Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
A Brain Adaptation View of Plasticity: Is Synaptic Plasticity An Overly Limited Concept? There is a long tradition, traceable to the early musings of Ramon y Cajal, of focusing upon the neuron as the only plastic cell type of any importance within the brain, and upon the synapse as the only important plastic aspect regulating the interactions among neurons. While neuronal plasticity is without question an important aspect of brain function, it has become increasingly clear that other cellular elements of brain are plastic and that their plasticity can contribute to brain function. Moreover, it is becoming clear in work of others that there are multiple forms of synaptic plasticity: the synaptic number response to a complex environment, for example, occurs in animals genetically rendered incapable of the most common form of LTP. Our work and that of others indicates that oligodendrocytes, astrocytes, vasculature, and perhaps other cellular elements exhibit plasticity quantitatively equivalent to that of neurons in the developing and mature brain and that modifications of these cellular elements may be brought about by experience. It also suggests that multiple forms of plasticity may occur at the synapse. In short, while memory researchers largely focus on naturallyand artificially-induced changes in synaptic connectivity, the brains of real animals (and presumably people) in realworld situations are in a dynamic state in which synaptic adjustment may in some cases be a relatively small part of the mix. The intent of this review is to consider the data that point to this view and consider how we might assess nonsynaptic effects of learning and/or determine whether the effects of learning upon measures of brain functional organization may already be affected by these nonsynaptic changes. Since the early speculations of Tanzi and Ramon y Cajal, the synapse has been the principal proposed site of plasticity underlying learning and memory in the brain. Tanzi () initially emphasized the possibility of strength changes in pre-exiisting connections while Ramon y Cajal () stressed the formation and loss of connections. The ability to examine these possibilities depended on development of adequate tools, but, by the early 1970s, electrophysiological and anatomical evidence for the ability of the nervous system to alter its functional connectivity in accord with its experience was becoming reasonably well established. Electrophysiologically, longterm potentiation had been described (Bliss and Lomo, 1973). Anatomically, there was evidence that synapses in the late developing and adult nervous system could both form and change in size in response to experience; innervation of neurons by surviving axons occurred spontaneously in response to denervation (Sprouting, Raisman, Lynch references) [when was first comparable Aplysia report?]; exposure to a complex environment from weaning through adolescence increased dendritic field dimensions (Volkmar & Greenough, 1972) and synaptic size (West & Greenough, 1972) in the rat visual cortex. This paper summarizes progress in understanding the brain plasticities thought to be associated with learning and memory, focusing heavily on our own work, since those relatively early beginnings. A relatively early specific demonstration that synapses formed in response to experience was the report by Turner and Greenough (1983, 1985) that there were more synapses per neuron in upper layers of the visual cortex in rats that had been reared from weaning in a complex environment. This rearing and adult housing paradigm, pioneered by Hebb (1949) and his students (e.g. Hymovitch, 19xx) using behavioral measures, and first used as a tool for exploring brain plasticity by Krech, Rosenzweig and Bennett (19xx), has been used extensively to examine the range of plasticity of various elements of brain other than neurons, but most of these results have failed to become incorporated into the continuing literature on brain plasticity. Early in this history, Diamond ** (19xx) reported that glial cells in visual cortex exhibited morphological changes in response to experience in paralell with the changes reported in neuronal dendrites and synapses. We have subsequently examined plasticity of nonneuronal elements of the cerebral cortex in response to complex environment exposure in some detail. Following up on these initial demonstrations of dendritic and synaptic responsiveness to rearing conditions, neuronal responsiveness to has subsequently been demonstrated in a wide variety of brain structures: hippocampus (Mosers et al.), basal ganglia (Comery papers), cerebellar cortex (Greenough, McDonald, Parnisari, , 19xx)— someone to fill this in with both our data and others.** At this point, neuronal plasticity seems to be the rule rather than the exception in CNS structures, although there are some striking failures to demonstrate it in some cases (Kleim LCN; is this the right thing to say? Kleim now has data showing dentate/interpositus?? plasticity in eyeblink conditioning. Similarly, these forms of neuronal plasticity occur relatively consistently across the age spectrum and do not appear to be restricted to particular critical or sensitive periods of development. Effects of adult exposure to a complex environment have been shown to affect dendritic field dimensions in the visual cortex of adult, middle-aged and even elderly rats (e.g., Juraska et al., 1980; Green et al., 1983; elderly reference). Similarly, cerebellar CHAPTER WORKING NOTES: Tissue cultures lacking astrocytes—how good a model? 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. Also local regulation in dendrites; protein synthesis; dynamic view; incorporate FMRP in this context Do also a TINS—go head to head with Menahem