Sound-modulations of visual motion perception implicate the cortico-vestibular brain.

A widely used example of the intricate (yet poorly understood) intertwining of multisensory signals in the brain is the audiovisual bounce inducing effect (ABE). This effect presents two identical objects moving along the azimuth with uniform motion and towards opposite directions. The perceptual interpretation of the motion is ambiguous and is modulated if a transient (sound) is presented in coincidence with the point of overlap of the two objects' motion trajectories. This phenomenon has long been written-off to simple attentional or decision-making mechanisms, although the neurological underpinnings for the effect are not well understood. Using behavioural metrics concurrently with event-related fMRI, we show that sound-induced modulations of motion perception can be further modulated by changing motion dynamics of the visual targets. The phenomenon engages the posterior parietal cortex and the parieto-insular-vestibular cortical complex, with a close correspondence of activity in these regions with behaviour. These findings suggest that the insular cortex is engaged in deriving a probabilistic perceptual solution through the integration of multisensory data.

Prospective motion correction of fMRI: Improving the quality of resting state data affected by large head motion.

The quality of functional MRI (fMRI) data is affected by head motion. It has been shown that fMRI data quality can be improved by prospectively updating the gradients and radio-frequency pulses in response to head motion during image acquisition by using an MR-compatible optical tracking system (prospective motion correction, or PMC). Recent studies showed that PMC improves the temporal Signal to Noise Ratio (tSNR) of resting state fMRI data (rs-fMRI) acquired from subjects not moving intentionally. Besides that, the time courses of Independent Components (ICs), resulting from Independent Component Analysis (ICA), were found to present significant temporal correlation with the motion parameters recorded by the camera. However, the benefits of applying PMC for improving the quality of rs-fMRI acquired under large head movements and its effects on resting state networks (RSN) and connectivity matrices are still unknown. In this study, subjects were instructed to cross their legs at will while rs-fMRI data with and without PMC were acquired, which generated head motion velocities ranging from 4 to 30 â€‹mm/s. We also acquired fMRI data without intentional motion. Independent component analysis of rs-fMRI was performed to evaluate IC maps and time courses of RSNs. We also calculated the temporal correlation among different brain regions and generated connectivity matrices for the different motion and PMC conditions. In our results we verified that the crossing leg movements reduced the tSNR of sessions without and with PMC by 45 and 20%, respectively, when compared to sessions without intentional movements. We have verified an interaction between head motion speed and PMC status, showing stronger attenuation of tSNR for acquisitions without PMC than for those with PMC. Additionally, the spatial definition of major RSNs, such as default mode, visual, left and right central executive networks, was improved when PMC was enabled. Furthermore, motion altered IC-time courses by decreasing power at low frequencies and increasing power at higher frequencies (typically associated with artefacts). PMC partially reversed these alterations of the power spectra. Finally, we showed that PMC provides temporal correlation matrices for data acquired under motion conditions more comparable to those obtained by fMRI sessions where subjects were instructed not to move.

Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks.

PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image analysis because of its powerful potential. In this paper, we developed a method for classifying subtypes of lung adenocarcinoma from pathological images using neural network whose that can evaluate phenotypic features from wider area to consider cellular distributions. METHODS: In order to recognize the types of tumors, we need not only to detail features of cells, but also to incorporate statistical distribution of the different types of cells. Variants of autoencoders as building blocks of pre-trained convolutional layers of neural networks are implemented. A sparse deep autoencoder which minimizes local information entropy on the encoding layer is then proposed and applied to images of size [Formula: see text]. We applied this model for feature extraction from pathological images of lung adenocarcinoma, which is comprised of three transcriptome subtypes previously defined by the Cancer Genome Atlas network. Since the tumor tissue is composed of heterogeneous cell populations, recognition of tumor transcriptome subtypes requires more information than local pattern of cells. The parameters extracted using this approach will then be used in multiple reduction stages to perform classification on larger images. RESULTS: We were able to demonstrate that these networks successfully recognize morphological features of lung adenocarcinoma. We also performed classification and reconstruction experiments to compare the outputs of the variants. The results showed that the larger input image that covers a certain area of the tissue is required to recognize transcriptome subtypes. The sparse autoencoder network with [Formula: see text] input provides a 98.9% classification accuracy. CONCLUSION: This study shows the potential of autoencoders as a feature extraction paradigm and paves the way for a whole slide image analysis tool to predict molecular subtypes of tumors from pathological features.

Iterative projection onto convex sets for quantitative susceptibility mapping.

PURPOSE: Quantitative susceptibility map (QSM) reconstruction is ill posed due to the zero values on the "magic angle cone" that make the maps prone to streaking artifacts. We propose projection onto convex sets (POCS) in the method of steepest descent (SD) for QSM reconstruction. METHODS: Two convex projections, an object-support projection in the image domain and a projection in k-space were used. QSM reconstruction using the proposed SD-POCS method was compared with SD and POCS alone as well as with truncated k-space division (TKD) for numerically simulated and 7 Tesla (T) human brain phase data. RESULTS: The QSM reconstruction error from noise-free simulated phase data using SD-POCS is at least two orders of magnitude lower than using SD, POCS, or TKD and has reduced streaking artifacts. Using the l1 -TV reconstructed susceptibility as a gold standard for 7T in vivo imaging, SD-POCS showed better image quality comparing to SD, POCS, or TKD from visual inspection. CONCLUSION: POCS is an alternative method for regularization that can be used in an iterative minimization method such as SD for QSM reconstruction.

Mechanism of liponecrosis, a distinct mode of programmed cell death.

An exposure of the yeast Saccharomyces cerevisiae to exogenous palmitoleic acid (POA) elicits "liponecrosis," a mode of programmed cell death (PCD) which differs from the currently known PCD subroutines. Here, we report the following mechanism for liponecrotic PCD. Exogenously added POA is incorporated into POA-containing phospholipids that then amass in the endoplasmic reticulum membrane, mitochondrial membranes and the plasma membrane. The buildup of the POA-containing phospholipids in the plasma membrane reduces the level of phosphatidylethanolamine in its extracellular leaflet, thereby increasing plasma membrane permeability for small molecules and committing yeast to liponecrotic PCD. The excessive accumulation of POA-containing phospholipids in mitochondrial membranes impairs mitochondrial functionality and causes the excessive production of reactive oxygen species in mitochondria. The resulting rise in cellular reactive oxygen species above a critical level contributes to the commitment of yeast to liponecrotic PCD by: (1) oxidatively damaging numerous cellular organelles, thereby triggering their massive macroautophagic degradation; and (2) oxidatively damaging various cellular proteins, thus impairing cellular proteostasis. Several cellular processes in yeast exposed to POA can protect cells from liponecrosis. They include: (1) POA oxidation in peroxisomes, which reduces the flow of POA into phospholipid synthesis pathways; (2) POA incorporation into neutral lipids, which prevents the excessive accumulation of POA-containing phospholipids in cellular membranes; (3) mitophagy, a selective macroautophagic degradation of dysfunctional mitochondria, which sustains a population of functional mitochondria needed for POA incorporation into neutral lipids; and (4) a degradation of damaged, dysfunctional and aggregated cytosolic proteins, which enables the maintenance of cellular proteostasis.

Resting state synchrony in long-term abstinent alcoholics with versus without comorbid drug dependence.

BACKGROUND: We previously reported that when long-term abstinent alcoholics (LTAA; with no drug comorbidity) are compared to controls, they show increased resting state synchrony (RSS) in the executive control network and reduced RSS in the appetitive drive network suggestive of compensatory mechanisms that may facilitate abstinence. The aim of the present study was to investigate whether long-term abstinent alcoholics with comorbid stimulants dependence (LTAAS) show similar RSS mechanisms. METHODS: Resting-state functional MRI data were collected on 36 LTAAS (20 females, age: 47.85±7.30), 23 LTAA (8 females, age: M=47.91±6.76), and 23 non-substance abusing controls (NSAC; 8 females, age: M=47.99±6.70). Using seed-based measures, we examined RSS with the nucleus accumbens (NAcc) and the subgenual anterior cingulate cortex (sgACC). RESULTS: Results showed commonalities in LTAA and LTAAS RSS (similar enhanced executive control RSS and left insula RSS) as well as differences (no attenuation of appetitive drive RSS in LTAAS and no enhancement of RSS in right insula in LTAA). CONCLUSIONS: We believe these differences are adaptive mechanisms that support abstinence. These findings suggest common as well as specific targets for treatment in chronic alcoholics with vs without comorbid stimulant dependence.

Resting-state synchrony in short-term versus long-term abstinent alcoholics.

BACKGROUND: We previously reported that when compared with controls, long-term abstinent alcoholics (LTAA) have increased resting-state synchrony (RSS) of the inhibitory control network and reduced synchrony of the appetitive drive network, and hypothesized that these levels of synchrony are adaptive and support the behavioral changes required to maintain abstinence. In this study, we investigate whether these RSS patterns can be identified in short-term abstinent alcoholics (STAA). METHODS: Resting-state functional magnetic resonance imaging data were collected from 27 STAA, 23 LTAA, and 23 nonsubstance abusing controls (NSAC). We examined baseline RSS using seed-based measures. RESULTS: We found ordered RSS effects from NSAC to STAA and then to LTAA within both the appetitive drive and executive control networks: increasing RSS of the executive control network and decreasing RSS of the reward processing network. Finally, we found significant correlations between strength of RSS in these networks and (i) cognitive flexibility, and (ii) current antisocial behavior. CONCLUSIONS: Findings are consistent with an adaptive progression of RSS from short- to long-term abstinence, so that, compared with normal controls, the synchrony (i) within the reward network progressively decreases, and (ii) within the executive control network progressively increases.