Researchers are uncovering another layer of complexity as to how the brain functions. Brain cells communicate with one another by chemicals through synaptic connections. The human brain contains billions of neurons and each neuron has a large amount of synaptic connections to other neurons. Each synapse itself contains a variety of receptor proteins that can alter the gross firing pattern of a neuron. It has only been recently that scientists have been able to better understand the role of synaptic protein interactions in the computational capacity of the brain. A lot of this activity functions at an even lower level than overall neuronal firing.
In the past, researchers have found that different organisms on the tree of life have varying amounts of these receptor proteins in the individual synapses of their neurons. As you go from simpler organisms up to mice, there are an increasing number of synaptic molecules. In that past study, the scientists had investigated approximately 651 different genes that directly encode for proteins in the postsynaptic junctions of mouse neurons. They specifically focused on proteins that can be phosphorylated. Phosphorylation of protein molecules changes their functioning. The researchers looked for the same proteins in a variety of other life forms besides mice that had varying levels of complexity (invertebrates, non-mammalian vertebrates and other mammals). Lower complexity organisms like invertebrates had about 45% fewer of these synaptic proteins than the mouse synapse, while an even simpler organism like yeast only had about 21% of the number of proteins.
Now those very same researchers have published more work uncovering the complex interactions of the molecular proteins in an individual synaptic connection.
Here, we define maps of molecular circuitry within the PSD based on phosphorylation of postsynaptic proteins. Activation of a single neurotransmitter receptor, the N-methyl-D-aspartate receptor (NMDAR), changed the phosphorylation status of 127 proteins. Stimulation of ionotropic and metabotropic glutamate receptors and dopamine receptors activated overlapping networks with distinct combinatorial phosphorylation signatures. Using peptide array technology, we identified specific phosphorylation motifs and switching mechanisms responsible for the integration of neurotransmitter receptor pathways and their coordination of multiple substrates in these networks. These combinatorial networks confer high information-processing capacity and functional diversity on synapses, and their elucidation may provide new insights into disease mechanisms and new opportunities for drug discovery.The researchers of this specific work used proteomic and also computational methods to disentangle all the relationships between these synaptic proteins. So being able to determine these relationships is really in some respects on outgrowth of certain accelerating trends in computing power and protein/genetic analyzing capability. I mentioned previously that Henry Markram talked about how certain newly developed methods are vastly speeding up scientific research. Research in uncovering some of these molecular mechanisms has moved rather slowly in the past, but greater computing power and software analyzing capability has the capacity to greatly accelerate progress.
The researchers have found that all of these molecular networks in the synapse may underly some of the overall computational capacity of the brain. You can read more about it at the press release here.
The team's discoveries led researchers to the conclusion that the brain is organised like the internet, where billions of these molecular computers - intricately complex in themselves - are connected by billions of nerve cells.So evolution has exploited multiple avenues to increase the brain's computational capacity. The avenues that were taken exist at differing "levels". Overall brain cell number is a "higher level" avenue. The human brain contains many more neurons than that of a mouse and other lower level organisms. Evolution has also favored mutations that cause increased branching and growth of neuronal axons. Mutations which increase levels of glucosylceramide in the brain, for instance, can increase the amount of neural axons. There is evidence that recent evolutionary selection pressure on humans has favored mutations which alter the amount of glucosylceramide and that these specific mutations may lead to a higher intelligence. More axons equal more synapses connecting each neuron. At a molecular "lower level", evolution has favored increasing the number of proteins in each individual synapse and a more complex interaction between those proteins. There are other potential ways that evolution may have worked on as well, which I won't mention here.
By merely simulating a higher level of brain functioning (overall neuron firing/activity) on a computer, researchers may totally miss a substantial amount of lower level functioning. So future computer brain simulations will likely have to model all of these protein interactions to function in a manner similar to a real brain. Even then, it is not clear if they will be successful in modeling the mind exactly (especially without the underlying physics of our world). I think you can probably model aspects of brain functioning very well on a computer, even with a simplified model (like without molecular interactions). However, getting a computer simulation of an entire brain to function exactly like a real brain (meaning it would have consciousness), may be a difficult task if not an impossible one. This new research, though, will certainly have an impact on our understanding of how the brain functions.
source: brainstimulant
