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A modeling study of the responses of the lateral superior olive to ipsilateral sinusoidally amplitude-modulated tones.

Wang L, Colburn HS - J. Assoc. Res. Otolaryngol. (2011)

Bottom Line: In the model, AHP channels alone were not sufficient to induce the observed rate decrease at high modulation frequencies.In contrast, both the small and large rate decreases were replicated when KLT channels were included in the LSO neuron model.These results support the conclusion that KLT channels may play a major role in the large rate decreases seen in some units and that background inhibition may be a contributing factor, a factor that could be adequate for small decreases.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Center for Hearing Research, Boston University, Boston, MA 02215, USA.

ABSTRACT
The lateral superior olive (LSO) is a brainstem nucleus that is classically understood to encode binaural information in high-frequency sounds. Previous studies have shown that LSO cells are sensitive to envelope interaural time difference in sinusoidally amplitude-modulated (SAM) tones (Joris and Yin, J Neurophysiol 73:1043-1062, 1995; Joris, J Neurophysiol 76:2137-2156, 1996) and that a subpopulation of LSO neurons exhibit low-threshold potassium currents mediated by Kv1 channels (Barnes-Davies et al., Eur J Neurosci 19:325-333, 2004). It has also been shown that in many LSO cells the average response rate to ipsilateral SAM tones decreases with modulation frequency above a few hundred Hertz (Joris and Yin, J Neurophysiol 79:253-269, 1998). This low-pass feature is not directly inherited from the inputs to the LSO since the response rate of these input neurons changes little with increasing modulation frequency. In the current study, an LSO cell model is developed to investigate mechanisms consistent with the responses described above, notably the emergent rate decrease with increasing frequency. The mechanisms explored included the effects of after-hyperpolarization (AHP) channels, the dynamics of low-threshold potassium channels (KLT), and the effects of background inhibition. In the model, AHP channels alone were not sufficient to induce the observed rate decrease at high modulation frequencies. The model also suggests that the background inhibition alone, possibly from the medial nucleus of the trapezoid body, can account for the small rate decrease seen in some LSO neurons, but could not explain the large rate decrease seen in other LSO neurons at high modulation frequencies. In contrast, both the small and large rate decreases were replicated when KLT channels were included in the LSO neuron model. These results support the conclusion that KLT channels may play a major role in the large rate decreases seen in some units and that background inhibition may be a contributing factor, a factor that could be adequate for small decreases.

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Rate–fm functions of the HH-type LSO model with inhibitory inputs. Different colors represent different levels of inhibition strength strI. A Number of inhibitory inputs equals 20. B Number of inhibitory inputs equals 200. Solid lines represent responses with simplified AN inputs. Dashed lines represent responses with Earlab AN inputs (see “Results”). For all cases shown, ratemean = 200 spikes/s, strE = 2.55 nS, NE= 20, and rateI = 30 spikes/s.
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Fig5: Rate–fm functions of the HH-type LSO model with inhibitory inputs. Different colors represent different levels of inhibition strength strI. A Number of inhibitory inputs equals 20. B Number of inhibitory inputs equals 200. Solid lines represent responses with simplified AN inputs. Dashed lines represent responses with Earlab AN inputs (see “Results”). For all cases shown, ratemean = 200 spikes/s, strE = 2.55 nS, NE= 20, and rateI = 30 spikes/s.

Mentions: To explore the effect of the inhibitory inputs on the model’s rate–fm function, the number of inhibitory input (NI) and the inhibitory synaptic strength (strI) were varied. The results of the LSO model using the simplified AN model are summarized in Figure 5 (solid lines). The model firing rate was plotted as a function of the modulation frequency when NI was set to 200 (Fig. 5A) and 20 (Fig. 5B), respectively. For each value of NI, the excitatory synaptic strength was chosen to produce a relatively high firing rate (250 spikes/s) at zero modulation frequency when no inhibition was present (solid blue curves in Fig. 5A, B). As seen in each panel of Figure 5, when no inhibition was present, the average rates of the LSO model response remained relatively high at all modulation frequencies. For both NI= 20 and NI= 200, rate–fm functions with two additional levels of inhibition (“weak” and “strong”) are shown in Figure 5. The strength strI of the weak inhibition was chosen to reduce the rate at the highest modulation frequency (1,500 Hz) to around 100 spikes/s, and the strI of the strong inhibition was chosen to reduce the rate at 1,500 Hz to around 25 spikes/s. These values of the firing rate were chosen to represent the firing rates of the two groups of LSO cells at the highest fm measured, as previously described in this paper. As expected, when the inhibitory synaptic strength strI increased from zero, the response rates decreased for all modulation frequencies. When NI= 200 (Fig. 5A), the RHP values of the rate–fm functions for both weak and strong inhibition were close to 100 spikes/s, approaching the size of the rate decrease in the empirical data (Fig. 1B). When NI= 20 (Fig. 5B), the rate–fm function showed a much smaller rate variation compared with the case of NI= 200 for both weak and strong inhibition. In particular, the dependence of the firing rate was almost eliminated by the strong inhibition when NI= 20. The results shown in Figure 5 can be understood by considering the level of randomness in the synaptic conductance for the different number of inhibitory inputs. As the input number NI becomes larger, the synaptic conductance approaches the rate function of the underlying Poisson process because the randomness introduced by each input is reduced due to temporal summation of PSCs. Therefore, the synaptic conductance was very close to a flat function when NI= 200. This constant inhibition, although decreasing the overall level of the excitation, did not significantly disrupt the temporal structure in the excitation that represented the modulation frequency, resulting in a larger rate variation in the rate–fm function. Conversely, when NI= 20, the observed smaller rate variation is probably due to a higher level of randomness in the inhibitory conductance.FIG. 5


A modeling study of the responses of the lateral superior olive to ipsilateral sinusoidally amplitude-modulated tones.

Wang L, Colburn HS - J. Assoc. Res. Otolaryngol. (2011)

Rate–fm functions of the HH-type LSO model with inhibitory inputs. Different colors represent different levels of inhibition strength strI. A Number of inhibitory inputs equals 20. B Number of inhibitory inputs equals 200. Solid lines represent responses with simplified AN inputs. Dashed lines represent responses with Earlab AN inputs (see “Results”). For all cases shown, ratemean = 200 spikes/s, strE = 2.55 nS, NE= 20, and rateI = 30 spikes/s.
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Related In: Results  -  Collection

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Fig5: Rate–fm functions of the HH-type LSO model with inhibitory inputs. Different colors represent different levels of inhibition strength strI. A Number of inhibitory inputs equals 20. B Number of inhibitory inputs equals 200. Solid lines represent responses with simplified AN inputs. Dashed lines represent responses with Earlab AN inputs (see “Results”). For all cases shown, ratemean = 200 spikes/s, strE = 2.55 nS, NE= 20, and rateI = 30 spikes/s.
Mentions: To explore the effect of the inhibitory inputs on the model’s rate–fm function, the number of inhibitory input (NI) and the inhibitory synaptic strength (strI) were varied. The results of the LSO model using the simplified AN model are summarized in Figure 5 (solid lines). The model firing rate was plotted as a function of the modulation frequency when NI was set to 200 (Fig. 5A) and 20 (Fig. 5B), respectively. For each value of NI, the excitatory synaptic strength was chosen to produce a relatively high firing rate (250 spikes/s) at zero modulation frequency when no inhibition was present (solid blue curves in Fig. 5A, B). As seen in each panel of Figure 5, when no inhibition was present, the average rates of the LSO model response remained relatively high at all modulation frequencies. For both NI= 20 and NI= 200, rate–fm functions with two additional levels of inhibition (“weak” and “strong”) are shown in Figure 5. The strength strI of the weak inhibition was chosen to reduce the rate at the highest modulation frequency (1,500 Hz) to around 100 spikes/s, and the strI of the strong inhibition was chosen to reduce the rate at 1,500 Hz to around 25 spikes/s. These values of the firing rate were chosen to represent the firing rates of the two groups of LSO cells at the highest fm measured, as previously described in this paper. As expected, when the inhibitory synaptic strength strI increased from zero, the response rates decreased for all modulation frequencies. When NI= 200 (Fig. 5A), the RHP values of the rate–fm functions for both weak and strong inhibition were close to 100 spikes/s, approaching the size of the rate decrease in the empirical data (Fig. 1B). When NI= 20 (Fig. 5B), the rate–fm function showed a much smaller rate variation compared with the case of NI= 200 for both weak and strong inhibition. In particular, the dependence of the firing rate was almost eliminated by the strong inhibition when NI= 20. The results shown in Figure 5 can be understood by considering the level of randomness in the synaptic conductance for the different number of inhibitory inputs. As the input number NI becomes larger, the synaptic conductance approaches the rate function of the underlying Poisson process because the randomness introduced by each input is reduced due to temporal summation of PSCs. Therefore, the synaptic conductance was very close to a flat function when NI= 200. This constant inhibition, although decreasing the overall level of the excitation, did not significantly disrupt the temporal structure in the excitation that represented the modulation frequency, resulting in a larger rate variation in the rate–fm function. Conversely, when NI= 20, the observed smaller rate variation is probably due to a higher level of randomness in the inhibitory conductance.FIG. 5

Bottom Line: In the model, AHP channels alone were not sufficient to induce the observed rate decrease at high modulation frequencies.In contrast, both the small and large rate decreases were replicated when KLT channels were included in the LSO neuron model.These results support the conclusion that KLT channels may play a major role in the large rate decreases seen in some units and that background inhibition may be a contributing factor, a factor that could be adequate for small decreases.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Center for Hearing Research, Boston University, Boston, MA 02215, USA.

ABSTRACT
The lateral superior olive (LSO) is a brainstem nucleus that is classically understood to encode binaural information in high-frequency sounds. Previous studies have shown that LSO cells are sensitive to envelope interaural time difference in sinusoidally amplitude-modulated (SAM) tones (Joris and Yin, J Neurophysiol 73:1043-1062, 1995; Joris, J Neurophysiol 76:2137-2156, 1996) and that a subpopulation of LSO neurons exhibit low-threshold potassium currents mediated by Kv1 channels (Barnes-Davies et al., Eur J Neurosci 19:325-333, 2004). It has also been shown that in many LSO cells the average response rate to ipsilateral SAM tones decreases with modulation frequency above a few hundred Hertz (Joris and Yin, J Neurophysiol 79:253-269, 1998). This low-pass feature is not directly inherited from the inputs to the LSO since the response rate of these input neurons changes little with increasing modulation frequency. In the current study, an LSO cell model is developed to investigate mechanisms consistent with the responses described above, notably the emergent rate decrease with increasing frequency. The mechanisms explored included the effects of after-hyperpolarization (AHP) channels, the dynamics of low-threshold potassium channels (KLT), and the effects of background inhibition. In the model, AHP channels alone were not sufficient to induce the observed rate decrease at high modulation frequencies. The model also suggests that the background inhibition alone, possibly from the medial nucleus of the trapezoid body, can account for the small rate decrease seen in some LSO neurons, but could not explain the large rate decrease seen in other LSO neurons at high modulation frequencies. In contrast, both the small and large rate decreases were replicated when KLT channels were included in the LSO neuron model. These results support the conclusion that KLT channels may play a major role in the large rate decreases seen in some units and that background inhibition may be a contributing factor, a factor that could be adequate for small decreases.

Show MeSH