The distinction between hebbian and homeostatic mechanisms is maybe not necessary and even confusing. Nevertheless, modifications of the network are certainly always a compromise between the promotion of individuality (hebbian) and the general interest (homeostatic). Here, macro-structural changes are discussed at the light of this duality.
Homeostatic regulation of the number of excitatory contacts is one of the principal reasons for which spine turnover is an uninterrupted process throughout life. Adaptation of spine density and
Discussion! Data synergy
related synapses occurs during the developmental refinement of connections and when the general levels of activity are altered (Zuo et al., 2005b).
Hebbian mechanisms are often associated with functional and micro-structural changes at existing synapses while macro-structural changes are generally considered as homeostatic. However, hebbian regulation of spinogenesis and pruning can be observed in our model of LTP induced macro-structural plasticity. First, new protrusions preferentially grow close to activated synapses.
Second, non-activated spines are selectively eliminated in comparison to activated contacts that are stabilized. These two observations don’t exclude the later participation of homeostatic mechanisms but they highlight the synapse specific nature of these initial macro-structural events.
Metaplasticity represents modifications of the threshold for the induction of further hebbian plasticity. This plasticity of plasticity has been first reported for the induction of functional and micro-structural changes at individual spines. Nevertheless, it has also been recently described as diffusing to surrounding synapses59 (Harvey and Svoboda, 2007). Our observation of spinogenesis close to previously stimulated synapses could rely on the same mechanisms but would concern macro-structural changes.
Taken together, the distinction between hebbian and homeostatic macro-structural changes is artificial because both types of plasticity are certainly intricate. However the possibility to identify hebbian properties in mechanisms of spinogenesis and pruning is an additional evidence in favor of their correlation with functional changes and of their importance for information storage.
Spinogenesis
Spine formation can be involved in the formation of new contacts with preexisting or new partners.
Both cases have been illustrated after activity induction with an increase in the proportion of MSBs contacted by spines form the same dendrite (Toni et al., 1999) or from different neurons (Nagerl et al., 2007). Results concerning the origin of the second spine are contradictory, but the interesting point is the possibility for the system to interact directly with preexisting connections. Thus spinogenesis could reinforce or challenge a preexisting contact.
In our model of activity, we know that the new spine originates from the same dendrite as the preexisting one but we ignore if it connects to the same presynaptic unit. Thus, it is interesting to consider two opposite possibilities: a rewiring or a change in weight that challenges or reinforces the preexisting synapses respectively. I voluntarily set aside the possibility of a competition
between two spines contacting the same elements as well as a possible reinforcement by connecting a different partner. The correct appreciation of these changes requires a strong knowledge of
hypothesis concerning signal processing, which is out of the range of this work.
Competition hypothesis:
In this model, the new spine connects a novel presynaptic partner to challenge the preexisting synapse. This rewiring process induces a competition between neighbor synapses and promotes elimination of the weakest one. In our LTP experiment, the differential survival of preexisting spines could result of a competition triggered locally by spinogenesis. Synaptogenesis with a novel
Discussion! Data synergy
59 10 "m
target close to a weak non-activated preexisting synapse could promote its removal. However, the lower probability to observe spinogenesis close to non-activated synapses is poorly compatible with this hypothesis60. Additionally, stability of new spines should be smaller or higher in function of their proximity to activated or non-activated preexisting spines respectively, but all new spines exhibit the same stability independently of their localization.
Reinforcement hypothesis:
Here we suggest that new spines connect the same presynaptic partner as selected preexisting synapses to reinforce the synaptic weight of some important contacts. In favor of this hypothesis, we reported that spinogenesis preferentially occurs close to preexisting activated synapses after LTP induction. However, new spines growing in proximity of potentially important synapses are not better stabilized than the small number of other new spines that are observed close to non-activated and potentially less important synapses. Maybe these non-activated synapses that exhibit a new spine in proximity represent a subclass that is also stabilized despite their not direct stimulation during LTP induction.
Taken together, hypothesis on the exact role played by LTP-induced spinogenesis are principally limited by the unknown nature of the presynaptic partner and by the relatively low temporal resolution of macro-structural changes description that could miss fast competition events.
Pruning
The role played by spine pruning is more difficult to discuss, because of the lack of data concerning the characteristics of this phenomenon in the literature and in our experiments. However, spine elimination seems to depend on the levels of activity (Zuo et al., 2005b). More precisely our data show that the relative absence of activity in comparison to other contacts favors the elimination of some less stimulated preexisting protrusions.
In summary, we reviewed the changes in structure and function during development and activity and proposed hypothesis to explain the putative links between morphology, stability and
functionality of dendritic spines. Unsurprisingly, the macro-structural aspects of spine dynamics are poorly described and understood in the context of functional and micro-structural changes. This lack of data is mainly due to differences concerning the timing. In contrast to micro-structural and functional changes that are relatively fast events, macro-structural dynamics operate generally on longer time scales that require a long-term follow-up to be correctly understood. Moreover, these long-lasting observations are often incompatible with other measurements like electrophysiological recordings that are necessary to investigate the functional aspects. Finally, spinogenesis and pruning appear to be severely delayed in comparison to functional and micro-structural changes that are early events after induction of plasticity.
Discussion! Data synergy
60 Except if this result is biased by our relatively long observation interval that could miss fast events
Conclusion
It is tempting to try the comparison between neural and electronic networks. Both rely on electric charges to transmit, process and store information but differ concerning their state and composition:
mineral and inert versus organic and living. Further comparison is out of the range of this work and beyond my knowledge. Nevertheless, it could be interesting to use the assumption that
transmission, processing and storage of information could represent the three pillars of all networks independently of their size and composition.
In the neural network information is transmitted without alteration by APs that flow in a saltatory mode through axons, while processing is proposed to occur mainly through integration of individual PSPs along the dendritic arborization (Spruston, 2008). Since the first observation of LTP,
information storage has been proposed to occur through modifications of the transmission strength at synapses and further investigations have even proposed an almost exclusive postsynaptic
mechanism, at least in hippocampus (Nicoll, 2003).
Storage of information at dendritic spine could rely on functional and structural mechanisms. Long-term modifications of synaptic transmission strength have been initially described by LTP-LTD mechanisms. Observation of spines after these hebbian changes also revealed persistent morphological alterations like spine enlargement or shrinkage and even spinogenesis or pruning (De Roo et al., 2008).
Thus, the neural network would have this particularity that localization of information storage (spines) would be at the junction between transmission (axons) and processing (dendrites).
This hypothetical intricacy render the study of brain functioning difficult. Without clearly defined spatial specificity, observation of changes at synapses can be due to transmission, processing, storage or even a combination of these mechanisms.
To distinguish information storage from the two other characteristics of the network, we first tried to define the basal properties of spine structural dynamics in our developmental model. Second, in conditions of hebbian changes on which information storage seems to rely at least partially, we tried to correlate structural alterations with functional modifications to identify those which could be linked to storage mechanisms.
Finally, we found that adaptation of the network to rhythmic stimuli like during mechanisms of learning or memory does not only depend on modulations of the transmission strength at the synaptic level, but also implies a long-lasting remodelling of synaptic contacts at the level of the dendritic tree that tends to consolidate efficient synapses while eliminating the other ones. Moreover, the establishment of new functional contacts close to busy synapses could participate to the spatial grouping of synergic inputs.
Future studies will benefit form technical developments to broad the field of research from spines to complete synapses and to assess simultaneously variations of synaptic structure and function over months in living and freely moving animals. However, if synapses are really this meeting point between the three pillars of information, then memory traces should not only depend on one structural basis like dendritic spines but should imply modifications of the entire information pathway, implicating also axons and dendrites. The complexity of this arrangement suggests that
Discussion
further investigations should maybe consider the global effects of connections instead of focusing on its multiple sources. Analysis of neuronal oscillations though frequencies analysis is certainly a promising way a research.
Discussion! Conclusion
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