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The role of network interactions in timing-dependent plasticity within the human motor cortex induced by paired associative stimulation

Spike timing-dependent plasticity (STDP) has been suggested as one of the key mechanism underlying learning and memory. Due to its importance, timing-dependent plasticity studies have been approached in the living human brain by means of non-invasive brain stimulation (NIBS) protocols such as paired associative stimulation (PAS). However, contrary to STDP studies at a cellular level, functional plasticity induction in the human brain implies the interaction among target cortical networks and investigates plasticity mechanisms at a systems level.

This thesis comprises of two independent studies that aim at understanding the importance of considering broad cortical networks when predicting the outcome of timing-dependent associative plasticity induction in the human brain. In the first study we developed a new protocol (ipsilateral PAS (ipsiPAS)) that required timing- and regional-specific information transfer across hemispheres for the induction of timing-dependent plasticity within M1 (see chapter 3). In the second study, we tested the influence of individual brain structure, as measured with voxel-based cortical thickness, on a standard PAS protocol (see chapter 4). In summary, we observed that the near-synchronous associativity taking place within M1 is not the only determinant influencing the outcome of PAS protocols. Rather, the online interaction of the cortical networks integrating information during a PAS intervention determines the outcome of the pairing of inputs in M1.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:15-qucosa-129770
Date04 December 2013
CreatorsConde Ruiz, Virginia
ContributorsMax Planck Institute for Human Cognitive and Brain Sciences, Neurology, Prof. Dr. Arno Villringer, PhD Patrick Ragert, Prof. Dr. med. Joseph Claßen, Prof. Dr. med. Michael Nitsche
PublisherUniversitätsbibliothek Leipzig
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:doctoralThesis
Formatapplication/pdf

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