Topic: computational simulations

Synapses show preferential responses to particular temporal patterns of activity. Across synapses, however, there is a large degree of response heterogeneity that is routinely and tacitly separated into classes. Furthermore, feedforward neural networks incorporating simple models of these dynamic responses outperform similar recurrent neural network (RNN) models in several neuroscience related tasks. Here we combined a kernel-based model and machine learning techniques to infer biologically grounded, and functionally distinct classes of short-term synaptic dynamics in data from the Allen Insti

Aging and neurodegenerative diseases, such as Alzheimer's (AD) or Amyotrophic Lateral Sclerosis (ALS), led to widespread degeneration of long-range connections in cortical structural connectivity (SC). These damages manifest as losses in connections or demyelination of axons. When the SC of the brain is damaged, the functional connectivity (FC, i.e. the dynamic interactions and information exchange between distinct brain regions) is locally and globally perturbed. Despite the close correlation between SC and FC, they are not identical; FC exhibits greater flexibility and can reorganize in resp