Thesis (M. App. Sc.)--Carleton University, 2004. / Includes bibliographical references (p. 119-122). Also available in electronic format on the Internet.

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.

No description available.

In this paper, we investigate how controlled changes to image properties and orientation affect eye movements for repeated viewings of images of natural scenes. We make changes to images by manipulating low-level image content (such as luminance or chromaticity) and/or inverting the image. We measure the effects of these manipulations on human scanpaths (the spatial and chronological path of fixations), additionally comparing these effects to those predicted by a widely used saliency model (L. Itti & C. Koch, 2000). Firstly we find that repeated viewing of a natural image does not significantly modify the previously known repeatability (S. A. Brandt & L. W. Stark, 1997; D. Noton & L. Stark, 1971) of scanpaths. Secondly we find that manipulating image features does not necessarily change the repeatability of scanpaths, but the removal of luminance information has a measurable effect. We also find that image inversion appears to affect scene perception and recognition and may alter fixation selection (although we only find an effect on scanpaths with the additional removal of luminance information). Additionally we confirm that visual saliency as defined by L. Itti and C. Koch's (2000) model is a poor predictor of real observer scanpaths and does not predict the small effects of our image manipulations on scanpaths.