Final Report Summary - TICS (Temporal Information in Crossmodal Stimuli)
The goal of the project has been to understand how the brain processes multisensory stimuli in the perceptual estimation of temporal properties. Our senses are exposed to separate streams of information, but our brain can integrate redundant signals into a unique perceptual experience despite different latency and processing speed. Perceptual integration has been shown to adhere to the principles of Bayesian statistics for spatial properties, but a similar analysis has not been fully developed for the temporal domain. In particular, the neural mechanisms that are responsible for perceptual effects associated with these computations are yet to be identified.
Our brain is able to represent statistical characteristics of sensory stimulation and regularities to predict incoming stimuli. Understanding how temporal properties are perceived and how the timing of sensory information is represented will allow identifying how sensory information is treated so so exploit this knowledge in terms of design guidelines for technological devices that produce multisensory signals.
The first and primary objective of the project has been to find a way to measure and describe the facilitatory and inhibitory effects of multisensory stimuli in the time domain. This research allowed a better understanding of the predictive abilities that underly the processing of multisensory stimuli. A second goal of the project has been to define integration and interference effects in the presence of multiple signals. This investigation allowed the generation of an accurate account of multisensory integration using the Bayesian Inference framework. The third goal has been to build a computational model of the perception of temporal properties that accounts for the dynamic and oscillatory nature of sensory signals and relate this model to the recording of brain activity. The fourth purpose of the proposal has been to understand the relation between the distance of an event in the environment and the asynchrony of crossmodal signals. Understanding the brain mechanisms involved has the potential to capture and make use of the distance-asynchrony relation for improving the reproduction of audiovisual environments. The fifth goal has been to identify the computational mechanisms that allow the brain to change perceptual latency. The results obtained have the potential of allowing the exploitation of the flexibility in multisensory perception for technological applications.
The results of the work have been published in 9 journal articles, plus several other manuscripts that are currently being prepared. The project lead to the successful development of a set of collaborative projects that investigate the perception of temporal properties and the production of timed responses, all captured in the framework of Bayesian inference.
Thanks to the project Dr Di Luca has obtained a permanent position as a Lecturer at the University of Birmingham. The fellowship delivered significant support for Dr Di Luca to allow him to start his lab, and also provided funds to employ a PhD student. The project has also attracted several postgraduate students that have enabled collaborations with other research labs.
Throughout the project, Dr Di Luca has engaged in several dissemination and training activities. The supervisory roles undertaken have enabled effective transfer of knowledge and expertise to the Universities of Birmingham. These include hosting a regular journal club, the delivery of postgraduate lectures on computational modeling of perception, active collaboration with colleague research staff that resulted in joint grant applications and publications beyond the scope of the project, participation in the activity of other research labs, mentoring research students, and the training of researchers on psychophysics methods.
Our brain is able to represent statistical characteristics of sensory stimulation and regularities to predict incoming stimuli. Understanding how temporal properties are perceived and how the timing of sensory information is represented will allow identifying how sensory information is treated so so exploit this knowledge in terms of design guidelines for technological devices that produce multisensory signals.
The first and primary objective of the project has been to find a way to measure and describe the facilitatory and inhibitory effects of multisensory stimuli in the time domain. This research allowed a better understanding of the predictive abilities that underly the processing of multisensory stimuli. A second goal of the project has been to define integration and interference effects in the presence of multiple signals. This investigation allowed the generation of an accurate account of multisensory integration using the Bayesian Inference framework. The third goal has been to build a computational model of the perception of temporal properties that accounts for the dynamic and oscillatory nature of sensory signals and relate this model to the recording of brain activity. The fourth purpose of the proposal has been to understand the relation between the distance of an event in the environment and the asynchrony of crossmodal signals. Understanding the brain mechanisms involved has the potential to capture and make use of the distance-asynchrony relation for improving the reproduction of audiovisual environments. The fifth goal has been to identify the computational mechanisms that allow the brain to change perceptual latency. The results obtained have the potential of allowing the exploitation of the flexibility in multisensory perception for technological applications.
The results of the work have been published in 9 journal articles, plus several other manuscripts that are currently being prepared. The project lead to the successful development of a set of collaborative projects that investigate the perception of temporal properties and the production of timed responses, all captured in the framework of Bayesian inference.
Thanks to the project Dr Di Luca has obtained a permanent position as a Lecturer at the University of Birmingham. The fellowship delivered significant support for Dr Di Luca to allow him to start his lab, and also provided funds to employ a PhD student. The project has also attracted several postgraduate students that have enabled collaborations with other research labs.
Throughout the project, Dr Di Luca has engaged in several dissemination and training activities. The supervisory roles undertaken have enabled effective transfer of knowledge and expertise to the Universities of Birmingham. These include hosting a regular journal club, the delivery of postgraduate lectures on computational modeling of perception, active collaboration with colleague research staff that resulted in joint grant applications and publications beyond the scope of the project, participation in the activity of other research labs, mentoring research students, and the training of researchers on psychophysics methods.