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We compare the robustness of humans and current convolutional deep neural networks (DNNs) on object recognition under twelve different types of image degradations. First, using three well known DNNs (ResNet-152, VGG-19, GoogLeNet) we find the human visual system to be more robust to nearly all of the tested image manipulations, and we observe progressively diverging classification error-patterns between humans and DNNs when the signal gets weaker. Secondly, we show that DNNs trained directly on distorted images consistently surpass human performance on the exact distortion types they were trained on, yet they display extremely poor generalisation abilities when tested on other distortion types. For example, training on salt-and-pepper noise does not imply robustness on uniform white noise and vice versa. Thus, changes in the noise distribution between training and testing constitutes a crucial challenge to deep learning vision systems that can be systematically addressed in a lifelong machine learning approach. Our new dataset consisting of 83K carefully measured human psychophysical trials provide a useful reference for lifelong robustness against image degradations set by the human visual system.
Background: Pavlovian processes are thought to play an important role in the development, maintenance and relapse of alcohol dependence, possibly by influencing and usurping on- going thought and behavior. The influence of Pavlovian stimuli on on-going behavior is paradigmatically measured by Pavlovian-to-instrumental-transfer (PIT) tasks. These involve multiple stages and are complex. Whether increased PIT is involved in human alcohol
dependence is uncertain. We therefore aimed to establish and validate a modified PIT paradigm that would be robust, consistent, and tolerated by healthy controls as well as by patients suffering from alcohol dependence, and to explore whether alcohol dependence is associated with enhanced Pavlovian-Instrumental transfer.
Methods: 32 recently detoxified alcohol-dependent patients and 32 age and gender matched healthy controls performed a PIT task with instrumental go/no-go approach behaviours. The task involved both Pavlovian stimuli associated with monetary rewards and losses, and images of drinks.
Results: Both patients and healthy controls showed a robust and temporally stable PIT effect. Strengths of PIT effects to drug-related and monetary conditioned stimuli were highly correlated. Patients more frequently showed a PIT effect and the effect was stronger in response to aversively conditioned CSs (conditioned suppression), but there was no group difference in response to appetitive CSs.
Conclusion: The implementation of PIT has favorably robust properties in chronic alcohol- dependent patients and in healthy controls. It shows internal consistency between monetary and drug-related cues. The findings support an association of alcohol dependence with an increased propensity towards PIT.