Neuroimage. Reports最新文献

The parahippocampal cingulum bundle (PHCB) interconnects regions known to be vulnerable to early Alzheimer's disease (AD) pathology, including posteromedial cortex and medial temporal lobe. While AD-related pathology has been robustly associated with alterations in PHCB microstructure, specifically lower fractional anisotropy (FA) and higher mean diffusivity (MD), emerging evidence indicates that the reverse pattern is evident in younger adults at increased risk of AD. In one such study, Hodgetts et al. (2019) reported that healthy young adult carriers of the apolipoprotein-E (APOE) ε4 allele – the strongest common genetic risk factor for AD – showed higher FA and lower MD in the PHCB but not the inferior longitudinal fasciculus (ILF). These results are consistent with proposals claiming that heightened neural activity and intrinsic connectivity play a significant role in increasing posteromedial cortex vulnerability to amyloid-β and tau spread beyond the medial temporal lobe. Given the implications for understanding AD risk, here we sought to replicate Hodgetts et al.‘s finding in a larger sample (N = 128; 40 APOE ε4 carriers, 88 APOE ε4 non-carriers) of young adults (age range = 19–33). Extending this work, we also conducted an exploratory analysis using a more advanced measure of white matter microstructure: hindrance modulated orientational anisotropy (HMOA). Contrary to the original study, we did not observe higher FA or lower MD in the PHCB of APOE ε4 carriers relative to non-carriers. Bayes factors (BFs) further revealed moderate-to-strong evidence in support of these null findings. In addition, we observed no APOE ε4-related differences in PHCB HMOA. Our findings indicate that young adult APOE ε4 carriers and non-carriers do not differ in PHCB microstructure, casting some doubt on the notion that early-life variation in PHCB tract microstructure might enhance vulnerability to amyloid-β accumulation and/or tau spread.

According to popular belief when engaged on the smartphone surrounding information is ignored. However, emerging ideas based on laboratory-designed tasks suggest that the processing of task-irrelevant (distractor) information is enhanced when cognitive load is high as anticipated during intense periods of smartphone usage. Here we address the neural processing of task-irrelevant auditory tones while interacting with the smartphone touchscreen. We analyzed neural activity (EEG) while people (N = 24) were seated in public spaces and used their smartphones for ∼1.5 h. During this period, the number of touchscreen interactions spontaneously varied from one moment to another. The central and frontal theta-band (4–8 Hz) oscillations, an index of cognitive load, increased proportionally to the number of interactions. Moreover, an index of excitation:inhibition balance derived from the aperiodic signal components increased with the interactions. The auditory tones resulted in prominent evoked potentials with peaks at ∼50 ms, ∼100 ms, and ∼200 ms, reflecting the different cortical information processing stages. Of these, the ∼100 ms component was specifically related to the number of interactions such that the higher the number of interactions, the larger the neural signal amplitudes. Contrary to the popular notions but in keeping with emerging ideas on cognitive load, auditory information processing is enhanced with increased smartphone usage. In daily life, neural processing of the surroundings is partly shaped by the immediate cognitive demands imposed by the smartphone.

An early component of the auditory event-related potential (ERP), the mismatch negativity (MMN), has been shown to be sensitive to native phonemic sound contrasts. The potential changes to this neural sensitivity from foreign language learning have only been marginally studied. The existing research seems to suggest that the neural sensitivity as indexed by the MMN can adapt to foreign language sound contrasts with very target-specific training, but whether the effects are long-lasting or generalize to proper foreign language learning is yet to be investigated in a viable longitudinal study design. We therefore recorded electroencephalography (EEG) from two groups of language officer cadets (learning either Arabic (n = 8) or Dari (n = 12)) while they listened to speech sound contrasts from both languages. We recorded their EEG four times over the course of 19 months of intensive foreign language training (immediately before they started, after three weeks, after six months, and after 19 months).

We did not find any language-specific effects of learning on the cadets’ MMNs to the speech sound contrasts. We did, however, elicit statistically reliable MMNs to both sound contrasts for both groups at most of the four times of measurement. Furthermore, we found that the Arabic learners’ MMNs to the Arabic stimuli diminished over time, and that the Dari learners’ P3a responses to the Arabic stimuli diminished over time. Correlating the participants’ MMNs with their behavioral responses to the language stimuli did not reveal any strong links between behavior and neurophysiology. However, those Dari learners whose MMNs to the Dari stimuli increased the most within the first three weeks, also received the highest grades on a listening task after 17 weeks.

Background

Several studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived “brain age gap” has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N = 2126 controls & N = 2675 cases; +1.08 years [SE 0.22], Cohen's d = 0.14, 95% CI: 0.08–0.20), in independent cohorts that were not part of the original study.

Methods

A previously trained brain age model (www.photon-ai.com/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18–75 years) from 13 new cohorts collected from 20 different scanners. Meta-regressions were used to examine potential moderating effects of basic cohort characteristics (e.g., clinical and scan technical) on the brain age gap.

Results

Our ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R² = 0.47, MAE = 7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohen's d = 0.15, 95% CI: 0.05–0.25) compared with controls, highly similar to our previous finding. Significant moderating effects of FreeSurfer version 6.0 (d = 0.41, p = 0.007) and Philips scanner vendor (d = 0.50, p < 0.0001) were found, leading to more positive effect size estimates.

Conclusions

This study further validates our previously developed ENIGMA brain age algorithm. Importantly, we replicated the brain age gap in depression with a comparable effect size. Thus, two large-scale independent mega-analyses across in total 32 cohorts and >3400 patients and >2800 controls worldwide show reliable but subtle effects of brain aging in adult depression. Future studies are needed to identify factors that may further explain the brain age gap variance between cohorts.

Brain aging causes loss of synaptic spines, neuronal apoptosis, and a reduction in neurotransmitter levels. These aging phenomena disturb cortical electrical activity and its synchronization with connected regions. Previous electroencephalography (EEG) studies reported an age-related decrease in electrical activity in the alpha frequency band at occipital, parietal, and temporal areas as well as a decrease in occipital delta activity. However, there is an ongoing debate about whether there is an increase or decrease of the activity in other frequency bands with aging due to inconsistent study findings. In this study, we aimed to detect age-related changes of cortical electrical activities in all five frequency bands (delta, theta, alpha, beta, and gamma) in a large sample of healthy subjects for the first time. Using eLORETA (exact low-resolution brain electromagnetic tomography) analysis, we applied an eLORETA source estimation method to resting-state EEG data in 147 healthy subjects (median age 55, IQR 26.5–67.0) to obtain cortical electrical activity and assessed age-related changes in this activity using correlation analysis with multiple comparison correction. The combination of the eLORETA source estimation method and correlation analysis implemented in eLORETA software detected age-related changes in specific cortical regions for each frequency band: (1) delta and theta cortical electrical activities decreased at the occipital area with age, (2) alpha cortical electrical activity decreased at the occipitoparietotemporal areas with age, (3) beta cortical electrical activity increased at the insula, sensorimotor area, supplementary motor area, premotor area, and right temporal areas with age (most significant correlation at the right insula), (4) gamma cortical electrical activity increased at the frontoparietal and left temporal areas with age. These findings extend previous EEG study findings and provide valuable information related to mechanisms of healthy aging. Overall, our findings revealed that even healthy aging greatly affects cortical electrical activities in a region-specific way.

An important tactile function is the active detection of small-scale features, such as edges or asperities, which depends on fine hand motor control. Using a resting-state fMRI paradigm, we sought to identify the functional connectivity of the brain network engaged in mapping tactile inputs to and from regions engaged in motor preparation and planning during active touch. Human participants actively located small-scale tactile features that were rendered by a computer-controlled tactile display. To induce rapid perceptual learning, the contrast between the target and the surround was reduced whenever a criterion level of success was achieved, thereby raising the task difficulty. Multiple cortical and subcortical neural connections within a parietal-cerebellar-frontal network were identified by correlating behavioral performance with changes in functional connectivity. These cortical areas reflected perceptual, cognitive, and attention-based processes required to detect and use small-scale tactile features for hand dexterity.

Previous studies have evidenced how the local prediction of physical stimulus features may affect the neural processing of incoming stimuli. Less known are the effects of cognitive priors on predictive processes, and how the brain computes local versus cognitive predictions and their errors. Here, we determined the differential brain mechanisms underlying prediction errors related to high-level, cognitive priors for melody (rhythm, contour) versus low-level, local acoustic priors (tuning, timbre). We measured with magnetoencephalography the mismatch negativity (MMN) prediction error signal in 104 adults having varying levels of musical expertise. We discovered that the brain regions involved in early predictive processes for local priors were primary and secondary auditory cortex and insula, whereas cognitive brain regions such as cingulate and orbitofrontal cortices were recruited for early melodic errors in cognitive priors. The involvement of higher-level brain regions for computing early cognitive errors was enhanced in musicians, especially in cingulate cortex, inferior frontal gyrus, and supplementary motor area. Overall, the findings expand knowledge on whole-brain mechanisms of predictive processing and the related MMN generators, previously mainly confined to the auditory cortex, to a frontal network that strictly depends on the type of priors that are to be computed by the brain.

Common research practices in neuroimaging studies using functional magnetic resonance imaging may produce outcomes that are difficult to replicate. Results that cannot be replicated have contributed to a replication crisis in psychology, neuroscience, and other disciplines over the years. Here we replicate two previous papers in which the authors present two analysis paths for a dataset in which participants underwent fMRI while performing a recognition memory test for old and new words. Both studies found activation in the medial temporal lobe including the hippocampus, with the first demonstrating a distinction in activation corresponding to true and perceived oldness of stimuli and the second demonstrating that activation reflects the subjective experience of the participant. We replicated the behavioral and MRI acquisition parameters reported in the two target articles (Daselaar et al., 2006; Daselaar et al., 2006) with N = 53 participants. We focused fMRI analyses on regions of interest reported in the target articles examining fMRI activation for differences corresponding with true and perceived oldness and those associated with the subjective memory experiences of recollection, familiarity, and novelty. Comparisons between true and perceived oldness revealed main effects not only for true, but also perceived oldness along with a significant interaction. We replicate the findings of recollection and familiarity signals in the hippocampus and medial temporal lobe cortex, respectively, but failed to replicate a novelty signal in the anterior medial temporal lobe. These results remained when we analyzed only correct trials, indicating that the effects were not due to selectively averaging correct and incorrect trials. Taken together, our findings demonstrate that activation in the hippocampus corresponds to the subjective experience associated with correct recognition memory retrieval.

In the past years, no event has affected people around the globe more than the SARS-COVID-2 pandemic. Besides the health system and the economy, it has affected social life. A grave sequela is the social distancing due to the ubiquitous use of medical face masks. Since these face masks cover approximately two thirds of the face including the mouth and nose, we hypothesized that they may impair affect reading of emotional face expressions. We used functional magnetic resonance imaging in 16 healthy volunteers to investigate brain activity changes related to the recognition of evolving emotional face expressions in short video-clips. We found that the face masks delayed emotion recognition, but at a normal nearly 100% success rate. This effect was related to a decreased activation in the cortical network mediating face recognition. Our data support the notion that face masks can have an adverse impact of social interactions.

Background

Normal aging is known to include declines in several cognitive domains, with parallel grey matter atrophy. However, there are inconsistencies in the largely cross-sectional literature as to which regions of grey matter show change over time, with some investigations reporting whole brain and others reporting more focal regions of atrophy. More longitudinal analyses are needed to better understand the neurostructural and functional changes that occur gradually in older adulthood.

Objective

The aim of the current study was to investigate changes in cognitive performance and grey matter atrophy in a sample of healthy older adults over four years.

Methods

MRI and cognitive data were retrieved from the Alzheimer's Disease Neuroimaging Initiative database for 35 participants in the cognitively normal cohort at two time points separated by four years (mean age at baseline = 75.02, SD = 6.51, 54% female). Grey matter structure was assessed via voxel-based morphometry and cognition was measured across four domains (memory, executive function, language and visuospatial skills).

Results

Results indicated widespread grey matter atrophy, including frontal, temporal, and subcortical regions. Cognitive performance was largely stable, with the exception of executive function, which showed significant decline over time.

Conclusion

Findings indicate that cognitive abilities are largely preserved over a four year period, even when grey matter atrophy is present in the aging brain.