Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

The developing hippocampus: Microstructural evolution through childhood and adolescence

The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.

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.

Whole brain multiparametric mapping in two minutes using a dual-flip-angle stack-of-stars blipped multi-gradient-echo acquisition

A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1- inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.

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.

Are older adults less generous? Age differences in emotion-related social decision making

In social interaction, age-related differences in emotional processing may lead to varied social decision making between young and older adults. However, previous studies of social decision making have paid less attention to the interactants' emotions, leaving age differences and underlying neural mechanisms unexplored. To address this gap, the present study combined functional and structural magnetic resonance imaging, employing a modified dictator game task with recipients displaying either neutral or sad facial expressions. Behavioral results indicated that although older adults' overall allocations did not differ significantly from those of young adults, older adults' allocations showing a decrease in emotion-related generosity compared to young adults. Using representational similarity analysis, we found that older adults showed reduced neural representations of recipients' emotions and gray matter volume in the right anterior cingulate gyrus (ACC), right insula, and left dorsomedial prefrontal cortex (DMPFC) compared to young adults. More importantly, mediation analyses indicated that age influenced allocations not only through serial mediation of neural representations of the right insula and left DMPFC, but also through serial mediation of the mean gray matter volume of the right ACC and left DMPFC. This study identifies the potential neural pathways through which age affects emotion-related social decision making, advancing our understanding of older adults' social interaction behavior that they may not be less generous unless confronted with individuals with specific emotions.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Association of polygenic scores for autism with volumetric MRI phenotypes in cerebellum and brainstem in adults

Previous research on autism spectrum disorders (ASD) have showed important volumetric alterations in the cerebellum and brainstem. Most of these studies are however limited to case-control studies with small clinical samples and including mainly children or adolescents. Herein, we aimed to explore the association between the cumulative genetic load (polygenic risk score, PRS) for ASD and volumetric alterations in the cerebellum and brainstem, as well as global brain tissue volumes of the brain among adults at the population level. We utilized the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and constructed the ASD PRS in an independent cohort, the UK Biobank. Regression analyses controlled for multiple comparisons with the false-discovery rate (FDR) at 5% were performed to investigate the association between ASD PRS and forty-four brain magnetic resonance imaging (MRI) phenotypes among ~ 31,000 participants. Primary analyses included sixteen MRI phenotypes: total volumes of the brain, cerebrospinal fluid (CSF), grey matter (GM), white matter (WM), GM of whole cerebellum, brainstem, and ten regions of the cerebellum (I_IV, V, VI, VIIb, VIIIa, VIIIb, IX, X, CrusI and CrusII). Secondary analyses included twenty-eight MRI phenotypes: the sub-regional volumes of cerebellum including the GM of the vermis and both left and right lobules of each cerebellar region. ASD PRS were significantly associated with the volumes of seven brain areas, whereby higher PRS were associated to reduced volumes of the whole brain, WM, brainstem, and cerebellar regions I-IV, IX, and X, and an increased volume of the CSF. Three sub-regional volumes including the left cerebellar lobule I-IV, cerebellar vermes VIIIb, and X were significantly and negatively associated with ASD PRS. The study highlights a substantial connection between susceptibility to ASD, its underlying genetic etiology, and neuroanatomical alterations of the adult brain.

Exploring white matter microstructural alterations in mild cognitive impairment: a multimodal diffusion MRI investigation utilizing diffusion kurtosis and free-water imaging

Background

Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear.

Methods

This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI).

Results

Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment.

Conclusion

In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline.

Effects of Aging, Fitness, and Cerebrovascular Status on White Matter Microstructural Health

White matter (WM) microstructural health declines with increasing age, with evidence suggesting that improved cardiorespiratory fitness (CRF) may mitigate this decline. Specifically, higher fit older adults tend to show preserved WM microstructural integrity compared to their lower fit counterparts. However, the extent to which fitness and aging independently impact WM integrity across the adult lifespan is still an open question, as is the extent to which cerebrovascular health mediates these relationships. In a large sample (N = 125, aged 25-72), we assessed the impact of age and fitness on fractional anisotropy (FA, derived using diffusion weighted imaging, DWI) and probed the mediating role of cerebrovascular health (derived using diffuse optical tomography of the cerebral arterial pulse, pulse-DOT) in these relationships. After orthogonalizing age and fitness and computing a PCA on whole brain WM regions, we found several WM regions impacted by age that were independent from the regions impacted by fitness (hindbrain areas, including brainstem and cerebellar tracts), whereas other areas showed interactive effects of age and fitness (midline areas, including fornix and corpus callosum). Critically, cerebrovascular health mediated both relationships suggesting that vascular health plays a linking role between age, fitness, and brain health. Secondarily, we assessed potential sex differences in these relationships and found that, although females and males generally showed the same age-related FA declines, males exhibited somewhat steeper declines than females. Together, these results suggest that age and fitness impact specific WM regions and highlight the mediating role of cerebrovascular health in maintaining WM health across adulthood.

Semantic structures facilitate threat memory integration throughout the medial temporal lobe and medial prefrontal cortex

Emotional experiences can profoundly impact our conceptual model of the world, modifying how we represent and remember a host of information even indirectly associated with that experienced in the past. Yet, how a new emotional experience infiltrates and spreads across pre-existing semantic knowledge structures (e.g., categories) is unknown. We used a modified aversive sensory preconditioning paradigm in fMRI (n = 35) to investigate whether threat memories integrate with a pre-established category to alter the representation of the entire category. We observed selective but transient changes in the representation of conceptually related items in the amygdala, medial prefrontal cortex, and occipitotemporal cortex following threat conditioning to a simple cue (geometric shape) pre-associated with a different, but related, set of category exemplars. These representational changes persisted beyond 24 h in the hippocampus and perirhinal cortex. Reactivation of the semantic category during threat conditioning, combined with activation of the hippocampus or medial prefrontal cortex, was predictive of subsequent amygdala reactivity toward novel category members at test. This provides evidence for online integration of emotional experiences into semantic categories, which then promotes threat generalization. Behaviorally, threat conditioning by proxy selectively and retroactively enhanced recognition memory and increased the perceived typicality of the semantic category indirectly associated with threat. These findings detail a complex route through which new emotional learning generalizes by modifying semantic structures built up over time and stored in memory as conceptual knowledge.

Brain activations elicited during task-switching generalize beyond the task: A partial least squares correlation approach to combine fMRI signals and cognition

An underlying hypothesis for broad transfer from cognitive training is that the regional brain signals engaged during the training task are related to the transfer tasks. However, it is unclear whether the brain activations elicited from a specific cognitive task can generalize to performance of other tasks, esp. in normal aging where cognitive training holds much promise. In this large dual-site functional magnetic resonance imaging (fMRI) study, we aimed to characterize the neurobehavioral correlates of task-switching in normal aging and examine whether the task-switching-related fMRI-blood-oxygen-level-dependent (BOLD) signals, engaged during varieties of cognitive control, generalize to other tasks of executive control and general cognition. We therefore used a hybrid blocked and event-related fMRI task-switching paradigm to investigate brain regions associated with multiple types of cognitive control on 129 non-demented older adults (65-85 years). This large dataset provided a unique opportunity for a data-driven partial least squares-correlation approach to investigate the generalizability of multiple fMRI-BOLD signals associated with task-switching costs to other tasks of executive control, general cognition, and demographic characteristics. While some fMRI signals generalized beyond the scanned task, others did not. Results indicate right middle frontal brain activation as detrimental to task-switching performance, whereas inferior frontal and caudate activations were related to faster processing speed during the fMRI task-switching, but activations of these regions did not predict performance on other tasks of executive control or general cognition. However, BOLD signals from the right lateral occipital cortex engaged during the fMRI task positively predicted performance on a working memory updating task, and BOLD signals from the left post-central gyrus that were disengaged during the fMRI task were related to slower processing speed in the task as well as to lower general cognition. Together, these results suggest generalizability of these BOLD signals beyond the scanned task. The findings also provided evidence for the general slowing hypothesis of aging as most variance in the data were explained by low processing speed and global low BOLD signal in older age. As processing speed shared variance with task-switching and other executive control tasks, it might be a possible basis of generalizability between these tasks. Additional results support the dedifferentiation hypothesis of brain aging, as right middle frontal activations predicted poorer task-switching performance. Overall, we observed that the BOLD signals related to the fMRI task not only generalize to the performance of other executive control tasks, but unique brain predictors of out-of-scanner performance can be identified.

Neural networks associated with eye movements in congenital blindness

Recent studies have shown that during the typical resting-state, echo planar imaging (EPI) time series obtained from the eye orbit area correlate with brain regions associated with oculomotor control and lower-level visual cortex. Here, we asked whether congenitally blind (CB) shows similar patterns, suggesting a hard-wired constraint on connectivity. We find that orbital EPI signals in CB do correlate with activity in the motor cortex, but less so with activity in the visual cortex. However, the temporal patterns of this eye movement-related signal differed strongly between CB and sighted controls. Furthermore, in CB, a few participants showed uncoordinated orbital EPI signals between the two eyes, each correlated with activity in different brain networks. Our findings suggest a retained circuitry between motor cortex and eye movements in blind, but also a moderate reorganization due to the absence of visual input, and the inability of CB to control their eye movements or sense their positions.

Association of Metabolic Syndrome With Neuroimaging and Cognitive Outcomes in the UK Biobank

OBJECTIVE

Metabolic syndrome (MetS) has been linked to dementia. In this study, we examined the association of MetS with neuroimaging and cognition in dementia-free adults, offering insight into the impact of MetS on brain health prior to dementia onset.

RESEARCH DESIGN AND METHODS

We included 37,395 dementia-free adults from the UK Biobank database. MetS was defined as having at least three of the following components: larger waist circumference; elevated levels of triglycerides, blood pressure, HbA1c; or reduced HDL cholesterol levels. Multivariable-adjusted linear regression was used to assess associations of MetS with structural neuroimaging and cognitive domains.

RESULTS

MetS was associated with lower total brain (standardized β: -0.06; 95% CI -0.08, -0.04), gray matter (β: -0.10; 95% CI -0.12, -0.08) and hippocampal (for left side, β: -0.03, 95% CI -0.05, -0.01; for right side, β: -0.04, 95% CI -0.07, -0.02) volumes, and greater white matter hyperintensity (WMH) volume (β: 0.08; 95% CI 0.06, 0.11). Study participants with MetS performed poorer on cognitive tests of working memory (β: -0.10; 95% CI -0.13, -0.07), verbal declarative memory (β: -0.08; 95% CI -0.11, -0.05), processing speed (β: -0.06; 95% CI -0.09, -0.04), verbal and numerical reasoning (β: -0.07; 95% CI -0.09, -0.04), nonverbal reasoning (β: -0.03; 95% CI -0.05, -0.01), and on tests of executive function, where higher scores indicated poorer performance (β: 0.05; 95% CI 0.03, 0.08). More MetS components were also associated with less brain volume, greater WMH, and poorer cognition across all domains.

CONCLUSIONS

MetS was associated poorer brain health in dementia-free adults, characterized by less brain volume, greater vascular pathology, and poorer cognition. Further research is necessary to understand whether reversal or improvement of MetS can improve brain health.

Acute effects of high-intensity exercise on brain mechanical properties and cognitive function

Previous studies have shown that engagement in even a single session of exercise can improve cognitive performance in the short term. However, the underlying physiological mechanisms contributing to this effect are still being studied. Recently, with improvements to advanced quantitative neuroimaging techniques, brain tissue mechanical properties can be sensitively and noninvasively measured with magnetic resonance elastography (MRE) and regional brain mechanical properties have been shown to reflect individual cognitive performance. Here we assess brain mechanical properties before and immediately after engagement in a high-intensity interval training (HIIT) regimen, as well as one-hour post-exercise. We find that immediately after exercise, subjects in the HIIT group had an average global brain stiffness decrease of 4.2% (p < 0.001), and an average brain damping ratio increase of 3.1% (p = 0.002). In contrast, control participants who did not engage in exercise showed no significant change over time in either stiffness or damping ratio. Changes in brain mechanical properties with exercise appeared to be regionally dependent, with the hippocampus decreasing in stiffness by 10.4%. We also found that one-hour after exercise, brain mechanical properties returned to initial baseline values. The magnitude of changes to brain mechanical properties also correlated with improvements in reaction time on executive control tasks (Eriksen Flanker and Stroop) with exercise. Understanding the neural changes that arise in response to exercise may inform potential mechanisms behind improvements to cognitive performance with acute exercise.

DSC-PWI presurgical differentiation of grade 4 astrocytoma and glioblastoma in young adults: rCBV percentile analysis across enhancing and non-enhancing regions

PURPOSE

The presurgical discrimination of IDH-mutant astrocytoma grade 4 from IDH-wildtype glioblastoma is crucial for patient management, especially in younger adults, aiding in prognostic assessment, guiding molecular diagnostics and surgical planning, and identifying candidates for IDH-targeted trials. Despite its potential, the full capabilities of DSC-PWI remain underexplored. This research evaluates the differentiation ability of relative-cerebral-blood-volume (rCBV) percentile values for the enhancing and non-enhancing tumor regions compared to the more commonly used mean or maximum preselected rCBV values.

METHODS

This retrospective study, spanning 2016-2023, included patients under 55 years (age threshold based on World Health Organization recommendations) with grade 4 astrocytic tumors and known IDH status, who underwent presurgical MR with DSC-PWI. Enhancing and non-enhancing regions were 3D-segmented to calculate voxel-level rCBV, deriving mean, maximum, and percentile values. Statistical analyses were conducted using the Mann-Whitney U test and AUC-ROC.

RESULTS

The cohort consisted of 59 patients (mean age 46; 34 male): 11 astrocytoma-4 and 48 glioblastoma. While glioblastoma showed higher rCBV in enhancing regions, the differences were not significant. However, non-enhancing astrocytoma-4 regions displayed notably higher rCBV, particularly in lower percentiles. The 30th rCBV percentile for non-enhancing regions was 0.705 in astrocytoma-4, compared to 0.458 in glioblastoma (p = 0.001, AUC-ROC = 0.811), outperforming standard mean and maximum values.

CONCLUSION

Employing an automated percentile-based approach for rCBV selection enhances differentiation capabilities, with non-enhancing regions providing more insightful data. Elevated rCBV in lower percentiles of non-enhancing astrocytoma-4 is the most distinguishable characteristic and may indicate lowly vascularized infiltrated edema, contrasting with glioblastoma's pure edema.

A high-resolution 7 Tesla resting-state fMRI dataset optimized for studying the subcortex

To achieve a comprehensive understanding of spontaneous brain dynamics in humans, in vivo acquisition of intrinsic activity across both cortical and subcortical regions is necessary. Here we present advanced whole-brain, resting-state functional magnetic resonance imaging (rs-fMRI) data acquired at 7 Tesla with 1.5 mm isotropic voxel resolution. Functional images were obtained from 56 healthy adults (33 females, ages 19-39 years) in two runs of 15 min eyes-open wakeful rest. The high spatial resolution and short echo times of the multiband echo-planar imaging (EPI) protocol optimizes blood oxygen level-dependent (BOLD)-sensitivity for the subcortex while concurrent respiratory and cardiac measures enable retrospective correction of physiological noise, resulting in data that is highly suitable for researchers interested in subcortical BOLD signal. Functional timeseries were coregistered to high-resolution T1-weighted structural data (0.75 mm isotropic voxels) acquired during the same scanning session. To accommodate data reutilization, functional and structural images were formatted to the Brain Imaging Data Structure (BIDS) and preprocessed with fMRIPrep.

Limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is associated with abnormalities in white matter structural integrity and connectivity: An ex-vivo diffusion MRI and pathology investigation

Limbic predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is common in older adults and is associated with neurodegeneration, cognitive decline and dementia. In this MRI and pathology investigation we tested the hypothesis that LATE-NC is associated with abnormalities in white matter structural integrity and connectivity of a network of brain regions typically harboring TDP-43 inclusions in LATE, referred to here as the "LATE-NC network". Ex-vivo diffusion MRI and detailed neuropathological data were collected on 184 community-based older adults. Linear regression revealed an independent association of higher LATE-NC stage with lower diffusion anisotropy in a set of white matter connections forming a pattern of connectivity that is consistent with the stereotypical spread of this pathology in the brain. Graph theory analysis revealed an association of higher LATE-NC stage with weaker integration and segregation in the LATE-NC network. Abnormalities were significant in stage 3, suggesting that they are detectable in later stages of the disease. Finally, LATE-NC network abnormalities were associated with faster cognitive decline, specifically in episodic and semantic memory.

Semantic details in autobiographical memory narratives increase with age among younger adults

It is well documented that older adults, compared to younger adults, produce fewer episodic details and more semantic details when recalling autobiographical memories. However, group comparisons have provided limited insight into the trajectories of detail generation across the lifespan. Utilising an open source dataset [Clark, I. A., & Maguire, E. A. (2023). Release of cognitive and multimodal MRI data including real-world tasks and hippocampal subfield segmentations. Scientific Data, 10(1), 1-29. https://doi.org/10.1038/s41597-022-01899-x], we examined how episodic and semantic detail generation varied with age among 194 younger adults, ages 20-41. We tested whether age differences were mediated by hippocampal subfield volumes and MTL resting-state functional connectivity. Results indicated that semantic details increased with age, while episodic details remained stable. We observed age differences in hippocampal subfield volumes and MTL connectivity, but these measures did not mediate age effects on semantic detail. Based on these and prior findings [Matijevic, S., Andrews-Hanna, J. R., Wank, A. A., Ryan, L., & Grilli, M. D. (2022). Individual differences in the relationship between episodic detail generation and resting state functional connectivity vary with age. Neuropsychologia, 166, 108138. https://doi.org/10.1016/j.neuropsychologia.2021.108138], we suggest a model of diverging episodic and semantic detail generation trajectories across the adult lifespan.

Macroscale brain states support the control of semantic cognition

A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic tasks of varying difficulty - global association and feature matching judgments - which are contrasted with non-semantic tasks on the cortical surface and within a whole-brain state space. Demanding semantic association tasks elicit activation in anterior prefrontal and temporal regions, while challenging semantic feature matching and non-semantic tasks predominantly activate posterior regions. Task difficulty also modulates activation along different dimensions of functional organization, suggesting different mechanisms of cognitive control. More demanding semantic association judgments engage cognitive control and default mode networks together, while feature matching and non-semantic tasks are skewed towards cognitive control networks. These findings highlight the brain's dynamic ability to tailor its networks to support diverse neurocognitive states, enriching our understanding of controlled cognition.

Conscious but not thinking-Mind-blanks during visuomotor tracking: An fMRI study of endogenous attention lapses

Attention lapses (ALs) are complete lapses of responsiveness in which performance is briefly but completely disrupted and during which, as opposed to microsleeps, the eyes remain open. Although the phenomenon of ALs has been investigated by behavioural and physiological means, the underlying cause of an AL has largely remained elusive. This study aimed to investigate the underlying physiological substrates of behaviourally identified endogenous ALs during a continuous visuomotor task, primarily to answer the question: Were the ALs during this task due to extreme mind-wandering or mind-blanks? The data from two studies were combined, resulting in data from 40 healthy non-sleep-deprived subjects (20M/20F; mean age 27.1 years, 20-45). Only 17 of the 40 subjects were used in the analysis due to a need for a minimum of two ALs per subject. Subjects performed a random 2-D continuous visuomotor tracking task for 50 and 20 min in Studies 1 and 2, respectively. Tracking performance, eye-video, and functional magnetic resonance imaging (fMRI) were recorded simultaneously. A human expert visually inspected the tracking performance and eye-video recordings to identify and categorise lapses of responsiveness as microsleeps or ALs. Changes in neural activity during 85 ALs (17 subjects) relative to responsive tracking were estimated by whole-brain voxel-wise fMRI and by haemodynamic response (HR) analysis in regions of interest (ROIs) from seven key networks to reveal the neural signature of ALs. Changes in functional connectivity (FC) within and between the key ROIs were also estimated. Networks explored were the default mode network, dorsal attention network, frontoparietal network, sensorimotor network, salience network, visual network, and working memory network. Voxel-wise analysis revealed a significant increase in blood-oxygen-level-dependent activity in the overlapping dorsal anterior cingulate cortex and supplementary motor area region but no significant decreases in activity; the increased activity is considered to represent a recovery-of-responsiveness process following an AL. This increased activity was also seen in the HR of the corresponding ROI. Importantly, HR analysis revealed no trend of increased activity in the posterior cingulate of the default mode network, which has been repeatedly demonstrated to be a strong biomarker of mind-wandering. FC analysis showed decoupling of external attention, which supports the involuntary nature of ALs, in addition to the neural recovery processes. Other findings were a decrease in HR in the frontoparietal network before the onset of ALs, and a decrease in FC between default mode network and working memory network. These findings converge to our conclusion that the ALs observed during our task were involuntary mind-blanks. This is further supported behaviourally by the short duration of the ALs (mean 1.7 s), which is considered too brief to be instances of extreme mind-wandering. This is the first study to demonstrate that at least the majority of complete losses of responsiveness on a continuous visuomotor task are, if not due to microsleeps, due to involuntary mind-blanks.

Brain Network Interconnectivity Dynamics Explain Metacognitive Differences in Listening Behavior

Complex auditory scenes pose a challenge to attentive listening, rendering listeners slower and more uncertain in their perceptual decisions. How can we explain such behaviors from the dynamics of cortical networks that pertain to the control of listening behavior? We here follow up on the hypothesis that human adaptive perception in challenging listening situations is supported by modular reconfiguration of auditory-control networks in a sample of N = 40 participants (13 males) who underwent resting-state and task functional magnetic resonance imaging (fMRI). Individual titration of a spatial selective auditory attention task maintained an average accuracy of ∼70% but yielded considerable interindividual differences in listeners' response speed and reported confidence in their own perceptual decisions. Whole-brain network modularity increased from rest to task by reconfiguring auditory, cinguloopercular, and dorsal attention networks. Specifically, interconnectivity between the auditory network and cinguloopercular network decreased during the task relative to the resting state. Additionally, interconnectivity between the dorsal attention network and cinguloopercular network increased. These interconnectivity dynamics were predictive of individual differences in response confidence, the degree of which was more pronounced after incorrect judgments. Our findings uncover the behavioral relevance of functional cross talk between auditory and attentional-control networks during metacognitive assessment of one's own perception in challenging listening situations and suggest two functionally dissociable cortical networked systems that shape the considerable metacognitive differences between individuals in adaptive listening behavior.

Striatal Response to Reward Anticipation as a Biomarker for Schizophrenia and Negative Symptoms: Effects, Test-Retest Reliability, and Stability Across Sites

BACKGROUND

Ventral striatal hypoactivation during reward anticipation has consistently been observed in patients with schizophrenia. In addition, that hypoactivation has been shown to correlate negatively with negative symptoms, and in particular with apathy. However, little is known about the stability of these results over time and their reliability across different centers.

METHODS

In total, 67 patients with schizophrenia (15 females) and 55 healthy controls (13 females) were recruited in 2 centers in Switzerland and Germany. To assess the neural bases of reward anticipation, all participants performed a variant of the Monetary Incentive Delay task while undergoing event-related functional magnetic resonance imaging at baseline and after 3 months. Stability over time was measured using intra-class correlation (ICC(A,1)) and stability between centers was measured with mixed models.

RESULTS

Results showed the expected ventral striatal hypoactivation in patients compared to controls during reward anticipation. We showed that these results were stable across centers. The primary analysis did not reveal an effect of time. Test-retest reliability was moderate for controls, and poor for patients. We did not find an association between ventral striatal hypoactivation and negative symptoms in patients.

CONCLUSIONS

Our results align with the hypothesis that ventral striatal activation is related to modulation of motivational saliency during reward anticipation. They also confirm that patients with schizophrenia show impaired reward anticipation. However, the poor test-retest reliability and the absence of an association with symptoms suggests that further research is needed before ventral striatal activity can be used as a biomarker on the individual patient level.

Modeling short visual events through the BOLD moments video fMRI dataset and metadata

Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1000 short (3 s) naturalistic video clips of visual events across ten human subjects. We use the videos' extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.

Algorithm-Based Modular Psychotherapy Alleviates Brain Inflammation in Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is marked by prolonged and excessive worry, physical signs of anxiety, and associated neuroinflammation. Traditional treatments, like pharmacotherapy and cognitive-behavioral therapy (CBT), often leave residual symptoms and have high relapse rates. This study aimed to explore the efficacy of algorithm-based modular psychotherapy (MoBa), a combination of CBT and mindfulness meditation as validated by the research domain criteria (RDoC), in reducing anxiety and neuroinflammation in GAD. A longitudinal design was used, with 50 patients with GAD undergoing a 12-week MoBa treatment. The patients were investigated pre- and post-treatment using MRI to measure neuroinflammatory markers (DBSI-RF, diffusion-basis spectral imaging-based restricted fraction) in the hippocampus, amygdala, and neocortex. Clinical symptoms were assessed using the Hamilton Anxiety Rating Scale (HAM-A) and the Generalized Anxiety Disorder 7-item scale (GAD-7). Results indicated significant reductions in both anxiety symptoms and MRI RF values in the amygdala, suggesting decreased neuroinflammation. A reduction in anxiety was associated with the amelioration of neuroinflammation in the amygdala. These results suggest that MoBa is effective in alleviating both the psychological and neuroinflammatory aspects of GAD, offering a promising personalized treatment approach. Future research should focus on long-term effects and the mechanisms through which MoBa impacts neuroinflammation and anxiety.

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Drug treatments for pain often do not outperform placebo, and a better understanding of placebo mechanisms is needed to improve treatment development and clinical practice. In a large-scale fMRI study (N = 392) with pre-registered analyses, we tested whether placebo analgesic treatment modulates nociceptive processes, and whether its effects generalize from conditioned to unconditioned pain modalities. Placebo treatment caused robust analgesia in conditioned thermal pain that generalized to unconditioned mechanical pain. However, placebo did not decrease pain-related fMRI activity in brain measures linked to nociceptive pain, including the Neurologic Pain Signature (NPS) and spinothalamic pathway regions, with strong support for null effects in Bayes Factor analyses. In addition, surprisingly, placebo increased activity in some spinothalamic regions for unconditioned mechanical pain. In contrast, placebo reduced activity in a neuromarker associated with higher-level contributions to pain, the Stimulus Intensity Independent Pain Signature (SIIPS), and affected activity in brain regions related to motivation and value, in both pain modalities. Individual differences in behavioral analgesia were correlated with neural changes in both modalities. Our results indicate that cognitive and affective processes primarily drive placebo analgesia, and show the potential of neuromarkers for separating treatment influences on nociception from influences on evaluative processes.

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks.

Structural network topology associated with naming improvements following intensive aphasia therapy in post-stroke aphasia

A stroke can disrupt the finely tuned language network resulting in aphasia, a language impairment. Though many stroke survivors with aphasia recover within the first 6 months, a significant proportion have lasting deficits. The factors contributing to optimal treatment response remain unclear. Some evidence suggests that increased modularity or fragmentation of brain networks may underlie post-stroke aphasia severity and the extent of recovery. We examined associations between network organization and aphasia recovery in sixteen chronic stroke survivors with non-fluent aphasia following 35 h of Multi-Modality Aphasia Therapy over 10 days and 20 healthy controls who underwent imaging at a single timepoint. Using diffusion-weighted scans obtained before and after treatment, we constructed whole-brain structural connectomes representing the number of probabilistic streamlines between brain regions. Graph theory metrics were quantified for each connectome using the Brain Connectivity Toolbox. Correlations were examined between graph metrics and speech performance measured using the Boston Naming Test (BNT) at pre-, post- and 3-months post-intervention. Compared to controls, participants with stroke demonstrated higher whole-brain modularity at pre-treatment. Modularity did not differ between pre- and post-treatment. In individuals who responded to therapy, higher pre-treatment modularity was associated with worse performance on the BNT. Moreover, higher pre-treatment participation coefficients (i.e., how well a region is connected outside its own module) for the left IFG, planum temporale, and posterior temporal gyri were associated with greater improvements at post-treatment. These results suggest that pre-treatment network topology may impact therapeutic gains, highlighting the influence of network organization on post-stroke aphasia recovery.

A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity

The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features-e.g. diffusion parameters-or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.

Bidirectional Copy-Paste Mamba for Enhanced Semi-Supervised Segmentation of Transvaginal Uterine Ultrasound Images

Automated perimetrium segmentation of transvaginal ultrasound images is an important process for computer-aided diagnosis of uterine diseases. However, ultrasound images often contain various structures and textures, and these structures have different shapes, sizes, and contrasts; therefore, accurately segmenting the parametrium region of the uterus in transvaginal uterine ultrasound images is a challenge. Recently, many fully supervised deep learning-based methods have been proposed for the segmentation of transvaginal ultrasound images. Nevertheless, these methods require extensive pixel-level annotation by experienced sonographers. This procedure is expensive and time-consuming. In this paper, we present a bidirectional copy-paste Mamba (BCP-Mamba) semi-supervised model for segmenting the parametrium. The proposed model is based on a bidirectional copy-paste method and incorporates a U-shaped structure model with a visual state space (VSS) module instead of the traditional sampling method. A dataset comprising 1940 transvaginal ultrasound images from Tongji Hospital, Huazhong University of Science and Technology is utilized for training and evaluation. The proposed BCP-Mamba model undergoes comparative analysis with two widely recognized semi-supervised models, BCP-Net and U-Net, across various evaluation metrics including Dice, Jaccard, average surface distance (ASD), and Hausdorff_95. The results indicate the superior performance of the BCP-Mamba semi-supervised model, achieving a Dice coefficient of 86.55%, surpassing both U-Net (80.72%) and BCP-Net (84.63%) models. The Hausdorff_95 of the proposed method is 14.56. In comparison, the counterparts of U-Net and BCP-Net are 23.10 and 21.34, respectively. The experimental findings affirm the efficacy of the proposed semi-supervised learning approach in segmenting transvaginal uterine ultrasound images. The implementation of this model may alleviate the expert workload and facilitate more precise prediction and diagnosis of uterine-related conditions.

Auditory hemispheric asymmetry for actions and objects

What is the function of auditory hemispheric asymmetry? We propose that the identification of sound sources relies on the asymmetric processing of two complementary and perceptually relevant acoustic invariants: actions and objects. In a large dataset of environmental sounds, we observed that temporal and spectral modulations display only weak covariation. We then synthesized auditory stimuli by simulating various actions (frictions) occurring on different objects (solid surfaces). Behaviorally, discrimination of actions relies on temporal modulations, while discrimination of objects relies on spectral modulations. Functional magnetic resonance imaging data showed that actions and objects are decoded in the left and right hemispheres, respectively, in bilateral superior temporal and left inferior frontal regions. This asymmetry reflects a generic differential processing-through differential neural sensitivity to temporal and spectral modulations present in environmental sounds-that supports the efficient categorization of actions and objects. These results support an ecologically valid framework of the functional role of auditory brain asymmetry.

Gaze and Arrows: Does the Gaze-Following Patch in the Posterior Temporal Cortex Differentiate Social and Symbolic Spatial Cues?

The gaze-following patch (GFP) is located in the posterior temporal cortex and has been described as a cortical module dedicated to processing other people's gaze-direction in a domain-specific manner. Thus, it appears to be the neural correlate of Baron-Cohen's eye direction detector (EDD) which is one of the core modules in his mindreading system-a neurocognitive model for the theory of mind concept. Inspired by Jerry Fodor's ideas on the modularity of the mind, Baron-Cohen proposed that, among other things, the individual modules are domain specific. In the case of the EDD, this means that it exclusively processes eye-like stimuli to extract gaze-direction and that other stimuli, which may carry directional information as well, are processed elsewhere. If the GFP is indeed EDD's neural correlate, it must meet this expectation. To test this, we compared the GFP's BOLD activity during gaze-direction following with the activity during arrow-direction following in the present human fMRI study. Contrary to the expectation based on the assumption of domain specificity, we did not find a differentiation between gaze- and arrow-direction following. In fact, we were not able to reproduce the GFP as presented in the previous studies. A possible explanation is that in the present study-unlike the previous work-the gaze stimuli did not contain an obvious change of direction that represented a visual motion. Hence, the critical stimulus component responsible for the identification of the GFP in the previous experiments might have been visual motion.

Developmental refinements to neural attentional state during semantic memory retrieval through adolescence

Despite the fact that attention undergoes protracted development, little is known about how it may support memory refinements in childhood and adolescence. Here, we asked whether people differentially focus their attention on semantic or perceptual information over development during memory retrieval. First, we trained a multivoxel classifier to characterize whole-brain neural patterns reflecting semantic versus perceptual attention in a cued attention task. We then used this classifier to quantify how attention varied in a separate dataset in which children, adolescents, and adults retrieved autobiographical, semantic, and episodic memories. All age groups demonstrated a semantic attentional bias during memory retrieval, with significant age differences in this bias during the semantic task. Trials began with a preparatory picture cue followed by a retrieval question, which allowed us to ask whether attentional biases varied by trial period. Adults showed a semantic bias earlier during the picture cues, whereas adolescents showed this bias during the question. Adults and adolescents also engaged different brain regions-superior parietal cortex and ventral visual regions, respectively-during preparatory picture cues. Our results demonstrate that retrieval-related attention undergoes refinement beyond childhood. These findings suggest that alongside expanding semantic knowledge, attention-related changes may support the maturation of factual knowledge retrieval.

High SNR full brain relaxometry at 7T by accelerated MR-STAT

PURPOSE

To demonstrate the feasibility and robustness of the Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) framework for fast, high SNR relaxometry at 7T.

METHODS

To deploy MR-STAT on 7T-systems, we designed optimized flip-angles using the BLAKJac-framework that incorporates the SAR-constraints. Transmit RF-inhomogeneities were mitigated by including a measuredB 1 + $$ {B}_1^{+} $$ -map in the reconstruction. Experiments were performed on a gel-phantom and on five volunteers to explore the robustness of the sequence and its sensitivity toB 1 + $$ {B}_1^{+} $$ inhomogeneities. The SNR-gain at 7T was explored by comparing phantom and in vivo results to MR-STAT at 3T in terms of SNR-efficiency.

RESULTS

The higher SNR at 7T enabled two-fold acceleration with respect to current 2D MR-STAT protocols at lower field strengths. The resulting scan had whole-brain coverage, with 1 x 1 x 3 mm3 resolution (1.5 mm slice-gap) and was acquired within 3 min including theB 1 + $$ {B}_1^{+} $$ -mapping. AfterB 1 + $$ {B}_1^{+} $$ -correction, the estimated T1 and T2 in a phantom showed a mean relative error of, respectively, 1.7% and 4.4%. In vivo, the estimated T1 and T2 in gray and white matter corresponded to the range of values reported in literature with a variation over the subjects of 1.0%-2.1% (WM-GM) for T1 and 4.3%-5.3% (WM-GM) for T2. We measured a higher SNR-efficiency at 7T (R = 2) than at 3T for both T1 and T2 with, respectively, a 4.1 and 2.3 times increase in SNR-efficiency.

CONCLUSION

We presented an accelerated version of MR-STAT tailored to high field (7T) MRI using a low-SAR flip-angle train and showed high quality parameter maps with an increased SNR-efficiency compared to MR-STAT at 3T.

Structural correlations between brain magnetic resonance image-derived phenotypes and retinal neuroanatomy

BACKGROUND AND PURPOSE

The eye is a well-established model of brain structure and function, yet region-specific structural correlations between the retina and the brain remain underexplored. Therefore, we aim to explore and describe the relationships between the retinal layer thicknesses and brain magnetic resonance image (MRI)-derived phenotypes in UK Biobank.

METHODS

Participants with both quality-controlled optical coherence tomography (OCT) and brain MRI were included in this study. Retinal sublayer thicknesses and total macular thickness were derived from OCT scans. Brain image-derived phenotypes (IDPs) of 153 cortical and subcortical regions were processed from MRI scans. We utilized multivariable linear regression models to examine the association between retinal thickness and brain regional volumes. All analyses were corrected for multiple testing and adjusted for confounders.

RESULTS

Data from 6446 participants were included in this study. We identified significant associations between volumetric brain MRI measures of subregions in the occipital lobe (intracalcarine cortex), parietal lobe (postcentral gyrus), cerebellum (lobules VI, VIIb, VIIIa, VIIIb, and IX), and deep brain structures (thalamus, hippocampus, caudate, putamen, pallidum, and accumbens) and the thickness of the innermost retinal sublayers and total macular thickness (all p < 3.3 × 10-5). We did not observe statistically significant associations between brain IDPs and the thickness of the outer retinal sublayers.

CONCLUSIONS

Thinner inner and total retinal thicknesses are associated with smaller volumes of specific brain regions. Notably, these relationships extend beyond anatomically established retina-brain connections.

Comparison of methods for intravoxel incoherent motion parameter estimation in the brain from flow-compensated and non-flow-compensated diffusion-encoded data

PURPOSE

Joint analysis of flow-compensated (FC) and non-flow-compensated (NC) diffusion MRI (dMRI) data has been suggested for increased robustness of intravoxel incoherent motion (IVIM) parameter estimation. For this purpose, a set of methods commonly used or previously found useful for IVIM analysis of dMRI data obtained with conventional diffusion encoding were evaluated in healthy human brain.

METHODS

Five methods for joint IVIM analysis of FC and NC dMRI data were compared: (1) direct non-linear least squares fitting, (2) a segmented fitting algorithm with estimation of the diffusion coefficient from higher b-values of NC data, (3) a Bayesian algorithm with uniform prior distributions, (4) a Bayesian algorithm with spatial prior distributions, and (5) a deep learning-based algorithm. Methods were evaluated on brain dMRI data from healthy subjects and simulated data at multiple noise levels. Bipolar diffusion encoding gradients were used with b-values 0-200 s/mm2 and corresponding flow weighting factors 0-2.35 s/mm for NC data and by design 0 for FC data. Data were acquired twice for repeatability analysis.

RESULTS

Measurement repeatability as well as estimation bias and variability were at similar levels or better with the Bayesian algorithm with spatial prior distributions and the deep learning-based algorithm for IVIM parametersD $$ D $$ andf $$ f $$ , and for the Bayesian algorithm only forv d $$ {v}_d $$ , relative to the other methods.

CONCLUSION

A Bayesian algorithm with spatial prior distributions is preferable for joint IVIM analysis of FC and NC dMRI data in the healthy human brain, but deep learning-based algorithms appear promising.

Neurobiological correlates of religious coping among older adults with and without mood disorders: An exploratory study

In this study, 32 older adults with and without mood disorders completed resting-state functional Magnetic Resonance Imaging and measures of demographics, spirituality/religion, positive and negative religious coping, and depression. Group Independent Component Analysis identified and selected three a priori resting state networks [cingulo-opercular salience (cSN), central executive (CEN) and Default Mode Networks (DMN)] within the Triple Network Mode. We investigated associations of religious coping with within- and between-network connectivity, controlling for age. Insular connectivity within the cSN was associated with negative religious coping. Religious coping was associated with anti-correlation between the DMN and CEN even when controlling for depression.

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging

Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisitions, and numerous studies have recently attempted to harness deep learning (DL) technology in enabling scan time reduction and image quality improvement. Various DL-based image reconstruction products allow for additional scan time reduction on top of existing accelerated acquisition methods without compromising the image quality.

Frontal-striatal tract integrity and depression in older adults with and without multiple sclerosis

OBJECTIVE

Lower white matter integrity of frontal-subcortical circuitry has been associated with late-life depression in normally aging older adults and with the presence of multiple sclerosis (MS). Frontal-striatal white matter tracts involved in executive, cognitive, emotion, and motor function may underlie depression in older adults with MS. The present study examined the association between depression score and frontal-striatal white matter integrity in older adults with MS and controls.

METHODS

Older adults with MS (OAMS) (n = 67, mean age = 64.55 ± 3.89) and controls (n = 74, mean age = 69.04 ± 6.32) underwent brain MRI, cognitive assessment, psychological, and motoric testing. Depression was assessed through the 30-item Geriatric Depression Scale. Fractional anisotropy (FA) was extracted from two bilateral tracts: dorsolateral prefrontal cortex to putamen nucleus (DLPFC-pn) and dorsolateral prefrontal cortex to caudate nucleus (DLPFC-cn).

RESULTS

OAMS reported significantly worse (i.e., higher) depression symptoms (β = .357, p < .001) compared to healthy controls. Adjusted moderation analyses revealed, via group by FA interactions, significantly stronger associations between FA of the left DLPFC-pn tract and total depression (B =  - 61.70, p = .011) among OAMS compared to controls. Conditional effects revealed that lower FA of the left DLPFC-pn was significantly associated with worse (i.e., higher) depression symptoms (b =  - 38.0, p = .028) only among OAMS. The other three tracts were not significant in moderation models.

CONCLUSIONS

We provided first evidence that lower white matter integrity of the left DLPFC-pn tract was related to worse depression in older adults with MS.

Effects of stress-related neuromodulators on amygdala and hippocampus resting state functional connectivity

BACKGROUND

The human stress response is characterized by increases in neuromodulators, including norepinephrine (NE) and cortisol. Both neuromodulators can enter the brain and affect neurofunctional responses. Two brain areas associated with stress are the amygdala and the hippocampus. The precise influence of NE and cortisol on the amygdala and hippocampal resting state functional connectivity (RSFC) is poorly understood.

AIMS

To investigate the influence of NE and cortisol on the amygdala and hippocampal RSFC.

METHODS

We recruited 165 participants who received 10 mg yohimbine and/or 10 mg hydrocortisone in a randomized, placebo-controlled design. With seed-based analyses, we compared RSFC of the hippocampus and amygdala separately between the three groups that received medication versus placebo.

RESULTS

We found no differences between yohimbine and placebo condition or between hydrocortisone and placebo condition regarding amygdala or hippocampal FC. Compared with placebo, the yohimbine/hydrocortisone condition showed increased amygdala and hippocampal RSFC with the cerebellum. Also, they had increased hippocampal RSFC with the amygdala and cerebral white matter.

DISCUSSION

The group with elevated NE and cortisol showed significantly increased RSFC between the amygdala, hippocampus, and cerebellum compared to placebo. These three brain areas are involved in associative learning and emotional memory, suggesting a critical role for this network in the human stress response. Our results show that NE and cortisol together may influence the strength of this association. Compared to placebo, we found no differences in the groups receiving only one medication, suggesting that increasing one neuromodulator alone may not induce differences in neurofunctional responses. The study procedure has been registered at clinicaltrials.gov (ID: NCT04359147).

A mathematical model for temporal cerebral blood flow response to acetazolamide evaluated in patients with Moyamoya disease

BACKGROUND

Paired cerebral blood flow (CBF) measurement is usually acquired before and after vasoactive stimulus to estimate cerebrovascular reserve (CVR). However, CVR may be confounded because of variations in time-to-maximum CBF response (tmax) following acetazolamide injection. With a mathematical model, CVR can be calculated insensitive to variations in tmax, and a model offers the possibility to calculate additional model-derived parameters. A model that describes the temporal CBF response following a vasodilating acetazolamide injection is proposed and evaluated.

METHODS

A bi-exponential model was adopted and fitted to four CBF measurements acquired using arterial spin labelling before and initialised at 5, 15 and 25 min after acetazolamide injection in a total of fifteen patients with Moyamoya disease. Curve fitting was performed using a non-linear least squares method with a priori constraints based on simulations.

RESULTS

Goodness of fit (mean absolute error) varied between 0.30 and 0.62 ml·100 g-1·min-1. Model-derived CVR was significantly higher compared to static CVR measures. Maximum CBF increase occurred earlier in healthy- compared to diseased vascular regions.

CONCLUSIONS

The proposed mathematical model offers the possibility to calculate CVR insensitive to variations in time to maximum CBF response which gives a more detailed characterisation of CVR compared to static CVR measures. Although the mathematical model adapts generally well to this dataset of patients with MMD it should be considered as experimental; hence, further studies in healthy populations and other patient cohorts are warranted.

Laminar CBV and BOLD response-characteristics over time and space in the human primary somatosensory cortex at 7T

Uncovering the cortical representation of the body has been at the core of human brain mapping for decades, with special attention given to the digits. In the last decade, advances in functional magnetic resonance imaging (fMRI) technologies have opened the possibility of noninvasively unraveling the 3rd dimension of digit representations in humans along cortical layers. In laminar fMRI it is common to combine the use of the highly sensitive blood oxygen level dependent (BOLD) contrast with cerebral blood volume sensitive measurements, like vascular space occupancy (VASO), that are more specific to the underlying neuronal populations. However, the spatial and temporal VASO response characteristics across cortical depth to passive stimulation of the digits are still unknown. Therefore, we characterized haemodynamic responses to vibrotactile stimulation of individual digit-tips across cortical depth at 0.75 mm in-plane spatial resolution using BOLD and VASO fMRI at 7T. We could identify digit-specific regions of interest (ROIs) in putative Brodmann area 3b, following the known anatomical organization. In the ROIs, the BOLD response increased towards the cortical surface due to the draining vein effect, while the VASO response was more shifted towards middle cortical layers, likely reflecting bottom-up input from the thalamus, as expected. Interestingly, we also found slightly negative BOLD and VASO responses for non-preferred digits in the ROIs, potentially indicating neuronal surround inhibition. Finally, we explored the temporal signal dynamics for BOLD and VASO as a function of distance from activation peaks resulting from stimulation of contralateral digits. With this analysis, we showed a triphasic response consisting of an initial peak and a subsequent negative deflection during stimulation, followed by a positive post-stimulus response in BOLD and to some extent in VASO. While similar responses were reported with invasive methods in animal models, here we demonstrate a potential neuronal excitation-inhibition mechanism in a center-surround architecture across layers in the human somatosensory cortex. Given that, unlike in animals, human experiments do not rely on anesthesia and can readily implement extensive behavioral testing, obtaining this effect in humans is an important step towards further uncovering the functional significance of the different aspects of the triphasic response.

Comparison of arterial spin labeled MRI (ASL MRI) between ADHD and control group (ages of 6-12)

This study utilized arterial spin labeling-magnetic resonance imaging (ASL-MRI) to explore the developmental trajectory of brain activity associated with attention deficit hyperactivity disorder (ADHD). Pulsed arterial spin labeling (ASL) data were acquired from 157 children with ADHD and 109 children in a control group, all aged 6-12 years old. Participants were categorized into the age groups of 6-7, 8-9, and 10-12, after which comparisons were performed between each age group for ASL analysis of cerebral blood flow (CBF). In total, the ADHD group exhibited significantly lower CBF in the left superior temporal gyrus and right middle frontal gyrus regions than the control group. Further analysis revealed: (1) The comparison between the ADHD group (N = 70) aged 6-7 and the age-matched control group (N = 33) showed no statistically significant difference between. (2) However, compared with the control group aged 8-9 (N = 39), the ADHD group of the same age (N = 53) showed significantly lower CBF in the left postcentral gyrus and left middle frontal gyrus regions. (3) Further, the ADHD group aged 10-12 (N = 34) demonstrated significantly lower CBF in the left superior occipital region than the age-matched control group (N = 37). These age-specific differences suggest variations in ADHD-related domains during brain development post age 6-7.

Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data

Purpose

The study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2) demonstrate the impact of spatial and angular resolution and processing settings on tractography and derived quantitative measures.

Methods

For the purpose of this study, the term-equivalent dMRIs (single-shell b800, and b2000, both 5 b0, and 45 gradient directions) of two moderate-late preterm infants (with and without motion artifacts) from a local cohort [Brain Imaging in Moderate-late Preterm infants (BIMP) study; Calgary, Canada] and one infant from the developing human connectome project with high-quality dMRI (using the b2600 shell, comprising 20 b0 and 128 gradient directions, from the multi-shell dataset) were selected. Diffusion tensor imaging (DTI) and CSD tractography were compared on b800 and b2000 dMRI. Varying image resolution modifications, (pre-)processing and tractography settings were tested to assess their impact on tractography. Each experiment involved visualizing local modeling and tractography for the corpus callosum and corticospinal tracts, and assessment of morphological and diffusion measures.

Results

Contrary to DTI, CSD enabled reconstruction of crossing fibers. Tractography was susceptible to image resolution, (pre-) processing and tractography settings. In addition to visual variations, settings were found to affect streamline count, length, and diffusion measures (fractional anisotropy and mean diffusivity). Diffusion measures exhibited variations of up to 23%.

Conclusion

Reconstruction of crossing fiber bundles using CSD tractography with unsedated neonatal dMRI data is feasible. Tractography settings affected streamline reconstruction, warranting careful documentation of methods for reproducibility and comparison of cohorts.

Seven Tesla Evidence for Columnar and Rostral-Caudal Organization of the Human Periaqueductal Gray Response in the Absence of Threat: A Working Memory Study

The periaqueductal gray (PAG) is a small midbrain structure that surrounds the cerebral aqueduct, regulates brain-body communication, and is often studied for its role in "fight-or-flight" and "freezing" responses to threat. We used ultra-high-field 7 T fMRI to resolve the PAG in humans and distinguish it from the cerebral aqueduct, examining its in vivo function during a working memory task (N = 87). Both mild and moderate cognitive demands elicited spatially similar patterns of whole-brain blood oxygenation level-dependent (BOLD) response, and moderate cognitive demand elicited widespread BOLD increases above baseline in the brainstem. Notably, these brainstem increases were not significantly greater than those in the mild demand condition, suggesting that a subthreshold brainstem BOLD increase occurred for mild cognitive demand as well. Subject-specific masks were group aligned to examine PAG response. In PAG, both mild and moderate demands elicited a well-defined response in ventrolateral PAG, a region thought to be functionally related to anticipated painful threat in humans and nonhuman animals-yet, the present task posed only the most minimal (if any) "threat," with the cognitive tasks used being approximately as challenging as remembering a phone number. These findings suggest that the PAG may play a more general role in visceromotor regulation, even in the absence of threat.

Reconfigurations of cortical manifold structure during reward-based motor learning

Adaptive motor behavior depends on the coordinated activity of multiple neural systems distributed across the brain. While the role of sensorimotor cortex in motor learning has been well established, how higher-order brain systems interact with sensorimotor cortex to guide learning is less well understood. Using functional MRI, we examined human brain activity during a reward-based motor task where subjects learned to shape their hand trajectories through reinforcement feedback. We projected patterns of cortical and striatal functional connectivity onto a low-dimensional manifold space and examined how regions expanded and contracted along the manifold during learning. During early learning, we found that several sensorimotor areas in the dorsal attention network exhibited increased covariance with areas of the salience/ventral attention network and reduced covariance with areas of the default mode network (DMN). During late learning, these effects reversed, with sensorimotor areas now exhibiting increased covariance with DMN areas. However, areas in posteromedial cortex showed the opposite pattern across learning phases, with its connectivity suggesting a role in coordinating activity across different networks over time. Our results establish the neural changes that support reward-based motor learning and identify distinct transitions in the functional coupling of sensorimotor to transmodal cortex when adapting behavior.

The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study design, data processing, and rationale

To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18-80 years, stratified by age decade and sex (median age 52, IQR 36-66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n = 120), we recorded sleep-wake rhythms using an actigraphy device (Actiwatch 2, Philips Respironics) for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience.

Relationship Between Resting State Functional Connectivity and Reading-Related Behavioural Measures in 69 Adults

In computational models of reading, written words can be read using print-to-sound and/or print-to-meaning pathways. Neuroimaging data associate dorsal stream regions (left posterior occipitotemporal cortex, intraparietal cortex, dorsal inferior frontal gyrus [dIFG]) with the print-to-sound pathway and ventral stream regions (left anterior fusiform gyrus, middle temporal gyrus) with the print-to-meaning pathway. In 69 typical adults, we investigated whether resting state functional connectivity (RSFC) between the visual word form area (VWFA) and dorsal and ventral regions correlated with phonological (nonword reading, nonword repetition, spoonerisms), lexical-semantic (vocabulary, sensitivity to morpheme units in reading), and general literacy (word reading, spelling) skills. VWFA activity was temporally correlated with activity in both dorsal and ventral reading regions. In pre-registered whole-brain analyses, spoonerisms performance was positively correlated with RSFC between the VWFA and left dorsal regions (dIFG, superior parietal and intraparietal cortex). In exploratory region-of-interest analyses, VWFA-dIFG connectivity was also positively correlated with nonword repetition, spelling, and vocabulary. Connectivity between the VWFA and ventral stream regions was not associated with performance on any behavioural measure, either in whole-brain or region-of-interest analyses. Our results suggest that tasks such as spoonerisms and spellings, which are both complex (i.e., involve multiple subprocesses) and have high between-subject variability, provide greater opportunity for observing resting-state brain-behaviour associations. However, the complexity of these tasks limits the conclusions we can draw about the specific mechanisms that drive these associations. Future research would benefit from constructing latent variables from multiple tasks tapping the same reading subprocess.

Improving the Reliability and Accuracy of Population Receptive Field Measures Using a Logarithmically Warped Stimulus

The population receptive field method, which measures the region in visual space that elicits a BOLD signal in a voxel in retinotopic cortex, is a powerful tool for investigating the functional organization of human visual cortex with fMRI (Dumoulin & Wandell, 2008). However, recent work has shown that population receptive field (pRF) estimates for early retinotopic visual areas can be biased and unreliable, especially for voxels representing the fovea. Here, we show that a 'log-bar' stimulus that is logarithmically warped along the eccentricity dimension produces more reliable estimates of pRF size and location than the traditional moving bar stimulus. The log-bar stimulus was better able to identify pRFs near the foveal representation, and pRFs were smaller in size, consistent with simulation estimates of receptive field sizes in the fovea.

Intersubject correlations in reward and mentalizing brain circuits separately predict persuasiveness of two types of ISIS video propaganda

The Islamist group ISIS has been particularly successful at recruiting Westerners as terrorists. A hypothesized explanation is their simultaneous use of two types of propaganda: Heroic narratives, emphasizing individual glory, alongside Social narratives, which emphasize oppression against Islamic communities. In the current study, functional MRI was used to measure brain responses to short ISIS propaganda videos distributed online. Participants were shown 4 Heroic and 4 Social videos categorized as such by another independent group of subjects. Persuasiveness was measured using post-scan predictions of recruitment effectiveness. Inter-subject correlation (ISC) was used to measure commonality of brain activity time courses across individuals. ISCs in ventral striatum predicted rated persuasiveness for Heroic videos, while ISCs in mentalizing and default networks, especially in dmPFC, predicted rated persuasiveness for Social videos. This work builds on past findings that engagement of the reward circuit and of mentalizing brain regions predicts preferences and persuasion. The observed dissociation as a function of stimulus type is novel, as is the finding that intersubject synchrony in ventral striatum predicts rated persuasiveness. These exploratory results identify possible neural mechanisms by which political extremists successfully recruit prospective members and specifically support the hypothesized distinction between Heroic and Social narratives for ISIS propaganda.

Distinct brain morphometry patterns revealed by deep learning improve prediction of post-stroke aphasia severity

BACKGROUND

Emerging evidence suggests that post-stroke aphasia severity depends on the integrity of the brain beyond the lesion. While measures of lesion anatomy and brain integrity combine synergistically to explain aphasic symptoms, substantial interindividual variability remains unaccounted. One explanatory factor may be the spatial distribution of morphometry beyond the lesion (e.g., atrophy), including not just specific brain areas, but distinct three-dimensional patterns.

METHODS

Here, we test whether deep learning with Convolutional Neural Networks (CNNs) on whole brain morphometry (i.e., segmented tissue volumes) and lesion anatomy better predicts chronic stroke individuals with severe aphasia (N = 231) than classical machine learning (Support Vector Machines; SVMs), evaluating whether encoding spatial dependencies identifies uniquely predictive patterns.

RESULTS

CNNs achieve higher balanced accuracy and F1 scores, even when SVMs are nonlinear or integrate linear or nonlinear dimensionality reduction. Parity only occurs when SVMs access features learned by CNNs. Saliency maps demonstrate that CNNs leverage distributed morphometry patterns, whereas SVMs focus on the area around the lesion. Ensemble clustering of CNN saliencies reveals distinct morphometry patterns unrelated to lesion size, consistent across individuals, and which implicate unique networks associated with different cognitive processes as measured by the wider neuroimaging literature. Individualized predictions depend on both ipsilateral and contralateral features outside the lesion.

CONCLUSIONS

Three-dimensional network distributions of morphometry are directly associated with aphasia severity, underscoring the potential for CNNs to improve outcome prognostication from neuroimaging data, and highlighting the prospective benefits of interrogating spatial dependence at different scales in multivariate feature space.