Qiang Wang

The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis.

BACKGROUND: Wernicke's concept of 'sejunction' or aberrant associations among specialized brain regions is one of the earliest hypotheses attempting to explain the myriad of symptoms in psychotic disorders. Unbiased data mining of all possible brain-wide connections in large data sets is an essential first step in localizing these aberrant circuits. METHODS: We analyzed functional connectivity using the largest resting-state neuroimaging data set reported to date in the schizophrenia literature (415 patients vs. 405 controls from UK, USA, Taiwan, and China). An exhaustive brain-wide association study at both regional and voxel-based levels enabled a continuous data-driven discovery of the key aberrant circuits in schizophrenia. RESULTS: Results identify the thalamus as the key hub for altered functional networks in patients. Increased thalamus-primary somatosensory cortex connectivity was the most significant aberration in schizophrenia (P=10(-18)). Overall, a number of thalamic links with motor and sensory cortical regions showed increased connectivity in schizophrenia, whereas thalamo-frontal connectivity was weakened. Network changes were correlated with symptom severity and illness duration, and support vector machine analysis revealed discrimination accuracies of 73.53-80.92%. CONCLUSIONS: Widespread alterations in resting-state thalamocortical functional connectivity is likely to be a core feature of schizophrenia that contributes to the extensive sensory, motor, cognitive, and emotional impairments in this disorder. Changes in this schizophrenia-associated network could be a reliable mechanistic index to discriminate patients from healthy controls.

Haploinsufficiency for or mutation in at least one gene from the velocardiofacial syndrome (VCFS) region at chromosome 22q11 is implicated in psychosis. Linkage disequilibrium mapping of the region in patients identified a segment containing two genes, proline dehydrogenase (PRODH) and DGCR6, as candidates [Liu et al., 2002a] and by analysis of additional polymorphisms the PRODH gene was associated with schizophrenia in adult and early onset patients. In the present study we provide additional evidence in support of genetic association between PRODH and schizophrenia in a Chinese population. We analyzed the PRODH gene in a samples of schizophrenic patients and their families from Sichuan, SW China consisting of 528 family trios and sibling pairs. We genotyped six SNPs, PRODH*1195C-->T, PRODH*1482C-->T, PRODH*1483A-->G, PRODH*1766A-->G, PRODH*1852G-->A PRODH*1945T-->C, two of which (PRODH*1483A-->G and PRODH*1852G-->A) have not been previously reported. We found association with schizophrenia for two haplotypes consisting of PRODH*1945T-->C and PRODH*1852G-->A (Global P = 0.006), and PRODH*1852G-->A and PRODH*1766A-->G (Global P = 0.01) which include one of the newly identified markers. After six-fold Bonferroni correction for multiple testing the PRODH*1945T-C/PRODH*1852G-A haplotypes remained significant. This is a sub-haplotype of the PRODH haplotype previously associated with schizophrenia and it also maps to the 3' region of the gene, indicating that this is the region most likely to contain the underlying risk alleles. Overall this finding supports a role for the PRODH locus in schizophrenia.