Back to the Future: Medicine Beyond the COVID-19 Pandemic

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Black holes vs. naked singularities formation in collapsing Einstein's clusters

Non-static, spherically symmetric clusters of counter-rotating particles, of the type first introduced by Einstein, are analysed here. The initial data space can be parameterized in terms of three arbitrary functions, namely; initial density, velocity and angular momentum profiles. The final state of collapse, black hole or naked singularity, turns out to depend on the order of the first non-vanishing derivatives of such functions at the centre. The work extends recent results by Harada, Iguchi and Nakao.Comment: 13 pages, LaTeX format. To appear in Physical Review

Heterothermy in Northern Cardinals

These data were used in the article on Northern Cardinal heterothermy published in the journal Animal Biologging

A Neural Model of Context Dependent Decision Making in the Prefrontal Cortex

In this paper, we present a spiking neural model of contextdependent decision making. Prefrontal cortex (PFC) plays afundamental role in context dependent behaviour. We modelthe PFC at the level of single spiking neurons, to explore theunderlying computations which determine its contextual re-sponses. The model is built using the Neural EngineeringFramework and performs input selection and integration as anonlinear recurrent dynamical process. The results obtainedfrom the model closely match behavioural and neural experi-mental data obtained from macaque monkeys that are trainedto perform a context sensitive perceptual decision task. Theclose match suggests that the low-dimensional, nonlinear dy-namical model we suggest captures central aspects of contextdependent decision making in primates

A Biologically Constrained Model of Semantic Memory Search

The semantic fluency task has been used to understand the ef-fects of semantic relationships on human memory search. Avariety of computational models have been proposed that ex-plain human behavioral data, yet it remains unclear how mil-lions of spiking neurons work in unison to realize the cogni-tive processes involved in memory search. In this paper, wepresent a biologically constrained neural network model thatperforms the task in a fashion similar to humans. The modelreproduces experimentally observed response timing effects,as well as similarity trends within and across semantic cate-gories derived from responses. Three different sources of theassociation data have been tested by embedding associationsin neural connections, with free association norms providingthe best match