Correct knowledge of the effective connectivity at the synaptic level in humans is a key prerequisite for increasing our understanding of the operation of the human central nervous system. Unfortunately, none of the current ambitious collaborative …
We present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in …
In this thesis, a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication is presented. This poses a great challenge since direct recordings from individual neurons …
Understanding functional synaptic connectivity of human central nervous system is one of the holy grails of the neuroscience. Due to the complexity of nervous system, it is common to reduce the problem to smaller networks such as motor unit pathways. …
In this paper, the early design of our self-organized agent-based simulation model for ex- ploration of synaptic connections that faithfully generates what is observed in natural situation is given. While we take inspiration from neu- roscience, our …
The understanding of human central nervous system (CNS) depends on knowledge of its wiring. However, there are still gaps in our understanding of its wiring due to technical difficulties. While some information is com- ing out from human experiments, …
The understanding of human central nervous system (CNS) depends on knowledge of its wiring. Although, neuroscientists are performing various experiments to explore wirings, there are still gaps in our understanding of this wiring due to technical …