The new concept of local interconnection neural network (LINN) is extended to two-dimensional case. Theoretical analysis and large number of computer simulations on 2-D LINN associative memory are presented. It is concluded that under the limitation of storage capacity LINN has the same associative memory ability as global interconnection neural network (GINN). Moreover, the LINN has a much smaller interconnection weight matrix compared with GINN. Therefore, 2-D LINN makes it possible to realize a large scale neural network by using presently available spatial light modulators.