Presentation 2013-07-19
A neuroscientific explanation for the brain's memory system with the cocktail party effect by the iterative learning method : A Hebb's learning model for the network system of neurons with the analog-digital operating characteristics
Miyuki Seino,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper describes the cocktail party effect as a phenomenon of the brain's active memory system by iterative learning mechanism. The quantity of memory for an object is increased with the number of times of learning the features in the object, along the sigmoid learning curve. The transient noise during learning may not be memorized because of the fewer number of learning. Indeed, the iterative learning mechanism is an automatic valuation system as well as an automatic noise reduction system for memorizing. The memory model is statistical as well as based on Hebb's learning model on the neuron-synapse level.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) cocktail party effect / iterative learning mechanism / active memory / noise reduction / evaluation / EPSP
Paper # NC2013-15
Date of Issue

Conference Information
Committee NC
Conference Date 2013/7/12(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A neuroscientific explanation for the brain's memory system with the cocktail party effect by the iterative learning method : A Hebb's learning model for the network system of neurons with the analog-digital operating characteristics
Sub Title (in English)
Keyword(1) cocktail party effect
Keyword(2) iterative learning mechanism
Keyword(3) active memory
Keyword(4) noise reduction
Keyword(5) evaluation
Keyword(6) EPSP
1st Author's Name Miyuki Seino
1st Author's Affiliation Seino Inc.()
Date 2013-07-19
Paper # NC2013-15
Volume (vol) vol.113
Number (no) 148
Page pp.pp.-
#Pages 6
Date of Issue