Auditory scene analysis is critical for complex auditory processing. We study auditory segregation from the neural network perspective, and develop a framework for primitive auditory scene analysis. The architecture is a laterally coupled two‐dimensional network of relaxation oscillators with a global inhibitor. One dimension represents time and another one represents frequency. We show that this architecture, plus systematic delay lines, can in real time group auditory features into a stream by phase synchrony and segregate different streams by desynchronization. The network (...) demonstrates a set of psychological phenomena regarding primitive auditory scene analysis, including dependency on frequency proximity and the rate of presentation, sequential capturing, and competition among different perceptual organizations. We offer a neurocomputational theory—shifting synchronization theory—for explaining how auditory segregation might be achieved in the brain, and the psychological phenomenon of stream segregation. Possible extensions of the model are discussed. (shrink)

Based on a sample of heavily polluting firms listed in China, we examine the impact of environmental taxes on the green M&A behavior of these firms. Our findings underscore that environmental taxes have significantly increased the likelihood of heavily polluting firms engaging in green M&A endeavors. This impact is particularly pronounced in areas with high media attention, low financing constraints, and high environmental investment. However, our examination of the economic consequences shows that green M&A does not improve the green innovation (...) performance and ESG performance of firms. The analysis of M&A motivations shows that the majority of heavy polluters' green M&A targets are located in regions with weak environmental regulation, confirming that green M&A under the environmental tax burden is a tool used by firms to engage in pollution transfer. In addition, green M&A under the environmental tax burden is characterized by financial investment, connected M&A, and nonsignificant M&A, confirming that green M&A under the environmental tax burden may be a tool used by companies seeking only the appearance of “greenwashing.” Therefore, green M&A under the environmental tax burden tends to be underpinned by opportunistic motives of pollution transfer and “greenwashing,” rather than substantive green transformation and upgrading. We provide evidence from emerging markets on the impact of environmental taxes on green M&A, which adds to the literature in this area and has policy implications for government regulation of corporate environmental governance practices. (shrink)

For scene analysis, it is important to ask the question of how synchronized population codes – the basic representation employed in the target article – are generated. Recent computational advances have resolved the critical challenges of rapid synchronization with local coupling and rapid desynchronization. The synchronized codes make real contributions to tackling the problem of scene analysis.