diff --git a/brian2genn/b2glib/convert_synapses.h b/brian2genn/b2glib/convert_synapses.h
index 3bc1cc16..d7953b92 100644
--- a/brian2genn/b2glib/convert_synapses.h
+++ b/brian2genn/b2glib/convert_synapses.h
@@ -14,19 +14,29 @@ void convert_dynamic_arrays_2_dense_matrix(vector<int32_t> &source, vector<int32
     assert(source.size() == gvector.size());
     unsigned int size= source.size(); 
     for (int s= 0; s < srcNN; s++) {
-	for (int t= 0; t < trgNN; t++) {
-	    g[s*trgNN+t]= (scalar) 0.0;
-	}
+        for (int t= 0; t < trgNN; t++) {
+            g[s*trgNN+t]= (scalar)NAN;
+        }
     }
-//    cerr << size << "!!!!!!" << endl;
+
     for (int i= 0; i < size; i++) {
-	assert(source[i] < srcNN);
-	assert(target[i] < trgNN);
-//	cerr << source[i] << " " << target[i] << " " << gvector[i] << endl;
-	g[source[i]*trgNN+target[i]]= gvector[i];
+        assert(source[i] < srcNN);
+        assert(target[i] < trgNN);
+        // Check for duplicate entries
+        if (! isnan(g[source[i]*trgNN+target[i]])) {
+            std::cerr << "*****" << std::endl;
+            std::cerr << "ERROR  Cannot run GeNN simulation: More than one synapse for pair " << source[i] << " - " << target[i] << std::endl;
+            std::cerr << "*****" << std::endl;
+            exit(222);
+        }
+        g[source[i]*trgNN+target[i]]= gvector[i];
+    }
+    for (int s= 0; s < srcNN; s++) {
+        for (int t= 0; t < trgNN; t++) {
+            if (isnan(g[s*trgNN+t]))
+                g[s*trgNN+t] = 0.0;
+        }
     }
-//    cerr << endl;
-//    cerr << "-------------------------";
 }
 
 namespace b2g {
@@ -46,52 +56,64 @@ void convert_dynamic_arrays_2_sparse_synapses(vector<int32_t> &source, vector<in
     static vector<vector<scalar> > bypreG;
     static unsigned int size;
     if (mode == b2g::FULL_MONTY) {
-	assert(source.size() == target.size());
-	assert(source.size() == gvector.size());
-	bypre.clear();
-	bypre.resize(srcNN);
-	bypreG.clear();
-	bypreG.resize(srcNN);
-	size= source.size();
-	for (int i= 0; i < size; i++) {
-	    assert(source[i] < srcNN);
-	    assert(target[i] < trgNN);
-	    bypre[source[i]].push_back(target[i]);
-	    bypreG[source[i]].push_back(gvector[i]);
-	}
-	// convert this intermediate representation into the sparse synapses struct
-	// assume it has been allocated properly
-	unsigned int cnt= 0;
-	for (int i= 0; i < srcNN; i++) {
-	    size= bypre[i].size();
-	    c.indInG[i]= cnt; 
-	    for (int j= 0; j < size; j++) {
-		c.ind[cnt]= bypre[i][j];
-		gv[cnt]= bypreG[i][j];
+    assert(source.size() == target.size());
+    assert(source.size() == gvector.size());
+    bypre.clear();
+    bypre.resize(srcNN);
+    bypreG.clear();
+    bypreG.resize(srcNN);
+    size= source.size();
+    for (int i= 0; i < size; i++) {
+        assert(source[i] < srcNN);
+        assert(target[i] < trgNN);
+        bypre[source[i]].push_back(target[i]);
+        bypreG[source[i]].push_back(gvector[i]);
+    }
+    // convert this intermediate representation into the sparse synapses struct
+    // assume it has been allocated properly
+    unsigned int cnt= 0;
+    for (int i= 0; i < srcNN; i++) {
+        size= bypre[i].size();
+        c.indInG[i]= cnt;
+        for (int j= 0; j < size; j++) {
+        c.ind[cnt]= bypre[i][j];
+        gv[cnt]= bypreG[i][j];
 //		os << i << " " << c.ind[cnt] << " " << gv[cnt] << endl;
-		cnt++;
-	    }
-	}
-	c.indInG[srcNN]= cnt;
+        cnt++;
+        }
+    }
+    c.indInG[srcNN]= cnt;
     }
     else { // COPY_ONLY
-	bypreG.clear();
-	bypreG.resize(srcNN);
-	size= source.size();
-	for (int i= 0; i < size; i++) {
-	    bypreG[source[i]].push_back(gvector[i]);	    
-	}
-	unsigned int cnt= 0;
-	for (int i= 0; i < srcNN; i++) {
-	    size= bypre[i].size();
-	    for (int j= 0; j < size; j++) {
-		gv[cnt]= bypreG[i][j];
+    bypreG.clear();
+    bypreG.resize(srcNN);
+    size= source.size();
+    for (int i= 0; i < size; i++) {
+        bypreG[source[i]].push_back(gvector[i]);
+    }
+    unsigned int cnt= 0;
+    for (int i= 0; i < srcNN; i++) {
+        size= bypre[i].size();
+        for (int j= 0; j < size; j++) {
+        gv[cnt]= bypreG[i][j];
 //		os << i << " " << c.ind[cnt] << " " << gv[cnt] << endl;
-		cnt++;
-	    }
-	}
+        cnt++;
+        }
+    }
+    }
+
+    // Check for duplicate entries
+    for (int i=0; i<srcNN; i++) {
+        vector<int32_t> targets = bypre[i];
+        std::sort(targets.begin(), targets.end());
+        auto duplicate_pos = std::adjacent_find(targets.begin(), targets.end());
+        if (duplicate_pos != targets.end()) {
+            std::cerr << "*****" << std::endl;
+            std::cerr << "ERROR  Cannot run GeNN simulation: More than one synapse for pair " << source[i] << " - " << *duplicate_pos << std::endl;
+            std::cerr << "*****" << std::endl;
+            exit(222);
+        }
     }
-//    convertCnt++;
 }
 
 template<class scalar>
@@ -101,9 +123,9 @@ void convert_dense_matrix_2_dynamic_arrays(scalar *g, int srcNN, int trgNN, vect
     assert(source.size() == gvector.size());
     unsigned int size= source.size(); 
     for (int i= 0; i < size; i++) {
-	assert(source[i] < srcNN);
-	assert(target[i] < trgNN);
-	gvector[i]= g[source[i]*trgNN+target[i]];
+    assert(source[i] < srcNN);
+    assert(target[i] < trgNN);
+    gvector[i]= g[source[i]*trgNN+target[i]];
     }
 }
 
@@ -116,28 +138,28 @@ void convert_sparse_synapses_2_dynamic_arrays(Conductance &c, scalar *gv, int sr
 //    ofstream os(name.c_str());
 // note: this does not preserve the original order of entries in the brian arrays - is that a problem?
     if (mode == b2g::FULL_MONTY) {
-	assert(source.size() == target.size());
-	assert(source.size() == gvector.size());
-	unsigned int size= source.size();
-	unsigned int cnt= 0;
-	for (int i= 0; i < srcNN; i++) {
-	    for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
-		source[cnt]= i;
-		target[cnt]= c.ind[j];
-		gvector[cnt]= gv[j];
+    assert(source.size() == target.size());
+    assert(source.size() == gvector.size());
+    unsigned int size= source.size();
+    unsigned int cnt= 0;
+    for (int i= 0; i < srcNN; i++) {
+        for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
+        source[cnt]= i;
+        target[cnt]= c.ind[j];
+        gvector[cnt]= gv[j];
 //		os << source[cnt] << " " << target[cnt] << " " << gvector[cnt] << endl;
-		cnt++;
-	    }
-	}
+        cnt++;
+        }
+    }
     }
     else {
-	unsigned int size= source.size();
-	unsigned int cnt= 0;
-	for (int i= 0; i < srcNN; i++) {
-	    for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
-		gvector[cnt++]= gv[j];
-	    }
-	}
+    unsigned int size= source.size();
+    unsigned int cnt= 0;
+    for (int i= 0; i < srcNN; i++) {
+        for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
+        gvector[cnt++]= gv[j];
+        }
+    }
     }
 //    os.close();
 //    convertCnt++;
@@ -146,12 +168,12 @@ void convert_sparse_synapses_2_dynamic_arrays(Conductance &c, scalar *gv, int sr
 void create_hidden_weightmatrix(vector<int32_t> &source, vector<int32_t> &target, char* hwm, int srcNN, int trgNN)
 {
     for (int s= 0; s < srcNN; s++) {
-	for (int t= 0; t < trgNN; t++) {
-	    hwm[s*trgNN+t]= 0;
-	}
+    for (int t= 0; t < trgNN; t++) {
+        hwm[s*trgNN+t]= 0;
+    }
     }
     for (int i= 0; i < source.size(); i++) {
-	hwm[source[i]*trgNN+target[i]]= 1;
+    hwm[source[i]*trgNN+target[i]]= 1;
     }
 }
 #endif
diff --git a/brian2genn/device.py b/brian2genn/device.py
index 21998e97..0a7d8579 100644
--- a/brian2genn/device.py
+++ b/brian2genn/device.py
@@ -677,12 +677,17 @@ def build(self, directory='GeNNworkspace', compile=True, run=True,
             try:
                 self.run(directory, use_GPU, with_output)
             except CalledProcessError as ex:
-                raise RuntimeError(('Project run failed (Command {cmd} '
-                                    'failed with error code {returncode}).\n'
-                                    'See the output above (if any) for more '
-                                    'details.').format(cmd=ex.cmd,
-                                                       returncode=ex.returncode)
-                                   )
+                if ex.returncode == 222:
+                    raise NotImplementedError('GeNN does not support multiple '
+                                              'synapses per neuron pair (use '
+                                              'multiple Synapses objects).')
+                else:
+                    raise RuntimeError(('Project run failed (Command {cmd} '
+                                        'failed with error code {returncode}).\n'
+                                        'See the output above (if any) for more '
+                                        'details.').format(cmd=ex.cmd,
+                                                           returncode=ex.returncode)
+                                       )
 
     def generate_code_objects(self, writer):
         # Generate data for non-constant values