Computational constraints that may have favoured the lamination of sensory cortex

被引:21
作者
Treves, A [1 ]
机构
[1] SISSA, Programme Neurosci, I-34014 Trieste, Italy
关键词
cortical layers; mammals; isocortex; neocortex; cortical organization; localization; attractor dynamics; recurrent collaterals;
D O I
10.1023/A:1023213010875
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
At the transition from early reptilian ancestors to primordial mammals, the areas of sensory cortex that process topographic modalities acquire the laminar structure of isocortex. A prominent step in lamination is granulation, whereby the formerly unique principal layer of pyramidal cells is split by the insertion of a new layer of excitatory, but intrinsic, granule cells, layer IV. I consider the hypothesis that granulation, and the differentiation between supra- and infra-granular pyramidal layers, may be advantageous to support fine topography in their sensory maps. Fine topography implies a generic distinction between "where" information, explicitly mapped on the cortical sheet, and "what" information, represented in a distributed fashion as a distinct firing pattern across neurons. These patterns can be stored on recurrent collaterals in the cortex, and such memory can help substantially in the analysis of current sensory input. The simulation of a simplified network model demonstrates that a non-laminated patch of cortex must compromise between transmitting "where" information or retrieving "what" information. The simulation of a modified model including differentiation of a granular layer shows a modest but significant quantitative advantage, expressed as a less severe trade-off between "what" and "where". The further connectivity differentiation between infra-granular and supra- granular pyramidal layers is shown to match the mix of "what" and "where" information optimal for their respective target structures.
引用
收藏
页码:271 / 282
页数:12
相关论文
共 54 条
[1]  
Abeles M., 1991, CORTICONICS
[2]   Genes that regulate neuronal migration in the cerebral cortex [J].
Allen, KM ;
Walsh, CA .
EPILEPSY RESEARCH, 1999, 36 (2-3) :143-154
[3]  
Allman J., 1990, Cerebral Cortex, V8A, P269
[4]  
Amit D., 1989, Modelling Brain Function: the World of Attractor Neural Networks
[5]  
AMIT DJ, 1995, BEHAV BRAIN SCI, V18, P617, DOI 10.1017/S0140525X00040164
[6]  
Bar Isabella, 2000, Novartis Foundation Symposium, V228, P114
[7]   Cortical structure predicts the pattern of corticocortical connections [J].
Barbas, H ;
RempelClower, N .
CEREBRAL CORTEX, 1997, 7 (07) :635-646
[8]  
Batardiere A, 1998, J COMP NEUROL, V396, P493, DOI 10.1002/(SICI)1096-9861(19980713)396:4<493::AID-CNE6>3.0.CO
[9]  
2-X
[10]  
Bosking WH, 1997, J NEUROSCI, V17, P2112