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A paradigm for thinking about wholes, their constitution and re-production, has long been provided by living organisms. While the emphasis is often on the relation between parts and wholes - between the functionally differentiated organs and the organism, or, on a lower level, between cells and organs - Robert Meunier and Valentine Reynaud's essay 'The Innate Plasticity of Bodies and Minds: Integrating Models of Genetic Determination and Environmental Formation' poses the question of the whole in biology with respect to the organism and its environment. A developmental system involves not only what we conventionally discern as the organism, that is, initially, the fertilized egg and the cellular mass arising from it by cell division, but also the physical and biological surrounding of the developing embryo. In the sense that not every aspect of the environment plays a role, the organism as part of the system constitutes this whole by determining what has an effect on the process and what does not. On the other hand, by not only enabling development or providing material but instead shaping the process in specific ways, the whole of organism-environment interactions constitutes its part, i.e., the developing organism. If there are therefore different, potentially incommensurable constitutions of the whole developmental system, there are also different ways of identifying the relevant units of selection in evolution, such as the living organism as a whole or the genes as the units of replication. In their essay, Meunier and Reynaud argue for a view on development and evolution that integrates notions of environmental influence and genetic determination. The notion of plasticity that has recently gained currency in the life sciences seems to oppose genetic determination and innateness by underlining the importance of environmental influence. However, while morphological and cognitive development is indeed plastic and sensitive to the environment, the essay emphasizes that the mechanisms and elements enabling a system to respond to influences must be available for development to happen in the first place. These resources for development are not homogeneous 'stuff' that becomes formed by the environment through the course of development. Instead, they are highly structured and specific and thus enable specific responses to contextual conditions. Under varying conditions they will of course appear in different combinations and produce different outcomes. Thus, they enable plasticity. And yet, as they are specific mechanisms and elements, which mainly gain their specificity from the structure of the genetic material on which the environment can act, it appears appropriate to refer to them as innate.
Plasticity supports the remarkable adaptability and robustness of cortical processing. It allows the brain to learn and remember patterns in the sensory world, to refine motor control, to predict and obtain reward, or to recover function after injury. Behind this great flexibility hide a range of plasticity mechanisms, affecting different aspects of neuronal communication. However, little is known about the precise computational roles of some of these mechanisms. Here, we show that the interaction between spike-timing dependent plasticity (STDP), intrinsic plasticity and synaptic scaling enables neurons to learn efficient representations of their inputs. In the context of reward-dependent learning, the same mechanisms allow a neural network to solve a working memory task. Moreover, although we make no any apriori assumptions on the encoding used for representing inputs, the network activity resembles that of brain regions known to be associated with working memory, suggesting that reward-dependent learning may be a central force in working memory development. Lastly, we investigated some of the clinical implications of synaptic scaling and showed that, paradoxically, there are situations in which the very mechanisms that normally are required to preserve the balance of the system, may act as a destabilizing factor and lead to seizures. Our model offers a novel explanation for the increased incidence of seizures following chronic inflammation.