Perspective-taking is associated with increased discriminability of affective states in the ventromedial prefrontal cortex.

Recent work using multivariate-pattern analysis (MVPA) on functional magnetic resonance imaging (fMRI) data has found that distinct affective states produce correspondingly distinct patterns of neural activity in the cerebral cortex. However, it is unclear whether individual differences in the distinctiveness of neural patterns evoked by affective stimuli underlie empathic abilities such as perspective-taking (PT). Accordingly, we examined whether we could predict PT tendency from the classification of blood-oxygen-level-dependent (BOLD) fMRI activation patterns while participants (n = 57) imagined themselves in affectively charged scenarios. We used an MVPA searchlight analysis to map where in the brain activity patterns permitted the classification of four affective states: happiness, sadness, fear and disgust. Classification accuracy was significantly above chance levels in most of the prefrontal cortex and in the posterior medial cortices. Furthermore, participants' self-reported PT was positively associated with classification accuracy in the ventromedial prefrontal cortex and insula. This finding has implications for understanding affective processing in the prefrontal cortex and for interpreting the cognitive significance of classifiable affective brain states. Our multivariate approach suggests that PT ability may rely on the grain of internally simulated affective representations rather than simply the global strength.

Laterality of Poststroke Cortical Motor Activity during Action Observation Is Related to Hemispheric Dominance.

Background: Increased activity in the lesioned hemisphere has been related to improved poststroke motor recovery. However, the role of the dominant hemisphere-and its relationship to activity in the lesioned hemisphere-has not been widely explored. Objective: Here, we examined whether the dominant hemisphere drives the lateralization of brain activity after stroke and whether this changes based on if the lesioned hemisphere is the dominant hemisphere or not. Methods: We used fMRI to compare cortical motor activity in the action observation network (AON), motor-related regions that are active both during the observation and execution of an action, in 36 left hemisphere dominant individuals. Twelve individuals had nondominant, right hemisphere stroke, twelve had dominant, left-hemisphere stroke, and twelve were healthy age-matched controls. We previously found that individuals with left dominant stroke show greater ipsilesional activity during action observation. Here, we examined if individuals with nondominant, right hemisphere stroke also showed greater lateralized activity in the ipsilesional, right hemisphere or in the dominant, left hemisphere and compared these results with those of individuals with dominant, left hemisphere stroke. Results: We found that individuals with right hemisphere stroke showed greater activity in the dominant, left hemisphere, rather than the ipsilesional, right hemisphere. This left-lateralized pattern matched that of individuals with left, dominant hemisphere stroke, and both stroke groups differed from the age-matched control group. Conclusions: These findings suggest that action observation is lateralized to the dominant, rather than ipsilesional, hemisphere, which may reflect an interaction between the lesioned hemisphere and the dominant hemisphere in driving lateralization of brain activity after stroke. Hemispheric dominance and laterality should be carefully considered when characterizing poststroke neural activity.

A large, open source dataset of stroke anatomical brain images and manual lesion segmentations.

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e.g., measures of brain structure) of long-term stroke recovery following rehabilitation. However, analyzing large rehabilitation-related datasets is problematic due to barriers in accurate stroke lesion segmentation. Manually-traced lesions are currently the gold standard for lesion segmentation on T1-weighted MRIs, but are labor intensive and require anatomical expertise. While algorithms have been developed to automate this process, the results often lack accuracy. Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation methods. We hope ATLAS release 1.1 will be a useful resource to assess and improve the accuracy of current lesion segmentation methods.

Increased iron levels and decreased tissue integrity in hippocampus of Alzheimer's disease detected in vivo with magnetic resonance imaging.

BACKGROUND: Iron can catalyze damaging free radical reactions. With age, iron accumulates in brain gray matter regions and may contribute to the risk of developing age-related diseases such as Alzheimer's disease (AD). Prior MRI studies demonstrated increased iron deposits in basal ganglia regions; however, the hippocampus (Hipp), which is heavily damaged in AD, and comparator regions that are resistant to AD damage, such as thalamus (Th), have rarely been examined. OBJECTIVE: To assess iron levels and evidence of tissue damage in Hipp and Th of AD subjects and healthy controls. METHODS: Thirty-one AD and sixty-eight healthy control subjects participated in this study. High- and low-field strength MRI instruments were used in combination to quantify iron content of ferritin molecules (ferritin iron) using the field dependent relaxation rate increase (FDRI) method. Decreased transverse relaxation rate (R2) was used as an index of tissue damage. RESULTS: Compared with healthy controls, AD subjects had increased ferritin iron in Hipp (p = 0.019) but not Th (p = 0.637), and significantly decreased R2 in Hipp (p < 0.001) but not Th (p = 0.37). In the entire sample, FDRI and R2 were negatively correlated. CONCLUSION: The data shows that in AD, Hipp damage occurs in conjunction with ferritin iron accumulation. Prospective studies are needed to evaluate how increasing iron levels may influence the trajectory of tissue damage and cognitive and pathologic manifestations of AD.

Multimodal magnetic resonance imaging assessment of white matter aging trajectories over the lifespan of healthy individuals.

BACKGROUND: Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers. METHODS: Healthy subjects (n = 171) 14-93 years of age were examined with transverse relaxation rate (R(2)) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively). RESULTS: Only R(2) reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R(2) < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R(2) and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor. CONCLUSIONS: The R(2) and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend.