Biology subjects

Stocker, A.

Publications and source records attributed to Stocker, A..

3 recordsLinked to original sources

bioRxiv2022

Efficient neural codes naturally emerge through gradient descent learning

Animal sensory systems are more sensitive to common features in the environment than uncommon features. For example, small deviations from the more frequently encountered horizontal orientations can be more easily detected than small deviations from the less frequent diagonal ones. Here we find that artificial neural networks trained to recognize objects also have patterns of sensitivity that match the statistics of features in images. To interpret these findings, we show mathematically that learning with gradient descent in deep neural networks preferentially creates representations that are more sensitive to common features, a hallmark of efficient coding. This result suggests that efficient coding naturally emerges from gradient-like learning on natural stimuli.

neuroscience↗

bioRxiv2020

Aberrant Sensory Encoding in Patients with Autism

Perceptual anomalies in patients with Autism Spectrum Disorder (ASD) have been attributed to irregularities in the Bayesian interpretation (i.e., decoding) of sensory information. Here we show that how sensory information is encoded and adapts to changing stimulus statistics also characteristically differs between healthy and ASD groups. In a visual estimation task, we extracted the accuracy of sensory encoding directly from psychophysical data, bypassing the decoding stage by using information theoretic measures. Initially, sensory representations in both groups reflected the statistics of visual orientations in natural scenes, but encoding capacity was overall lower in the ASD group. Exposure to an artificial statistical distribution of visual orientations altered the sensory representations of the control group toward the novel experimental statistics, while also increasing their total encoding resources. Neither total encoding resources nor their allocation changed significantly in the ASD group. Most interestingly, across both groups the adaptive re-allocation of encoding resources was correlated with subjects initial encoding capacity. These findings suggest that neural encoding resources are limited in ASD, and this limitation may explain their reduced perceptual flexibility.

neuroscience↗

bioRxiv2017

High- to low-level decoding does not generally improve perceptual performance

Ding et al. (1) recently proposed that the brain automatically encodes high-level, relative stimulus information (i.e. the ordinal relation between two lines), which it then uses to constrain the decoding of low-level, absolute stimulus features (i.e. when recalling the actual lines orientation). This is an interesting idea that is in line with the self-consistent Bayesian observer model (2, 3) and may have important implications for understanding how the brain processes sensory information. However, the notion suggested in Ding et al. (1) that the brain uses this decoding strategy because it improves perceptual performance is misleading. Here we clarify the decoding model and compare its perceptual performance under various noise and signal conditions.

animal behavior and cognition↗