Abstract
As sensory systems deteriorate in aging or disease, the brain must relearn the appropriate weights to assign each modality during multisensory integration. Using blood-oxygen level dependent functional magnetic resonance imaging of human subjects, we tested a model for the neural mechanisms of sensory weighting, termed “weighted connections.” This model holds that the connection weights between early and late areas vary depending on the reliability of the modality, independent of the level of early sensory cortex activity. When subjects detected viewed and felt touches to the hand, a network of brain areas was active, including visual areas in lateral occipital cortex, somatosensory areas in inferior parietal lobe, and multisensory areas in the intraparietal sulcus (IPS). In agreement with the weighted connection model, the connection weight measured with structural equation modeling between somatosensory cortex and IPS increased for somatosensory-reliable stimuli, and the connection weight between visual cortex and IPS increased for visual-reliable stimuli. This double dissociation of connection strengths was similar to the pattern of behavioral responses during incongruent multisensory stimulation, suggesting that weighted connections may be a neural mechanism for behavioral reliability weighting.
Highlights
Integrating information from different sensory modalities is critical for obtaining an accurate representation of the environment
A better understanding of the neural mechanisms for reliabilityweighted multisensory integration may help in the development of treatment and rehabilitation strategies for the many disorders in which the information from a sensory modality is degraded, such as vision loss due to macular degeneration
When unreliable stimuli were presented in both modalities simultaneously, performance improved to 79 ± 3% for visual-somatosensory (Figure 2A)
Summary
Integrating information from different sensory modalities is critical for obtaining an accurate representation of the environment. Computational modeling studies have suggested that reliability weighting could occur by a simple linear summation of neuronal responses (Ma et al, 2006; Ma and Pouget, 2008) This model, which we term the “linear summation” model, predicts that increasing stimulus reliability scales the responses of neurons in sensory cortex (“early” areas) that respond to that stimulus. In an alternative model, which we term the “weighted connections” model, the connection weights between early and late areas change depending on the reliability of the stimulus (and are independent of the level of activity in early areas). Morgan et al, derived these weights from response measurements within a single area without directly measuring connection strengths between areas
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