All papers

Spatial model predicts dispersal and cell turnover cause reduced intra-tumor heterogeneity

Presents a novel spatial model of tumor growth that challenges conventional wisdom about genetic mutations and cancer heterogeneity. The authors propo...
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Alpha-1 adrenergic receptor antagonists to prevent hyperinflammation and death from lower respiratory tract infection

In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation, which ca...
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Cortical Dynamics of Neural-Connectivity Fields

Active Inference and Intentional Behaviour

Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuro...
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Supervised structure learning

Concerns structure learning or discovery of discrete generative models. It focuses on Bayesian model selection and the assimilation of training data o...
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Bayesian sparsification for deep neural networks with Bayesian model reduction

Deep learning's immense capabilities are often constrained by the complexity of its models, leading to an increasing demand for effective sparsificati...
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Life-inspired Interoceptive Artificial Intelligence for Autonomous and Adaptive Agents

Building autonomous --- i.e., choosing goals based on one's needs -- and adaptive -- i.e., surviving in ever-changing environments -- agents has been ...
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Linking fast and slow: the case for generative models

A pervasive challenge in neuroscience is testing whether neuronal connectivity changes over time due to specific causes, such as stimuli, events, or c...
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Frontal effective connectivity increases with task demands and time on task: a Dynamic Causal Model of electrocorticogram in macaque monkeys

We apply Dynamic Causal Models to electrocorticogram recordings from two macaque monkeys performing a problem-solving task that engages working memory...
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Dynamic causal modelling of COVID-19

This technical report describes a dynamic causal model of the spread of coronavirus through a population. The model is based upon ensemble or populati...
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A tutorial on group effective connectivity analysis, part 1: first level analysis with DCM for fMRI

Serves as a tutorial on employing Dynamic Causal Modelling (DCM) for effective connectivity analysis in fMRI studies, focusing on the first level of a...
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Bayesian fusion and multimodal DCM for EEG and fMRI

Asks whether integrating multimodal EEG and fMRI data offers a better characterisation of functional brain architectures than either modality alone. T...
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