A study by The Scripps Research Institute (TSRI) has uncovered new clues to the wiring of the brain. Apparently, neurons in brain regions that store memory have the ability to form networks in the absence of synaptic activity.
The team was led by Associate Professor Anton Maximov. The results of the study implied that assembly of neural circuits in areas needed for cognition is largely controlled by intrinsic genetic programs that operate independently of the external world.
In a press release via Science Daily, it was reported that the different senses: vision, hearing, smell and touch play important roles during early postnatal life, which is when majority of synapses is formed. New synapses have also been found to appear in the adult brain during learning.
The team investigated if neurons can form and maintain connections in genetically engineered animals that live into adulthood with no synaptic activity in the hippocampus. Several observations found evidence that this is can technically be done.
One of the researchers generated mice that permanently lacked a secretion of glutamate, a neurotransmitter that activates neurons when a memory is formed, in the hippocampus. Even though they had no ability to learn and remember, the animals were able to eat, walk around, groom and engage in social interactions.
They examined the connectivity in permanently inactive areas. They found that majority of the key stages of neural circuit development, which were widely believed to require synaptic activity, were unaffected in the mice.
The results of ultra-structural analyses showed that neurotransmission is not necessary for the assembly of basic building blocks of single synaptic connections. This includes the dendritic spines that recruit signaling complexes and enable neurons to sense the neurotransmitter glutamate.
Maximov noted that the test subjects were not able to function normally. This is because their hippocampus functions similar to a computer that goes through the assembly line but do not get plugged to a power source and loaded with software. The team aims to exploit new chemical-genetic methods to test whether intrinsically-formed networks can support learning.
