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Determining similarities and differences in brain structure across psychiatric disorders is important to determine if psychiatric taxonomy is reflected in distinct brain structural changes. As previous neuroimaging meta-analyses have typically focused on a single disorder, precluding transdiagnostic comparisons, we aimed to quantify patterns of similarity and differences between psychiatric disorders in terms of regional brain volumes. Here we show, in network and pairwise meta-analyses of 498 studies (51,227 individuals, 17 psychiatric disorders and 17 brain regions), that psychiatric disorders show both distinct and overlapping patterns of brain volume gain and loss. A principal components analysis demonstrated that the first principal component could account for 48% of variance and corresponded to a pattern of increased basal ganglia and decreased hippocampal and amygdala volumes. This component loaded most strongly for disorders on the psychosis spectrum, and most weakly for affective disorders. Our findings illustrated that, while similar volumetric alterations are frequently shared between disorders, neuroanatomical patterns also appear related to clinically meaningful categories. (PROSPERO Registration: CRD42020221143.)

Evidence from post-mortem studies and in vivo imaging studies suggests there may be reducedIn this study, we investigated the relationship between hippocampal NMDAR and striatal glutamate using simultaneous positron emission tomography-magnetic resonance (PET-MR) imaging. We recruited 40 volunteers to this cross-sectional study; 21 patients with schizophrenia, all in their first episode of illness, and 19 healthy controls. We measured hippocampal NMDAR availability using the PET ligand [A total of 33 individuals (15 healthy controls, 18 patients) were included in the analyses (mean (SD) age of controls, 27.31 (4.68) years; mean (SD) age of patients, 24.75 (4.33), 27 male and 6 female). We found an inverse relationship between hippocampal DVR and striatal glutamate levels in people with first-episode psychosis (rho = -0.74,This study show that lower relative NMDAR availability in the hippocampus may drive increased striatal glutamate levels in patients with schizophrenia. Further work is required to determine whether these findings may yield new targets for drug development in schizophrenia.

Background: Evidence from post-mortem studies and in vivo imaging studies suggests there may be reduced N-methyl-d-aspartate receptor (NMDAR) levels in the hippocampus in patients with schizophrenia. Other studies have reported increased glutamate in striatum in schizophrenia patients. It has been hypothesised that NMDAR hypofunction leads to the disinhibition of glutamatergic signalling; however, this has not been tested in vivo. Methods: In this study, we investigated the relationship between hippocampal NMDAR and striatal glutamate using simultaneous positron emission tomography-magnetic resonance (PET-MR) imaging. We recruited 40 volunteers to this cross-sectional study; 21 patients with schizophrenia, all in their first episode of illness, and 19 healthy controls. We measured hippocampal NMDAR availability using the PET ligand [18F]GE179. This was indexed relative to whole brain as the distribution volume ratio (DVR). Striatal glutamatergic indices (glutamate and Glx) were acquired simultaneously, using combined PET-MR proton magnetic resonance spectroscopy (1H-MRS). Results: A total of 33 individuals (15 healthy controls, 18 patients) were included in the analyses (mean (SD) age of controls, 27.31 (4.68) years; mean (SD) age of patients, 24.75 (4.33), 27 male and 6 female). We found an inverse relationship between hippocampal DVR and striatal glutamate levels in people with first-episode psychosis (rho = −0.74, p Conclusion: This study show that lower relative NMDAR availability in the hippocampus may drive increased striatal glutamate levels in patients with schizophrenia. Further work is required to determine whether these findings may yield new targets for drug development in schizophrenia.

Recent advances in deep generative models led to the development of neural face video compression codecs that use an order of magnitude less bandwidth than engineered codecs. These neural codecs reconstruct the current frame by warping a source frame and using a generative model to compensate for imperfections in the warped source frame. Thereby, the warp is encoded and transmitted using a small number of keypoints rather than a dense flow field, which leads to massive savings compared to traditional codecs. However, by relying on a single source frame only, these methods lead to inaccurate reconstructions (e.g. one side of the head becomes unoccluded when turning the head and has to be synthesized). Here, we aim to tackle this issue by relying on multiple source frames (views of the face) and present encouraging results.