It is a fundamental challenge to understand how the function of a network is related to its
structural organization. Adaptive dynamical networks represent a broad class of systems that …

While neuromorphic systems may be the ultimate platform for deploying spiking neural
networks (SNNs), their distributed nature and optimization for specific types of models …

Several brain disorders are characterized by abnormal neuronal synchronization. To
specifically counteract abnormal neuronal synchrony and, hence, related symptoms …

We provide a well-posedness theory for a class of nonlocal continuity equations on co-
evolving graphs. We describe the connection among vertices through an edge weight …

Neuroscience models commonly have a high number of degrees of freedom and only
specific regions within the parameter space are able to produce dynamics of interest. This …

Mounting experimental evidence suggests that brain-state-specific neural mechanisms,
supported by connectomic architectures, play a crucial role in integrating past and …

The impairment of cognitive function in Alzheimer's disease is clearly correlated to synapse
loss. However, the mechanisms underlying this correlation are only poorly understood …

In this work we propose a new biophysical computational model of brain regions relevant to
Parkinson's Disease (PD) based on local field potential data collected from the brain of …

Neuronal network simulators are central to computational neuroscience, enabling the study
of the nervous system through in-silico experiments. Through the utilization of high …

Agent-based models (ABMs) are used to simulate human-subject experiments. A
comprehensive understanding of these human systems often requires executing large …