“…Multiple phenomenological models of the ANF responses to electrical stimulation have been proposed (Bruce et al 1999a, 1999b; Miller et al 1999; Rubinstein et al 2001; Litvak et al 2003; Nourski et al 2006; Macherey et al 2007; Fredelake and Hohmann 2012; Goldwyn et al 2012; Morse et al 2015; Horne et al 2016). These models do not consider multiple sites of spike generation and their effect on spike time statistics, and hence cannot be generalized to assess different CI stimulation strategies (Joshi et al 2014).…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, it has been assumed that only the cathodic phase of a biphasic pulse will generate a spike. Based on this assumption, state-of-the-art quantitative models of ANF responses have mainly focused on the responsiveness of the ANF to the depolarizing cathodic phase (Bruce et al 1999a; Hamacher 2004; Fredelake and Hohmann 2012; Goldwyn et al 2012) or on inhibitory properties of the hyperpolarizing anodic phase (Rubinstein et al 2001; Horne et al 2016). Any charge-balanced pulse can be decomposed into anodic and cathodic charges, and responses to various pulse shapes are a consequence of the sensitivity to the single pulse phases and the interaction between these.…”
A computational model of cat auditory nerve fiber (ANF) responses to electrical stimulation is presented. The model assumes that (1) there exist at least two sites of spike generation along the ANF and (2) both an anodic (positive) and a cathodic (negative) charge in isolation can evoke a spike. A single ANF is modeled as a network of two exponential integrate-and-fire point-neuron models, referred to as peripheral and central axons of the ANF. The peripheral axon is excited by the cathodic charge, inhibited by the anodic charge, and exhibits longer spike latencies than the central axon; the central axon is excited by the anodic charge, inhibited by the cathodic charge, and exhibits shorter spike latencies than the peripheral axon. The model also includes subthreshold and suprathreshold adaptive feedback loops which continuously modify the membrane potential and can account for effects of facilitation, accommodation, refractoriness, and spike-rate adaptation in ANF. Although the model is parameterized using data for either single or paired pulse stimulation with monophasic rectangular pulses, it correctly predicts effects of various stimulus pulse shapes, stimulation pulse rates, and level on the neural response statistics. The model may serve as a framework to explore the effects of different stimulus parameters on psychophysical performance measured in cochlear implant listeners.
“…Multiple phenomenological models of the ANF responses to electrical stimulation have been proposed (Bruce et al 1999a, 1999b; Miller et al 1999; Rubinstein et al 2001; Litvak et al 2003; Nourski et al 2006; Macherey et al 2007; Fredelake and Hohmann 2012; Goldwyn et al 2012; Morse et al 2015; Horne et al 2016). These models do not consider multiple sites of spike generation and their effect on spike time statistics, and hence cannot be generalized to assess different CI stimulation strategies (Joshi et al 2014).…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, it has been assumed that only the cathodic phase of a biphasic pulse will generate a spike. Based on this assumption, state-of-the-art quantitative models of ANF responses have mainly focused on the responsiveness of the ANF to the depolarizing cathodic phase (Bruce et al 1999a; Hamacher 2004; Fredelake and Hohmann 2012; Goldwyn et al 2012) or on inhibitory properties of the hyperpolarizing anodic phase (Rubinstein et al 2001; Horne et al 2016). Any charge-balanced pulse can be decomposed into anodic and cathodic charges, and responses to various pulse shapes are a consequence of the sensitivity to the single pulse phases and the interaction between these.…”
A computational model of cat auditory nerve fiber (ANF) responses to electrical stimulation is presented. The model assumes that (1) there exist at least two sites of spike generation along the ANF and (2) both an anodic (positive) and a cathodic (negative) charge in isolation can evoke a spike. A single ANF is modeled as a network of two exponential integrate-and-fire point-neuron models, referred to as peripheral and central axons of the ANF. The peripheral axon is excited by the cathodic charge, inhibited by the anodic charge, and exhibits longer spike latencies than the central axon; the central axon is excited by the anodic charge, inhibited by the cathodic charge, and exhibits shorter spike latencies than the peripheral axon. The model also includes subthreshold and suprathreshold adaptive feedback loops which continuously modify the membrane potential and can account for effects of facilitation, accommodation, refractoriness, and spike-rate adaptation in ANF. Although the model is parameterized using data for either single or paired pulse stimulation with monophasic rectangular pulses, it correctly predicts effects of various stimulus pulse shapes, stimulation pulse rates, and level on the neural response statistics. The model may serve as a framework to explore the effects of different stimulus parameters on psychophysical performance measured in cochlear implant listeners.
“…This requires more advanced neural models that include modelling of central processing. An example of the latter appears in Fredelake et al (2012), who developed a model to predict speech perception.…”
Three-dimensional (3D) computational modeling of the auditory periphery forms an integral part of modern-day research in cochlear implants (CIs). These models consist of a volume conduction description of implanted stimulation electrodes and the current distribution around these, coupled with auditory nerve fiber models. Cochlear neural activation patterns can then be predicted for a given input stimulus. The objective of this article is to present the context of 3D modeling within the field of CIs, the different models, and approaches to models that have been developed over the years, as well as the applications and potential applications of these models. The process of development of 3D models is discussed, and the article places specific emphasis on the complementary roles of generic models and user-specific models, as the latter is important for translation of these models into clinical application.
“…Since it is paramount for CIs to achieve optimal speech perception, recent approaches have used simple electric field models together with phenomenological or biophysical auditory nerve models as front ends to predict speech intelligibility with CIs. Fredelake and Hohmann (2012) have used the model by Hamacher (2004), integrated the output across multiple fibers and time, and used this as input to a statistical classifier to predict speech intelligibility.…”
This special issue of Network: Computation in Neural Systems on the topic of "Computational models of the electrically stimulated auditory system" incorporates review articles spanning a wide range of approaches to modeling cochlear implant stimulation of the auditory system. The purpose of this overview paper is to provide a historical context for the different modeling endeavors and to point toward how computational modeling could play a key role in the understanding, evaluation, and improvement of cochlear implants in the future.
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