Objective
The neocortex underlies higher cognitive functions in mammals and humans. Its computational function is essential for categorizing external objects into supramodal percepts. This natural categorization depends on multisensory integration to become largely independent of the modality through which relevant input is acquired. In contrast, this remarkable cognitive ability is poorly emulated by artificial systems. The anatomical cortical architecture shows extensive connectivity across its different sensory areas, departing from the classically assumed hierarchical processing scheme. Recent studies demonstrated that primary sensory cortical areas coding for distinct modalities are already interconnected, but the computational role of these heteromodal connections is unknown. My goal is to test whether heteromodal interactions in primary sensory cortical areas transmit inferences about the identity of behaviorally relevant objects perceived across multiple sensory channels. The working hypothesis is that these interactions modify the primary representation of unimodal sensory stimuli, resulting in supramodal perceptual invariance, even in ambiguous unimodal contexts. This study will be carried out in awake behaving rodents trained to discriminate between two multimodal objects, which require the two sensory modalities to be fully distinguished. State-of-the art techniques (two-photon calcium imaging and multisite electrode arrays) to record from large scale neural assemblies, will be combined with modern analysis of neural population dynamics and network simulations. Underlying mechanisms will be explored by optogenetic targeting of specific neuronal populations. My long-term aim is to quantitatively explain encoding and classification of multisensory cues across primary sensory cortical areas. I hope to derive novel generic computational principles by which brain circuits build invariant representations of the environment from ever-changing multisensory input streams.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesneurobiologycognitive neuroscience
- natural scienceschemical sciencesinorganic chemistryalkaline earth metals
- natural sciencesbiological scienceszoologymammalogy
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Call for proposal
FP7-PEOPLE-2012-CIG
See other projects for this call
Coordinator
75794 Paris
France