Predictive coding networks for temporal prediction.

One of the key problems the brain faces is inferring the state of the world from a sequence of dynamically changing stimuli, and it is not yet clear how the sensory system achieves this task. A well-established computational framework for describing perceptual processes in the brain is provided by the theory of predictive coding. Although the original proposals of predictive coding have discussed temporal prediction, later work developing this theory mostly focused on static stimuli, and key questions on neural implementation and computational properties of temporal predictive coding networks remain open. Here, we address these questions and present a formulation of the temporal predictive coding model that can be naturally implemented in recurrent networks, in which activity dynamics rely only on local inputs to the neurons, and learning only utilises local Hebbian plasticity. Additionally, we show that temporal predictive coding networks can approximate the performance of the Kalman filter in predicting behaviour of linear systems, and behave as a variant of a Kalman filter which does not track its own subjective posterior variance. Importantly, temporal predictive coding networks can achieve similar accuracy as the Kalman filter without performing complex mathematical operations, but just employing simple computations that can be implemented by biological networks. Moreover, when trained with natural dynamic inputs, we found that temporal predictive coding can produce Gabor-like, motion-sensitive receptive fields resembling those observed in real neurons in visual areas. In addition, we demonstrate how the model can be effectively generalized to nonlinear systems. Overall, models presented in this paper show how biologically plausible circuits can predict future stimuli and may guide research on understanding specific neural circuits in brain areas involved in temporal prediction.

Detecting localised prostate cancer using radiomic features in PSMA PET and multiparametric MRI for biologically targeted radiation therapy.

BACKGROUND: Prostate-Specific Membrane Antigen (PSMA) PET/CT and multiparametric MRI (mpMRI) are well-established modalities for identifying intra-prostatic lesions (IPLs) in localised prostate cancer. This study aimed to investigate the use of PSMA PET/CT and mpMRI for biologically targeted radiation therapy treatment planning by: (1) analysing the relationship between imaging parameters at a voxel-wise level and (2) assessing the performance of radiomic-based machine learning models to predict tumour location and grade. METHODS: PSMA PET/CT and mpMRI data from 19 prostate cancer patients were co-registered with whole-mount histopathology using an established registration framework. Apparent Diffusion Coefficient (ADC) maps were computed from DWI and semi-quantitative and quantitative parameters from DCE MRI. Voxel-wise correlation analysis was conducted between mpMRI parameters and PET Standardised Uptake Value (SUV) for all tumour voxels. Classification models were built using radiomic and clinical features to predict IPLs at a voxel level and then classified further into high-grade or low-grade voxels. RESULTS: Perfusion parameters from DCE MRI were more highly correlated with PET SUV than ADC or T2w. IPLs were best detected with a Random Forest Classifier using radiomic features from PET and mpMRI rather than either modality alone (sensitivity, specificity and area under the curve of 0.842, 0.804 and 0.890, respectively). The tumour grading model had an overall accuracy ranging from 0.671 to 0.992. CONCLUSIONS: Machine learning classifiers using radiomic features from PSMA PET and mpMRI show promise for predicting IPLs and differentiating between high-grade and low-grade disease, which could be used to inform biologically targeted radiation therapy planning.

A method for investigating spatiotemporal growth patterns at cell and tissue levels during C-looping in the embryonic chick heart.

We developed a workflow using multi-scale and multi-disciplinary experimental and computational approaches to analyze C-looping (the first phase of cardiac looping) of the chick across four developing hearts. We provide the first 3D datasets for the C-looping heart with cell to organism level information, including datasets of heart images and segmented myocardial cells within the heart. We used these datasets to investigate, as a proof-of-concept, the differential spatiotemporal patterns of growth at both the cellular and tissue levels, and demonstrate how geometrical changes of C-looping at the tissue level are linked to growth features at the cellular level. Our methodological pipeline provides preliminary results for qualitative and quantitative evidence of various cellular and tissue features as potential candidates regarding the mechanism of C-looping. This pipeline can be used and extended in future studies to include larger specimen samples for detailed analyses of, and potentially new insights into, cardiac C-looping.

Neutrophil-vascular interactions drive myeloperoxidase accumulation in the brain in Alzheimer's disease.

INTRODUCTION: Neutrophil accumulation is a well-established feature of Alzheimer's disease (AD) and has been linked to cognitive impairment by modulating disease-relevant neuroinflammatory and vascular pathways. Neutrophils express high levels of the oxidant-generating enzyme myeloperoxidase (MPO), however there has been controversy regarding the cellular source and localisation of MPO in the AD brain. MATERIALS AND METHODS: We used immunostaining and immunoassays to quantify the accumulation of neutrophils in human AD tissue microarrays and in the brains of APP/PS1 mice. We also used multiplexed immunolabelling to define the presence of NETs in AD. RESULTS: There was an increase in neutrophils in AD brains as well as in the murine APP/PS1 model of AD. Indeed, MPO expression was almost exclusively confined to S100A8-positive neutrophils in both human AD and murine APP/PS1 brains. The vascular localisation of neutrophils in both human AD and mouse models of AD was striking and driven by enhanced neutrophil adhesion to small vessels. We also observed rare infiltrating neutrophils and deposits of MPO around plaques. Citrullinated histone H3, a marker of neutrophil extracellular traps (NETs), was also detected in human AD cases at these sites, indicating the presence of extracellular MPO in the vasculature. Finally, there was a reduction in the endothelial glycocalyx in AD that may be responsible for non-productive neutrophil adhesion to the vasculature. CONCLUSION: Our report indicates that vascular changes may drive neutrophil adhesion and NETosis, and that neutrophil-derived MPO may lead to vascular oxidative stress and be a relevant therapeutic target in AD.

3D single cell scale anatomical map of sex-dependent variability of the rat intrinsic cardiac nervous system.

We developed and analyzed a single cell scale anatomical map of the rat intrinsic cardiac nervous system (ICNS) across four male and three female hearts. We find the ICNS has a reliable structural organizational plan across individuals that provide the foundation for further analyses of the ICNS in cardiac function and disease. The distribution of the ICNS was evaluated by 3D visualization and data-driven clustering. The pattern, distribution, and clustering of ICNS neurons across all male and female rat hearts is highly conserved, demonstrating a coherent organizational plan where distinct clusters of neurons are consistently localized. Female hearts had fewer neurons, lower packing density, and slightly reduced distribution, but with identical localization. We registered the anatomical data from each heart to a geometric scaffold, normalizing their 3D coordinates for standardization of common anatomical planes and providing a path where multiple experimental results and data types can be integrated and compared.

The SPARC DRC: Building a Resource for the Autonomic Nervous System Community.

The Data and Resource Center (DRC) of the NIH-funded SPARC program is developing databases, connectivity maps, and simulation tools for the mammalian autonomic nervous system. The experimental data and mathematical models supplied to the DRC by the SPARC consortium are curated, annotated and semantically linked via a single knowledgebase. A data portal has been developed that allows discovery of data and models both via semantic search and via an interface that includes Google Map-like 2D flatmaps for displaying connectivity, and 3D anatomical organ scaffolds that provide a common coordinate framework for cross-species comparisons. We discuss examples that illustrate the data pipeline, which includes data upload, curation, segmentation (for image data), registration against the flatmaps and scaffolds, and finally display via the web portal, including the link to freely available online computational facilities that will enable neuromodulation hypotheses to be investigated by the autonomic neuroscience community and device manufacturers.

Lung and fissure shape is associated with age in healthy never-smoking adults aged 20-90 years.

Lung shape could hold prognostic information for age-related diseases that affect lung tissue mechanics. We sought to quantify mean lung shape, its modes of variation, and shape associations with lung size, age, sex, and Body Mass Index (BMI) in healthy subjects across a seven-decade age span. Volumetric computed tomography from 83 subjects (49 M/34 F, BMI [Formula: see text]) was used to derive two statistical shape models using a principal component analysis. One model included, and the other controlled for, lung volume. Volume made the strongest contribution to shape when it was included. Shape had a strong relationship with age but not sex when volume was controlled for, and BMI had only a small but significant association with shape. The first principal shape mode was associated with decrease in the antero-posterior dimension from base to apex. In older subjects this was rapid and obvious, whereas younger subjects had relatively more constant dimension. A shift of the fissures of both lungs in the basal direction was apparent for the older subjects, consistent with a change in tissue elasticity with age. This study suggests a quantifiable structure-function relationship for the healthy adult lung that can potentially be exploited as a normative description against which abnormal can be compared.