Optimal Time Window for the Integration of Spatial Audio-Visual Information in Virtual Environments

Sound duration and location may influence both auditory and visual perception with consequences for the judgement of both auditory-visual event location and integration. This study investigated audio-visual integration in a virtual environment using both short- and long-duration auditory stimuli with visual stimuli temporally offset from the start of the auditory stimulus, to investigate the effects of top-down neural effects on perception. Two tasks were used, an auditory localization task and a detection task (judgement of audio-visual synchrony). Eleven participants took part in the study using a HTC Vive Pro. The short-duration auditory stimuli (35-ms spatialized sound) and long-duration auditory stimuli (600-ms non-spatialized sound followed by 35 ms of spatialized sound) were presented at -60°, -30°, 0°, +30° and +60° degrees azimuth, with the visual stimulus presented synchronously or asynchronously with respect to the start of the auditory stimulus. Results showed that localization errors were larger for the longer-duration stimuli and judgements of audiovisual synchrony tended to be improved for stimuli presented at ±30°. Top-down neural processing can affect spatial localization and audio-visual processing. Auditory localization errors and audio-visual synchrony detection may reveal the effects of underlying neural feedback mechanisms that can be harnessed to optimize audio-visual experiences in virtual environments

Toward an Analysis of the Abductive Moral Argument for God’s Existence: Assessing the Evidential Quality of Moral Phenomena and the Evidential Virtuosity of Christian Theological Models

The moral argument for God’s existence is perhaps the oldest and most salient of the arguments from natural theology. In contemporary literature, there has been a focus on the abductive version of the moral argument. Although the mode of reasoning, abduction, has been articulated, there has not been a robust articulation of the individual components of the argument. Such an articulation would include the data quality of moral phenomena, the theoretical virtuosity of theological models that explain the moral phenomena, and how both contribute to the likelihood of moral arguments. The goal of this paper is to provide such an articulation. Our method is to catalog the phenomena, sort them by their location on the emergent hierarchy of sciences, then describe how the ecumenical Christian theological model exemplifies evidential virtues in explaining them. Our results show that moral arguments are neither of the highest or lowest quality yet can be assented to on a principled level of investigation, especially given existential considerations

Multimodal Object Classification Models Inspired by Multisensory Integration in the Brain

Two multimodal classification models aimed at enhancing object classification through the integration of semantically congruent unimodal stimuli are introduced. The feature-integrating model, inspired by multisensory integration in the subcortical superior colliculus, combines unimodal features which are subsequently classified by a multimodal classifier. The decision-integrating model, inspired by integration in primary cortical areas, classifies unimodal stimuli independently using unimodal classifiers and classifies the combined decisions using a multimodal classifier. The multimodal classifier models are implemented using multilayer perceptrons and multivariate statistical classifiers. Experiments involving the classification of noisy and attenuated auditory and visual representations of ten digits are designed to demonstrate the properties of the multimodal classifiers and to compare the performances of multimodal and unimodal classifiers. The experimental results show that the multimodal classification systems exhibit an important aspect of the “inverse effectiveness principle” by yielding significantly higher classification accuracies when compared with those of the unimodal classifiers. Furthermore, the flexibility offered by the generalized models enables the simulations and evaluations of various combinations of multimodal stimuli and classifiers under varying uncertainty conditions