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A previously published study showed that stress may interfere with associative aversive learning and facilitate mood-related disorders. However, whether emotional stress alone affects aversive learning is unknown. Using three chamber-vicarious social defeat stress (3C-VSDS) model mice, we investigated the effect of emotional stress on aversive learning. An important origin of dopamine (DA) neurons, the zona incerta (ZI), is expected to be a novel target for the modulation of aversive learning. However, less is known about the circuit mechanism of ZIDA neurons in aversive learning. Here, we subjected mice to a fear-conditioning system (FCS) and observed an increased calcium activity of ZI TH+ neurons in aversive expectation during the conditioning phase, especially during the late stage of the conditional stimulus (CS) when CS and unconditional stimulus (US) pairings were used. Optogenetic inhibition of ZI TH+ neurons at the late stage of CS disrupted conditioned fear learning in mice. We further identified a TH+ projection from the ZI to the basomedial amygdala (BMA) and found that optogenetic inhibition of the ZI-BMA circuit could also block aversive learning. Finally, we used 3C-VSDS mice as a model of emotional stress. We found that the 3C-VSDS model mice demonstrated reduced aversive expectation associated with ZI TH+ neurons in the late stage of CS and impaired aversive learning in FCS. Optogenetic activation of ZI-BMA TH+ projections in the late stage of CS significantly reversed the aversive FCS learning disability of 3C-VSDS model mice. These data suggest that a TH+ circuit from the ZI to the BMA is required for aversive expectation, both at baseline and in 3C-VSDS-induced aversive learning deficits and that this circuit is a potential target for the modulation of aversive learning. Low activity of ZI-BMA TH+ projections is one reason for 3C-VSDS-induced aversive learning deficits.

We present a novel active imaging approach that uses optimized wide band filtered illumination to obtain multi-spectral reflectance information. Our optimization algorithm utilizes light source and camera spectral information in order to maximize the signal strength and the robustness to noise. Through the use of active wide band illumination, our system can obtain material reflectance information in the presence of moderate (indoor) unknown ambient illumination. Our method is very simple and does not require special equipment. It can be used by photographers to obtain material properties in uncontrolled environment and to synthesize captured scenes under arbitrary illumination.

Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland, 2009