The aim of this thesis is to develop a novel technique for the estimation of firing rate dynamics from single-unit recordings of neural pulse trains. This method applies an offline digital filtering technique to extract information transmitted by a neuron in teens of a rate code. While there is increasing evidence that the traditional rate coding cannot account for all the information transmitted by a cell, and that information may also be contained in the precise timing of spikes, the firing rate signal remains the benchmark by which the vast majority of electrophysiological studies relating neural activity to functional behaviour have been interpreted. Nevertheless, there does not seem to be an agreement on a single definition of a rate code let alone a consensus on an optimal estimation method. This study raises significant concerns about the validity of some of the most common methods in systems neuroscience, and proposes a simple yet more robust alternative. This latter is based on the convolution of the spike train with an optimally designed Kaiser window. Using computer-simulated as well as experimental data obtained from single-unit recordings of vestibular canal afferents, the proposed technique is shown to consistently outperform the current methods and even to permit robust estimations under time-varying conditions. These results suggest that estimates acquired with the conventional methods are biased and hence models of neural dynamics based on these latter may not be reliable.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.112387 |
| Date | January 2007 |
| Creators | Cherif, Sofiane. |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Engineering (Department of Biomedical Engineering Dept.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002698783, proquestno: AAIMR51077, Theses scanned by UMI/ProQuest. |
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