| dc.contributor.author | Standage, Dominic. | en_US |
| dc.date.accessioned | 2014-10-21T12:33:57Z | |
| dc.date.available | 2007 | |
| dc.date.issued | 2007 | en_US |
| dc.identifier.other | AAINR31493 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10222/54955 | |
| dc.description | Computational models have a long and fruitful history in neuroscience, addressing the information-theoretic properties of neural substrates and making predictions to guide physiological and psychological enquiry. Computational analyses and simulations have been extensively applied to the study of memory and are rightly considered core methods of this broad research field. Here, we study memory at two levels of analysis, investigating neural representations in cerebral cortex and synaptic plasticity. | en_US |
| dc.description | Neural field models have been used to study numerous cortical regions and functions. Their use is thus compatible with the view that cortex is, in general, architecturally and mechanistically uniform, regardless of the function of specific cortices. In this regard, we use neural field models to investigate interactions within and between regions of cortex. We demonstrate parameter regimes that correlate with experimental findings on the active maintenance of short term memories and the spatial distribution of selective visual attention, making predictions for further experimental research. | en_US |
| dc.description | Innumerable computational models show that learning results from activity-dependent changes in synaptic strength. In this regard, we extend earlier analyses of correlations between pre- and post-synaptic spike timing to the case of highly correlated spikes, showing a unique relationship between the contributions of spike timing and spike rate to plasticity. We also demonstrate that the common use of weight-dependent terms in spike-time dependent learning rules is not supported by experimental data, and we shout that the data on which these terms are based may reflect experimental artifacts. Our research addresses important questions about, cortical processing, and our results are compatible with theories of cortex in which attention and novelty-detection emerge from activity-dependent plasticity between hierarchically-arranged, bidirectionally-connected cortical regions. | en_US |
| dc.description | Thesis (Ph.D.)--Dalhousie University (Canada), 2007. | en_US |
| dc.language | eng | en_US |
| dc.publisher | Dalhousie University | en_US |
| dc.publisher | | en_US |
| dc.subject | Biology, Neuroscience. | en_US |
| dc.subject | Computer Science. | en_US |
| dc.title | Mechanisms of short term and long term memory in cortex: Neural fields and synaptic plasticity. | en_US |
| dc.type | text | en_US |
| dc.contributor.degree | Ph.D. | en_US |
