Electrical and Electronic Engineering - Research Publications

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Author: Grayden, David × End date: 2010 × Type: Journal Article ×

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    The Effect of Visual Cues on Auditory Stream Segregation in Musicians and Non-Musicians
    Marozeau, J ; Innes-Brown, H ; Grayden, DB ; Burkitt, AN ; Blamey, PJ ; Louis, M (PUBLIC LIBRARY SCIENCE, 2010-06-23)
    BACKGROUND: The ability to separate two interleaved melodies is an important factor in music appreciation. This ability is greatly reduced in people with hearing impairment, contributing to difficulties in music appreciation. The aim of this study was to assess whether visual cues, musical training or musical context could have an effect on this ability, and potentially improve music appreciation for the hearing impaired. METHODS: Musicians (N = 18) and non-musicians (N = 19) were asked to rate the difficulty of segregating a four-note repeating melody from interleaved random distracter notes. Visual cues were provided on half the blocks, and two musical contexts were tested, with the overlap between melody and distracter notes either gradually increasing or decreasing. CONCLUSIONS: Visual cues, musical training, and musical context all affected the difficulty of extracting the melody from a background of interleaved random distracter notes. Visual cues were effective in reducing the difficulty of segregating the melody from distracter notes, even in individuals with no musical training. These results are consistent with theories that indicate an important role for central (top-down) processes in auditory streaming mechanisms, and suggest that visual cues may help the hearing-impaired enjoy music.
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    Dynamically adjustable contrast enhancement from cortical background activity
    Meffin, H ; Burkitt, AN ; Grayden, DB (ELSEVIER, 2005-06)
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    Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity-strengthening correlated input pathways
    Gilson, M ; Burkitt, AN ; Grayden, DB ; Thomas, DA ; van Hemmen, JL (SPRINGER, 2009-08)
    Spike-timing-dependent plasticity (STDP) determines the evolution of the synaptic weights according to their pre- and post-synaptic activity, which in turn changes the neuronal activity. In this paper, we extend previous studies of input selectivity induced by (STDP) for single neurons to the biologically interesting case of a neuronal network with fixed recurrent connections and plastic connections from external pools of input neurons. We use a theoretical framework based on the Poisson neuron model to analytically describe the network dynamics (firing rates and spike-time correlations) and thus the evolution of the synaptic weights. This framework incorporates the time course of the post-synaptic potentials and synaptic delays. Our analysis focuses on the asymptotic states of a network stimulated by two homogeneous pools of "steady" inputs, namely Poisson spike trains which have fixed firing rates and spike-time correlations. The (STDP) model extends rate-based learning in that it can implement, at the same time, both a stabilization of the individual neuron firing rates and a slower weight specialization depending on the input spike-time correlations. When one input pathway has stronger within-pool correlations, the resulting synaptic dynamics induced by (STDP) are shown to be similar to those arising in the case of a purely feed-forward network: the weights from the more correlated inputs are potentiated at the expense of the remaining input connections.