exp_felsheim2024(flag)
exp_felsheim2024(flag) reproduces the figures from Felsheim and Dietz (2024).
The following flags can be specified:
'fig5a' | The |
'fig5b' | The spike probability for different amplitdues for mono- and biphasic pulses
with a phase duration 100 |
'fig5cd' | The spike latency (c) and the spike jitter (d) of monophasic pulses are shown.
The data is shown togehter with the predictions of the aLIPF model and was
collected by Miller et al. (1999), who used monophasic pulses with a duration
of 40 |
'fig6ab' | The mean I_50 (a) and relative spread (b) during the refractory period recorded
with monophasic pulses with a length of 40 |
'fig6cd' | In (c), the data by Dynes (1996) for facilitation by a single sub-threshold
pulse is shown, again, together with the predictions by both models and in (d),
the same is shown for four and 40 sub-threshold masker. Dynes (1996) used
monophasic pulses with a duration of 100 |
'fig6e' | The spike rate adaptation for different pulse rates and amplitudes, as measured
by Zhang et al. (2007). Our model was fitted at two amplitudes for each of the
pulse rates 250 pps, 1000 pps, and 5000 pps. The low amplitude was always
1.4 dB re |
'fig7' | The decrease in threshold due to facilitation is measured by Cartee et al. (2000)
by dividing the |
'fig8' | Facilitation and accommodation as calculated from spike trains by Heffer et al. (2010). Negative values indicate accommodation, while positive ones denote facilitation. The predictions from the aLIFP model fit the data nicely, except for 2000 pps at low levels, where the aLIFP model overestimates the facilitation. |
'fig9' | Mean firing probability over level for four 100 |
'fig10' | Data collected by Miller et al. (2011), who measured the impact of a low amplitude stimulus on a subsequent probe in 48 cat nerve fibers. The amplitudes were placed around the spike threshold for the masker, defined as the level where firing just started. |
'fig11' | The vector strength from Miller et al. (2008), Hartmann and Klinke (1990) and
Dynes and Delgutte (1992) for different pulse rates measured in cats. As the
were made both for duration of the IPG was not clear, the predictions an IPG
of 0 |
'fig12' | The spike rate and the vector strength of 100 Hz sinusoidally amplitude modulated and unmodulated pulse trains with a rate of 5000 pps were calculated. The predictions the aLIFP model were compared to data of 72 cat nerve fibers from Hu et al. (2010). |
'figA1' | The vector strength obtained from the predictions of the aLIFP model for different
IPG durations and two amplitudes: 1 dB and 2 dB relative to single pulse |
'redo' | Force recalculation of the data. Cached data are shown per default. |
To display Fig. 5a use :
exp_felsheim2024('fig5a'); |
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To display Fig. 5b use :
exp_felsheim2024('fig5b'); |
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To display Fig. 5cd use :
exp_felsheim2024('fig5cd'); |
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To display Fig. 6ab use :
exp_felsheim2024('fig6ab'); |
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To display Fig. 6cd use :
exp_felsheim2024('fig6cd'); |
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To display Fig. 6e use :
exp_felsheim2024('fig6e'); |
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To display Fig. 7 use :
exp_felsheim2024('fig7'); |
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To display Fig. 8 use :
exp_felsheim2024('fig8'); |
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To display Fig. 9 use :
exp_felsheim2024('fig9'); |
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To display Fig. 10 use :
exp_felsheim2024('fig10'); |
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To display Fig. 11 use :
exp_felsheim2024('fig11'); |
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To display Fig. 12 use :
exp_felsheim2024('fig12'); |
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R. C. Felsheim and M. Dietz. An adaptive leaky integrate and firing probability model of an electrically stimulated auditory nerve fiber. Trends in Heaaring, 2024. submitted.