Mitchison G J, Swindale N V
Laboratory of Molecular Biology, Medical Research Council Centre, Hills Road, Cambridge, CB2 2QH, United Kingdom.
Neural Comput. 1999 Oct 1;11(7):1519-26. doi: 10.1162/089976699300016115.
It has recently been shown that orientation and retinotopic position, both of which are mapped in primary visual cortex, can show correlated jumps (Das & Gilbert, 1997). This is not consistent with maps generated by Kohonen's algorithm (Kohonen, 1982), where changes in mapped variables tend to be anticorrelated. We show that it is possible to obtain correlated jumps by introducing a Hebbian component (Hebb, 1949) into Kohonen's algorithm. This correspondents to a volume learning mechanism where synaptic facilitation depends not only on the spread of a signal from a maximally active neuron but also requires postsynaptic activity at a synapse. The maps generated by this algorithm show discontinuities across which both orientation and retinotopic position change rapidly, but these regions, which include the orientation singularities, are also aligned with the edges of ocular dominance columns, and this is not a realistic feature of cortical maps. We conclude that cortical maps are better modeled by standard, non-Hebbian volume learning, perhaps coupled with some other mechanism (e.g., that of Ernst, Pawelzik, Tsodyks, & Sejnowski, 1999) to produce receptive field shifts.
最近的研究表明，在初级视觉皮层中映射的方向和视网膜位置都可能出现相关的跳跃（达斯和吉尔伯特，1997年）。这与科霍宁算法（科霍宁，1982年）生成的图谱不一致，在该算法中，映射变量的变化往往是反相关的。我们表明，通过将赫布成分（赫布，1949年）引入科霍宁算法，可以获得相关的跳跃。这对应于一种体积学习机制，其中突触易化不仅取决于来自最大激活神经元的信号传播，还需要突触处的突触后活动。该算法生成的图谱显示出不连续性，在这些不连续处，方向和视网膜位置都会迅速变化，但这些区域，包括方向奇点，也与眼优势柱的边缘对齐，而这并不是皮质图谱的现实特征。我们得出结论，皮质图谱可以通过标准的、非赫布式的体积学习更好地建模，或许再结合一些其他机制（例如，恩斯特、帕维尔齐克、乔迪克斯和塞乔诺斯基，1999年提出的机制）来产生感受野的移动。
