A new mathematical model that identifies essential connections between neurons reveals some neural networks in the brain are more essential than others.
A new computational model of the C. elegans neural activity serves to unmask the roles of different neurons.
A new mathematical model is able to predict the optimal exercise regime to help build muscles.
A new mathematical model incorporates fear, both of infection and vaccination, to better understand how pandemics occur in multiple waves of infection, as we are witnessing with COVID-19.
A new mathematical model delves into the biological changes that occur in both the aging brain and brains with neurodegenerative disorders. The implications lay forth a new path into developing therapies for neurodegenerative disorders that affect cognition.
A single neuron is able to select between different patterns, dependent upon the properties of individual stimuli.
A new mathematical algorithm examines data from EEG and brain implants to learn each epilepsy patient's unique brain pattern signatures. The system can predict the onset of a seizure within an hour, allowing the patient to take necessary interventions.
Researchers used data of active COVID-19 case rates from China to set the parameters for the model. Applying the formula to other counties, including the UK, France, and Brazil, they found a match in the evolution of active cases and fatality rates over time.
A new mathematical model examined the immune response in patients with coronavirus. The findings suggest adaptive immune response may kick in before target immune cells are depleted, slowing the infection. The interaction of the innate and adaptive immune response may explain why some with coronavirus experience a second wave infection, appearing to get better before the symptoms return and get worse. Other studies have shown those who received immunosuppressants at the start of infection had a better clinical outcome than those who did not.
A new mathematical model reveals a more realistic picture of the number of likely COVID-19 cases, both in the US and worldwide, compared to reported data.
Mathematical model uses real-time monitoring data of COVID-19 transmissibility and severity to fine-tune control strategies, offering a better chance of minimizing a second wave of infection in mainland China.
Mathematical model incorporated several strategies to help flatten the COVID-19 curve, focusing on scarcity in hospital resources over two years. The models showed current physical distancing can help maintain healthcare capacity and reduce infections. The model also allowed for periodic economic and psychological breaks from social restrictions.
