Neuroimage. Reports最新文献

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.

Empathy, which is important for social functioning and mental health, is recognized to have both cognitive and affective components. While several studies have demonstrated unique neural underpinnings of empathy components in adults, few have investigated this in young people. Investigating associations between empathy and brain functional connectivity during childhood is beneficial to begin to build a comprehensive picture of the neural correlates of empathy across the lifespan. One hundred and twelve children (52% female, mean age 10 years) underwent magnetic resonance imaging brain scans including a resting-state sequence and completed empathy self-report measures. Seed-to-whole-brain resting-state functional connectivity analyses demonstrated that higher affective empathy (affective sharing and empathic distress) was associated with weaker connectivity between key hubs of the default mode network (DMN) and other widespread areas in the brain. Analyses of resting-state networks demonstrated that higher cognitive empathy was associated with both stronger and weaker connectivity between dorsal and lateral regions of the DMN and regions outside of the DMN, including the pre- and postcentral gyrus, and the cerebellum. Higher affective sharing was associated with greater connectivity between the anterior salience network and the pre- and postcentral gyrus. However, these associations did not withstand correction for multiple models. While interpretations should be made cautiously, findings suggest wide-ranging and diffuse connectivity patterns may be related to several components of empathy in children. These findings could indicate a more complex picture of the neural correlates of empathy processes in childhood, with less specialization and more widespread involvement of regions and networks. Future studies should attempt to replicate these findings using different measurement approaches.

Background

Neurometabolic abnormalities and amyloid-beta plaque deposition are important early pathophysiologic changes in Alzheimer's disease (AD). This study investigated the relationship between high-energy phosphorus-containing metabolites, glucose uptake, and amyloid plaque using phosphorus magnetic resonance spectroscopy (³¹P-MRS) and positron emission tomography (PET).

Methods

We measured ³¹P-MRS, fluorodeoxyglucose (FDG)-PET, and Pittsburgh Compound B (PiB)-PET in a cohort of 20 cognitively normal middle-aged adults at risk for AD. We assessed ³¹P-MRS reliability by scanning a separate cohort of 13 healthy volunteers twice each. We calculated the coefficient-of-variation (CV) of metabolite ratios phosphocreatine-to-adenosine triphosphate (PCr/α-ATP), inorganic phosphate (Pi)-to-α-ATP, and phosphomonoesters-to-phosphodiesters (PME/PDE), and pH in pre-defined brain regions. We performed linear regression analysis to determine the relationship between ³¹P measurements and tracer uptake, and Dunn's multiple comparison tests to investigate regional differences in phosphorus metabolism. Finally, we performed linear regression analysis on ³¹P-MRS measurements in both cohorts to investigate the relationship of phosphorus metabolism with age.

Results

Most regional ³¹P metabolite ratio and pH inter- and intra-day CVs were well below 10%. There was an inverse relationship between FDG-SUV levels and metabolite ratios PCr/α-ATP, Pi/α-ATP, and PME/PDE in several brain regions in the AD risk group. There were also several regional differences among ³¹P metabolites and pH in the AD risk group including elevated PCr/α-ATP, depressed PME/PDE, and elevated pH in the temporal cortices. Increased PCr/α-ATP throughout the brain was associated with aging.

Conclusions

Phosphorus spectroscopy in the brain can be performed with high repeatability. Phosphorus metabolism varies with region and age, and is related to glucose uptake in adults at risk for AD. Phosphorus spectroscopy may be a valuable approach to study early changes in brain energetics in high-risk populations.

A reproducibility crisis has been reported across many research fields, including neuroimaging, reaching up to 70% of studies. Neuroimaging data, such as magnetic resonance imaging (MRI), requires pre-processing to allow for inter-subject comparison, increase signal contrast and noise reduction. As manual MRI pre-processing is time consuming and requires expertise, multiple automatic pre-processing frameworks have been proposed. However, neuroimaging studies often report divergent results, even for similar populations, thus it is important to determine whether this occurs as a result of different processing tools. Two of the most used tools are FreeSurfer and the Computational Anatomy Toolbox (CAT12). In this study we assessed the reproducibility between these two automatic pre-processing frameworks for structural MRI and test-retest reliability within framework on estimation of cortical thickness. Our results show that the reproducibility between the frameworks is lower at the region-of-interest (ROI) level than at individual level. Furthermore, we found that the reproducibility was lower in paediatric samples than in adults. Finally, an acquisition site effect was also identified. Given the widespread use of these frameworks in basic and clinical neuroscience, the results of multicentric cross-sectional studies must be interpreted with caution, particularly with paediatric samples. The observed reproducibility issue might be one of the sources of discrepancies reported in neuroimaging studies. On a positive note, framework test-retest reliability within subject is high, suggesting that inconsistency of results may be less concerning in longitudinal studies. The code is available at: https://cibit-uc.github.io/fs-cat12-cortical-thickness-reproducibility.

Human decision making can be influenced by presenting different options with positive or negative connotations. This phenomenon is termed the framing effect. Neuroeconomic studies have found that the amygdala plays a significant role in the framing effect, as it incorporates emotional (or intuitive) information into the decision process, which may lead to bias or irrationality. However, previous studies have focused only on the gain domain, in which the initial state is positive (appetitive). The mechanisms underlying the framing effect in the loss (aversive) domain are less well understood, despite their importance for evolution and survival. In this study, we first replicated the findings of De Martino et al. on the framing effect in the gain domain. We then searched for similarities and differences between the gain and loss domains using a similar experimental design combined with functional magnetic resonance imaging. Behaviorally, the participants showed comparable effects for both frame types, suggesting a frame-indiscriminate decision bias. In contrast, at the neuronal level, we found that the amygdala specifically represented the framing effect in the gain domain, and its connectivity to the ventromedial prefrontal cortex was positively modulated by the framing bias, similar to the findings of De Martino et al. However, the striatum was found to represent the framing effect in the loss domain. Striatal connectivity to the dorsomedial prefrontal cortex was similarly affected by the framing bias, suggesting domain-specific neural substrates. Our study emphasizes the importance of distinguishing between gain and loss domains when studying decision making, and highlights the governing role of the cortical–striatal–limbic network in the framing effect.