Download What drives the plasticity of brain tissues?

******BILL – WORK BELOW THIS LINE*****
What drives the plasticity of brain tissues?
here we start to parcel out the dichotomies of trainings that induce plasticity
(activity vs. metabolic; learning vs activity; skill vs reach; LTP vs EC). in this
section, I see a parallel-structured discussion of whether each specific form of
plasticity (within the broader neuronal and non-neuronal categories) was involved
in that type of training
The existence of short-term and long-term processes of brain cellular
adaptation, and the fact that brain activity HAS THE IDEA OF PHYSICAL
ACTIVITY INDUCING CHANGES BEEN BROUGHT UP YET? {not really
physical activity, but neuronal activity} and learning are both involved in the
behavioral events that appear to drive these processes, leads to the next natural
question: what causes changes in neurons, glia and vasculature: Can we rule out
artifactual causes such as hormonal or metabolic responses to behavioral
manipulations and can we then ascribe the cellular changes to the general
categories of activity and learning. With regard to activity, we have muscle as a
model: with sufficient activity, muscle will hypertrophy, the particular details
varying with the extent and pattern of activation. One can suppose that
activation of brain tissues in association with peripheral activity, via intermediary
cellular events, might similarly trigger neuronal, glial or vascular hypertrophy of
the sort seen in rats after complex environment housing. With regard to learning,
it seems plausible that certain changes in neurons, astrocytes or
oligodendrocytes might be learning-specific, although it is harder to imagine that
changes in capillaries would play very specific roles in learning.
At a broader level, it is also possible to imagine that responses to training
such as stress, or related metabolic consequences of behavioral manipulations
could lead to changes in brain tissue that would be artifacts in the sense that they
are non-adaptive responses to the behavioral manipulations. Certainly stress
can have negative consequences for at least some brain regions (e.g., Sapolsky,
1996 other refs on stress effects on HPC morphology), although the adrenal
hypertrophy-correlated astroglial changes in the hippocampal formation appear
to be dissociated from the experience-correlated visual cortex changes in
complex environment research (Sirevaag et al., 1991).
early models to tease apart these two
chang and greenough ’82
To examine the roles of learning vs. other consequences of training (e.g., activity,
stress, etc) on neuronal changes, we have utilized paradigms in which the effects
of learning would be focused in particular regions of the brain for which other
regions could serve as control or comparison samples. In one early study,
Chang and Greenough (1982) compared rats trained in a complex series of
changing maze patterns that learned with either the same eye always occluded
or with occlusion of alternate eyes on successive days. In rodents,
approximately 90-95% of retinal ganglion cell axons project to the opposite side
of the brain (Lund, 1965) such that the unilaterally-trained rats should have most
training-related activity restricted to the hemisphere opposite the open eye,
whereas the bilaterally-alternating training should have allocated the learning-
related activity about equally to both hemispheres. Both groups had been
previously subjected to transection of the corpus callosum, a “split-brain”
procedure that eliminates communication between the two hemispheres of the
brain. Controls that were surgically operated and subsequently handled but not
trained were divided into unilaterally and bilaterally occluded groups.
The result indicated increased dendritic branching, a correlate of
increased synapse number, in both hemispheres of the alternately trained group
relative to a non-trained group and only in the non-occluded hemisphere of the
unilaterally trained group. These results indicate that either training or trainingrelated activity drives dendritic plasticity.
reach training -- again, plasticity (dend. branching) limited to where
neural activity occurred
Transition between previous paradigm/though and this one Greenough et
al. (1985) used unilateral and bilateral training to study the effects of forelimb
reaching on plasticity in rat primary motor cortex of the trained vs. untrained (or
activated vs. unactivated) hemisphere. These animals were compared to
untrained controls AWK. The results in this study were similar to those of Chang
and Greenough (1982): for deep pyramidal neurons of the type that control
forelimb activity, dendritic branching was greater in the hemisphere opposite
trained forelimbs than in….. For more superficial pyramidal neurons, there were
effects of training, but these effects were not restricted to the “trained” side in
unilaterally-trained animals tie in Gilbert work on interhemispheric changes via
horizontal connections??? do you not want to mention the forked-apicals?
(Withers and Greenough, 1989). Taken with the study above, these results
indicate that learning or some other aspect of training-related activity drives
morphological change in neurons. Both experiments make clear that nonspecific effects such as globally-acting hormonal or metabolic differences, which
would be expected to alter comparable regions of the brain whether or not they
were selectively activated by learning-related activity, were not the primary
driving force behind these observations. XXXXXXXx
how to distinguish between learning- and motor/sensory activitybased neural activity??
An obvious issue remaining is that with which we opened this section:
whether activity or learning causes structural changes in the brain.
AC/VX/IC I’m trying to combine work in cerebellum & motor cortex
To address this issue of non-specific effects more directly, Black et al.
(1990) designed a paradigm in which adult rats were given the opportunity for
either 1) a substantial amount of learning with relatively little physical activity (AC
below), 2) a substantial amount of physical activity with relatively little learning
(FX and VX below) or 3) minimal opportunity for physical activity or learning (IC
below). ACrobatic rats (AC) completed a multi-element elevated obstacle course
that required learning significant motor skill while providing only limited exercise.
Forced eXercise (FX) rats ran on a treadmill, reaching durations of 60 minutes a
day, exercising but with very little opportunity for learning. Voluntary eXercise
(VX) rats had access to running wheels attached to their cages and were the only
group to exhibit increased heart weight, a sign of aerobic exercise. Inactive
Condition (IC) rats were merely removed from their cages for brief daily
experimenter handling, providing neither activity nor learning. Results were clear
in initial studies focusing on cerebellar cortex.
the rest of this segment goes like this…. learning was associated with
neuronal changes; activity was associated with non-neuronal changes.
(observed in both cerebellar and motor cortex)
When the number of synapses per neuron was measured, as depicted in
Figure 3A, the learning group, AC, exceeded the other 3 groups, which did not
differ, suggesting that when learning takes place (and not just as a result of
neural/motor activity), new synapses are formed. By contrast, as Figure 3B
shows, when blood vessel density was measured, the FX and VX groups both
had more more what? AWK than the AC or IC groups, which did not differ; this
suggests that the formation of new capillaries was driven by neural activity, and
not by learning. (the role of this and other non-neuronal changes will be
discussed further below)
It should be noted that these effects are not limited to cerebellar cortex.
Kleim et al. (papers and absts) have described synaptogenesis and changes in
synapse morphology in association with the same AC motor learning procedure
in the somatosensory-somatomotor forelimb cortex of rats. The first
morphological change to occur is, on average, an increase in the size of PSDs,
PSD BEEN DEFINED YET? which occurs within one to two days after training
begins. Subsequently, at the next day examined, day 5, an increase in the
number of synapses per neuron was detected, and the average size of synapses
decreased, possibly because the new synapses were, on average, smaller than
the pre-existing synapse population. The increase in synapse number was
maintained, drifting slowly, but not statistically, upward across the remainder of
training. As training progressed, the average size of synapses again increased,
possibly suggesting that the new synapses were growing larger or that the
population of synapses overall was doing so. A schematic interpretation of these
findings appears in Figure 4. There is a long history of evidence for involvement
of synapse size changes in plasticity that cannot be reviewed here due to space
limitations (is there a Harris or other review to which we could refer?) (Ask
Jeff for input on this paragraph.)
There is one other interesting thing about these (cerebellar) synapses—
many of them involve additional postsynaptic spines contacting presynaptic
varicosities on which one or more spines already exist (Federmeier et al.,
submitted). The implications of this finding for wiring diagram level models of the
learning process remain to be determined. It should be noted that this
phenomenon is not unique to the cerebellum—we have seen multiple
postsynaptic contacts increased on excitatory morphology presynaptic
varicosities in the visual cortex of rats reared in complex environments in
comparison to individually-caged control rats (Jones et al., 1997).
Role of non-neuronal changes in learning / activity based plasticity. –
MAINTENANCE!!!!
One is Brenda's 1994? Paper showing the correlation between synapse number
and astrocyte Vv. The other is Jeff's astrocyte persistence paper.
Regulation of Astrocyte Plasticity
Is this redundant? This was mentioned in the section on non-neuronal
plasticity and perhaps should merely be elaborated more in that section there are
two studies that might be discussed in more detail either in that section or here.
Tj's ensheathment paper fits in this discussion. The point of putting it here is by
way of a segue into a discussion of the tendency to ignore non neuronal (or even
nonsynaptic) changes.
BILL, IT SEEMS THAT MOST OF THIS PARAGRAPH PROVIDES FURTHER
SUPPORT FOR THE NON-GLOBAL (METABOLIC) EFFECT OF ACTIVITY ON
PLASTICITY, BUT DOESN’T SAY MUCH ABOUT “DIFFERENT TYPES OF
PLASTICITY. MAYBE YOU CAN INTEGRATE IT INTO OTHER PARTS OF
THE TEXT, OR MOVE THE WHOLE THING…..
Although differential experience can induce widespread plastic changes
within the brain, the concept that different kinds of plasticity occur in different
situations, and suggests that the type and location of the plasticity is dependent
upon the nature of the experience (Morris et al., 1989; Klintsova & Greenough,
1999). As discussed above, motor training experiences that involve the
development of motor skill induce changes in synapse number within the
cerebellar and motor cortices while extensive repetition of unskilled movements
causes non-neuronal changes, but no change in synapse number (Black et al.,
1990; Kleim et al., 1998c; Kleim et al., 1996; Kleim et al., 2002b). Similarly, the
acquisition of skilled forelimb movements causes a reorganization of forelimb
movement representations within motor cortex (Nudo et al., 1996; Kleim et al.,
1998a) while extensive repetition of unskilled movements (Plautz et al., 2000;
Kleim et al., 2002a) and forelimb strength training (Remple et al., 2001) do not.
However, strength training does increase synapse number within the ventral
spinal cord but motor skill training does not (Kleim et al., 2001). Differential
patterns of plasticity can also be observed across different forms of learning. For
example, complex motor skill training does not alter synapse number within the
deep cerebellar nuclei (Kleim et al., 1998b) whereas eye blink conditioning does
(Bruneau et al., 2001). BUT WHO IS SAYING THAT THESE DIFFERENT
FORMS OF ACTIVITY ARE UTILIZING THE SAME AREAS??? CAN WE BE
MORE SPECIFIC ABOUT “DEEP CEREBELLAR NUCLEUS”?? Even within a
specific learning experience plasticity can be found within some brain regions but
not others. DOESN’T THIS SIMPLY SAY THAT NOT ALL BRAIN AREAS ARE
INVOLVED IN ALL BEHAVIORS? Complex housing causes dendritic
hypertrophy in visual and sensory cortices but not in prefrontal or temporal cortex
(Kolb ref). SAME ISSUE AS ABOVE. Skilled forelimb reach training causes a
reorganization of movement representations and an increase in synapse number
within the caudal forelimb area but not within the neighboring rostral forelimb
area (Kleim et al., 2002b). THIS SEEMS OUT OF PLACE, IMPORTANT, BUT
NOT IN THE RIGHT SPOT . Interestingly, reach training induced increase of
field potential in forelimb contralateral to preferred limb (vs. ipsilateral) in layer
II/III (Rioult-Pedotti et al., 1998), suggesting a selective strengthening of
horizontal cortical connections associated with learning new motor skill.
Complex motor training is associated with an increase in synapse number within
the cerebellar cortex (Kleim et al., 1998c) but not within the deep cerebellar
nuclei (Kleim et al., 1998b). REDUNDANT FROM ABOVE. The specificity of the
plasticity can even be reduced to subpopulations of neurons within the same
brain region. For example, complex housing causes dendritic hypertrophy within
cerebellar Purkinje cells but not granule cells (Floeter and Greenough, 1979).
Reach training causes dendritic hypertrophy within layer II/III of the motor cortex
that is restricted to a specific class of pyramidal cells (Withers and Greenough,
1989). Finally, plasticity can even be observed to be restricted to specific
afferents onto individual neurons. Complex motor skill training causes an
increase in parallel fiber synapses onto Purkinje cells but not climbing fibers
(Kleim et al., 1998c). Eyeblink conditioning causes an increase in the number of
excitatory synapses within the anterior interpositus without alter inhibitory
synapse number (Bruneau et al., 2001). Similarly strength training causes an
increase in excitatory but not inhibitory axosomatic synapses within the ventral
spinal cord (Kleim et al., 2001).
THESE CONCEPTS SEEMS TO GO WITH THIS SECTION:
Synaptic specificity supported by “synaptic tag” that is localized and
protein-synthesis independent (Frey and Morris, 1997). Fits concept of
metaplasticity in that history of synapse (even sub optimal stimulation patterns)
pre-disposes synapse to subsequent modification.
Could consider integrating notion of differential parameters
necessary/sufficient to induce LTP (emphasize model of learning, not that it is
equivalent or necessary for) in multiple areas of the brain. That one type of
stimulus does not result in the same effect in numerous areas of the brain
suggests (obviously) differential make-up of that area and surely different
mechanisms. This notion would simply parallel our argument of different “types of
plasticity” (as defined anatomically), with physiological correlates (Yun et al.,
2002); (Trepel and Racine, 1998).
these next two sections seem out of place now…..
This goes on the end or might be placed elsewhere:
A note on Long-term potentiation
Engert and Bonhoeffer have reported apparent synaptogenesis in vitro in
association with LTP induction. High-frequency stimulation produced enhanced
growth of filopodia-like protrusions in CA1 slices (viewed with 2-photon), an effect
that was blocked by NMDAR antagonism (Maletic-Savatic et al., 1999).
ALSO WORK OF ANDERSEN AND SOLENG (Andersen and Soleng,
1998) WHO SHOWED SYNAPTOGENESIS ASSOCIATED WITH LTP AND
SPATIAL LEARNING (THEY SUGGESTED BIFURCATION/BRANCHING OF
EXISTING SPINES)
At least 3 studies, HOWEVER, dissociate LTP from spatial behavior and
morphological change. The primary point I want to make is the apparent
dissociation of LTP from EC effects on synapses published by J. Tsien in Nature
Neuroscience. This suggests that LTP and synaptogenesis are independent
phenomena. I am not sure what the range of the evidence is or the weight of it
(e.g., other more recent work that bears on this issue, most of which are likely to
have cited both of the above studies (Tsien and E-B) and hence should be
locatable via the science citation index, which I have not used for the last million
years), but the dissociation to me seems most powerful-synapse addition may
mediate LTP, but synapse addition need not involve an LTP-like process for its
induction.
On the Horizon: A Role for Protein Synthesis at the synapse
Since the first report of morphological evidence for protein synthesis at the
synapse (Steward & Levy, 1992) there has been a growing literature
investigating this phenomenon. Synaptic and dendritic protein synthesis have
been shown to be activated by metabotropic glutamate receptors in some cases
(e.g., Weiler & Greenough, 1993; Weiler et al., 1994, 1997; Eberwine PNAS-still
in press?) and by NMDA receptors as well (Sheetz et al., 2000). Proteins
synthesized at synapses include the fragile X protein FMRP and
calcium/calmodulin-dependent protein kinase II (CAMKII). FMRP has also been
shown to be necessary for the mGluR-dependent synthesis, which is not
observed in FMR1 knockout mice (cite Spangler abstract). Plasticity-inducing
forms of electrical stimulation have been shown to trigger the transcription and
transport of mRNA for the protein ARC to dendritic sites of stimulation, where it is
translated (Steward and Worley references). mGluR1 activation, ARC
synthesis and CAMKII activity have been proposed to be involved in various
forms of plasticity (Huber/Bear work; Steward; Mary Kennedy), although details
of the specific functions of synaptic or dendritic protein synthesis are still under
investigation. Do you think we need to say anything more here? The chapter is
really not "about" this, and I am not sure (but open to suggestions) what
additional data makes sense to include.
The principal thing I want to add at this point is a summary that comes
back to the main point of the chapter--that we are only looking at a small portion
of what the brain does when it accomplishes plastic change. I really would like
your feedback on the earlier stuff. I have attached a copy of the chapter file as it
exists on my computer. There is a demarcated line below which all of my
additions occur, so it should be possible to just paste what you have and the part
that I added together.
ANOTHER “TYPE” OF PLASTICITY TO CONSIDER: NEUROGENESIS.
Housing in an complex environment resulted in enhanced survival of “new
neurons” (aka, neurogenesis) (tested 4 weeks later) but no effect on number
generated (tested 1 day after BrdU injection) (Nilsson et al., 1999).
Neurogenesis rate is doubled in dentate following training on an
associative learning task requiring hippocampus (Gould et al., 1999).
DO WE WANT TO DISCUSS ANY SORT OF TEMPORAL COMPONENT
THAT COULD DIFFERENTIALLY INFLUENCE THE “TYPE” OF PLASTICITY
GOING ON? FOR EXAMPLE:
Consider temporal component of morphological changes. For example,
following one-trial learning, the density of axospinous synapses was increased
77% in IMHV of chicks and PSD (measured by “height” of synapse) was
decreased at 1 HR post training. Yet 24-hours later there were no differences
(Doubell and Stewart, 1993). Of course this is consistent with Kleim work,
possibly integrate this study with that section???
STRUCTURE-FUNCTION RELATIONSHIP, NEEDS TO BE
INCORPORATED SOMEWHERE:
Housing in complex environment resulted in 50% increase in somatotopic
representation of forepaw, most of which came from glaborous surface and more
specifically, from digit tips (Coq and Xerri, 1998).
Primary neurons and the cortex: Is the current approach overly-restrictive?
Historically, investigations into neuronal plasticity have focused, almost
exclusively, on modifications in the structure and function of primary neurons and
circuits. While the importance of these systems can not be overlooked, it belies
the fact that neurons not directly involved in such pathways far out number those
that do. Seress et al. (Seress et al., 2001) have reported that 95% of terminals
forming asymmetric synapses with parvalbumin-positive dendrites in the dentate
and strata pyramidale and lucidum of CA3 originated from granule cells. SO
WHY DO WE ALWAYS LOOK @ PYRAMIDAL CELLS? Modification of
“modulatory” neurons can have dramatic effects on the function of primary
neurons. For example, receptive field size in sensory cortex has been shown to
be sensitive to pharmacological disinhibition (Tremere et al., 2001a); (Tremere et
al., 2001b); (Jacobs and Donoghue, 1991). The source of such inhibition likely
stems from extragranular layers of cortex as rapid (physiologically-defined)
changes in both visual ((Trachtenberg et al., 2000); (Trachtenberg and Stryker,
2001)) and somatosensory cortices ((Diamond et al., 1994)) have been reported
to occur prior to the expression of modifications in layer IV. Finally, observations
by Gilbert and colleagues ((Gilbert and Wiesel, 1979); (Gilbert, 1992)) further
suggest that horizontal connections may be the source of such changes in visuoand topographic-maps.
The cerebral cortex is often-times considered “where” changes occur,
ignoring subcortical contributions and importance. Numerous changes outside
cortex such as striatum ((Comery et al., 1995); (Comery et al., 1996)), spinal cord
((Devor and Wall, 1978)), temporal dynamics of change are distributed across
the neuroaxis ((Faggin et al., 1997)),
In summary, brain plasticity appears to be a phenomenon that is not
restricted to elements that are neuron-specific. In fact, it could be argued that
neuronal plasticity is but a small fraction of the overall changes that occur in
response to experience and that we are just beginning to understand the
importance of these other forms of brain plasticity. Blah, blah, blah.
CHAPTER WORKING NOTES:
MSVs—Kara; TJ; specialized synaptic morph changes.
Tissue cultures lacking astrocytes—how good a model? Lack of synapse
formation in cultures without astrocytes ((Ullian et al., 2001)). Moreover, even
when synapses do form, they are functionally immature. Obvious implications on
studies of “synaptic plasticity” in vitro.
Lack of astro part of ECM. Lack of basis for TPA, other actions probably
involved in synaptogenesis. MMP3, MMP6, MMP9 (Metalomatrix proteins),
stromolysin, gelatinase. Roles of Astros, ECM, TPA, etc. in synaptogenesis;
adhesions; rec aggregation
Incorporate Harris, Matus, Segal. Motility and shape issues. Put together
a model, slow accumulation of synapses via overproduction-selection as a basis
for the stable long-term substrate of memory; plus fast shape changes, PSD size,
perfs, interpret multiple synapses from local and wiring diagram view. NOT
SURE WE HAVE TIME FOR THIS NOR IS THIS NECESSARILY CONSISTENT
WITH UNDERLYING THEME OF THE PAPER.