GeNN  1.1
GPU enhanced Neuronal Networks (GeNN)
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extra_neurons.h
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1 
2 
3  // Add new neuron type - LIntF:
4  n.varNames.clear();
5  n.varTypes.clear();
6 
7  n.varNames.push_back(tS("V"));
8  n.varTypes.push_back(tS("float"));
9  n.varNames.push_back(tS("V_NB"));
10  n.varTypes.push_back(tS("float"));
11  n.varNames.push_back(tS("tSpike_NB"));
12  n.varTypes.push_back(tS("float"));
13  n.varNames.push_back(tS("__regime_val"));
14  n.varTypes.push_back(tS("int"));
15  n.pNames.clear();
16 
17  n.pNames.push_back(tS("VReset_NB"));
18  n.pNames.push_back(tS("VThresh_NB"));
19  n.pNames.push_back(tS("tRefrac_NB"));
20  n.pNames.push_back(tS("VRest_NB"));
21  n.pNames.push_back(tS("TAUm_NB"));
22  n.pNames.push_back(tS("Cm_NB"));
23  n.dpNames.clear();
24 
25  n.simCode = tS(" \
26  $(V) = -1000000; \
27  if ($(__regime_val)==1) { \n \
28 $(V_NB) += (Isyn_NB/$(Cm_NB)+($(VRest_NB)-$(V_NB))/$(TAUm_NB))*DT; \n \
29  if ($(V_NB)>$(VThresh_NB)) { \n \
30 $(V_NB) = $(VReset_NB); \n \
31 $(tSpike_NB) = t; \n \
32  $(V) = 100000; \
33 $(__regime_val) = 2; \n \
34 } \n \
35 } \n \
36 if ($(__regime_val)==2) { \n \
37 if (t-$(tSpike_NB) > $(tRefrac_NB)) { \n \
38 $(__regime_val) = 1; \n \
39 } \n \
40 } \n \
41 ");
42 
43  nModels.push_back(n);
44 
45 
46 
47  // Add new neuron type - regular spike:
48  n.varNames.clear();
49  n.varTypes.clear();
50 
51  n.varNames.push_back(tS("V"));
52  n.varTypes.push_back(tS("float"));
53  n.varNames.push_back(tS("count_t_NB"));
54  n.varTypes.push_back(tS("float"));
55  n.varNames.push_back(tS("__regime_val"));
56  n.varTypes.push_back(tS("int"));
57  n.pNames.clear();
58 
59  n.pNames.push_back(tS("max_t_NB"));
60  n.dpNames.clear();
61 
62  n.simCode = tS(" \
63  $(V) = -1000000; \
64  if ($(__regime_val)==1) { \n \
65 $(count_t_NB) += (1)*DT; \n \
66  if ($(count_t_NB) > $(max_t_NB)-0.0001) { \n \
67 $(count_t_NB) = 0; \n \
68  $(V) = 100000; \
69 $(__regime_val) = 1; \n \
70 } \n \
71 } \n \
72 ");
73 
74  nModels.push_back(n);
75 
76 
77 
78  // Add new neuron type - LInt:
79  n.varNames.clear();
80  n.varTypes.clear();
81 
82  n.varNames.push_back(tS("V"));
83  n.varTypes.push_back(tS("float"));
84  n.varNames.push_back(tS("V_NB"));
85  n.varTypes.push_back(tS("float"));
86  n.varNames.push_back(tS("tSpike_NB"));
87  n.varTypes.push_back(tS("float"));
88  n.varNames.push_back(tS("__regime_val"));
89  n.varTypes.push_back(tS("int"));
90  n.pNames.clear();
91 
92  n.pNames.push_back(tS("VReset_NB"));
93  n.pNames.push_back(tS("VThresh_NB"));
94  n.pNames.push_back(tS("tRefrac_NB"));
95  n.pNames.push_back(tS("VRest_NB"));
96  n.pNames.push_back(tS("TAUm_NB"));
97  n.pNames.push_back(tS("Cm_NB"));
98  n.dpNames.clear();
99 
100  n.simCode = tS(" \
101  $(V) = -1000000; \
102  if ($(__regime_val)==1) { \n \
103 $(V_NB) += (Isyn_NB/$(Cm_NB)+($(VRest_NB)-$(V_NB))/$(TAUm_NB))*DT; \n \
104  if ($(V_NB)>$(VThresh_NB)) { \n \
105 $(V_NB) = $(VReset_NB); \n \
106 $(tSpike_NB) = t; \n \
107  $(V) = 100000; \
108 $(__regime_val) = 2; \n \
109 } \n \
110 } \n \
111 if ($(__regime_val)==2) { \n \
112 if (t-$(tSpike_NB) > $(tRefrac_NB)) { \n \
113 $(__regime_val) = 1; \n \
114 } \n \
115 } \n \
116 ");
117 
118  nModels.push_back(n);
119 
120 
tS
#define tS(X)
Macro providing the abbreviated syntax tS() instead of toString().
Definition: toString.h:43
nModels
vector< neuronModel > nModels
Global c++ vector containing all neuron model descriptions.
Definition: utils.h:166