Computational and Psychophysical Experiments on the Pacinian Corpuscle's Ability to Discriminate Complex Stimuli
| Autor: | Nicholas D. Theis, Julia C. Quindlen-Hotek, Tiffany L. Senkow, Victor H. Barocas |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Stimulus (physiology) Vibration 03 medical and health sciences Discrimination Psychological 0302 clinical medicine Frequency conversion Humans 030304 developmental biology 0303 health sciences business.industry Pattern recognition Models Theoretical Discrimination testing Frequency difference Computer Science Applications Human-Computer Interaction Vibrotactile stimulus Touch Perception Touch Sensory Thresholds Artificial intelligence business Pacinian Corpuscles 030217 neurology & neurosurgery Pacinian Corpuscle |
| Zdroj: | IEEE Transactions on Haptics. 12:635-644 |
| ISSN: | 2334-0134 1939-1412 |
| DOI: | 10.1109/toh.2019.2903500 |
| Popis: | Recognizing and discriminating vibrotactile stimuli is an essential function of the Pacinian corpuscle. This function has been studied at length in both a computational and an experimental setting, but the two approaches have rarely been compared, especially when the computational model has a high level of structural detail. In this paper, we explored whether the predictions of a multiscale, multiphysical computational model of the Pacinian corpuscle can predict the outcome of a corresponding psychophysical experiment. The discrimination test involved either two simple stimuli with frequency in the 160-500 Hz range, or two complex stimuli formed by combining the waveforms for a 100-Hz stimulus with a second stimulus in the 160-500 Hz range. The subjects' ability to distinguish between the simple stimuli increased as the frequency increased, a result consistent with the model predictions for the same stimuli. The model also predicted correctly that subjects would find the complex stimuli more difficult to distinguish than the simple ones and also that the discriminability of the complex stimuli would show no trend with frequency difference. |
| Databáze: | OpenAIRE |
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