clustering, but comparable registration accuracy compared to clustering based on chronological age. By registering images groupwise to reduce registration bias and capitalizing on the consistency of features in tensor maps across early infancy, our groupwise registration framework facilitates more accurate alignment of longitudinal infant brain images.

Spurious correlations in surface-based functional brain imaging

The study of functional MRI data is increasingly performed after mapping from volumetric voxels to surface vertices. Processing pipelines commonly used to achieve this mapping produce meshes with uneven vertex spacing, with closer neighbours in sulci compared to gyri. Consequently, correlations between the fMRI time series of neighbouring sulcal vertices are stronger than expected. However, the causes, extent, and impacts of this bias are not well understood or widely appreciated. We explain the origins of these biases, and using in-silico models of fMRI data, illustrate how they lead to spurious results. The bias leads to leakage of anatomical cortical folding information into fMRI time series. We show that many common analyses can be affected by this "gyral bias", including test-retest reliability, fingerprinting, functional parcellations, regional homogeneity, and brain-behaviour associations. Finally, we provide recommendations to avoid or remedy this spatial bias.

Trying Harder: How Cognitive Effort Sculpts Neural Representations during Working Memory

While the exertion of mental effort improves performance on cognitive tasks, the neural mechanisms by which motivational factors impact cognition remain unknown. Here, we used fMRI to test how changes in cognitive effort, induced by changes in task difficulty, impact neural representations of working memory (WM). Participants (both sexes) were precued whether WM difficulty would be hard or easy. We hypothesized that hard trials demanded more effort as a later decision required finer mnemonic precision. Behaviorally, pupil size was larger and response times were slower on hard compared with easy trials suggesting our manipulation of effort succeeded. Neurally, we observed robust persistent activity during delay periods in the prefrontal cortex (PFC), especially during hard trials. Yet, details of the memoranda could not be decoded from patterns in prefrontal activity. In the patterns of activity in the visual cortex, however, we found strong decoding of memorized targets, where accuracy was higher on hard trials. To potentially link these across-region effects, we hypothesized that effort, carried by persistent activity in the PFC, impacts the quality of WM representations encoded in the visual cortex. Indeed, we found that the amplitude of delay period activity in the frontal cortex predicted decoded accuracy in the visual cortex on a trial-wise basis. These results indicate that effort-related feedback signals sculpt population activity in the visual cortex, improving mnemonic fidelity.

Childhood obesity's effect on cognition and brain connectivity worsens with low family income

Childhood obesity and its adverse health consequences have risen worldwide, with low socioeconomic status increasing the risk in high-income countries like the United States. Understanding the interplay between childhood obesity, cognition, socioeconomic factors, and the brain is crucial for prevention and treatment. Using data from the Adolescent Brain Cognitive Development (ABCD) study, we investigated how body mass index (BMI) relates to brain structural and functional connectivity metrics. Children with obesity or who are overweight (n = 2,356) were more likely to live in poverty and exhibited lower cognitive performance compared with children with a healthy weight (n = 4,754). Higher BMI was associated with multiple brain measures that were strongest for lower longitudinal diffusivity in corpus callosum; increased activity in cerebellum, insula, and somatomotor cortex; and decreased functional connectivity in multimodal brain areas, with effects more pronounced among children from low-income families. Notably, nearly 80% of the association of low income and 70% of the association of impaired cognition on BMI were mediated by higher brain activity in somatomotor areas. Increased resting activity in somatomotor areas and decreased structural and functional connectivity likely contribute to the higher risk of being overweight or having obesity among children from low-income families. Supporting low-income families and implementing educational interventions to improve cognition may promote healthy brain function and reduce the risk of obesity.

Prenatal and childhood air pollution exposure, cellular immune biomarkers, and brain connectivity in early adolescents

Introduction

Ambient air pollution is a neurotoxicant with hypothesized immune-related mechanisms. Adolescent brain structural and functional connectivity may be especially vulnerable to ambient pollution due to the refinement of large-scale brain networks during this period, which vary by sex and have important implications for cognitive, behavioral, and emotional functioning. In the current study we explored associations between air pollutants, immune markers, and structural and functional connectivity in early adolescence by leveraging cross-sectional sex-stratified data from the Adolescent Brain Cognitive Development℠ Study®.

Methods

Pollutant concentrations of fine particulate matter, nitrogen dioxide, and ozone were assigned to each child's primary residential address during the prenatal period and childhood (9-10 years-old) using an ensemble-based modeling approach. Data collected at 11-13 years-old included resting-state functional connectivity of the default mode, frontoparietal, and salience networks and limbic regions of interest, intracellular directional and isotropic diffusion of available white matter tracts, and markers of cellular immune activation. Using partial least squares correlation, a multivariate data-driven method that identifies important variables within latent dimensions, we investigated associations between 1) pollutants and structural and functional connectivity, 2) pollutants and immune markers, and 3) immune markers and structural and functional connectivity, in each sex separately.

Results

Air pollution exposure was related to white matter intracellular directional and isotropic diffusion at ages 11-13 years, but the direction of associations varied by sex. There were no associations between pollutants and resting-state functional connectivity at ages 11-13 years. Childhood exposure to nitrogen dioxide was negatively correlated with white blood cell count in males. Immune biomarkers were positively correlated with white matter intracellular directional diffusion in females and both white matter intracellular directional and isotropic diffusion in males. Lastly, there was a reliable negative correlation between lymphocyte-to-monocyte ratio and default mode network resting-state functional connectivity in females, as well as a compromised immune marker profile associated with lower resting-state functional connectivity between the salience network and the left hippocampus in males. In post-hoc exploratory analyses, we found that the PLSC-identified white matter tracts and resting-state networks related to processing speed and cognitive control performance from the NIH Toolbox.

Conclusions

We identified novel links between childhood nitrogen dioxide and cellular immune activation in males, and brain network connectivity and immune markers in both sexes. Future research should explore the potentially mediating role of immune activity in how pollutants affect neurological outcomes as well as the potential consequences of immune-related patterns of brain connectivity in service of improved brain health for all.

Selective activations and functional connectivities to the sight of faces, scenes, body parts and tools in visual and non-visual cortical regions leading to the human hippocampus

Connectivity maps are now available for the 360 cortical regions in the Human Connectome Project Multimodal Parcellation atlas. Here we add function to these maps by measuring selective fMRI activations and functional connectivity increases to stationary visual stimuli of faces, scenes, body parts and tools from 956 HCP participants. Faces activate regions in the ventrolateral visual cortical stream (FFC), in the superior temporal sulcus (STS) visual stream for face and head motion; and inferior parietal visual (PGi) and somatosensory (PF) regions. Scenes activate ventromedial visual stream VMV and PHA regions in the parahippocampal scene area; medial (7m) and lateral parietal (PGp) regions; and the reward-related medial orbitofrontal cortex. Body parts activate the inferior temporal cortex object regions (TE1p, TE2p); but also visual motion regions (MT, MST, FST); and the inferior parietal visual (PGi, PGs) and somatosensory (PF) regions; and the unpleasant-related lateral orbitofrontal cortex. Tools activate an intermediate ventral stream area (VMV3, VVC, PHA3); visual motion regions (FST); somatosensory (1, 2); and auditory (A4, A5) cortical regions. The findings add function to cortical connectivity maps; and show how stationary visual stimuli activate other cortical regions related to their associations, including visual motion, somatosensory, auditory, semantic, and orbitofrontal cortex value-related, regions.

Adolescent substance use initiation and long-term neurobiological outcomes: insights, challenges and opportunities

The increased frequency of risk taking behavior combined with marked neuromaturation has positioned adolescence as a focal point of research into the neural causes and consequences of substance use. However, little work has provided a summary of the links between adolescent initiated substance use and longer-term brain outcomes. Here we review studies exploring the long-term effects of adolescent-initiated substance use with structural and microstructural neuroimaging. A quarter of all studies reviewed conducted repeated neuroimaging assessments. Long-term alcohol use, as well as tobacco use were consistently associated with smaller frontal cortices and altered white matter microstructure. This association was mostly observed in the ACC, insula and subcortical regions in alcohol users, and for the OFC in tobacco users. Long-term cannabis use was mostly related to altered frontal cortices and hippocampal volumes. Interestingly, cannabis users scanned more years after use initiation tended to show smaller measures of these regions, whereas those with fewer years since initiation showed larger measures. Long-term stimulant use tended to show a similar trend as cannabis in terms of years since initiation in measures of the putamen, insula and frontal cortex. Long-term opioid use was mostly associated with smaller subcortical and insular volumes. Of note, null findings were reported in all substance use categories, most often in cannabis use studies. In the context of the large variety in study designs, substance use assessment, methods, and sample characteristics, we provide recommendations on how to interpret these findings, and considerations for future studies.

Immersive scene representation in human visual cortex with ultra-wide-angle neuroimaging

While human vision spans 220°, traditional functional MRI setups display images only up to central 10-15°. Thus, it remains unknown how the brain represents a scene perceived across the full visual field. Here, we introduce a method for ultra-wide angle display and probe signatures of immersive scene representation. An unobstructed view of 175° is achieved by bouncing the projected image off angled-mirrors onto a custom-built curved screen. To avoid perceptual distortion, scenes are created with wide field-of-view from custom virtual environments. We find that immersive scene representation drives medial cortex with far-peripheral preferences, but shows minimal modulation in classic scene regions. Further, scene and face-selective regions maintain their content preferences even with extreme far-periphery stimulation, highlighting that not all far-peripheral information is automatically integrated into scene regions computations. This work provides clarifying evidence on content vs. peripheral preferences in scene representation and opens new avenues to research immersive vision.

Dynamic off-resonance correction improves functional image analysis in fMRI of awake behaving non-human primates

Introduction

Use of functional MRI in awake non-human primate (NHPs) has recently increased. Scanning animals while awake makes data collection possible in the absence of anesthetic modulation and with an extended range of possible experimental designs. Robust awake NHP imaging however is challenging due to the strong artifacts caused by time-varying off-resonance changes introduced by the animal's body motion. In this study, we sought to thoroughly investigate the effect of a newly proposed dynamic off-resonance correction method on brain activation estimates using extended awake NHP data.

Methods

We correct for dynamic B0 changes in reconstruction of highly accelerated simultaneous multi-slice EPI acquisitions by estimating and correcting for dynamic field perturbations. Functional MRI data were collected in four male rhesus monkeys performing a decision-making task in the scanner, and analyses of improvements in sensitivity and reliability were performed compared to conventional image reconstruction.

Results

Applying the correction resulted in reduced bias and improved temporal stability in the reconstructed time-series data. We found increased sensitivity to functional activation at the individual and group levels, as well as improved reliability of statistical parameter estimates.

Conclusions

Our results show significant improvements in image fidelity using our proposed correction strategy, as well as greatly enhanced and more reliable activation estimates in GLM analyses.

The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in psychiatry

An important aim in psychiatry is the establishment of valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset, which we hope will accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.

The relevance of Spearman's g for epilepsy

Whilst the concept of a general mental factor known as 'g' has been of longstanding interest, for unknown reasons, it has never been interrogated in epilepsy despite the 100+ year empirical history of the neuropsychology of epilepsy. This investigation seeks to identify g within a comprehensive neuropsychological data set and compare participants with temporal lobe epilepsy to controls, characterize the discriminatory power of g compared with domain-specific cognitive metrics, explore the association of g with clinical epilepsy and sociodemographic variables and identify the structural and network properties associated with g in epilepsy. Participants included 110 temporal lobe epilepsy patients and 79 healthy controls between the ages of 19 and 60. Participants underwent neuropsychological assessment, clinical interview and structural and functional imaging. Cognitive data were subjected to factor analysis to identify g and compare the group of patients with control participants. The relative power of g compared with domain-specific tests was interrogated, clinical and sociodemographic variables were examined for their relationship with g, and structural and functional images were assessed using traditional regional volumetrics, cortical surface features and network analytics. Findings indicate (i) significantly (P < 0.005) lower g in patients compared with controls; (ii) g is at least as powerful as individual cognitive domain-specific metrics and other analytic approaches to discriminating patients from control participants; (iii) lower g was associated with earlier age of onset and medication use, greater number of antiseizure medications and longer epilepsy duration (Ps < 0.04); and lower parental and personal education and greater neighbourhood deprivation (Ps < 0.012); and (iv) amongst patients, lower g was linked to decreased total intracranial volume (P = 0.019), age and intracranial volume adjusted total tissue volume (P = 0.019) and age and intracranial volume adjusted total corpus callosum volume (P = 0.012)-particularly posterior, mid-posterior and anterior (Ps < 0.022) regions. Cortical vertex analyses showed lower g to be associated specifically with decreased gyrification in bilateral medial orbitofrontal regions. Network analysis of resting-state data with focus on the participation coefficient showed g to be associated with the superior parietal network. Spearman's g is reduced in patients, has considerable discriminatory power compared with domain-specific metrics and is linked to a multiplex of factors related to brain (size, connectivity and frontoparietal networks), environment (familial and personal education and neighbourhood disadvantage) and disease (epilepsy onset, treatment and duration). Greater attention to contemporary models of human cognition is warranted in order to advance the neuropsychology of epilepsy.

Individual Brain Charting dataset extension, third release for movie watching and retinotopy data

The Individual Brain Charting (IBC) is a multi-task functional Magnetic Resonance Imaging dataset acquired at high spatial-resolution and dedicated to the cognitive mapping of the human brain. It consists in the deep phenotyping of twelve individuals, covering a broad range of psychological domains suitable for functional-atlasing applications. Here, we present the inclusion of task data from both naturalistic stimuli and trial-based designs, to uncover structures of brain activation. We rely on the Fast Shared Response Model (FastSRM) to provide a data-driven solution for modelling naturalistic stimuli, typically containing many features. We show that data from left-out runs can be reconstructed using FastSRM, enabling the extraction of networks from the visual, auditory and language systems. We also present the topographic organization of the visual system through retinotopy. In total, six new tasks were added to IBC, wherein four trial-based retinotopic tasks contributed with a mapping of the visual field to the cortex. IBC is open access: source plus derivatives imaging data and meta-data are available in public repositories.

Simultaneous cortical, subcortical, and brainstem mapping of sensory activation

Nonpainful tactile sensory stimuli are processed in the cortex, subcortex, and brainstem. Recent functional magnetic resonance imaging studies have highlighted the value of whole-brain, systems-level investigation for examining sensory processing. However, whole-brain functional magnetic resonance imaging studies are uncommon, in part due to challenges with signal to noise when studying the brainstem. Furthermore, differentiation of small sensory brainstem structures such as the cuneate and gracile nuclei necessitates high-resolution imaging. To address this gap in systems-level sensory investigation, we employed a whole-brain, multi-echo functional magnetic resonance imaging acquisition at 3T with multi-echo independent component analysis denoising and brainstem-specific modeling to enable detection of activation across the entire sensory system. In healthy participants, we examined patterns of activity in response to nonpainful brushing of the right hand, left hand, and right foot (n = 10 per location), and found the expected lateralization, with distinct cortical and subcortical responses for upper and lower limb stimulation. At the brainstem level, we differentiated the adjacent cuneate and gracile nuclei, corresponding to hand and foot stimulation respectively. Our findings demonstrate that simultaneous cortical, subcortical, and brainstem mapping at 3T could be a key tool to understand the sensory system in both healthy individuals and clinical cohorts with sensory deficits.

Abnormal intrinsic brain functional network dynamics in first-episode drug-naïve adolescent major depressive disorder

BACKGROUND

Alterations in brain functional connectivity (FC) have been frequently reported in adolescent major depressive disorder (MDD). However, there are few studies of dynamic FC analysis, which can provide information about fluctuations in neural activity related to cognition and behavior. The goal of the present study was therefore to investigate the dynamic aspects of FC in adolescent MDD patients.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from 94 adolescents with MDD and 78 healthy controls. Independent component analysis, a sliding-window approach, and graph-theory methods were used to investigate the potential differences in dynamic FC properties between the adolescent MDD patients and controls.

RESULTS

Three main FC states were identified, State 1 which was predominant, and State 2 and State 3 which occurred less frequently. Adolescent MDD patients spent significantly more time in the weakly-connected and relatively highly-modularized State 1, spent significantly less time in the strongly-connected and low-modularized State 2, and had significantly higher variability of both global and local efficiency, compared to the controls. Classification of patients with adolescent MDD was most readily performed based on State 1 which exhibited disrupted intra- and inter-network FC involving multiple functional networks.

CONCLUSIONS

Our study suggests local segregation and global integration impairments and segregation-integration imbalance of functional networks in adolescent MDD patients from the perspectives of dynamic FC. These findings may provide new insights into the neurobiology of adolescent MDD.

Retinotopic cortical mapping in objective functional monitoring of macular therapy

BACKGROUND/AIMS

To determine the suitability of functional MRI (fMRI) as an objective measure of macular function following therapeutic intervention; conventional psychophysical measures rely heavily on patient compliance.

METHODS

Twenty patients with neovascular age-related macular degeneration (nAMD) were studied with high-resolution fMRI, visual acuity, reading accuracy and speed, contrast sensitivity (CS) and microperimetry (MP) before and after 3 monthly intravitreal injections of ranibizumab. Population-receptive field retinotopic maps calculated from fMRI data were compared with psychophysical measures and optical coherence tomography.

RESULTS

Best-corrected visual acuity (BCVA) responders (≥5 letters) showed an increase of 29.5% in activated brain area, while non-responders showed a decrease of 0.8%. Radial histograms over eccentricity allowed quantification of the absolute number of significant voxels and thus differences before and after treatment. Responders showed increases in foveal (α<0.5°) activation, while non-responders did not. Absence of intraretinal fluid and preservation of outer retinal layers was associated with higher numbers of active V1 voxels and better BCVA. Higher voxel numbers were associated with improved reading performance and, less marked, with BCVA, CS and MP.

CONCLUSION

The data show that retinotopic mapping using fMRI can successfully be applied objectively to evaluate the therapeutic response in nAMD patients treated with anti-vascular endothelial growth factor therapy. This demonstrates the ability of retinotopic mapping to provide an objective assessment of functional recovery at a cortical level; the technique can therefore be applied, in other degenerative macular diseases, to the assessment of potential therapeutic interventions such as gene therapy or cell replacement therapy.

A tale of two n-backs: Diverging associations of dorsolateral prefrontal cortex activation with n-back task performance

Background

In studying the neural correlates of working memory (WM) ability via functional magnetic resonance imaging (fMRI) in health and disease, it is relatively uncommon for investigators to report associations between brain activation and measures of task performance. Additionally, how the choice of WM task impacts observed activation-performance relationships is poorly understood. We sought to illustrate the impact of WM task on brain-behavior correlations using two large, publicly available datasets.

Methods

We conducted between-participants analyses of task-based fMRI data from two publicly available datasets: the Human Connectome Project (HCP; n = 866) and the Queensland Twin Imaging (QTIM) Study (n = 459). Participants performed two distinct variations of the n-back WM task with different stimuli, timings, and response paradigms. Associations between brain activation ([2-back - 0-back] contrast) and task performance (2-back % correct) were investigated separately in each dataset, as well as across datasets, within the dorsolateral prefrontal cortex (dlPFC), medial prefrontal cortex, and whole cortex.

Results

Global patterns of activation to task were similar in both datasets. However, opposite associations between activation and task performance were observed in bilateral pre-supplementary motor area and left middle frontal gyrus. Within the dlPFC, HCP participants exhibited a significantly greater activation-performance relationship in bilateral middle frontal gyrus relative to QTIM Study participants.

Conclusions

The observation of diverging activation-performance relationships between two large datasets performing variations of the n-back task serves as a critical reminder for investigators to exercise caution when selecting WM tasks and interpreting neural activation in response to a WM task.

Uncovering Hemispheric Asymmetry and Directed Oscillatory Brain-Heart Interplay in Anxiety Processing: An fMRI Study

Brain-heart interactions (BHI) are critical for generating and processing emotions, including anxiety. Understanding specific neural correlates would be instrumental for greater comprehension and potential therapeutic interventions of anxiety disorders. While prior work has implicated the pontine structure as a central processor in cardiac regulation in anxiety, the distributed nature of anxiety processing across the cortex remains elusive. To address this, we performed a whole-brain-heart analysis using the full frequency directed transfer function to study resting-state spectral differences in BHI between high and low anxiety groups undergoing fMRI scans. Our findings revealed a hemispheric asymmetry in low-frequency interplay (0.05 Hz - 0.15 Hz) characterized by ascending BHI to the left insula and descending BHI from the right insula. Furthermore, we provide evidence supporting the "pacemaker hypothesis", highlighting the pons' function in regulating cardiac activity. Higher frequency interplay (0.2 Hz - 0.4Hz) demonstrate a preference for ascending interactions, particularly towards ventral prefrontal cortical activity in high anxiety groups, suggesting the heart's role in triggering a cognitive response to regulate anxiety. These findings highlight the impact of anxiety on BHI, contributing to a better understanding of its effect on the resting-state fMRI signal, with further implications for potential therapeutic interventions in treating anxiety disorders.

Sparse Blind Spherical Deconvolution of diffusion weighted MRI

Diffusion-weighted magnetic resonance imaging provides invaluable insights into in-vivo neurological pathways. However, accurate and robust characterization of white matter fibers microstructure remains challenging. Widely used spherical deconvolution algorithms retrieve the fiber Orientation Distribution Function (ODF) by using an estimation of a response function, i.e., the signal arising from individual fascicles within a voxel. In this paper, an algorithm of blind spherical deconvolution is proposed, which only assumes the axial symmetry of the response function instead of its exact knowledge. This algorithm provides a method for estimating the peaks of the ODF in a voxel without any explicit response function, as well as a method for estimating signals associated with the peaks of the ODF, regardless of how those peaks were obtained. The two stages of the algorithm are tested on Monte Carlo simulations, as well as compared to state-of-the-art methods on real in-vivo data for the orientation retrieval task. Although the proposed algorithm was shown to attain lower angular errors than the state-of-the-art constrained spherical deconvolution algorithm on synthetic data, it was outperformed by state-of-the-art spherical deconvolution algorithms on in-vivo data. In conjunction with state-of-the art methods for axon bundles direction estimation, the proposed method showed its potential for the derivation of per-voxel per-direction metrics on synthetic as well as in-vivo data.

Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla

The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this paper, we investigate the use of a finely tuned version of 3D-SPARKLING. This is a non-Cartesian CS-based acquisition technique for high spatial resolution whole-brain fMRI. We compare it to state-of-the-art Cartesian 3D-EPI during both a retinotopic mapping paradigm and resting-state acquisitions at 1mm3 (isotropic spatial resolution). This study involves six healthy volunteers and both acquisition sequences were run on each individual in a randomly-balanced order across subjects. The performances of both acquisition techniques are compared to each other in regards to tSNR, sensitivity to the BOLD effect and spatial specificity. Our findings reveal that 3D-SPARKLING has a higher tSNR than 3D-EPI, an improved sensitivity to detect the BOLD contrast in the gray matter, and an improved spatial specificity. Compared to 3D-EPI, 3D-SPARKLING yields, on average, 7% more activated voxels in the gray matter relative to the total number of activated voxels.

Topological Embedding of Human Brain Networks with Applications to Dynamics of Temporal Lobe Epilepsy

We introduce a novel, data-driven topological data analysis (TDA) approach for embedding brain networks into a lower-dimensional space in quantifying the dynamics of temporal lobe epilepsy (TLE) obtained from resting-state functional magnetic resonance imaging (rs-fMRI). This embedding facilitates the orthogonal projection of 0D and 1D topological features, allowing for the visualization and modeling of the dynamics of functional human brain networks in a resting state. We then quantify the topological disparities between networks to determine the coordinates for embedding. This framework enables us to conduct a coherent statistical inference within the embedded space. Our results indicate that brain network topology in TLE patients exhibits increased rigidity in 0D topology but more rapid flections compared to that of normal controls in 1D topology.

Characterization of pulsations in the brain and cerebrospinal fluid using ultra-high field magnetic resonance imaging

The development of innovative non-invasive neuroimaging methods and biomarkers is critical for studying brain disease. Imaging of cerebrospinal fluid (CSF) pulsatility may inform the brain fluid dynamics involved in clearance of cerebral metabolic waste. In this work, we developed a methodology to characterize the frequency and spatial localization of whole brain CSF pulsations in humans. Using 7 Tesla (T) human magnetic resonance imaging (MRI) and ultrafast echo-planar imaging (EPI), in-vivo images were obtained to capture pulsations of the CSF signal. Physiological data were simultaneously collected and compared with the 7 T MR data. The primary components of signal pulsations were identified using spectral analysis, with the most evident frequency bands identified around 0.3, 1.2, and 2.4 Hz. These pulsations were mapped spatially and temporally onto the MR image domain and temporally onto the physiological measures of electrocardiogram and respiration. We identified peaks in CSF pulsations that were distinct from peaks in grey matter and white matter regions. This methodology may provide novel in vivo biomarkers of disrupted brain fluid dynamics.

Spatial attention alters visual cortical representation during target anticipation

Attention enables us to efficiently and flexibly interact with the environment by prioritizing some image features in preparation for responding to a stimulus. Using a concurrent psychophysics- fMRI experiment, we investigated how covert spatial attention affects responses in human visual cortex prior to target onset, and how it affects subsequent behavioral performance. Performance improved at cued locations and worsened at uncued locations, relative to distributed attention, demonstrating a selective tradeoff in processing. Pre-target BOLD responses in cortical visual field maps changed in two ways: First, there was a stimulus-independent baseline shift, positive in map locations near the cued location and negative elsewhere, paralleling the behavioral results. Second, population receptive field centers shifted toward the attended location. Both effects increased in higher visual areas. Together, the results show that spatial attention has large effects on visual cortex prior to target appearance, altering neural response properties throughout and across multiple visual field maps.

Associations of Brain Entropy Estimated by Resting State fMRI With Physiological Indices, Body Mass Index, and Cognition

BACKGROUND

In recent years, resting-state fMRI (rsfMRI)-based brain entropy (BEN) has gained increasing interest as a tool to characterize brain activity. While previous studies indicate that BEN is correlated with cognition, it remains unclear whether BEN is influenced by other factors that typically affect brain activity measured by fMRI.

PURPOSE

To investigate the relationship between BEN and physiological indices, including respiratory rate (RR), heart rate (HR), systolic blood pressure (s-BP), and body mass index (BMI), and to investigate whether and to what extent the relationship between BEN and cognition is influenced by physiological variables.

STUDY TYPE

Retrospective.

SUBJECTS

One thousand two hundred six healthy subjects (mean age: 28.83 ± 3.69 years; 550 male) with rsfMRI datasets selected from the Human Connectome Project (HCP).

FIELD STRENGTH/SEQUENCE

Multiband echo planar imaging (EPI) sequence at 3.0 Tesla.

ASSESSMENT

Neurocognitive, physical health (RR, HR, s-BP, BMI), and rsfMRI data were retrieved from the HCP datasets. Neurocognition was measured through the total cognition composite (TCC) score provided by HCP. BEN maps were calculated from rsfMRI data.

STATISTICAL TESTS

Multiple regression models, pheight-family wise error (FWE) < 0.05 and pcluster-FWE < 0.05 were considered statistically significant.

RESULTS

BEN was negatively associated with RR (T-thresholds ranging from 4.75 to 4.8; r-threshold = |0.15|) and positively associated with s-BP and BMI (T-thresholds ranging from 4.75 to 4.8; r-threshold = |0.15|) in areas overlapping with the default mode network. After controlling the physiological effects, BEN still showed regional associations with TCC, including negative associations (T-thresholds = 3.09; r-threshold = |0.1|) in the fronto-parietal cortex and positive associations (T-thresholds = 3.09; r-threshold = |0.1|) in the sensorimotor system (motor network and the limbic system).

DATA CONCLUSIONS

RR negatively affects rsfMRI-derived BEN, while s-BP and BMI positively affect BEN. The positive associations between BEN and cognition in the motor network and the limbic system might indicate a facilitation of information processing in the sensorimotor system.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Functional Localization of the Human Auditory and Visual Thalamus Using a Thalamic Localizer Functional Magnetic Resonance Imaging Task

Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due in part to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmark their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

Effects of Age on Cross-Cultural Differences in the Neural Correlates of Memory Retrieval

Culture can shape memory, but little research investigates age effects. The present study examines the neural correlates of memory retrieval for old, new, and similar lures in younger and older Americans and Taiwanese. Results show that age and culture impact discrimination of old from new items. Taiwanese performed worse than Americans, with age effects more pronounced for Taiwanese. Americans activated the hippocampus for new more than old items, but pattern of activity for the conditions did not differ for Taiwanese, nor did it interact with age. The engagement of left inferior frontal gyrus (LIFG) differed across cultures. Patterns of greater activity for old (for Americans) or new (for Taiwanese) items were eliminated with age, particularly for older Americans. The results are interpreted as reflecting cultural differences in orientation to novelty vs. familiarity for younger, but not older, adults, with the LIFG supporting interference resolution at retrieval. Support is not as strong for cultural differences in pattern separation processes. Although Americans had higher levels of memory discrimination than Taiwanese and engaged the LIFG for correct rejections more than false alarms, the patterns of behavior and neural activity did not interact with culture and age. Neither culture nor age impacted hippocampal activity, which is surprising given the region's role in pattern separation. The findings suggest ways in which cultural life experiences and concomitant information processing strategies can contribute to consistent effects of age across cultures or contribute to different trajectories with age in terms of memory.