Journal: Scientific Reports

Article Title: How deeply does your mutant sleep? Probing arousal to better understand sleep defects in Drosophila

doi: 10.1038/srep08454

Figure Lengend Snippet: (a). Opposing effects of fumin and dumb 2 on dopamine (DA) function and sleep. Released DA impacts DA1 receptors to initiate cAMP signaling pathways (left black arrow) before being recycled back into the cell (red arrow). fumin is mutant for the DA transporter, leading to increased DA levels in the synapse, and consequently increases cAMP signaling in post-synaptic neurons (right thick black arrow). dumb 2 is mutant for the DA1 receptor, leading to decreased cAMP signaling (dashed black arrow). (b). Classical beam-crossing sleep profiles (min sleep/hour (±SEM)) based on a 5 min inactivity criterion, for the w 2202 background strain (blue), fumin (red), dumb 2 (green), and the double mutant fumin ; dumb 2 (black). N = 68 for w 2202 ; N = 67 for fumin ; N = 62 for dumb 2 ; N = 66 for fumin ; dumb 2 . The w 2202 profile is shown in grey for comparison in the three mutant panels. (c). Sleep intensity profiles (% reactive ± SEM) for the same four strains as in b. (d). Multidimensional scaling (MDS) was used to project the data into a two-dimensional space for easier visualization of the multidimensional relationships between different strains. MDS analyses were performed for fumin ; dumb 2 (blue border) compared to its genetic background strain, w 2202 (black border), for daytime (yellow) and nighttime (grey) metrics. Left panel: four beam-crossing metrics (as for b) were used in combination for MDS comparing both strains. The different metrics used are indicated in the green box (bottom of the panel). The daytime effects overlap while the nighttime effects are distinct. Right panel: four arousal-based metrics were combined with four beam-crossing sleep metrics (indicated by the larger magenta box) for MDS analyses, resulting in a complete separation between day and night effects in both strains. a.u., arbitrary units.

Article Snippet: The MDS algorithms used within DART are Classical MDS (using the Matlab function cmdscale ) and Non-Classical Metric/Non-Metric MDS (using the Matlab function mdscale ).

Techniques: Protein-Protein interactions, Mutagenesis, Comparison

Journal: Developmental Cognitive Neuroscience

Article Title: Identifying reproducible individual differences in childhood functional brain networks: An ABCD study

doi: 10.1016/j.dcn.2019.100706

Figure Lengend Snippet: Scanner manufacturer effects. (A) RSFC similarity across individuals, sorted by scanner manufacturer (Siemens, Philips, GE). Each cell represents the whole brain correlation (similarity) between a pair of participants. Siemens scanners demonstrated higher similarity across participants than Philips or GE scanners. (B) MDS plots. Within these plots, each data point represents the mean across participants in multidimensional space, colored by the scanner manufacturer. Circles around the data points represent the 2-dimensional standard error of the mean. RSFC obtained with GE/Philips scanners are clearly dissociable from RSFC obtained with Siemens scanners (C) Correlations between RSFC and scanner manufacturer. Strong positive and negative correlations between the visual network and several other networks. (D) RSFC/scanner correlations demonstrate distance dependence, such that short-range ROI correlations, especially within the visual network, are weaker in GE/Philips scanners compared to Siemens, whereas long distance correlations are stronger in GE/Philips scanners compared to Siemens.

Article Snippet: RSFC matrices from each participant were entered into an MDS algorithm (implemented using Matlab 2018b, cmdscale.m ) and grouped by scanner, site, and sex, separately.

Techniques:

Journal: NeuroImage

Article Title: Clarifying the role of higher-level cortices in resolving perceptual ambiguity using Ultra High Field fMRI

doi: 10.1016/j.neuroimage.2020.117654

Figure Lengend Snippet: Dynamic Reconfiguration of Face Network as a function of Task Top Row: Connectivity Matrices for Stimulus Relevant Face Detection Task (Left) and Stimulus Irrelevant Fixation Task (Right). Asterisks indicate correlation coefficients that significantly (p<0.05) difference between tasks and are identical between matrices for visualization purposes. Bottom Row. Classic Multidimensional Scaling for connectivity matrices highlights the higher proximity of the rAIT to the core face areas as a function of increased connectivity during face detection relative to the fixation task. ROIs in grey text indicate those regions with no significant connectivity modulations across tasks.

Article Snippet: For display purposes only, after computing the mean between the Fisher z-normalized connectivity matrices, we computed the inverse of such transformation on the group average connectivity matrices to convert these scores back into meaningful and interpretable Pearson’s r. To better visualize the results of our functional connectivity analysis, we further performed classic multidimensional scaling (MDS - using the function “cmdscale” in MATLAB) on the participants average dissimilarity matrix (i.e. 1- Pearson’s r).

Techniques: