Human Brain Mapping最新文献

Magnetic resonance imaging (MRI) at 7T has a superior signal-to-noise ratio to 3T but also presents higher signal inhomogeneities and geometric distortions. A key knowledge gap is to robustly investigate the sensitivity and accuracy of 3T and 7T MRI in assessing brain morphometrics. This study aims to (a) aggregate a large number of paired 3T and 7T scans to evaluate their differences in quantitative brain morphological assessment using a widely available brain segmentation tool, FreeSurfer, as well as to (b) examine the impact of normalization methods for subject variability and smaller sample sizes on data analysis. A total of 401 healthy participants aged 29–68 were imaged at both 3T and 7T. Structural T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images were processed and segmented using FreeSurfer. To account for head size variability, the brain volumes underwent intracranial volume (ICV) correction using the Residual (regression model) and Proportional (simple division to ICV) methods. The resulting volumes and thicknesses were correlated with age using Pearson's correlation and false discovery rate correction. The correlations were also calculated in increasing sample size from three to the whole sample to estimate the sample size required to detect aging-related brain variation. Three hundred and fifty subjects (208 females) passed the image quality control, with 51 subjects excluded due to excessive motion artifacts on 3T, 7T, or both. 7T MRI showed an overall stronger correlation between morphometrics and age and a larger number of significantly correlated brain volumes and cortical thicknesses. While the ICV is consistent between both field strengths, the Residual normalization method shows markedly higher correlation with age for 3T when compared with the Proportional normalization method. The 7T results are consistent regardless of the normalization method used. In a large cohort of healthy participants with paired 3T and 7T scans, we compared the statistical performance in assessing age-related brain morphological changes. Our study reaffirmed the inverse correlation between brain volumes and cortical thicknesses and age and highlighted varying correlations in different brain regions and normalization methods at 3T and 7T. 7T imaging significantly improves statistical power and thus reduces the required sample size.

Nostalgia is a mixed emotion that is often evoked by music. Nostalgic music may induce temporary improvements in autobiographical memory in individuals with cognitive decline. However, the neural mechanism underlying music-evoked nostalgia and its associated memory improvements is unclear. With the ultimate goal of understanding how nostalgia-evoking music may help retrieve autobiographical memories in individuals with cognitive impairment, we first sought to understand the neural underpinnings of these processes in healthy younger and older adults. Methodological constraints, including the lack of personally tailored and experimentally controlled stimuli, have impeded our understanding of this mechanism. Here, we utilized an innovative machine-learning-based method to construct three categories of songs, all matched for musical features: (1) personalized nostalgic, (2) familiar non-nostalgic, and (3) unfamiliar non-nostalgic. In 57 participants (29 aged 18–35; 28 aged 60 and older), we investigated the functional neural correlates of music-evoked nostalgia using fMRI. Four main findings emerged: (1) Listening to nostalgic music, more than familiar non-nostalgic or unfamiliar music, was associated with bilateral activity in the default mode network, salience network, reward network, medial temporal lobe, and supplementary motor regions, (2) Psychophysiological interaction (PPI) models indicated that listening to nostalgic music involved increased functional connectivity of self-referential (posteromedial cortex) and affect-related regions (insula), (3) Older adults had stronger BOLD signals than younger adults in nostalgia-related regions during nostalgic listening, (4) While the BOLD response to nostalgic music in younger adults was associated with trait-level factors of nostalgia proneness and cognitive ability, the response in older adults was related to affective responses to the music. Overall, our findings serve as a foundation for understanding the neural basis of music-evoked nostalgia and its potential use in future clinical interventions.

Emotions remarkably impact our creative minds; nevertheless, a comprehensive mapping of their underlying neural mechanisms remains elusive. Therefore, we examined the influence of emotion induction on ideational originality and its associated neural dynamics. Participants were randomly presented with three short videos with sad, neutral, and happy content. After each video, ideational originality was evaluated using the alternate uses task. Both happy and sad inductions significantly enhanced ideational originality relative to the neutral induction condition. However, no significant difference was observed in ideational originality between the happy and sad emotion inductions. Associated neural dynamics were assessed through EEG time-frequency (TF) power and phase-amplitude coupling (PAC) analyses. Our findings suggest that emotional states elicit distinct TF and PAC profiles associated with ideational originality. Relative to baseline, gamma activity was enhanced after the neutral induction and more enhanced after the induction of a happy emotion but reduced after the induction of sad emotion 2–4 s after starting the task. Our functional connectivity couplings suggest that inducing happy and sad emotions may influence the working memory and attentional system differently, leading to varying effects on associated processing modes. Inducing a happy emotion may result in decreased neural activity and processing of rich information in working memory for exploring more original ideas through cognitive flexibility. In contrast, inducing a sad emotion may enhance neural activity and increase coupling within the attention system to exploit and select fewer original ideas through cognitive persistence.

Self-reported physical activity is associated with lower brain food cue responsiveness in reward-related regions, but relationships utilizing objective physical activity measurement tools have not been explored. This cross-sectional study examined whether device-measured moderate-to-vigorous intensity physical activity and sedentary time are related to neural responses to visual food cues using functional magnetic resonance imaging. Fifty-one healthy adults (30 men, 21 women; mean ± SD: age 26 ± 6 years; body mass index 24.1 ± 3.0 kg/m²) underwent a functional magnetic resonance imaging scan after an overnight fast while viewing images of high/very high-energy density foods (HED), very low/low-energy density foods (LED) and non-food objects. Free-living moderate-to-vigorous intensity physical activity and sedentary time were measured for seven consecutive days using an ActiGraph wGT3X-BT and activPAL4 accelerometer, respectively. Associations of behavioural variables with brain food cue reactivity were examined in regression models controlling for physiological and behavioural covariates. After adjusting for age, sex, body mass index and device weartime, moderate-to-vigorous intensity physical activity was negatively associated with reactivity to LED versus non-food cues in the precentral gyrus, hippocampus, posterior insula, and amygdala, which may diminish inhibitory-related responses towards healthier lower energy value foods. Time spent in moderate-to-vigorous intensity physical activity was positively associated with reactivity to LED versus non-food cues in the dorsal striatum, a region implicated in food motivation. A positive association was identified between sedentary time and reactivity to HED versus non-food cues in the dorsal division of the posterior cingulate gyrus that has been implicated in attention allocation. These findings suggest that moderate-to-vigorous intensity physical activity may enhance the appeal of and motivation to consume LED foods, whereas sedentary time may promote attention towards HED foods, highlighting the potential for engaging in greater physical activity and less sedentary time to positively influence the central (brain) appetite control system.

Whole-brain proton magnetic resonance spectroscopic imaging (¹H-MRSI) is a non-invasive technique for assessing neurochemical distribution in the brain, offering valuable insights into brain functions and neural diseases. It greatly benefits from the improved SNR at ultrahigh field strengths (≥ 7T). However, ¹H-MRSI still faces several challenges, such as long acquisition time and severe signal contamination from water and lipids. In this study, 2D and 3D short TR/TE ¹H-FID-MRSI sequences using rosette trajectories were developed with nominal spatial resolutions of 4.48 × 4.48 mm² and 4.48 × 4.48 × 4.50 mm³, respectively. Water signals were suppressed using an optimized Five-variable-Angle-gaussian-pulses-with-ShorT-total-duration (FAST) water suppression scheme of 76 ms, and lipid signals were removed using the L₂ regularization method. Metabolic maps of major ¹H metabolites were obtained in 5:40 min with 16 averages and 1 average for the 2D and 3D acquisitions, respectively. Excellent intra-session reproducibility was shown, with the coefficients of variance (CV) being lower than 6% for N-Acetyl-L-aspartic acid (NAA), Glutamate (Glu), total Choline (tCho), Creatine and Phosphocreatine (tCr), and Glycine and Myo-inositol (Gly + Ins). To explore the potential of further acceleration, compressed sensing was applied retrospectively to the 3D datasets. The structural similarity index (SSIM) remained above 0.85 and 0.8 until R = 2 and 3 for the metabolite maps of Glu, NAA, tCr, and tCho, indicating the possibility for further reduction of acquisition time to around 2 min.

The clinical translation of diffusion magnetic resonance imaging (dMRI)-derived quantitative contrasts hinges on robust reproducibility, minimizing both same-scanner and cross-scanner variability. As multi-site data sets, including multi-shell dMRI, expand in scope, enhancing reproducibility across variable MRI systems and MRI protocols becomes crucial. This study evaluates the reproducibility of diffusion kurtosis imaging (DKI) metrics (beyond conventional diffusion tensor imaging (DTI)), at the voxel and region-of-interest (ROI) levels on magnitude and complex-valued dMRI data, using denoising with and without harmonization. We compared same-scanner, cross-scanner, and cross-protocol variability for a multi-shell dMRI protocol (2-mm isotropic resolution, b = 0, 1000, 2000 s/mm²) in 20 subjects. We first evaluated the effectiveness of Marchenko-Pastur Principal Component Analysis (MPPCA) based denoising strategies for both magnitude and complex data to mitigate noise-induced bias and variance, to improve dMRI parametric maps and reproducibility. Next, we examined the impact of denoising under different population analysis approaches, specifically comparing voxel-wise versus region of interest (ROI)-based methods. We also evaluated the role of denoising when harmonizing dMRI across scanners and protocols. The results indicate that DTI and DKI maps visually improve after MPPCA denoising, with noticeably fewer outliers in kurtosis maps. Denoising, either using magnitude or complex dMRI, enhances voxel-wise reproducibility, with test–retest variability of kurtosis indices reduced from 15%–20% without denoising to 5%–10% after denoising. Complex dMRI denoising reduces the noise floor by up to 60%. Denoising not only reduced variability across scans and protocols, but also increased statistical power for low SNR voxel-wise comparisons when comparing cross sectional groups. In conclusion, MPPCA denoising, either over magnitude or complex dMRI data, enhances the reproducibility and precision of higher-order diffusion metrics across same-scanner, cross-scanner, and cross-protocol assessments. The enhancement in data quality and precision facilitates the broader application and acceptance of these advanced imaging techniques in both clinical practice and large-scale neuroimaging studies.

Negative BOLD fMRI responses (NBR) occur commonly in sensory cortex and default mode network regions but remain poorly utilized as a marker of brain function due to an incomplete understanding. To better understand how NBR manifest across the brain, compare between different sensory stimuli and how they are modulated by changes in task demand, we recorded fMRI during trials of visual, auditory, or somatosensory stimulation, delivered either alone or in concurrent pairs. Twenty young-adult participants were cued to attend to a single modality and detect targets in each trial. We found that NBR were consistently induced in all non-task-relevant primary sensory cortices and default mode regions during all stimuli. NBR were observed within the stimulated modality, in the cortex ipsilateral to the stimulus; as well as cross-modal responses bilaterally within the cortex of an unstimulated sensory modality. The NBR regions showed high spatial overlap with the primary sensory positive BOLD response (PBR) of the stimulated modality. The NBR occurred in spatially comparable regions across different modality stimuli such that the peak voxel location and spatial extent were comparable between within and cross-modal NBRs. Some specific differences were seen, such as stronger magnitude sensorimotor NBR to somatosensory stimuli than to visual or auditory. No significant relationships were found between subjects' PBR and NBR magnitude, but significant linear correlations were observed between NBRs indicating that subjects with high magnitude NBR within one sensory modality also displayed high magnitude cross-modal NBR in a different modality. These findings suggest that cortical NBR are largely consistent between different sensory stimuli but also contain stimulus-specific variability in magnitude and spatial extent. Finally, positive BOLD responses were stronger to dual stimuli in all contralateral primary sensory regions, whilst NBR were slightly increased in specific regions of ipsilateral visual and sensorimotor cortex. This finding suggests a strong contribution to NBR from bottom-up stimulus input that was further modulated by attention during dual conditions and that NBR is driven by a combination of bottom-up and top-down influences whereby contributions to its generation arise from both feed-forward signals from subcortical or activated sensory regions and feedback mechanisms such as higher-level attentional control.

Movie-watching fMRI has emerged as a theoretically viable platform for studying neurobiological substrates of affective states and emotional disorders such as pathological anxiety. However, using anxiety-inducing movie clips to probe relevant states impacted by psychopathology could risk exacerbating in-scanner movement, decreasing signal quality/quantity and thus statistical power. This could be especially problematic in target populations such as children who typically move more in the scanner. Consequently, we assessed: (1) the extent to which an anxiety-inducing movie clip altered in-scanner data quality (movement, censoring, and DVARS) in a pediatric sample with and without anxiety disorders (n = 78); and (2) investigated interactions between anxiety symptoms and movie-attenuated motion in a highly powered, transdiagnostic pediatric sample (n = 2058). Our results suggest anxiogenic movie-watching in fact reduces in-scanner movement compared to resting-state, increasing the quantity/quality of data. In one measure, pathological anxiety appeared to impact movie-attenuated motion, but the effect was small. Given potential boosts to data quality, future developmental neuroimaging studies of anxiety may benefit from the use of movie paradigms.

The ability to balance between being persistent versus flexible during cognitive control is referred to as “metacontrol” and reflected in the exponent of aperiodic neural activity. Theoretical considerations suggest that metacontrol is affected by the interplay of the GABAergic, glutamatergic, and catecholaminergic systems. Moreover, evidence suggests that fronto-striatal structures play an important role. Yet, the nexus between neurobiochemistry and structural neuroanatomy when it comes to the foundations of metacontrol is not understood. To examine this, we investigated how an experimental manipulation of catecholaminergic signaling via methylphenidate (MHP) and baseline levels of GABA and glutamate in the anterior cingulate cortex (ACC), supplementary motor area (SMA), and striatum as assessed via MR spectroscopy altered task performance and associated aperiodic activity (assessed via EEG) during a conflict monitoring task. We investigated N = 101 healthy young adults. We show that the EEG-aperiodic exponent was elevated during task performance, as well as during cognitively challenging task conditions requiring more persistent processing and was further enhanced by MPH administration. Correlation analyses also provided evidence for an important role of individual characteristics and dispositions as reflected by the observed role of GABA+ and Glx baseline levels in the ACC, the SMA, and the striatum. Our observations point to an important role of catecholamines in the amino acid neurotransmitter-driven regulation of metacontrol and task-specific (changes in) metacontrol biases. The results suggest an interplay of the GABA/Glx and the catecholaminergic system in prefrontal-basal ganglia structures crucial for metacontrol.