Beyond imagination: Hypnotic visual hallucination induces greater lateralised brain activity than visual mental imagery

Hypnotic suggestions can produce a broad range of perceptual experiences, including hallucinations. Visual hypnotic hallucinations differ in many ways from regular mental images. For example, they are usually experienced as automatic, vivid, and real images, typically compromising the sense of reality. While both hypnotic hallucination and mental imagery are believed to mainly rely on the activation of the visual cortex via top-down mechanisms, it is unknown how they differ in the neural processes they engage. Here we used an adaptation paradigm to test and compare top-down processing between hypnotic hallucination, mental imagery, and visual perception in very highly hypnotisable individuals whose ability to hallucinate was assessed. By measuring the N170/VPP event-related complex and using multivariate decoding analysis, we found that hypnotic hallucination of faces involves greater top-down activation of sensory processing through lateralised neural mechanisms in the right hemisphere compared to mental imagery. Our findings suggest that the neural signatures that distinguish hypnotically hallucinated faces from imagined faces lie in the right brain hemisphere.Fil: Lanfranco, Renzo C.. University of Edinburgh; Reino Unido. Karolinska Huddinge Hospital. Karolinska Institutet; SueciaFil: Rivera Rei, Álvaro. Universidad Adolfo Ibañez; ChileFil: Huepe, David. Universidad Adolfo Ibañez; ChileFil: Ibañez, Agustin Mariano. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina. University of California; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Canales Johnson, Andrés. University of Cambridge; Estados Unidos. Universidad Catolica de Maule; Chil

Higher Order Thought and the Problem of Radical Confabulation

Currently, one of the most influential theories of consciousness is Rosenthal's version of higher-order-thought (HOT). We argue that the HOT theory allows for two distinct interpretations: a one-component and a two-component view. We further argue that the two-component view is more consistent with his effort to promote HOT as an explanatory theory suitable for application to the empirical sciences. Unfortunately, the two-component view seems incapable of handling a group of counterexamples that we refer to as cases of radical confabulation. We begin by introducing the HOT theory and by indicating why we believe it is open to distinct interpretations. We then proceed to show that it is incapable of handling cases of radical confabulation. Finally, in the course of considering various possible responses to our position, we show that adoption of a disjunctive strategy, one that would countenance both one-component and two-component versions, would fail to provide any empirical or explanatory advantage

Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement

We address the problem of restoring a high-resolution face image from a blurry low-resolution input. This problem is difficult as super-resolution and deblurring need to be tackled simultaneously. Moreover, existing algorithms cannot handle face images well as low-resolution face images do not have much texture which is especially critical for deblurring. In this paper, we propose an effective algorithm by utilizing the domain-specific knowledge of human faces to recover high-quality faces. We first propose a facial component guided deep Convolutional Neural Network (CNN) to restore a coarse face image, which is denoted as the base image where the facial component is automatically generated from the input face image. However, the CNN based method cannot handle image details well. We further develop a novel exemplar-based detail enhancement algorithm via facial component matching. Extensive experiments show that the proposed method outperforms the state-of-the-art algorithms both quantitatively and qualitatively.Comment: In IJCV 201