Why Study Networks of Neurons?
The human brain consists of approximately 1012 individual neurons connected together by their synapses. We may understand the components of this system to some extent but it is the interactions between them that determine how the brain functions and understanding this remains a great challenge.
What Physical Applications Does this Project Have?
This project deals with multi-time-scale spike burst behaviour in networks of neurons. Physically speaking this occurs in the thalamus in mammalian brains during periods of low activity, for example sleep or tiredness. More interestingly, some types of epileptic seizures are also linked to spike-burst behaviour and therefore it is a worthy area for research.
How Can we Study Networks of Neurons?
The basis for neuronal models is that individual neurons can be treated as electrical circuits and therefore lend themselves to description by differential equations. Using numerical techniques on a computer simulations of these equations can be studied. Since connections exist between neurons the effects of one neuron firing an action potential can have repercussions throughout the network.
How does a Single Neuron Typically Behave and Why?
The neuron has a cell membrane which restricts the flow of ions in and out of the cell thereby creating a potential difference across the membrane. This potential difference increases, due to the gradual traversal of ions across the membrane, until the cell fires an `action potential' which appears as a voltage spike. Following this the potential of the cell returns to its reset value.
So How Does This Differ in a Network?
That's what this project's all about! One such effect, which is seen in real networks of neurons, is synchronisation. When neurons synchronise they are seen to fire action potentials at the same point in time as each other. This synchronisation may not be absolute, for example one neuron may lag another by a small time period, or some spikes may be synchronise and others may not. Networks of neurons may also anti-synchronise whereby one neuron spikes half a phase after another.
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