Show simple item record

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorAarnoutse, E.J.
dc.contributor.advisorRamsey, N.F.
dc.contributor.authorVermaas, M.
dc.date.accessioned2014-08-31T17:00:22Z
dc.date.available2014-08-31T17:00:22Z
dc.date.issued2014
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/17952
dc.description.abstractSince the advent of multielectrodes, interest in the low-frequency part of the extracellular field potential (EFP) has surged. Interpreting this electric signal is complicated because it is a superposition of transmembrane currents originating from multiple neuronal processes. The magnitude and shape of the recorded potential are dependent on factors such as the dynamics of the individual sources generating the currents, the amount of synchrony in synaptic activity and the neuron morphology. Here the relation between the EFP and its underlying mechanisms is addressed based on literature studying the signal intracranially (electrocorticogram, ECoG) and intracortically (local field potentials, LFPs). The traditional approach of decomposing the EFP signal based on the power spectrum of the frequencies is evaluated. Several alternatives more sensitive to dissociate between different frequency bands are suggested such as the matching pursuit algorithm and optimization techniques. Furthermore, mathematical modeling schemes are used to describe quantitatively how factors like synchrony and cytoarchitecture affect characteristics of the EFP and how different current sources contribute to the signal. These modeling studies are suggested as a means to predict limitations and optimum experimental stimuli for measurements such as ECoG. Simulating and combining experimental data recorded at different spatial scales with reconstructed neuronal tissue is necessary to optimally make use of the network signaling information embedded in the EFP and is essential for future progress.
dc.description.sponsorshipUtrecht University
dc.format.extent3195731
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleRelating ECoG and the local field potential to underlying mechanisms
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsECoG, LFP, forward modeling, spatial spread, frequency filtering
dc.subject.courseuuNeuroscience and Cognition


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record