Stability of Satellite Planes in M31 II: Effects of the Dark Subhalo Population

The planar arrangement of nearly half the satellite galaxies of M31 has been a source of mystery and speculation since it was discovered. With a growing number of other host galaxies showing these satellite galaxy planes, their stability and longevity have become central to the debate on whether the presence of satellite planes are a natural consequence of prevailing cosmological models, or represent a challenge. Given the dependence of their stability on host halo shape, we look into how a galaxy plane's dark matter environment influences its longevity. An increased number of dark matter subhalos results in increased interactions that hasten the deterioration of an already-formed plane of satellite galaxies in spherical dark halos. The role of total dark matter mass fraction held in subhalos in dispersing a plane of galaxies present non trivial effects on plane longevity as well. But any misalignments of plane inclines to major axes of flattened dark matter halos lead to their lifetimes being reduced to < 3 Gyrs. Distributing > 40% of total dark mass in subhalos in the overall dark matter distribution results in a plane of satellite galaxies that is prone to change through the 5 Gyr integration time period.Comment: 11 pages, 9 figures, accepted to MNRAS September 22 201

Table_1_The Impact of Caregiving on the Association Between Infant Emotional Behavior and Resting State Neural Network Functional Topology.docx

The extent to which neural networks underlying emotional behavior in infancy serve as precursors of later behavioral and emotional problems is unclear. Even less is known about caregiving influences on these early brain-behavior relationships. To study brain-emotional behavior relationships in infants, we examined resting-state functional network metrics and infant emotional behavior in the context of early maternal caregiving. We assessed 46 3-month-old infants and their mothers from a community sample. Infants underwent functional MRI during sleep. Resting-state data were processed using graph theory techniques to examine specific nodal metrics as indicators of network functionality. Infant positive and negative emotional behaviors, and positive, negative and mental-state talk (MST) indices of maternal caregiving were coded independently from filmed interactions. Regression analyses tested associations among nodal metrics and infant emotionality, and the moderating effects of maternal behavior on these relationships. All results were FDR corrected at alpha = 0.05. While relationships between infant emotional behavior or maternal caregiving, and nodal metrics were weak, higher levels of maternal MST strengthened associations between infant positive emotionality and nodal metrics within prefrontal (p < 0.0001), and occipital (p < 0.0001) cortices more generally. Positive and negative aspects of maternal caregiving had little effect. Our findings suggest that maternal MST may play an important role in strengthening links between emotion regulation neural circuitry and early infant positive behavior. They also provide objective neural markers that could inform and monitor caregiving-based interventions designed to improve the health and well-being of vulnerable infants at-risk for behavioral and emotional problems.</p

Illustration of a pattern regression model with hypothetical 2D data.

<p>The numbers in the squares correspond to activation levels in different brain voxels. Each brain scan corresponds to a point in a 2D voxel space. The goal is to “train” a predictive function that given a new brain scan can accurately decode the correspondent clinical score.</p

Maps for decoding PGBI-10M at screen based on patterns of activation to win blocks using a leave-one-out cross-validation framework.

<p>A: Voxel-based predictive pattern. The colour bar indicates the weight of the voxels for decoding the clinical score. B: Region-based pattern localization map computed from the voxel based predictive pattern displayed in Fig 2A. The colour bar indicates the percentage of the total normalized weights that each anatomically labelled region explains.</p