Contributions to Dynamic Behaviour of Materials Professor John Edwin Field, FRS 1936–2020

Professor John Edwin Field passed away on October 21st, 2020 at the age of 84. Professor Field was widely regarded as a leader in high-strain rate physics and explosives. During his career in the Physics and Chemistry of Solids (PCS) Group of the Cavendish Laboratory at Cambridge University, John made major contributions into our understanding of friction and erosion, brittle fracture, explosives, impact and high strain-rate effects in solids, impact in liquids, and shock physics. The contributions made by the PCS group are recognized globally and the impact of John’s work is a lasting addition to our knowledge of the dynamic effects in materials. John graduated 84 Ph.D. students and collaborated broadly in the field. Many who knew him attribute their success to the excellent grounding in research and teaching they received from John Field

Contributions to Dynamic Behaviour of Materials Professor John Edwin Field, FRS 1936–2020

Professor John Edwin Field passed away on October 21st, 2020 at the age of 84. Professor Field was widely regarded as a leader in high-strain rate physics and explosives. During his career in the Physics and Chemistry of Solids (PCS) Group of the Cavendish Laboratory at Cambridge University, John made major contributions into our understanding of friction and erosion, brittle fracture, explosives, impact and high strain-rate effects in solids, impact in liquids, and shock physics. The contributions made by the PCS group are recognized globally and the impact of John’s work is a lasting addition to our knowledge of the dynamic effects in materials. John graduated 84 Ph.D. students and collaborated broadly in the field. Many who knew him attribute their success to the excellent grounding in research and teaching they received from John Field

The default mode network and recurrent depression: a neurobiological model of cognitive risk factors

A neurobiological account of cognitive vulnerability for recurrent depression is presented based on recent developments of resting state neural networks. We propose that alterations in the interplay between task positive (TP) and task negative (TN) elements of the Default Mode Network (DMN) act as a neurobiological risk factor for recurrent depression mediated by cognitive mechanisms. In the framework, depression is characterized by an imbalance between TN-TP components leading to an overpowering of TP by TN activity. The TN-TP imbalance is associated with a dysfunctional internally-focused cognitive style as well as a failure to attenuate TN activity in the transition from rest to task. Thus we propose the TN-TP imbalance as overarching neural mechanism involved in crucial cognitive risk factors for recurrent depression, namely rumination, impaired attentional control, and cognitive reactivity. During remission the TN-TP imbalance persists predisposing to vulnerability of recurrent depression. Empirical data to support this model is reviewed. Finally, we specify how this framework can guide future research efforts