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Realizing the Now-or-Never bottleneck and Chunk-and-Pass processing with Item-Order-Rank working memories and masking field chunking networks

Published online by Cambridge University Press:  02 June 2016

Stephen Grossberg
Stephen Grossberg*
Affiliation:
Center for Adaptive Systems, Boston University, Boston, MA 02215. [email protected]://cns.bu.edu/~steve
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Abstract

Christiansen & Chater's (C&C's) key goals for a language system have been realized by neural models for short-term storage of linguistic items in an Item-Order-Rank working memory, which inputs to Masking Fields that rapidly learn to categorize, or chunk, variable-length linguistic sequences, and choose the contextually most predictive list chunks while linguistic inputs are stored in the working memory.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 39 , 2016 , e75
Copyright
Copyright © Cambridge University Press 2016 

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References

Ames, H. & Grossberg, S. (2008) Speaker normalization using cortical strip maps: A neural model for steady state vowel categorization. Journal of the Acoustical Society of America 124:3918–36.CrossRefGoogle ScholarPubMed
Boardman, I., Grossberg, S., Myers, C. & Cohen, M. (1999) Neural dynamics of perceptual order and context effects for variable-rate speech syllables. Perception and Psychophysics 6:1477–500.CrossRefGoogle Scholar
Cohen, M. A. & Grossberg, S. (1986) Neural dynamics of speech and language coding: Developmental programs, perceptual grouping, and competition for short-term memory. Human Neurobiology 5:1–22.Google Scholar
Grossberg, S. (1973) Contour enhancement, short-term memory, and constancies in reverberating neural networks. Studies in Applied Mathematics 52:213–57.Google Scholar
Grossberg, S. (1978a) A theory of human memory: Self-organization and performance of sensory- motor codes, maps, and plans. In: Progress in theoretical biology, volume 5, ed. Rosen, R. & Snell, F., pp. 233–74. Academic Press.Google Scholar
Grossberg, S. (1978b) Behavioral contrast in short-term memory: Serial binary memory models or parallel continuous memory models? Journal of Mathematical Psychology 3:199–19.CrossRefGoogle Scholar
Grossberg, S. (1986) The adaptive self-organization of serial order in behavior: Speech, language, and motor control. In: Pattern recognition by humans and machines, vol. 1: Speech perception, ed. Schwab, E. C. & Nusbaum, H. C., pp. 187–94. Academic Press.Google Scholar
Grossberg, S. (2003) Resonant neural dynamics of speech perception. Journal of Phonetics 31:423–45.Google Scholar
Grossberg, S. (2013) Adaptive resonance theory: How a brain learns to consciously attend, learn, and recognize a changing world. Neural Networks 37:1–47.Google Scholar
Grossberg, S., Boardman, I. & Cohen, C. (1997) Neural dynamics of variable-rate speech categorization. Journal of Experimental Psychology: Human Perception and Performance 23:418–503.Google Scholar
Grossberg, S. & Kazerounian, S. (2011) Laminar cortical dynamics of conscious speech perception: A neural model of phonemic restoration using subsequent context in noise. Journal of the Acoustical Society of America 130:440–60.Google Scholar
Grossberg, S. & Myers, C. W. (2000) The resonant dynamics of speech perception: Interword integration and duration-dependent backward effects. Psychological Review 107:735–67.Google Scholar
Grossberg, S. & Pearson, L. (2008) Laminar cortical dynamics of cognitive and motor working memory, sequence learning and performance: Toward a unified theory of how the cerebral cortex works. Psychological Review 115:677–32.Google Scholar
Kazerounian, S. & Grossberg, S. (2014) Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory. Frontiers in Psychology: Language Sciences. doi: 10.3389/fpsyg.2014.01053.Google Scholar
Silver, M. R., Grossberg, S., Bullock, D., Histed, M. H. & Miller, E. K. (2011) A neural model of sequential movement planning and control of eye movements: Item-order-rank working memory and saccade selection by the supplementary eye fields. Neural Networks 26:29–58.Google Scholar