Novel metrics to measure the effect of additive inputs on the activity of sensory system neurons
| Autor: | Maryam Hosseini, Hubert H. Lim, Eric Plourde, Gerardo Rodriguez, Hongsun Guo |
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| Rok vydání: | 2020 |
| Předmět: |
Sensory Receptor Cells
Computer science Guinea Pigs Models Neurological Sensory system Measure (mathematics) 03 medical and health sciences 0302 clinical medicine medicine Auditory system Animals 030304 developmental biology 0303 health sciences Quantitative Biology::Neurons and Cognition Noise measurement business.industry Brain Pattern recognition Noise Nonlinear system medicine.anatomical_structure Metric (mathematics) Artificial intelligence Vocalization Animal business 030217 neurology & neurosurgery |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | Sensory systems, such as the visual or auditory system, are highly non linear. It is therefore not easy to predict the effect of additive inputs on the spiking activity of related brain structures. Here, we propose two metrics to study the effect of additive covariates on the spiking activity of neurons. These metrics are directly obtained from a generalized linear model. We apply these metrics to the study of the effect of additive input audio noise on the spiking activity of neurons in the auditory system. To do so, we combine clean vocalisations with natural stationary or non-stationary noises and record activity in the auditory system while presenting the noisy vocalisations. We found that non-stationary noise has a greater effect on the neural activity than stationary noise. We observe that the results, obtained using the proposed metrics, is more consistent with current knowledge in auditory neuroscience than the results obtained when using a common metric from the literature, the extraction index. |
| Databáze: | OpenAIRE |
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