We are going to predict neuronal connections from calcium
imaging data by this project. First we should understand basics of neurons and
neural networks. Then we are trying to predict the connections between neurons.
To do that, we are using calcium imaging data sets. Then we can make an algorithm
that can predict the neuronal connections. Later we are going to test that
algorithm by given data sets.
The neuron is the basic working unit of the
brain. It is a specialized cell designed to transmit information to other nerve
cells such as muscle, or gland cells. Nervous system consists of millions of neurons.
They transmit information to other nerve cells. Most neurons have a cell
body, an axon, and dendrites. When neurons receive or send messages, they
transmit electrical impulses along their axons. Adult human brain has about a
trillion neurons. So it is not an easy task to find the connectivity among
them. We will have to use special methods to map the connectivity.
Connectomics is the production and study of comprehensive
maps of connections within an organism's
nervous
system. It is hard to trace them out physically even with powerful
microscopes. Florescent calcium ions can be used to observe the firing of
neurons. So we can predict the connections between neurons using calcium
fluorescence data. Using those data we are going to create algorithm to predict
the map of connections between neurons. After
creating the algorithm we can check it by using calcium imaging data sets from
small networks of about hundreds neurons to millions of neurons.
