Introduction
Methods and Results
Selection of Models
Characteristics of Models
C++
, MATLAB®) to implement their model and made their model code available both as a supplementary to their article and in GitHub (https://github.com/LeonidSavtchenko/Arachne/tree/master/ExamplePLOS). Stimberg et al. (2019) implemented their model with Brian 2 (Goodman & Brette, 2008) and made their model code available in GitHub (https://github.com/mdepitta/comp-glia-book/tree/master/Ch18.Stimberg). Nine models were specialized to cerebral cortex, eight to hippocampus, one to spinal cord, and two to thalamocortical networks, while 12 models were generic models not developed for any specific brain area. Only two of the studies compared the simulation results to experimental data either qualitatively or quantitatively (Amiri et al., 2013a; Chan et al., 2017). Amiri et al. (2013a) compared their model to local field potential (LFP) recordings from rat hippocampal cornu ammonis 1 (CA1) brain slices in vitro. Chan et al. (2017) compared their model to multi-electrode array (MEA) recordings from dissociated cortical cultures of Wistar rat embryos at day 18. In addition, bifurcation analysis was done with a couple of models (see, e.g., Amiri et al., 2012b; Hayati et al., 2016; Li et al., 2016; Tang et al., 2017; Makovkin et al., 2020) which, in general, helps in understanding the dynamical behavior of the models.Cell Models
Modeled Neuronal Mechanisms
Modeled Astrocytic Mechanisms
Interactions between Cells
Mechanisms of Functional Interaction between Modeled Neurons and Astrocytes
Spatial Organization and Structure of Interactions between Cells
Neural Functions Studied with Models
Discussion
Conclusion
Study
|
Tool/ availability
|
Brain area/data
|
Neurons
|
Astrocytes
|
Function
|
---|---|---|---|---|---|
Abed et al. (2020) | n/a | Generic | 10,000 E & I | n/a | Sgn./Inf. |
Aleksin et al. (2017) | Arachne/GitHub | Hippocampal CA1 | 100 PY & 100 IN | 100 | Sync., Plast. |
Allegrini et al. (2009) | n/a | Cortex | 39 E & 10 I | 400 | Sync. |
Amiri et al. (2012a) | n/a | Hippocampal CA1 | 5 PY & 5 IN | 5 | Sync. |
Amiri et al. (2012b) | Simulink® | Thalamocortical | Lumps of PY, IN, TC & RE | Lumps | Hyper. |
Amiri et al. (2012c) | n/a | Thalamocortical | Lumps of PY & IN | Lumps | Sync. |
Amiri et al. (2013a) | Simulink® | Hippocampal CA1/in vitro LFP | 50 PY & 50 IN | 50 | Sync. |
Chan et al. (2017) | C++
| Cortex/MEA cultures | 8,000 E & 2,000 I | 10,000 | Sync. |
Gordleeva et al. (2019) | n/a | Hippocampal CA1-CA3 | 2, 4, 36, 100 E | 1–2 | Ca2+, Sync., Plast. |
Haghiri et al. (2016) | HW | Generic | 2–100 E | 1–90 | Sync., HW |
Haghiri et al. (2017) | HW | Generic | 2–1,000 E | 1–500 | Sync., HW |
Haghiri and Ahmadi (2020) | n/a | Generic | 1,000 E | 500 | Sync. |
Hayati et al. (2016) | HW | Generic | n/a E | n/a | Sync., Plast., HW |
Kanakov et al. (2019) | n/a | Hippocampus | 5 E & 1 I / 6 E | 6 | Sgn./Inf. |
Lenk et al. (2020) | INEXA | Generic | 200 E & 50 I | 28, 63, 107 | Sync. |
Li et al. (2016) | n/a | Hippocampus | 50 PY & 50 IN | 50 | Sgn./Inf. |
Li et al. (2020) | Brian 2 | Cortex | 400 E & 100 I | 400 | Sync., E-I balance |
Liu and Li (2013a) | n/a | Cortex | 800 E & 200 I / 1,000 E | 4,221 | Sgn./Inf., Sync. |
Liu and Li (2013b) | n/a | Generic | 3 E & I | 6 | Ca2+, Sgn./Inf. |
Liu et al. (2016) | HW | Generic | 10–250,000 E | 1–25,000 | HW |
Makovkin et al. (2020) | n/a | Generic | 2 E / 2 I | 2 | Sync. |
Mesiti et al. (2015) | n/a | Hippocampal CA3 | 2 PY | 1, 20 | Ca2+, Plast. |
Naeem et al. (2015) | n/a | Generic | 22–110 E | 1–5 | Plast. |
Nazari and Faez (2019) | n/a | Cortex | 2,500 PY & 2,500 IN | 2,500 | Sgn./Inf., Classif. |
Nazari et al. (2020) | n/a | Cortex | 4,010 PY & 1,000 IN | 1,501,674 | Sgn./Inf., Classif. |
Postnov et al. (2009) | n/a | Generic | 2–3 E | 1–10 | Ca2+, E-I balance |
Soleimani et al. (2015) | HW | Generic | n/a E | 1–24 | Sync., HW |
Stimberg et al. (2019) | Brian 2/GitHub | Neocortex | 3,200 E & 800 I | 3,200 | Sync. |
Tang et al. (2017) | n/a | Cortex | 100 E | 100 | Hyper. |
Yang and Yeo (2015) | n/a | Spinal cord | 107 E | 28 | Sgn./Inf. |
Yao et al. (2018) | n/a | Cortex | 1–6 E | 1–6 | Hyper. |
Yu et al. (2020) | n/a | Hippocampal CA3 | 50 PY & 50 IN | 50 | Sync. |
Study
|
NN interactions
|
NA interactions
|
AN interactions
|
AA interactions
|
---|---|---|---|---|
Abed et al. (2020) | EE/EI/IE/II: \(V_{\textrm{m,pre}} \rightarrow S \rightarrow V_{\textrm{m,post}}\) | EA/IA: \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow \mathrm {IP_{3ast}}\) | AE/AI: \(I_{\textrm{ast}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}}=c\mathrm {Glu_{ext}}\) | AA: IP3 via GJs |
Aleksin et al. (2017) | EE/II(2), EI/IE(0–1): \(V_{\textrm{m,pre}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA/IA(0–1): \(V_{\textrm{m,pre}} \rightarrow \mathrm {[NT]} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(0–1): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow p_{\textrm{syn,rel}}\) | AA(2): Ca2+ via GJs |
Allegrini et al. (2009) | EE/EI/IE/II: \(V_{\textrm{m,pre}} \rightarrow S \rightarrow V_{\textrm{m,post}}\) | EA(1): \(V_{\textrm{m,pre}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI: \(I_{\textrm{astro}} \rightarrow V_{\textrm{m,post}}\) | AA(2–4): Ca2+ and IP3 via GJs |
Amiri et al. (2012a) | EE/II(0–1), EI(1), IE(1–2): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA(1): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(1): \(I_{\textrm{ast}} \rightarrow V_{\mathrm {m,PY/IN}}\), \(I_{\textrm{ast}}=cf\) | AA(1–2): IP3 via GJs |
Amiri et al. (2012b) | EE/EI/IE: \(V_{\textrm{m,pre}} \rightarrow g_{\mathrm{syn},\mathrm{AMPAR}/\mathrm{GABAAR}/\mathrm{GABABR}} \rightarrow\) \(I_{\mathrm{syn},\mathrm{AMPAR}/\mathrm{GABAAR}/\mathrm{GABABR}} \rightarrow V_{\textrm{m,post}}\), \(C_{\textrm{gain}}\) | EA: \(F_{\textrm{PY}} \rightarrow S_{\textrm{m}}\) | AE/AI: \(G_{\textrm{m}} \rightarrow C_{\textrm{gain}}\) | AA: IP3 via GJs |
Amiri et al. (2012c) | EE/EI/IE: \(V_{\textrm{m,pre}} \rightarrow g_{\mathrm{syn},\mathrm{AMPAR}/\mathrm{GABAAR}/\mathrm{GABABR}} \rightarrow\) \(I_{\mathrm{syn},\mathrm{AMPAR}/\mathrm{GABAAR}/\mathrm{GABABR}} \rightarrow V_{\textrm{m,post}}\), \(C_{\textrm{gain}}\) | EA: \(F_{\textrm{PY}} \rightarrow S_{\textrm{m}}\) | AE/AI: \(G_{\textrm{m}} \rightarrow C_{\textrm{gain}}\) | AA: IP3 via GJs |
Amiri et al. (2013a) | EE/II(0–1), EI(1), IE(1–2): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA/IA(1): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(1): \(I_{\textrm{ast}} \rightarrow V_{\mathrm {m,PY/IN}}\), \(I_{\textrm{ast}}=cf\) | AA(1–2): IP3 via GJs |
Chan et al. (2017) | Network 1 & 2: EE(\(p=0.19\)), EI(\(p=0.23\)), IE(\(p=0.21\)), II(\(p=0.17\)): \(V_{\textrm{m,pre}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1 & 2: EA/IA: \(V_{\textrm{m,N}} \rightarrow \mathrm {[IP_3]_{ast}}\) | Network 1 & 2: AE/AI: \(I_{\textrm{ast}} \rightarrow V_{\mathrm {m,E/I}}\), \(I_{\textrm{ast}}=cf\) | Network 2: AA: IP3 via GJs |
Gordleeva et al. (2019) | EE(\(p=0.2\)): \(V_{\textrm{m,pre}} \rightarrow \mathrm {Glu_{syn}} \rightarrow\) \(I_{\textrm{syn,NMDAR}} \rightarrow V_{\textrm{m,post}}\) | EA(1–2): \(V_{\textrm{m,pre}} \rightarrow \mathrm {Glu_{syn}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE(1, 14, 28): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow \mathrm {D\text {-}serine_{ext}}\rightarrow I_{\textrm{syn,NMDAR}} \rightarrow V_{\textrm{m,post}}\), \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow \mathrm {Glu_{ext}} \rightarrow\mathrm {Glu_{syn}} \rightarrow I_{\mathrm{syn,NMDAR}}\rightarrow V_{\textrm{m,post}}\) | AA(1): Ca2+ and IP3 via GJs |
Haghiri et al. (2016) | Network 1 & 2: EE(0–1): \(V_{\textrm{m,pre}} \rightarrow z \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1: EA(1–4); Network 2: EA(1–2): \(u_{\textrm{post}} \rightarrow \mathrm {{Ca^{2+}_{ast}}}\), \(V_{\textrm{m,pre}} \rightarrow z \rightarrow S_{\textrm{m}}\) | Network 1 & 2: AE(1): \(G_{\textrm{m}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}}=cG_{\textrm{m}}\), \(I_{\textrm{syn}} = (k-cG_{\textrm{m}})(z-z_0)\) | Network 2: AA(1–2): n/a |
Haghiri et al. (2017) | Network 1: EE(0–1); Network 2: EE: \(V_{\textrm{m,pre}} \rightarrow z \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1: EA(1–2); Network 2: EA(0–2): \(u_{\textrm{post}} \rightarrow \mathrm {{Ca^{2+}_{ast}}}\), \(V_{\textrm{m,pre}} \rightarrow z \rightarrow S_{\textrm{m}}\) | Network 1 & 2: AE(1): \(G_{\textrm{m}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\), \(I_{\mathrm {ast,ATP/Glu}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast,ATP}}=cG_{\textrm{a}}\), \(I_{\textrm{ast,Glu}}=cG_{\textrm{m}}\), \(I_{\textrm{syn}} = (k-cG_{\textrm{m}})(z-z_0)\) | None |
Haghiri and Ahmadi (2020) | EE: \(V_{\textrm{m,pre}} \rightarrow z \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA(1): \(u_{\textrm{post}} \rightarrow \mathrm {{Ca^{2+}_{ast}}}\), \(V_{\textrm{m,pre}} \rightarrow z \rightarrow S_{\textrm{m}}\) | AE(1): \(G_{\textrm{m}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}}=cG_{\textrm{m}}\), \(I_{\textrm{syn}} = (k-cG_{\textrm{m}})(z-z_0)\) | None |
Hayati et al. (2016) | EE(0–1): \(V_{\textrm{m,pre}} \rightarrow z \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA(1–4): \(V_{\textrm{m,pre}} \rightarrow z \rightarrow S_{\textrm{m}}\), \(w_{\textrm{post}} \rightarrow \mathrm {{Ca^{2+}_{ast}}}\) | AE(2): \(G_{\textrm{m}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}} \rightarrow V_{\textrm{m,post}}\), \(I_{\textrm{ast}}=cG_{\textrm{m}}\), \(I_{\textrm{syn}} = (k-cG_{\textrm{m}})(z-z_0)\) | AA: n/a |
Kanakov et al. (2019) | Network 1: EE/EI/IE(\(p=0.33\)); Network 2: EE(5): \(V_{\textrm{m,pre}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1: EA/IA(1); Network 2: EA(1): n/a | Network 1: AE/AI(1); Network 2: AE(1): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow g_{\textrm{syn}}\) \(\rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1 & 2: AA(2–3): Ca2+ and IP3 via GJs |
Lenk et al. (2020) | EE/EI/IE/II(\(p=0.29\)): \(F_{\textrm{pre}} \rightarrow p_{\textrm{spike}} \rightarrow p_{\textrm{syn,rel}}\) \(\rightarrow \textrm{NT} \rightarrow I_{\textrm{syn}} \rightarrow F_{\textrm{post}}\) | EA(0–1): \(F_{\textrm{pre}} \rightarrow p_{\textrm{spike}} \rightarrow\) \(p_{\textrm{syn,rel}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(130–250): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow s_{\textrm{Rpre}} \rightarrow p_{\textrm{syn,rel}}\), \(S_{\textrm{ast}} \rightarrow F_{\textrm{post}}\) | AA(1–5): IP3 via GJs |
Li et al. (2016) | EE/II(0–1), EI(1), IE(1–2): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow g_{\textrm{syn}}\) \(\rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA/IA(1): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(1): Dext: [ATP]ext and [Glu]ext, \(I_{\textrm{ast,ATP}} \rightarrow V_{\textrm{m,PY}}\), \(I_{\textrm{ast,Glu}} \rightarrow V_{\textrm{m,IN}}\), \(I_{\textrm{ast,ATP}}=c\mathrm {[ATP]_{ext}}\), \(I_{\textrm{ast,Glu}}=c\mathrm {[Glu]_{ext}}\) | AA(1–2): IP3 via GJs |
Li et al. (2020) | EE/EI/IE/II(\(p=0.2\)): \(V_{\textrm{m,pre}} \rightarrow p_{\textrm{syn,rel}} \rightarrow \mathrm {[Glu]_{syn}} \rightarrow g_{\mathrm {syn,AMPAR/NMDAR}} \rightarrow\) \(I_{\mathrm {syn,AMPAR/NMDAR}} \rightarrow V_{\textrm{m,post}}\), \(V_{\textrm{m,pre}} \rightarrow p_{\textrm{syn,rel}} \rightarrow \mathrm {[GABA]_{syn}} \rightarrow g_{\textrm{syn,GABAAR}} \rightarrow\) \(I_{\textrm{syn,GABAAR}} \rightarrow V_{\textrm{m,post}}\) | EA(\(\approx\) 100): \(V_{\textrm{m,pre}} \rightarrow p_{\textrm{syn,rel}} \rightarrow\) \(\mathrm {[Glu]_{syn}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE(\(\approx\) 100): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow p_{\textrm{ast,rel}} \rightarrow \mathrm {[Glu]_{ext}} \rightarrow\) \(s_{\textrm{mGluRpre}} \rightarrow p_{\textrm{syn,rel}}\), \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow p_{\textrm{ast,rel}} \rightarrow\) \(\mathrm {[Glu]_{ext}} \rightarrow g_{\mathrm {syn,AMPAR/NMDAR}} \rightarrow\) \(I_{\mathrm {ast,AMPAR/NMDAR}} \rightarrow V_{\textrm{m,post}}\) | AA(\(\approx\) 4): IP3 via GJs |
Liu and Li (2013a) | Network 1: EE/IE(80), EI/II(20); Network 2: EE(100): \(V_{\textrm{m,pre}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1 & 2: EA: \(V_{\textrm{m,pre}} \rightarrow \mathrm {[Glu]_{syn}} \rightarrow \mathrm {[IP_3]_{ast}}\) | Network 1: AE/AI; Network 2: AE: \(I_{\textrm{astro}} \rightarrow V_{\textrm{m,N}}\) | Network 1 & 2: AA(2–4): Ca2+ and IP3 via GJs |
Liu and Li (2013b) | Network 1: EE(0–2); Network 2: EE/EI(0–1), IE(1); Network 3: EE(0–1), EI(1); Network 4: EI(2), II(0–1): \(V_{\textrm{m,pre}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1, 2, 3 & 4: EA(1): \(V_{\textrm{m,pre}} \rightarrow \mathrm {[IP_3]_{ast}}\) | Network 1: AE(0–1); Network 2 & 3: AE/AI(0–1); Network 4: AI(0–1): \(I_{\textrm{astro}} \rightarrow V_{\textrm{m,N}}\) | Network 1, 2, 3 & 4: AA(2–3): Ca2+ and IP3 via GJs |
Liu et al. (2016) | EE: \(p_{\textrm{syn,rel}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\), \(V_{\textrm{m,post}} \rightarrow \mathrm {[2\text {-}AG]_{post}}\) \(\rightarrow \textrm{DSE} \rightarrow p_{\textrm{syn,rel}}\) | EA: \(V_{\textrm{m,post}} \rightarrow \mathrm {[2\text {-}AG]_{post}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE: \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow \mathrm {[Glu]_{ext}} \rightarrow \mathrm {e\text {-}SP} \rightarrow p_{\textrm{syn,rel}}\) | AA: IP3 via GJs |
Makovkin et al. (2020) | Network 1: EE(0–1); Network 2: II(0–1): \(V_{\textrm{m,pre}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1: EA(1); Network 2: IA(1): \(V_{\mathrm {m,pre/post}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | Network 1: AE(0–1); Network 2: AI(0–1): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | Network 1 & 2: AA(1): Ca2+ and IP3 via GJs |
Mesiti et al. (2015) | EE(0–1): \(V_{\textrm{m,presoma}} \rightarrow g_{\mathrm {syn,AMPAR/NMDAR}} \rightarrow\) \(I_{\mathrm {syn,AMPAR/NMDAR}} \rightarrow V_{\textrm{m,postdent}}\) | EA(0–1): \(V_{\textrm{m,presoma}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE(0–2): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow \mathrm {[Ca^{2+}]_{pre}}\), \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow g_{\mathrm {syn,AMPAR/NMDAR}} \rightarrow\) \(I_{\mathrm {ast,AMPAR/NMDAR}} \rightarrow V_{\textrm{m,postdent}}\), \(I_{\textrm{astro}} \rightarrow V_{\textrm{m,presoma}}\) | AA(1–2): IP3 via GJs |
Naeem et al. (2015) | EE(1): \(p_{\textrm{syn,rel}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\), \(V_{\textrm{m,post}} \rightarrow \mathrm {[2\text {-}AG]_{post}} \rightarrow \textrm{DSE} \rightarrow p_{\textrm{syn,rel}}\) | EA(0–1): \(V_{\textrm{m,post}} \rightarrow \mathrm {[2\text {-}AG]_{post}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE(1): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow \mathrm {[Glu]_{ext}} \rightarrow \mathrm {e\text {-}SP} \rightarrow p_{\textrm{syn,rel}}\) | AA(2): IP3 via GJs |
Nazari and Faez (2019) | EE/EI/IE/II(\(p=0.08\)): \(V_{\textrm{m,pre}} \rightarrow x_{\mathrm {AMPAR/GABAR}} \rightarrow\) \(I_{\mathrm {syn,AMPAR/GABAR}} \rightarrow V_{\textrm{m,post}}\) | EA/IA(1): \(V_{\mathrm {m,pre/post}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(1): \(I_{\textrm{ast}} \rightarrow x_{\mathrm {AMPAR/GABAR}} \rightarrow\) \(I_{\mathrm {syn,AMPAR/GABAR}}\) \(\rightarrow V_{\mathrm {m,PY/IN}}\), \(I_{\textrm{ast}}=c\mathrm {[Ca^{2+}]_{ast}}\) | AA(\(p=0.1\)): IP3 via GJs |
Nazari et al. (2020) | L2: EE/EI/IE/II(\(p=0.2\)); From L2 to output layer: EE/IE(10): \(V_{\textrm{m,pre}} \rightarrow x_{\mathrm {AMPAR/GABAR}} \rightarrow\) \(I_{\mathrm {syn,AMPAR/GABAR}} \rightarrow V_{\textrm{m,post}}\) | L2: EA/IA(0–1): \(V_{\mathrm {m,pre/post}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | L2: AE/AI(1): \(I_{\textrm{ast}} \rightarrow x_{\mathrm {AMPAR/GABAR}} \rightarrow\) \(I_{\mathrm {syn,AMPAR/GABAR}} \rightarrow\) \(V_{\mathrm {m,PY/IN}}\), \(I_{\textrm{ast}}=c\mathrm {[Ca^{2+}]_{ast}}\) | L2: AA(1,501,673): IP3 via GJs |
Postnov et al. (2009) | EE(1): \(V_{\textrm{m,pre}} \rightarrow z \rightarrow I_{\textrm{syn}} \rightarrow w_{\textrm{post}}\) | EA(1): \(V_{\textrm{m,pre}} \rightarrow z \rightarrow S_{\textrm{m}}\), \(w_{\textrm{post}} \rightarrow \mathrm {{Ca^{2+}_{ast}}}\) | AE: \(G_{\textrm{m}} \rightarrow I_{\textrm{syn}} \rightarrow w_{\textrm{post}}\), \(I_{\mathrm {ast,ATP/Glu}} \rightarrow w_{\textrm{post}}\), \(I_{\textrm{ast,ATP}}=cG_{\textrm{a}}\), \(I_{\textrm{ast,Glu}}=cG_{\textrm{m}}\), \(I_{\textrm{syn}} = (k-cG_{\textrm{m}})(z-z_0)\) | AA: Ca2+ and IP3 via GJs, Dext: ATPext (\(G_{\textrm{a}}\)) and Gluext (\(G_{\textrm{m}}\)) |
Soleimani et al. (2015) | Network 1: EE(2–4); Network 2: EE: \(X_{\textrm{pre}} \rightarrow I_{\textrm{syn}} \rightarrow X_{\textrm{post}}\), \(Y_{\textrm{pre}} \rightarrow I_{\textrm{syn}} \rightarrow Y_{\textrm{post}}\) | Network 1: EA(2–4); Network 2: EA: \(X_{\textrm{N}} \rightarrow Z \rightarrow S_{\textrm{m}}\), \(Y_{\textrm{N}} \rightarrow Z \rightarrow S_{\textrm{m}}\) | Network 1 & 2: AE(1): \(I_{\textrm{ast}} \rightarrow X_{\textrm{N}}\), \(I_{\textrm{ast}} \rightarrow Y_{\textrm{N}}\), \(I_{\textrm{ast}} = c \mathrm {Ca^{2+}}\) | None |
Stimberg et al. (2019) | EE/IE(\(p=0.05\)), EI/II(\(p=0.2\)):\(V_{\textrm{m,pre}} \rightarrow p_{\textrm{syn,rel}} \rightarrow\) \(g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA(1): \(V_{\textrm{m,pre}} \rightarrow p_{\textrm{syn,rel}} \rightarrow \mathrm {[NT]} \rightarrow\) \(s_{\textrm{mGluRast}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE(1): \(\mathrm {[Ca^{2+}]_{ast}} \rightarrow p_{\textrm{ast,rel}} \rightarrow\) \(\mathrm {[GT]} \rightarrow s_{\textrm{Rpre}} \rightarrow p_{\textrm{syn,rel}}\) | AA: IP3 via GJs |
Tang et al. (2017) | EE(2–4): \(V_{\textrm{m,pre}} \rightarrow S \rightarrow V_{\textrm{m,post}}\) | EA(1): \(V_{\textrm{m,N}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE(1): \(I_{\textrm{astro}} \rightarrow V_{\textrm{m,N}}\) | AA(1–2): IP3 via GJs |
Yang and Yeo (2015) | EE: \(\mathrm {[Glu]_{syn}}\) | EA: \(\mathrm {[Glu]_{syn}} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE: \(\mathrm {[ATP]_{ext}}\rightarrow \mathrm {NMDAR_{post}}\), \(\mathrm {[Glu]_{ext}} \rightarrow \mathrm {NMDAR_{post}}\) | AA: IP3 via GJs, Dext: [ATP]ext and [Glu]ext |
Yao et al. (2018) | EE(0–1): [K+]ext, [Na+]ext,\(V_{\textrm{m,pre}} \rightarrow \mathrm {[Glu]_{ext}} \rightarrow\) \(I_{\mathrm {syn,K/NaNMDAR}} \rightarrow V_{\textrm{m,post}}\) | EA(1): [K+]ext, [Na+]ext | AE(1): [K+]ext, [Na+]ext, \(\mathrm {[ATP]_{ext}} \rightarrow \mathrm {[Glu]_{ext}} \rightarrow\) \(I_{\mathrm {syn,K/NaNMDAR}} \rightarrow V_{\textrm{m,post}}\) | AA: [K+]ext, [Na+]ext, \(\mathrm {[ATP]_{ext}} \rightarrow \mathrm {G_{ast}} \rightarrow \mathrm {[IP_3]_{ast}}\), \(\mathrm {[ATP]_{ext}} \rightarrow \mathrm {[Glu]_{ext}}\), Dext: [ATP]ext, [K+]ext, and [Na+]ext |
Yu et al. (2020) | EE/II(0–1), EI(1), IE(1–2): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow g_{\textrm{syn}} \rightarrow I_{\textrm{syn}} \rightarrow V_{\textrm{m,post}}\) | EA/IA(50): \(V_{\textrm{m,pre}} \rightarrow \textrm{NT} \rightarrow \mathrm {[IP_3]_{ast}}\) | AE/AI(50): \(I_{\textrm{ast}} \rightarrow V_{\mathrm {m,PY/IN}}\), \(I_{\textrm{ast}}=c \sum f\) | AA(1–2): IP3 via GJs |
Study
|
Spatial organization of cells
|
Structure of interaction scheme
|
Direction of information flow
|
---|---|---|---|
Abed et al. (2020) | All cells/E/I/A: 2D, random placement | EE/EI/IE/II: all-to-all; EA/AE/IA/AI: one-to-one; AA: n/a | Global: recurrent. Local: EE/EI(IE)/II/AA: recurrent; EA(AE)/IA(AI): feed-forward |
Aleksin et al. (2017) | All cells: 2D, grid of rings; E/I/A: 1D, ring | EE/II/AA: explicitly defined; EI/IE/EA/AE/IA/AI: one-to-one | Global: recurrent. Local: EE/II/EA(AE)/IA(AI)/AA: recurrent; EI(IE): feed-forward |
Allegrini et al. (2009) | All cells/E/I/A: 2D, grid | EE/EI/IE/II/EA: random; AE/AI/AA: distance dependent; IA: none | Global: recurrent. Local: EE/EI(IE)/II/AA: recurrent; EA(AE)/IA(AI): feed-forward |
Amiri et al. (2012a) | All cells: 2D, grid; E/I/A: 1D, array | EE/EI/II/EA/AE/AI: one-to-one; IE/AA: explicitly defined; IA: none | Global: feed-forward. Local: EE/II/IA(AI): feed-forward; EI(IE)/EA(AE)/AA: recurrent |
Amiri et al. (2012b) | All cells/E/I/A: 3D, multiple populations; E = PY, TC; I = IN, RE | EE/EI/IE/EA/AE/AI/AA: explicitly defined; II/IA: none | Global: recurrent. Local: EE/EI(IE)/EA(AE)/AA: recurrent; II: none; IA(AI): feed-forward |
Amiri et al. (2012c) | All cells/E/I/A: 3D, multiple populations | EE/EI/IE/EA/AE/AI/AA: explicitly defined; II/IA: none | Global: recurrent. Local: EE/EI(IE)/EA(AE)/AA: recurrent; II: none; IA(AI): feed-forward |
Amiri et al. (2013a) | All cells: 2D, grid; E/I/A: 1D, array | EE/EI/II/EA/AE/IA/AI: one-to-one; IE/AA: explicitly defined | Global: feed-forward. Local: EE/II: feed-forward; EI(IE)/EA(AE)/IA(AI)/AA: recurrent |
Chan et al. (2017) | Network 1: All cells/E/I/A: 2D, random placement; Network 2: All cells/E/I/A: 2D, grid | Network 1: EE/EI/IE/II/EA/AE/IA/AI: random; AA:none; Network 2: EE/EI/IE/II/EA/AE/IA/AI/AA: distance dependent | Global: recurrent. Local: EE/EI(IE)/II/EA(AE)/IA(AI): recurrent; Network 1: AA: none; Network 2: AA: recurrent |
Gordleeva et al. (2019) | All cells/E: 2D, random placement; A: 1D, two-node motif | EE/EA: random; AE: distance dependent; AA: one-to-one | Global: recurrent. Local: EE/EA(AE)/AA: recurrent |
Haghiri et al. (2016) | Network 1: All cells/E/A: 1D, few node motif; E: 1D, motif with convergent inputs; E and A: 1D, three-node motif; Network 2: All cells/E/A: 2D, grid | EE: one-to-one; EA/AE: explicitly defined; Network 1: AA: none; Network 2: AA: explicitly defined | Global: feed-forward. Local: EE: feed-forward; EA(AE): recurrent; Network 1: AA: none; Network 2: AA: recurrent |
Haghiri et al. (2017) | Network 1: All cells/E/A: 1D, array; Network 2: All cells/E/A: 2D, random placement | AA: none; Network 1: EE: one-to-one; EA/AE: explicitly defined; Network 2: EE/EA/AE: random | Global: Network 1: feed-forward; Network 2: recurrent. Local: EA(AE): recurrent; AA: none; Network 1: EE: feed-forward; Network 2: EE: recurrent |
Haghiri and Ahmadi (2020) | All cells/E/A: 2D, multilayer | AA:none; Between layers: EE: random; Within layers: EE/EA: one-to-one; AE: explicitly defined | Global: feed-forward. Local: EE: feed-forward; EA(AE): recurrent; AA: none |
Hayati et al. (2016) | All cells/E/A: 2D, grid | EE: one-to-one; EA/AE/AA: explicitly defined | Global: feed-forward. Local: EE: feed-forward; EA(AE)/AA: recurrent |
Kanakov et al. (2019) | All cells/E/I/A: 2D, grid | AE: one-to-one; AA: explicitly defined; Network 1: EE/EI/IE/EA/IA: random; II: none; AI: one-to-one; Network 2: EE/EA: all-to-all | Global: recurrent. Local: EE/EI(IE)/AA: recurrent; II: none; EA(AE)/IA(AI): n/a; Network 1: both E and I; Network 2: only E |
Lenk et al. (2020) | All cells/E/I/A: 2D, random placement | EE/EI/IE/II/EA/AE/AI/AA: distance dependent; IA: none | Global: recurrent. Local: EE/EI(IE)/II/EA(AE)/AA: recurrent; IA(AI): feed-forward |
Li et al. (2016) | All cells: 2D, grid; E/I/A: 1D, array | EE/EI/II/EA/AE/IA/AI: one-to-one; IE/AA: explicitly defined | Global: feed-forward. Local: EE/II: feed-forward; EI(IE)/EA(AE)/IA(AI)/AA: recurrent |
Li et al. (2020) | All cells/E/I/A: 2D, random placement | EE/EI/IE/II: random; EA/AE/AA: distance dependent; IA/AI: none | Global: recurrent. Local: EE/EI(IE)/II/EA(AE)/AA: recurrent; IA(AI): none |
Liu and Li (2013a) | All cells/A: 2D, grid; Network 1: E/I: 2D, multilayer; Network 2: E: 2D, multilayer | AE/AI/AA: explicitly defined; IA: none; Between neuron-defined layers: EE/EI/IE/II/EA: all-to-all; Within layers: EE/EI/IE/II: none; Network 1: both E and I; Network 2: only E | Global: feed-forward. Local: EE/EI(IE)/II/IA(AI): feed-forward; EA(AE)/AA: recurrent; Network 1: both E and I; Network 2: only E |
Liu and Li (2013b) | All cells/A: 2D, grid; E/I: 1D, three-node motif | EE/EI/IE/II/EA/AE/AI/AA: explicitly defined; IA: none | Global: feed-forward. Local: EE/EI(IE)/II/IA(AI): feed-forward; EA(AE)/AA: recurrent |
Liu et al. (2016) | All cells/E/A: 3D, multilayer | EE/EA/AE/AA: hierarchical | Global: model dependent. Local: EE/AA: recurrent; EA(AE): feed-forward |
Makovkin et al. (2020) | All cells: 1D, four-node motif; E/I/A: 1D, two-node motif | Network 1: EE/EA/AE/AA: one-to-one; Network 2: II/IA/AI/AA: one-to-one | Global: recurrent. Local: AA: recurrent; Network 1: EE: feed-forward; EA(AE): recurrent; Network 2: II: feed-forward; IA(AI): recurrent |
Mesiti et al. (2015) | All cells/A: 1D, array; E: 1D, two-node motif | EE/EA: one-to-one; AE/AA: explicitly defined | Global: recurrent. Local: EE: feed-forward; EA(AE)/AA: recurrent |
Naeem et al. (2015) | All cells/A: 1D, ring; E: 1D, motif with convergent inputs | EE/EA: one-to-one; AE/AA: explicitly defined | Global: recurrent. Local: EE/AA: recurrent; EA(AE): feed-forward |
Nazari and Faez (2019) | All cells/E/I/A: 2D, grid | EE/EI/IE/II/EA/AE/IA/AI/AA: random | Global: recurrent. Local: EE/EI(IE)/II/EA(AE)/IA(AI)/AA: recurrent |
Nazari et al. (2020) | All cells/E/I: 3D, multilayer; A: 2D, grid | L2: EE/EI/IE/II/EA/AE/IA/AI: random; AA: all-to-all; L2 to Output layer: EE/IE: all-to-all | Global: feed-forward. Local: L2: EE/EI(IE)/II/EA(AE)/IA(AI)/AA: recurrent; L2 to Output layer: EE/EI(IE): feed-forward |
Postnov et al. (2009) | All cells/E/A: 2D, random placement | EE: explicitly defined; EA/AE/AA: distance dependent | Global: recurrent. Local: EE/EA(AE)/AA: recurrent |
Soleimani et al. (2015) | All cells/E/A: 2D, grid | AA: none; Network 1: EE/EA/AE: explicitly defined; Network 2: EE/EA/AE: all-to-all | Global: recurrent. Local: EE/EA(AE): recurrent; AA: none |
Stimberg et al. (2019) | All cells/E/I/A: 2D, grid | EE/EI/IE/II/EA: random; AE/AA: distance dependent; IA/AI: none | Global: recurrent. Local: EE/EI(IE)/II/EA(AE)/AA: recurrent; IA(AI): none |
Tang et al. (2017) | All cells/E/A: 1D, array | EE/AA: explicitly defined; EA/AE: one-to-one | Global: recurrent. Local: EE/EA(AE)/AA: recurrent |
Yang and Yeo (2015) | All cells/E/A: 3D, multilayer; L1: E: 2D, grid | L1: EE: explicitly defined; Between L1 and L2: EE: one-to-one; Between L2 and L3: EA/AE: one-to-one; Between L3 and L4: AA: hierarchical | Global: feed-forward. Local: L1: EE: recurrent; Between L1 and L2: EE: feed-forward; Between L2 and L3: EA(AE): feed-forward; Between L3 and L4: AA: recurrent |
Yao et al. (2018) | All cells/E/A: 1D, array | EE/EA/AE: one-to-one; AA: explicitly defined | Global: feed-forward. Local: EE: feed-forward; EA(AE)/AA: recurrent |
Yu et al. (2020) | All cells: 2D, grid; E/I/A: 1D, array | EE/EI/II: one-to-one; IE/AA: explicitly defined; EA/AE/IA/AI: all-to-all | Global: feed-forward. Local: EE/EI(IE)/II/EA(AE)/IA(AI)/AA: recurrent |