 
 			const int threadIdGrp = (threadIdx.x % UPWTS_CLUSTERING_SZ);
 			// use 32 threads to update 32 synapses parallely
-			for (unsigned int synIdOffset = cumulativePre; synIdOffset < cumulativePre + Npre_plastic; synIdOffset += UPWTS_CLUSTERING_SZ) {
+			for(unsigned int synIdOffset = cumulativePre; synIdOffset < cumulativePre + Npre_plastic; synIdOffset += UPWTS_CLUSTERING_SZ) {
 				//excitatory connection change the synaptic weights
 				unsigned int synId = synIdOffset + threadIdGrp;
-				if (synId < cumulativePre + Npre_plastic) {
+				if(synId < cumulativePre + Npre_plastic) {
 					updateSynapticWeights(nid, synId, grpId, diff_firing, homeostasisScale, baseFiring, avgTimeScaleInv);
 				}
 			}

	}

	// beginning position for the pre-synaptic information
	if (allocateMem)
		CUDA_CHECK_ERRORS(cudaMalloc((void**)&dest->cumulativePre, sizeof(int) * networkConfigs[netId].numNAssigned));
	CUDA_CHECK_ERRORS(cudaMemcpy(&dest->cumulativePre[posN], &src->cumulativePre[posN], sizeof(int) * lengthN, kind));


	assert(runtimeData[netId].memType == GPU_MEM);
	checkAndSetGPUDevice(netId);

	kernel_findFiring<<<NUM_BLOCKS, NUM_THREADS>>>(simTime);
	CUDA_GET_LAST_ERROR("findFiring kernel failed\n");
}

