3D Contrast Image Reconstruction From Human Brain Activity.

Several studies demonstrated that functional magnetic resonance imaging (fMRI) signals in early visual cortex can be used to reconstruct 2-dimensional (2D) visual contents. However, it remains unknown how to reconstruct 3-dimensional (3D) visual stimuli from fMRI signals in visual cortex. 3D visual stimuli contain 2D visual features and depth information. Moreover, binocular disparity is an important cue for depth perception. Thus, it is more challenging to reconstruct 3D visual stimuli than 2D visual stimuli from the fMRI signals of visual cortex. This study aimed to reconstruct 3D visual images by constructing three decoding models: contrast-decoding, disparity-decoding and contrast-disparity-decoding models, and testing these models with fMRI data from humans viewing 3D contrast images. The results revealed that the 3D contrast stimuli can be reconstructed from the visual cortex. And the early visual regions (V1, V2) showed predominant advantages in reconstructing the contrast in 3D images for the contrast-decoding model. The dorsal visual regions (V3A, V7 and MT) showed predominant advantages in decoding the disparity in 3D images for the disparity-decoding model. The combination of the early and dorsal visual regions showed predominant advantages in decoding both the contrast and disparity for the contrast-disparity-decoding model. The results suggested that the contrast and disparity in 3D images were mainly represented in the early and dorsal visual regions separately. The two visual systems may interact with each other to decode 3D-contrast images.

Prognostic Significance of 18F-FDG PET/CT Metabolic Parameters and Tumor Galectin-1 Expression in Patients With Surgically Resected Lung Adenocarcinoma.

PURPOSE: To study the prognostic significance of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) metabolic parameters and tumor galectin-1 (Gal-1) expression in patients surgically treated for lung adenocarcinoma. PATIENTS AND METHODS: The medical records of 96 patients with primary lung adenocarcinoma who underwent surgery after 18F-FDG PET/CT were retrospectively reviewed. The maximal standardized uptake value (SUVmax), metabolic tumor volume, and total lesion glycolysis of the primary tumor were measured through PET/CT imaging. The expression of tumor Gal-1, glucose transporter 1 (GLUT-1), and hexokinase II (HK-II) were examined through immunohistochemistry. RESULTS: There were significant positive correlations between tumor Gal-1 and SUVmax, tumor Gal-1 and metabolic tumor volume, tumor Gal-1 and total lesion glycolysis, tumor Gal-1 and GLUT-1 expression, tumor Gal-1 and HK-II expression, and SUVmax and tumor GLUT-1 and HK-II expression (P < .0001 in all cases). SUVmax was the only independent predictor of tumor Gal-1 expression. On receiver operating characteristic analysis, the optimal cutoff value of SUVmax for predicting tumor Gal-1 expression was 5.1. Progression-free and overall survival were significantly shorter in patients with Gal-1-positive tumors than in those with Gal-1-negative tumors (P ≤ .001). On multivariate analysis, advanced tumor stage (P = .001) and tumor Gal-1 expression (P < .0001) were independent prognostic indicators of poor progression-free survival, while advanced tumor stage (P < .0001) and SUVmax (P = .024) were independent prognostic indicators of poor overall survival. CONCLUSION: 18F-FDG PET/CT has the potential to be used as a noninvasive imaging modality to assess tumor Gal-1 status and prognosis in lung adenocarcinoma.

Disparity level identification using the voxel-wise Gabor model of fMRI data.

Perceiving disparities is the intuitive basis for our understanding of the physical world. Although many electrophysiology studies have revealed the disparity-tuning characteristics of the neurons in the visual areas of the macaque brain, neuron population responses to disparity processing have seldom been investigated. Many disparity studies using functional magnetic resonance imaging (fMRI) have revealed the disparity-selective visual areas in the human brain. However, it is unclear how to characterize neuron population disparity-tuning responses using fMRI technique. In the present study, we constructed three voxel-wise encoding Gabor models to predict the voxel responses to novel disparity levels and used a decoding method to identify the new disparity levels from population responses in the cortex. Among the three encoding models, the fine-coarse model (FCM) that used fine/coarse disparities to fit the voxel responses to disparities outperformed the single model and uncrossed-crossed model. Moreover, the FCM demonstrated high accuracy in predicting voxel responses in V3A complex and high accuracy in identifying novel disparities from responses in V3A complex. Our results suggest that the FCM can better characterize the voxel responses to disparities than the other two models and V3A complex is a critical visual area for representing disparity information.

The dynamic characteristics of the anterior cingulate cortex in resting-state fMRI of patients with depression.

BACKGROUND: The anterior cingulate cortex (ACC) is part of the limbic system of the brain. It is a bridge between attentional and emotional processing, which is responsible for the integration of visceral, attentional, and affective information. Lesioning of the ACC, which produces striking changes, is used to treat major depression disorder (MDD). Moreover, the brain dynamically integrates and coordinates functions of its different subparts to realize its cognitive capability. Hence, the spatio-temporal community distribution of the ACC is necessary to completely understand MDD. METHODS: First, community structure detection was used to reveal the community distribution of brain regions. Thereafter, the flexibility, i.e., the frequency of community assignment changes of the ACC in such a community, and the module allegiance matrix (MAM) between the ACC and other brain regions, were analyzed. RESULTS: Our analysis demonstrated significant differences in the distribution of community assignment and flexibility of the ACC in MDD, compared to healthy controls (HC). The results also showed that the pairwise values of the MAMs between the ACC and the amygdala, insula, precuneus, and thalamus were significantly lower in patients with MDD compared to those in HC. LIMITATIONS: The data collected is subject to patient-specific noise because (1) the medication effect varies from patient to patient, and (2) with most fMRI studies, the thoughts of the participants during imaging are difficult to control. CONCLUSION: ACC exhibits abnormal flexibility in community structures in MDD. The pairwise abnormal entries in the MAM for the ACC with four other brain regions, i.e., amygdala, insula, precuneus, and thalamus, quantified the role played by the ACC in MDD.

The Altered Triple Networks Interaction in Depression under Resting State Based on Graph Theory.

The triple network model (Menon, 2011) has been proposed, which helps with finding a common framework for understanding the dysfunction in core neurocognitive network across multiple disorders. The alteration of the triple networks in the major depression disorder (MDD) is not clear. In our study, the altered interaction of the triple networks, which include default model network (DMN), central executive network (CEN), and salience network (SN), was examined in the MDD by graph theory method. The results showed that the connectivity degree of right anterior insula (rAI) significantly increased in MDD compared with healthy control (HC), and the connectivity degree between DMN and CEN significantly decreased in MDD. These results not only supported the proposal of the triple network model, but also prompted us to understand the dysfunction of neural mechanism in MDD.