But on the kinds of
figures that are coming out now, it seems like the whole brain must
be recycled about every other month
Do you know the half-life of a microtubule,
the protein filaments that form the internal scaffolding a cell?
Just ten minutes. That's an average of ten minutes between assembly
Now the brain is supposed to be some sort
of computer. It is an intricate network of some 1,000 trillion
synaptic connections, each of these synapses having been lovingly
crafted by experience to have a particular shape, a particular
neurochemistry. It is of course the information represented at these
junctions that makes us who we are. But how the heck do these
synapses retain a stable identity when the chemistry of cells is
almost on the boil, with large molecules falling apart nearly as
soon as they are made?
The issue of molecular turnover is
starting to hit home in neuroscience, especially now that the latest
research techniques such as fluorescent tagging are revealing a far
more frantic pace of
activity than ever suspected. For instance,
the actin filaments in dendrites can need replacing within 40
seconds, making microtubules look like positive greybeards (Star et
al, 2002). A turnover time of five days for NMDA receptors seemed
pretty steep when it was reported a few years back. (Shimizu et al,
2000). But recently Michael Ehlers at Duke University Medical Center
in Durham, North Carolina, reported that the entire post-synaptic
density (PSD) – the proteinpacked zone that powers synaptic activity
- is replaced, molecule for molecule, almost by the hour. Ehlers had
expected the turnover to take days and when he found no labelled
protein on his first 24 hour assay, he thought he must have mucked
up the experiment (Ehlers 2003).
Myelin and RNA molecules seem to last
months. And DNA is of course fairly hardy, though it still needs
continual repair. But on the kinds of figures that are coming out
now, it seems like the whole brain must get recycled about every
other month. And certainly everything points to the synapses as
being about the most dynamic part of the whole system.
Clearly the shape of the synapses IS
somehow maintained despite the molecular turmoil. But there is an
issue here that demands some specific theory. The stability of brain
circuits cannot simply be taken for granted. Princeton University's
Joe Tsien - famous for making mice smarter by splicing in
slower-closing NMDA receptors - is one of a number of researchers
pursuing the idea that synaptic structure may be stabilized by
pressure from both above and below.
Many people know about the emerging "below"
picture of how shifts in gene expression patterns could be necessary
to underpin neural learning. Put simply, the genes remember what
kind of state a junction ought to be in and so keep rebuilding the
same old structure. As a relative oasis of calm in the thermodynamic
bustle of a cell, the genes could anchor the homeostatic network
needed to allow a given synaptic pattern to persist. Of course, this
story is complicated by evidence that RNA actually in the dendrites
may do the same job. But it seems to be a "loops within loops"
mechanism with short-loop local feedback nested in longloop feedback
between synapses and genes (Lisman and Fallon, 1999).
But Tsien says that as well as this
shape-maintaining pressure from within, synapses may be just as
dependent on pressures from without - the old "jangling trace"
hypothesis. Back in the early 1990s it was discovered that there is
a kind of compressed replay of the day's accumulated memories during
slow wave sleep. The networks of cells active during learning would
burst to life again. This led to the theory that the hippocampus
consolidates new learning to the cortex when the brain is off-line.
But Tsien feels this spontaneous jangling of neural traces is
probably a much more general homeostatic mechanism that helps to
keep labile synapses stabilized. And the jangling probably goes on
around the clock, in all areas of the brain, at regular intervals to
remind each synaptic connection of its place in the great scheme of
things (Wittenberg, Sullivan and Tsien, 2002).
All this Byzantine complexity does matter.
To make sense of the brain as an information processing system,
clearly we must be physically able to locate its information. And
it's long been an almost unquestioned tenet of neuroscience that
neurons with their weighted junctions and crisp connection patterns
are devices for trapping information. The hardwired network is the
solid foundation for all the pretty patterns that play across it.
Yet when we zero in on these synapses, suddenly their "information"
appears to scatter. The synapses turn out to be merely reflecting a
living confluence of top-down and bottom-up pressures. The
information is now out there in the system and it is making the
synaptic patterns we observe.
This kind of topsy-turvey picture can only
be resolved by taking a more holistic view of the brain as the organ
of consciousness. The whole shapes the parts as much as the parts
shape the whole. No component of the system is itself stable but the
entire production locks together to have stable existence. This is
how you can manage to persist even though much of you is being
recycled by day if not the hour.
Copyright © John McCrone, 2004
Star EN, Kwiatkowski DJ and Murthy VN.
Rapid turnover of actin in dendritic spines and its regulation by
activity, Nature Neuroscience 5:239-246 (2002)
Ehlers MD. Activity-dependent regulation of postsynaptic
composition and signaling by the ubiquitin-proteasome system. Nature
Shimizu E, Tang YP, Rampon C and Tsien JZ. NMDA receptor
dependent synaptic reinforcement as a crucial process for memory
Lisman JE and Fallon JR. What maintains memories? Science
283:339-340 (1999) Wittenberg GM, Sullivan MR and Tsien JZ. Synaptic
Based Network Model for Long-Term Memory
Consolidation Hippocampus 12:637-647 (2002)