dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Aarnoutse, E.J. | |
dc.contributor.advisor | Ramsey, N.F. | |
dc.contributor.author | Vermaas, M. | |
dc.date.accessioned | 2014-08-31T17:00:22Z | |
dc.date.available | 2014-08-31T17:00:22Z | |
dc.date.issued | 2014 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/17952 | |
dc.description.abstract | Since 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.sponsorship | Utrecht University | |
dc.format.extent | 3195731 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.title | Relating ECoG and the local field potential to underlying mechanisms | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | ECoG, LFP, forward modeling, spatial spread, frequency filtering | |
dc.subject.courseuu | Neuroscience and Cognition | |