The brain is made up of millions of cells called neurons. There are, of course, other supporting cells in the brain like glia and some vasculature, but the neuron is arguably the most interesting cell in the brain because neurons can fire. They propagate information down axons and form synapses onto one another. It is believed that this information integration and propagation forms the basis for thought and consciousness.
How do these synapses arise between neurons? How does a neural circuit for information processing arise from different types of synapses? How does one cell form a synapse onto another such that a firing pattern is propagated between cells? And why are some synapses excitatory while others are inhibitory or even modulatory?
Types of Synapses
Most people are aware of two types of synapses in the brain. The most common synapses include inhibitory and excitatory synapses (GABA-ergic and glutamatergic, respectively) and these form the majority of synapses, yet there is also a group of synapses which is considered modulatory in nature. This group is less famous, however very important when it comes to patterns arising from cellular firing.
Modulatory Synapses
Modulatory synapses arise from a neurotransmitter called acetylcholine. There are two types of acetylcholine receptors, those being nicotinic and muscarinic. These receptors allow a cell to modulate a response pattern and often fire in rhythms. Rhythms of cellular firing and neural firing patterns are thought to be a fundamental cause for potentiation which is the underlying basis for learning and memory and the plasticity of neuron-mediated thought.
Inhibitory Synapses
Gamma-amino-butyric acid (GABA) is an inhibitory neurotransmitter produced by inhibitory interneurons. These neurons serve as a silencing mechanism, without which, feedback mechanisms of excitatory synapses would quickly get out of hand and wouldn’t allow for information integration. GABAergic synapses can form onto any type of cell, but the neurotransmitter is only produced by GABAergic neurons.
Excitatory Synapses
Glutamate is the most common excitatory neurotransmitter in the brain. Glutamatergic synapses often form onto dendritic spines of postsynaptic cells. The size and shape of dendritic spines is highly dynamic and is thought to play a significant role in learning and memory. There are two common types of glutamatergic receptors found in active glutamatergic synapses. These are NMDA receptors and alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA) receptors.
Glutamatergic Synapse Formation
Exactly how synapses form is still unclear. A great deal of research has been done on how excitatory synapses, in particular, form. The current accepted model in neuroscience is in accordance with the fact that NMDA receptors will often cluster at something like a synapse but yet no signal is transduced. These “synapses” are considered “silent synapses”.
NMDA receptors are thought to get transported in vesicles which occasionally dock at the surface of the membrane and sometimes remain docked there for a long period of time. NMDA receptors form robust responses but they require the internal cell to lose its voltage polarization, thereby releasing a magnesium block from the center of the NMDA pore.
AMPA receptors must come along and provide this initial internal depolarization. AMPA receptors alone don’t form very strong synapses, as NMDA receptors allow an influx of calcium and a strong internal depolarization. Thus, both AMPA receptors and NMDA receptors are required for excitation of glutamatergic synapses. AMPA receptors unsilence NMDA receptors and NMDA receptors lend strength to AMPA receptor responses.
Based on how synapses form and the different types of synapses in the brain, one could imagine building a neural circuit by using inhibitory and excitatory synapses as logic gates, much in the same way a computer works. This is the basic underlying principle behind computational neuroscience and supports the idea that scientists might someday be able to model a human brain on a computer.
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