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dc.contributor.advisorDouglas, Rodney James-
dc.contributor.advisorHahnloser, Richard-
dc.contributor.authorRohrkemper, Robert-
dc.date.accessioned2018-07-27T08:13:31Z-
dc.date.available2018-07-27T08:13:31Z-
dc.date.issued2009-
dc.identifier.isbn978-3847327462de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/8658-
dc.description.abstractA principle goal of Neuroscience is to understand how brain-like computations are enabled by the structure of the cortex. Complex developmental processes required to build and maintain the cortex point to the importance of the brain’s structural properties. During development, significant resources, time, and energy are required—suggesting a need to optimize to build the best structure possible. In this work, tools have been developed based on state transition analysis for understanding when computational performance is enhanced by changes in the topology. A dynamic state is defined as the set of neurons that are active at any moment. This state changes as neurons are affected by external and recurrent inputs. In these reservoirs of linear-threshold neurons, performance can be optimized by evaluating the learning capacity of a network when parameters are changed. It is demonstrated that both having more unique states and more transitions between these states will improve the ability of the network to learn and match a target signal with a higher precision. These results allow for optimizing the computational abilities of a small group of neurons by changing the network topology.de_CH
dc.format.extent214de_CH
dc.language.isoende_CH
dc.publisherETH Zürichde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleEffective topologies for computation in cortex-like networksde_CH
dc.typeDissertationde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitut für Wirtschaftsinformatik (IWI)de_CH
zhaw.publisher.placeZürichde_CH
dc.identifier.doi10.3929/ethz-a-005951784de_CH
zhaw.originated.zhawNode_CH
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Rohrkemper, R. (2009). Effective topologies for computation in cortex-like networks [Doctoral dissertation, ETH Zürich]. https://doi.org/10.3929/ethz-a-005951784
Rohrkemper, R. (2009) Effective topologies for computation in cortex-like networks. Doctoral dissertation. ETH Zürich. Available at: https://doi.org/10.3929/ethz-a-005951784.
R. Rohrkemper, “Effective topologies for computation in cortex-like networks,” Doctoral dissertation, ETH Zürich, Zürich, 2009. doi: 10.3929/ethz-a-005951784.
ROHRKEMPER, Robert, 2009. Effective topologies for computation in cortex-like networks. Doctoral dissertation. Zürich: ETH Zürich
Rohrkemper, Robert. 2009. “Effective Topologies for Computation in Cortex-like Networks.” Doctoral dissertation, Zürich: ETH Zürich. https://doi.org/10.3929/ethz-a-005951784.
Rohrkemper, Robert. Effective Topologies for Computation in Cortex-like Networks. ETH Zürich, 2009, https://doi.org/10.3929/ethz-a-005951784.


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