The scientific study of consciousness emerged as an organized field of research only a few decades ago. As empirical results have begun to enhance our understanding of consciousness, it is important to find out whether other factors, such as funding for consciousness research and status of consciousness scientists, provide a suitable environment for the field to grow and develop sustainably. We conducted an online survey on people’s views regarding various aspects of the scientific study of consciousness as a field of (...) research. 249 participants completed the survey, among which 80% were in academia, and around 40% were experts in consciousness research. Topics covered include the progress made by the field, funding for consciousness research, job opportunities for consciousness researchers, and the scientific rigor of the work done by researchers in the field. The majority of respondents (78%) indicated that scientific research on consciousness has been making progress. However, most participants perceived obtaining funding and getting a job in the field of consciousness research as more difficult than in other subfields of neuroscience. Overall, work done in consciousness research was perceived to be less rigorous than other neuroscience subfields, but this perceived lack of rigor was not related to the perceived difficulty in finding jobs and obtaining funding. Lastly, we found that, overall, the global workspace theory was perceived to be the most promising (around 28%), while most non-expert researchers (around 22% of non-experts) found the integrated information theory (IIT) most promising. We believe the survey results provide an interesting picture of current opinions from scientists and researchers about the progresses made and the challenges faced by consciousness research as an independent field. They will inspire collective reflection on the future directions regarding funding and job opportunities for the field. (shrink)
When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...) unattended stimulus, they rely less on prior information about the probed stimulus’ identity. The model is in part inspired by recent findings that attention reduces trial-by-trial variability of the neuronal population response and that they use a common criterion for attended and unattended trials. In five different visual discrimination experiments, when attention was directed away from the target stimulus, subjects did not adjust their response bias in reaction to a change in stimulus presentation frequency despite being fully informed and despite the presence of performance feedback and monetary and social incentives. This indicates that subjects did not rely more on the priors under conditions of inattention as would be predicted by a Bayes-optimal observer model. These results inform and constrain future models of Bayesian inference in the human brain. (shrink)
It has been widely asserted that humans have a “Bayesian brain.” Surprisingly, however, this term has never been defined and appears to be used differently by different authors. I argue that Bayesian brain should be used to denote the realist view that brains are actual Bayesian machines and point out that there is currently no evidence for such a claim.