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A neural network model can explain ventriloquism aftereffect and its generalization across sound frequencies.

Magosso E, Cona F, Ursino M - Biomed Res Int (2013)

Bottom Line: Exposure to synchronous but spatially disparate auditory and visual stimuli produces a perceptual shift of sound location towards the visual stimulus (ventriloquism effect).The model provides a coherent theoretical framework to explain the apparently contradictory results found in the literature.Model mechanisms and hypotheses are discussed in relation to neurophysiological and psychophysical data.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521 Cesena, Italy.

ABSTRACT
Exposure to synchronous but spatially disparate auditory and visual stimuli produces a perceptual shift of sound location towards the visual stimulus (ventriloquism effect). After adaptation to a ventriloquism situation, enduring sound shift is observed in the absence of the visual stimulus (ventriloquism aftereffect). Experimental studies report opposing results as to aftereffect generalization across sound frequencies varying from aftereffect being confined to the frequency used during adaptation to aftereffect generalizing across some octaves. Here, we present an extension of a model of visual-auditory interaction we previously developed. The new model is able to simulate the ventriloquism effect and, via Hebbian learning rules, the ventriloquism aftereffect and can be used to investigate aftereffect generalization across frequencies. The model includes auditory neurons coding both for the spatial and spectral features of the auditory stimuli and mimicking properties of biological auditory neurons. The model suggests that different extent of aftereffect generalization across frequencies can be obtained by changing the intensity of the auditory stimulus that induces different amounts of activation in the auditory layer. The model provides a coherent theoretical framework to explain the apparently contradictory results found in the literature. Model mechanisms and hypotheses are discussed in relation to neurophysiological and psychophysical data.

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Aftereffect generalization when using different values of intensity for the adaption stimulus (E0aadapt) and for the test stimulus (E0atest). In the left panels, E0aadapt was kept fixed (E0aadapt= 17 in (a) and E0aadapt = 20 in (c)), while E0atest ranged from 17 to 23 (the meaning of the line color is indicated in the legend). In the right panels, E0atest was kept constant (E0atest = 17 in (b) and E0atest = 20 in (d)) to test the network trained with E0aadapt ranging from 17 to 23 (the meaning of the line color is indicated in the legend).
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fig11: Aftereffect generalization when using different values of intensity for the adaption stimulus (E0aadapt) and for the test stimulus (E0atest). In the left panels, E0aadapt was kept fixed (E0aadapt= 17 in (a) and E0aadapt = 20 in (c)), while E0atest ranged from 17 to 23 (the meaning of the line color is indicated in the legend). In the right panels, E0atest was kept constant (E0atest = 17 in (b) and E0atest = 20 in (d)) to test the network trained with E0aadapt ranging from 17 to 23 (the meaning of the line color is indicated in the legend).

Mentions: It is worth noticing that model results shown in Figures 8–10 were obtained with the test stimulus having the same intensity as the adaptation one (as done in in vivo studies). Hence, two joined factors contributed to the aftereffect generalization: the different amount of synapses modifications (due to the different adaptation intensities) and the different intensities of the test stimulus. In order to discern the role of these two factors, we performed two additional sets of simulations: (i) the network trained at a given adaptation intensity was tested at each of the test intensities (ranging from 17 to 23); (ii) a given test intensity was used to test the network trained at each of the adaptation intensities (ranging from 17 to 23). Exemplary results are reported in Figure 11. The model predicts that the intensity of the test stimulus plays a crucial role in determining the range of frequencies over which aftereffect is generalized (Figures 11(a) and 11(c)). At E0aadapt = 17 (a), the network behavior shifted from no generalization to generalization across more than two octaves, when E0atest shifted from 17 to 23. At E0aadapt = 20 (c), a significant shrinking of generalization occurred when E0atest decreased down to 17.


A neural network model can explain ventriloquism aftereffect and its generalization across sound frequencies.

Magosso E, Cona F, Ursino M - Biomed Res Int (2013)

Aftereffect generalization when using different values of intensity for the adaption stimulus (E0aadapt) and for the test stimulus (E0atest). In the left panels, E0aadapt was kept fixed (E0aadapt= 17 in (a) and E0aadapt = 20 in (c)), while E0atest ranged from 17 to 23 (the meaning of the line color is indicated in the legend). In the right panels, E0atest was kept constant (E0atest = 17 in (b) and E0atest = 20 in (d)) to test the network trained with E0aadapt ranging from 17 to 23 (the meaning of the line color is indicated in the legend).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3818813&req=5

fig11: Aftereffect generalization when using different values of intensity for the adaption stimulus (E0aadapt) and for the test stimulus (E0atest). In the left panels, E0aadapt was kept fixed (E0aadapt= 17 in (a) and E0aadapt = 20 in (c)), while E0atest ranged from 17 to 23 (the meaning of the line color is indicated in the legend). In the right panels, E0atest was kept constant (E0atest = 17 in (b) and E0atest = 20 in (d)) to test the network trained with E0aadapt ranging from 17 to 23 (the meaning of the line color is indicated in the legend).
Mentions: It is worth noticing that model results shown in Figures 8–10 were obtained with the test stimulus having the same intensity as the adaptation one (as done in in vivo studies). Hence, two joined factors contributed to the aftereffect generalization: the different amount of synapses modifications (due to the different adaptation intensities) and the different intensities of the test stimulus. In order to discern the role of these two factors, we performed two additional sets of simulations: (i) the network trained at a given adaptation intensity was tested at each of the test intensities (ranging from 17 to 23); (ii) a given test intensity was used to test the network trained at each of the adaptation intensities (ranging from 17 to 23). Exemplary results are reported in Figure 11. The model predicts that the intensity of the test stimulus plays a crucial role in determining the range of frequencies over which aftereffect is generalized (Figures 11(a) and 11(c)). At E0aadapt = 17 (a), the network behavior shifted from no generalization to generalization across more than two octaves, when E0atest shifted from 17 to 23. At E0aadapt = 20 (c), a significant shrinking of generalization occurred when E0atest decreased down to 17.

Bottom Line: Exposure to synchronous but spatially disparate auditory and visual stimuli produces a perceptual shift of sound location towards the visual stimulus (ventriloquism effect).The model provides a coherent theoretical framework to explain the apparently contradictory results found in the literature.Model mechanisms and hypotheses are discussed in relation to neurophysiological and psychophysical data.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Via Venezia 52, 47521 Cesena, Italy.

ABSTRACT
Exposure to synchronous but spatially disparate auditory and visual stimuli produces a perceptual shift of sound location towards the visual stimulus (ventriloquism effect). After adaptation to a ventriloquism situation, enduring sound shift is observed in the absence of the visual stimulus (ventriloquism aftereffect). Experimental studies report opposing results as to aftereffect generalization across sound frequencies varying from aftereffect being confined to the frequency used during adaptation to aftereffect generalizing across some octaves. Here, we present an extension of a model of visual-auditory interaction we previously developed. The new model is able to simulate the ventriloquism effect and, via Hebbian learning rules, the ventriloquism aftereffect and can be used to investigate aftereffect generalization across frequencies. The model includes auditory neurons coding both for the spatial and spectral features of the auditory stimuli and mimicking properties of biological auditory neurons. The model suggests that different extent of aftereffect generalization across frequencies can be obtained by changing the intensity of the auditory stimulus that induces different amounts of activation in the auditory layer. The model provides a coherent theoretical framework to explain the apparently contradictory results found in the literature. Model mechanisms and hypotheses are discussed in relation to neurophysiological and psychophysical data.

Show MeSH
Related in: MedlinePlus