Multisensory Causal Inference in the Brain
By Christoph Kayser, Ladan Shams. 2015
133 citations recorded by the source corpus.
At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions.
Subfields: Experimental and Cognitive Psychology, Nutrition and Dietetics, Sensory Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Experimental and Cognitive Psychology
- Brian Odegaard
- David R. Wozny
- German Ignacio Parisi
- Ladan Shams
- Stefan Wermter
- Pablo V. A. Barros
- Xun Liu
- Haiyan Wu
In Nutrition and Dietetics
In Sensory Systems
- Brian Odegaard
- German Ignacio Parisi
- Stefan Wermter
- David R. Wozny
- Pablo V. A. Barros
- Xun Liu
- Ladan Shams
- Micah M. Murray
Citations in the corpus
- Expectation Learning for Adaptive Crossmodal Stimuli Association (2018, background): “Neurophysiological findings evidence that different brain regions are activated and communicating with each other also when processing unisensory information [10].”
- Biases in Visual, Auditory, and Audiovisual Perception of Space (2015, methodology): “This model has been very successful in accounting for human observers’ data in a variety of multisensory tasks [30–35] and a recent brain imaging study has provided further support for the brain utilizing this computation in the spatial localization task that is used in this study [36,37].”
- A computational model of crossmodal processing for conflict resolution (2017, background): “Although it is known that prior knowledge and expectations modulate multimodal processing [9], behavioral studies have so far mostly focused on the processing of simple stimuli that neglect the role of cortical areas (e.”