In this work we investigated the spectral dynamics of cesium lead mixed-halide, CsPb(Br x Cl1–x )3 perovskite nanocrystals probed with complementary spectral techniques: time-resolved photoluminescence and transient absorption spectroscopy. Mixed-halide perovskite nanocrystals were synthesized via a hot-injection method followed by anion exchange reactions. Our results show that increased Cl content in perovskite nanocrystals (a) diminished the photoluminescence quantum yield and gave rise to rapid radiative recombination of carriers; (b) resulted in rapid thermalization of hot carriers and low carrier temperatures, which suggests weaker hot-phonon bottleneck and Burstein–Moss effects; (c) decreased the bandgap renormalization energy, which suggests high exciton binding energy and poor charge extraction in Cl substituted perovskite nanocrystals; and (d) increased the number of carriers undergoing Auger losses, where Auger processes dominate over trap-assisted recombination. These findings provide a generalized framework to guide researchers as to when mixed-halide perovskite nanocrystals would be useful for optoelectronic technologies and when they would be detrimental to device performance.
Primates constantly explore their surroundings via saccadic eye movements that bring different parts of an image into high resolution. In addition to exploring new regions in the visual field, primates also make frequent return fixations, revisiting previously foveated locations. We systematically studied a total of 44,328 return fixations out of 217,440 fixations. Return fixations were ubiquitous across different behavioral tasks, in monkeys and humans, both when subjects viewed static images and when subjects performed natural behaviors. Return fixations locations were consistent across subjects, tended to occur within short temporal offsets, and typically followed a 180-degree turn in saccadic direction. To understand the origin of return fixations, we propose a proof-of-principle, biologically-inspired and image-computable neural network model. The model combines five key modules: an image feature extractor, bottom-up saliency cues, task-relevant visual features, finite inhibition-of-return, and saccade size constraints. Even though there are no free parameters that are fine-tuned for each specific task, species, or condition, the model produces fixation sequences resembling the universal properties of return fixations. These results provide initial steps towards a mechanistic understanding of the trade-off between rapid foveal recognition and the need to scrutinize previous fixation locations.
Early theories of efficient coding suggested the visual system could compress the world by learning to represent features where information was concentrated, such as contours. This view was validated by the discovery that neurons in posterior visual cortex respond to edges and curvature. Still, it remains unclear what other information-rich features are encoded by neurons in more anterior cortical regions (e.g., inferotemporal cortex). Here, we use a generative deep neural network to synthesize images guided by neuronal responses from across the visuocortical hierarchy, using floating microelectrode arrays in areas V1, V4 and inferotemporal cortex of two macaque monkeys. We hypothesize these images (“prototypes”) represent such predicted information-rich features. Prototypes vary across areas, show moderate complexity, and resemble salient visual attributes and semantic content of natural images, as indicated by the animals’ gaze behavior. This suggests the code for object recognition represents compressed features of behavioral relevance, an underexplored aspect of efficient coding.
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