Further Work on the Shaping of Cortical Development and Function by Synchrony and Metabolic Competition

被引:9
作者
Wright, James J. [1 ]
Bourke, Paul D. [2 ]
机构
[1] Univ Auckland, Sch Med, Dept Psychol Med, Auckland, New Zealand
[2] Univ New South Wales, EPICtr, Sydney, NSW, Australia
关键词
synchronous oscillation; cortical development; synaptic development; cortical information flow; cortical computation; PRIMARY VISUAL-CORTEX; ORIENTATION COLUMNS; HORIZONTAL CONNECTIONS; RECEPTIVE-FIELD; SELF-ORGANIZATION; OCULAR DOMINANCE; FEATURE LINKING; SINGLE NEURONS; MODEL; MAPS;
D O I
10.3389/fncom.2016.00127
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
This paper furthers our attempts to resolve two major controversieswhether gamma synchrony plays a role in cognition, and whether cortical columns are functionally important. We have previously argued that the configuration of cortical cells that emerges in development is that which maximizes the magnitude of synchronous oscillation and minimizes metabolic cost. Here we analyze the separate effects in development of minimization of axonal lengths, and of early Hebbian learning and selective distribution of resources to growing synapses, by showing in simulations that these effects are partially antagonistic, but their interaction during development produces accurate anatomical and functional properties for both columnar and non-columnar cortex. The resulting embryonic anatomical order can provide a cortex-wide scaffold for postnatal learning that is dimensionally consistent with the representation of moving sensory objects, and, as learning progressively overwrites the embryonic order, further associations also occur in a dimensionally consistent framework. The role ascribed to cortical synchrony does not demand specific frequency, amplitude or phase variation of pulses to mediate feature linking. Instead, the concerted interactions of pulse synchrony with short-term synaptic dynamics, and synaptic resource competition can further explain cortical information processing in analogy to Hopfield networks and quantum computation.
引用
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页数:16
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