聲音療癒特性的評估

Abstract

Many psychological studies have shown an effect of environment on human stress, and emphasized that natural environments, on the contrary to urban ones, have positive effects at several levels: cognitive, affective and physiological. Different theories tried to propose a global frame that explains these observations, but a key issue that seems to make them contradict each other is to know if human response facing an environment is first cognitive or affective. However, in all the proposed theories, evolution plays an important role as it gives us tools to deal with information we received, which isn’t possible without establishing preferences. In this study, we try to have a more objective view on the phenomenon, as we hope retrieving any psychological aspect from the reasoning. We consider human a little like a machine, but one shouldn’t be fooled, it is only to understand better our differences. This paper aims to establish a first attempt to understand how the environment, seen as neutral information as long as it has not been treated yet, may hide in its very structure some triggers of stress or even meaning. Can we analyze independently this structure from the receiver that deals with the information? To this end we set up an experiment that tries to determine a complexity effect of the signal on affective and cognitive state. For this experiment we recorded EEG from 40 participants while they were listening to 4 songs of different complexities and doing some simple arithmetical tasks. At the end they were asked to rank the sounds according to their preference. We used several measures of complexity of the stimuli to see more in detail how it would impact the EEG, the participants’ results and the song they preferred. We got significant results for the preference ratings but not for the tasks results. Because our way of recording EEG was a little inadequate, it was difficult to draw any definitive conclusion out of the data but we presented a lot of techniques to be applied in further studies and drew some hypothesis from the literature. In this respect, our paper doesn’t have any other claim that proposing a general frame and hypothesis that link stress recovery and predictive coding, before a stronger validation from robust EEG data.