Paradise Lost: The relationships between neurological and psychological changes in nicotine-dependent patients

The neural reward circuit and cognitive distortion play an important role in addiction; however, the relationship between the two has not yet been addressed. In this article, we review recent findings on nicotine dependence and propose a novel hypothesis. Previous research using functional magnetic resonance imaging (fMRI) has shown that while activation of the reward circuit (ventral striatum) appears in response to tobacco-related rewards in nicotine dependence, responses to rewards other than tobacco (e.g. food and money) are reduced. Moreover, this change is observed at the very early stages of smoking, even when a person has smoked fewer than 10 cigarettes in his/her lifetime. Thus, we propose the following hypothesis, called the Paradise Lost theory: given addicts’ lower ventral striatal responses to non-tobacco rewards, nicotine addiction disables smokers from sensing the pleasures of ordinary life (the Paradise Lost state). However, since smokers do not notice this, they produce an overestimation of tobacco (cognitive distortion), such that they do not have many pastimes other than smoking or feel that quitting smoking would reduce the happiness and pleasure and increase the difficulty of life. Cognitive distortion thus makes it difficult for smokers to take the initiative to quit smoking and even causes relapse after smoking cessation. This theory furthers our understanding of addiction and could improve our approach to the prevention and treatment of addiction

Particle motions around regular black holes

We investigate the bound orbits of massive/massless, neutral particles and photons moving around regular black holes of Fan and Wang. For massive particles, we show the existence of stable/unstable circular orbits and the charge dependence of the radius of the innermost stable circular orbit. Remarkably, we find an unstable circular orbit of photons inside the event horizon. For massless particles and photons, we show that both stable and unstable circular orbits can exist in a regular and horizonless spacetime with a slight overcharge. Then, we also discuss the periapsis shift of massive neutral particles orbiting around the black hole, and show that the charge gives a negative correction to the shift for black holes with small nonlinearity of electrodynamics.Comment: 19 pages, 8 figures; v2: analysis of photon orbits improved, refs added, 21 pages; v3: published version, fixed minor typos, fixed figures, 20 page

Bayesian Filtering with Multiple Internal Models: Toward a Theory of Social Intelligence

To exhibit social intelligence, animals have to recognize whom they are communicating with. One way to make this inference is to select among internal generative models of each conspecific who may be encountered. However, these models also have to be learned via some form of Bayesian belief updating. This induces an interesting problem: When receiving sensory input generated by a particular conspecific, how does an animal know which internal model to update? We consider a theoretical and neurobiologically plausible solution that enables inference and learning of the processes that generate sensory inputs (e.g., listening and understanding) and reproduction of those inputs (e.g., talking or singing), under multiple generative models. This is based on recent advances in theoretical neurobiology—namely, active inference and post hoc (online) Bayesian model selection. In brief, this scheme fits sensory inputs under each generative model. Model parameters are then updated in proportion to the probability that each model could have generated the input (i.e., model evidence). The proposed scheme is demonstrated using a series of (real zebra finch) birdsongs, where each song is generated by several different birds. The scheme is implemented using physiologically plausible models of birdsong production. We show that generalized Bayesian filtering, combined with model selection, leads to successful learning across generative models, each possessing different parameters. These results highlight the utility of having multiple internal models when making inferences in social environments with multiple sources of sensory information