A Modeling Study of Notch Noise Responses of Type III Units in the Gerbil Dorsal Cochlear Nucleus

Zheng, Xiaohan; Voigt, Herbert

doi:10.1007/s10439-005-9073-5

Cited by 9 publications

(10 citation statements)

References 21 publications

(28 reference statements)

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“…4b-d). Reproducing salient response properties of DCN projection neurons, has also been the focus of several other modeling studies Blum et al, 1995;Franosch et al, 2003;Zheng and Voigt, 2006a;Zheng and Voigt, 2006b). Our model is similar to the model of Reed et al (1995), as it is also rate-based, whereas the more recent models of Franosch et al (2003) and Zheng and Voigt (2006b) employ spiking neurons.…”

Section: Discussionmentioning

confidence: 96%

Development of hyperactivity after hearing loss in a computational model of the dorsal cochlear nucleus depends on neuron response type

Schaette

Kempter

2008

Hearing Research

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Section: Discussionmentioning

confidence: 96%

Development of hyperactivity after hearing loss in a computational model of the dorsal cochlear nucleus depends on neuron response type

Schaette

Kempter

2008

Hearing Research

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“…The function of the DCN as a filter for sound localization cues has been discussed extensively in the literature (Davis et al 1996b;Ding et al 1999;May 2000;Oertel and Young 2004;Reiss and Young 2005;Young et al 1995;Young and Davis 2002;Zheng and Voigt 2006). Spectral cues from the head transfer function are thought to be combined in DCN with proprioception information to determine the location of a sound source.…”

Section: The Dcn As An Adaptive Filter For Auditory Stimulimentioning

confidence: 99%

Design principles of sensory processing in cerebellum-like structures

Roberts

Portfors

2008

Biol Cybern

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Cerebellum-like structures are compared for two sensory systems: electrosensory and auditory. The electrosensory lateral line lobe of mormyrid electric fish is reviewed and the neural representation of electrosensory objects in this structure is modeled and discussed. The dorsal cochlear nucleus in the auditory brainstem of mammals is reviewed and new data are presented that characterize the responses of neurons in this structure in the mouse. Similarities between the electrosensory and auditory cerebellum-like structures are shown, in particular adaptive processes that may reduce responses to predictable stimuli. We suggest that the differences in the types of sensory objects may drive the differences in the anatomical and physiological characteristics of these two cerebellum-like structures.

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“…However, we obtained type III-i units when the values of σ AN→P and σ I2→P are low. We have previously shown that P-cells in both gerbil and cat versions of the model are sensitive to notch noise stimuli (Zheng and Voigt 2006). These notch noises simulate the spectral notches created by the filtering properties of the external ear and are thought to be a major cue for locating sounds in the medial plane.…”

Section: Discussionmentioning

confidence: 99%

“…This suggests that we keep σ AN→P to a lower value, maybe lower than 0.5. In another work of ours, when we tried to fit the notch noise responses of P-cells to the physiological data of 15 gerbil type III units, the best σ AN→P for all 15 units was less than or equal to 0.45 (see Table 4 in Zheng and Voigt 2006). Shown in Fig.…”

Section: Response Maps Of P-cells Simulated With the Nominal Parametementioning

confidence: 94%

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Computational model of response maps in the dorsal cochlear nucleus

Zheng

Voigt

2006

Biol Cybern

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The neurons in the mammalian (gerbil, cat) dorsal cochlear nucleus (DCN) have responses to tones and noise that have been used to classify them into unit types. These types (I-V) are based on excitatory and inhibitory responses to tones organized into plots called response maps (RMs). Type I units show purely excitatory responses, while type V units are primarily inhibited. A computational model of the neural circuitry of the mammalian DCN, based on the MacGregor neuromime, was used to investigate RMs of the principal cells (P-cells) that represent the fusiform and giant cells. In gerbils, fusiform cells have been shown to have primarily type III unit response properties; however, fusiform cells in the cat DCN are thought to have type IV unit response properties. The DCN model is based on a previous computational model of the cat (Hancock and Voigt Ann Biomed Eng 27: 73-87, 1999) and gerbil (Zheng and Voigt Ann Biomed Eng 34: 697-708, 2006) DCN. The basic model for both species is architecturally the same, and to get either type III unit RMs or type IV unit RMs, connection parameters were adjusted. Interestingly, regardless of the RM type, these units in gerbils and cats show spectral notch sensitivity and are thought to play a role in sound localization in the median plane. In this study, further parameter adjustments were made to systematically explore their effect on P-cell RMs. Significantly, type I, type III, type III-i, type IV, type IV-T and type V unit RMs can be created for the modeled P-cells. Thus major RMs observed in the cat and gerbil DCN are recreated by the model. These results suggest that RMs of individual DCN projection neurons are the result of specific assortment of excitatory and inhibitory inputs to that neuron and that subtle differences in the complement of inputs can result in different RM types. Modulation of the efficacy of certain synapses suggests that RM type may change dynamically.

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A Modeling Study of Notch Noise Responses of Type III Units in the Gerbil Dorsal Cochlear Nucleus

Cited by 9 publications

References 21 publications

Development of hyperactivity after hearing loss in a computational model of the dorsal cochlear nucleus depends on neuron response type

Development of hyperactivity after hearing loss in a computational model of the dorsal cochlear nucleus depends on neuron response type

Design principles of sensory processing in cerebellum-like structures

Computational model of response maps in the dorsal cochlear nucleus

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