Overgeneralization of dangerous stimuli is a possible etiological account for anxiety disorders, yet the underlying behavioral and neural origins remain vague. Specifically, it is unclear whether this is a choice behavior in an unsafe environment ("better safe than sorry") or also a fundamental change in how the stimulus is perceived. We show that anxiety patients have wider generalization for loss-conditioned tone when compared to controls and do so even in a safe context that requires a different behavioral policy. Moreover, patients overgeneralized for gain-conditioned tone as well. Imaging (fMRI) revealed that in anxiety only, activations during conditioning in the dACC and the putamen were correlated with later overgeneralization of loss and gain, respectively, whereas valence distinction in the amygdala and hippocampus during conditioning mediated the difference between loss and gain generalization. During generalization itself, neural discrimination based on multivoxel patterns in auditory cortex and amygdala revealed specific stimulus-related plasticity. Our results suggest that overgeneralization in anxiety has perceptual origins and involves affective modulation of stimulus representations in primary cortices and amygdala.

Learning includes the ability to generalize to new situations and respond to similar, yet not identical stimuli. We use stimulus generalization in humans to show that tones that were negatively reinforced induce wider generalization curves than tones that were positively reinforced, and these in turn induce wider curves than neutral memory. Importantly, these wider generalization curves persist even if outcomes for all tones are made identical, indicating that the learning induced a perceptual change, and not merely a decision bias. Moreover, it persists after taking into account loss-aversion, suggesting it is a result of valence per se, and not intensity that reflects overweighting of the aversive stimuli. This effect of emotional valence on learning suggests different locations of plasticity and network mechanisms in the brain. Particularly, it suggests that brain areas that mediate reinforcement and emotions are involved during the learning process to induce a neural representation that can support this broader behavioral generalization. In addition, these findings highlight a model for anxiety and trauma disorders in which aversive experiences affect more than they should, sometimes even in seemingly irrational situations.

The influence of monetary loss on decision making and choice behavior is extensively studied. However, the effect of loss on sensory perception is less explored. Here, we use conditioning in human subjects to explore how monetary loss associated with a pure tone can affect changes in perceptual thresholds for the previously neutral stimulus. We found that loss conditioning, when compared with neutral exposure, decreases sensitivity and increases perceptual thresholds (i.e., a relative increase in the just-noticeable-difference). This was so even when compared with gain conditioning of comparable intensity, suggesting that the finding is related to valence. We further show that these perceptual changes are related to future decisions about stimuli that are farther away from the conditioned one (wider generalization), resulting in overall increased and irrational monetary loss for the subjects. We use functional imaging to identify the neural network whose activity correlates with the deterioration in sensitivity on an individual basis. In addition, we show that activity in the amygdala was tightly correlated with the wider behavioral generalization, namely, when wrong decisions were made. We suggest that, in principle, less discrimination can be beneficial in loss scenarios, because it assures an accurate and fast response to stimuli that resemble the original stimulus and hence have a high likelihood of entailing the same outcome. But whereas this can be useful for primary reinforcers that can impact survival, it can also underlie wrong and costly behaviors in scenarios of contemporary life that involve secondary reinforcers.

Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted.Objective: We conducted an exploratory, cross-sectional study to evaluate several digital technologies in subjects with major depressive disorder (MDD) and persistent depressive disorder (PDD), and healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for unipolar depression, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression.Methods: A cross-sectional, non-interventional study of 20 participants with unipolar depression (MDD and PDD/dysthymia) and 20 healthy controls was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, seven digital technologies were evaluated in this study. Three technologies were administered via mobile applications: an interactive tool for the self-assessment of mood, and a cognitive test; a passive behavioral monitor to assess social interactions and global mobility; and a platform to perform voice recordings and obtain vocal biomarkers. Four technologies were evaluated in the clinic: a neuropsychological test battery; an eye motor tracking system; a standard high-density electroencephalogram (EEG)-based technology to analyze the brain network activity during cognitive testing; and a task quantifying bias in emotion perception.Results: Our data analysis was organized by technology – to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression.Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof-of-concept clinical trials in depression and possibly other indications.

The accumulation of tau and amyloid beta proteins is the major molecular pathology of Alzheimer's disease (AD). The mechanisms leading to the accumulation of these proteins are not completely clear. Hsc-70/Hsp-70, a chaperone protein, has been shown to bind both these proteins and regulate their degradation. We have previously shown that the co-chaperone protein BAG-1 can inhibit the degradation of tau by forming a complex with Hsc-70 and tau. In this current work, we show that there is an increase in the BAG-1M isoform in the hippocampus of AD patients. In addition, BAG-1 binds to both tau and amyloid precursor protein physically, and is found highly expressed in the same neurons that contain intracellular tau or amyloid in hippocampal sections from AD patients. Over-expression of BAG-1M in cell culture also induced an increase in both tau and amyloid precursor protein levels. In conclusion, we report a specific increase of BAG-1M in human AD patients, which is both physically and functionally associated to the two major molecular markers of AD.