The nature of neural networks is perhaps better understood by more people nowadays than used to the be the case. Forms of neural network are used for a range of computational purposes, where they have proved useful as a way to economically discover solutions to difficult problems in pattern recognition, optimization, and other fields. How a particular solution works isn’t always clear, especially when using larger networks, but if it can be proven to work well then why worry?
We ourselves are neural networks: the complex adaptive phenomena that we choose to call the self arises from comparatively simple exchanges between many, many neurons. The machine is the connections and the state of its neurons, constantly altering itself in response to circumstances and its own operation.
The brain, like all tissues, suffers due to the accumulation of cellular and molecular damage that drives aging. But which of the characteristic differences between a young brain and an old brain are aging, and which are the expected operation of the neural network as it processes and reprocesses the data gathered throughout life? In some cases the classification is obvious: broken blood vessels and white matter hyperintensities are damage, as is the amyloid that accumulates in Alzheimer’s disease. We would be better off without them, and they harm us by destroying physical structures needed for operation of the brain. Once researchers start looking at the structure of neural connections, or activity in response to stimulus, or gene expression maps in various portions of the brain things become a little less clear, however:
The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses – including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline.
Theoretical neurobiology offers a simpler explanation for all of these effects – from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning.
Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.
My suspicion is that it would be faster to implement rejuvenation biotechnologies and then assess what happens to an aging brain that remains physiologically young than to fully pick apart and understand present contributions to changes over time in the brain.
This line of research is of interest because of a potential threat to extreme longevity, past the present limits of human life span, once we have build the necessary medical technologies. The threat is this: it is possible that the brain is like the immune system, in that it is poorly structured for long term use, and will fail for reasons inherent to that structure, even in the absence of damage. We have no reason to suspect that this is the case, but equally there is no good reason to rule this out – the scientific community simply doesn’t understand enough about the detailed operation of the brain to say either way with confidence.
On the plus side, this is a comparatively remote potential threat, something that lies decades past all the other fatal forms of damage and age-related disease that we have to deal with. Old people with little physical damage to their brains are sharp and on the ball, to the degree allowed by their failing bodies and decades of increasing caution required in their interaction with the world. Further, by the time we are at the point of worrying about this, biotechnology will be far more advanced. So it is, I think, worth considering, but not worth panicking over.
Reason is the founder of The Longevity Meme (now Fight Aging!). He saw the need for The Longevity Meme in late 2000, after spending a number of years searching for the most useful contribution he could make to the future of healthy life extension. When not advancing the Longevity Meme or Fight Aging!, Reason works as a technologist in a variety of industries.
This work is reproduced here in accord with a Creative Commons Attribution license. It was originally published on FightAging.org.