bioRxiv Science⌕ Search

Biology subjects

Remington, E.

Publications and source records attributed to Remington, E..

2 recordsLinked to original sources
bioRxiv2022

Sound localization acuity of the common marmoset (Callithrix jacchus)

The common marmoset (Callithrix jacchus) is a small arboreal New World primate which has emerged as a promising model in auditory neuroscience. One potentially useful application of this model system is in the study of the neural mechanism underlying spatial hearing in primate species, as the marmosets visually occluded natural habitat in the forest would make sound localization an essential behavior for survival. However, interpretation of neurophysiological data on sound localization requires an understanding of perceptual abilities, and the sound localization behavior of marmosets has not been well studied. The present experiment measured sound localization acuity using an operant conditioning procedure in which marmosets were trained to discriminate changes in sound location in the horizontal (azimuth) or vertical (elevation) dimension. Our results showed that the minimum audible angle (MAA) for horizontal discrimination was on average 15{degrees} for band-passed Gaussian noise and 13{degrees} for Random Spectral Shape (RSS) stimuli, whereas the MAA for vertical locations was at 17{degrees} and 22{degrees} for band-passed Gaussian noises containing more and less high frequency energy, respectively.

neuroscience↗
bioRxiv2017

Late Bayesian inference in sensorimotor behavior

Sensorimotor skills rely on performing noisy sensorimotor computations on noisy sensory measurements. Bayesian models suggest that humans compensate for measurement noise and reduce behavioral variability by biasing perception toward prior expectations. Whether the same holds for noise in sensorimotor computations is not known. Testing human subjects in tasks with different levels of sensorimotor complexity, we found a similar bias-variance tradeoff associated with increased sensorimotor noise. This result was accurately captured by a model which implements Bayesian inference after - not before - sensorimotor transformation. These results indicate that humans perform \"late inference\" downstream of sensorimotor computations rather than, or in addition to, \"early inference\" in the perceptual domain. The brain thus possesses internal models of noise in both sensory measurements and sensorimotor computations.

animal behavior and cognition↗