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Extension of Superior Colliculus Based Models of Multisensory Integration to the Cortex. Michael Hadley. Multisensory Integration. Windows of interaction Convert physical properties to neural firings Integrate to create a more accurate representation. Sensory Structures.
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Extension of Superior Colliculus Based Models of Multisensory Integration to the Cortex Michael Hadley
Multisensory Integration • Windows of interaction • Convert physical properties to neural firings • Integrate to create a more accurate representation
Sensory Structures • Information is information • Similar hierarchy • Plasticity rules • Topographical maps • SOM
Multisensory Integration in the Cortex Traditional View New Evidence
Major Discoveries • Connections between sensory areas • ERP time frames of integration • Earliest window defies traditional view • Later windows fit traditional view • Convergence • Single/multi-cell recordings • Population recordings
Computational Modeling • Test hypotheses • Generation of testable predictions
My Proposal • Move subcortical model to cortex • Change the model to fit cortical data • Start to put the puzzle together
Anastasio & Patton’s Model of the SC Modulatory projections come from parietal regions V = visual A = auditory S = somatosensory DSC stands for the deep layer of the SC Primary inputs come from sensory receptors
A&P Two Stage Training • Hebb • Primary connections • Uses SOM • Extracts information • Hebb-anti-Hebb • Modulatory connections • Loosely based on opposite of Hebb • Training to produce MSE
Fit with Literature • Ascending/descending from literature • Modulatory role of descending • Developmental window • Does not show MSD • No inhibition
Stage 1 Training of the forward sensory projections with SOM Training of the projections to association areas with SOM
Stage 2 Hebb-anti-Hebb training according to traditional theories Hebb-anti-Hebb training according to new evidence
Evaluation • Use definition of multisensory integration • Determine which theories are plausible • Information theory • Incorporate inhibition • Supervised learning Future