and complex networks are constructed by linking correlated events. For example, the region studied may be divided into small cubic cells. Each cell becomes a node in the network if an event happens within it. The network is linked by directed edges between nodes representing successive events in the catalog [3, 7, 8]. Alternately, correlations have been quantified with a metric which incorporates the fractal dimension d$_{f}$ and the b value of the catalog used. Links are made between highly correlated events with directed edges [4, 5, 9]. A third procedure involves identifying record breaking recurrences of an event and linking each event in the catalog to its recurrences with directed edges [2, 10]. This procedure, illustrated on the earthquake catalog of Southern California had evolved a general method for inferring causal connections. The patterns exhibited by a network constructed from the actual catalog of the region was compared with the network of a randomly shuffled catalog (acausal) in order to establish causal features. In addition, this approach provides a method of estimating the rupture length, its scaling with magnitude and in identifying new scaling laws associated with the seismicity of the region. In this paper, we apply the procedure developed by the authors[2, 10] on the earthquake catalog of Japan, in order to study the patterns exhibited by its network and to examine the robustness of the procedure for different seismic regions. This paper is organised as follows:- Section II briefly describes the construction of the network, Section III will describe the catalogs used for the analysis, Section IV contains the results and a discussion of it and in Section V we conclude. The procedure described in [10] is followed here to identify the recurrences and to con- struct the network. A directed network is constructed by linking each event i , (i = 1,2,3, · · · ,N) in a catalog of N events with a magnitude threshold of m$_{th}$ , with an edge pointing from it ( main event) to its recurrence. Each recurrence j , ( j = i+1, · · · ,N) is a record breaking event which is closer to the main event i than any event k in the intervening period t$_{j}$ − t$_{i}$ where t$_{j}$ > t$_{k}$ > t$_{i}$ . This implies that the ( i +1) th event is the first recurrence of the i th event for i = 1 , 2 , · · · , N − 1 and is always a recurrence however distant it might be. In this way, each event gets to have its own list of recurrences which follow it in time. This definition of a recurrence is based solely on the spatiotemporal relations between events in the catalog 3 II. CONSTRUCTION OF THE NETWORK