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Fig. 1A,B
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WIN: 10 neurons, 4 mice, DMSO: 21 neurons, 7 mice |
| mGPSC frequency: DMSO × WIN |
ANOVA |
F(1,28) = 14.704, p = 0.001 |
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| mGPSC amplitude: DMSO × WIN |
ANOVA |
F(1,29) = 0.598, p = 0.445 |
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Fig. 1D
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AM251: 5 neurons, 3 mice |
| mGPSC frequency: DMSO × AM251 |
ANOVA |
F(1,30) = 1.153, p = 0.292 |
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| mGPSC amplitude: DMSO × AM251 |
ANOVA |
F(1,30) = 2.975, p = 0.095 |
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| mGPSC frequency: AM251 × AM251 + WIN |
Repeated measures ANOVA |
F(2,8) = 1.719, p = 0.239 |
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Fig. 1F
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FC: 8 neurons, 3 mice |
| mGPSC frequency: DMSO × FC |
ANOVA |
F(1,28) = 3.52, p = 0.071 |
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Fig. 3A,B,E,F
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WIN: 4 mice, 6 slices, 38 soma (s), 194 non-soma (ns) |
| Increase magnitude: treatment (WIN/DMSO) × ROI (s/ns) |
Kruskal–Wallis |
H(3) = 169.052, p < 0.001 |
DMSO: 3 mice, 4 slices, 70 s, 86 ns |
| Increase magnitude DMSO: s × ns |
Median post hoc
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p = 1 |
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| Increase magnitude WIN: s × ns |
Median post hoc
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p = 1 |
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| Increase magnitude (both s and ns): DMSO × WIN |
Median post hoc
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p < 0.001 |
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| Decrease magnitude: treatment (WIN/DMSO) × ROI (s/ns) |
Kruskal–Wallis |
H(3) = 60.729, p < 0.001 |
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| Decrease magnitude DMSO: s × ns |
Median post hoc
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p = 1 |
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| Decrease magnitude WIN: s × ns |
Median post hoc
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p = 1 |
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| Increase magnitude (both s and ns): DMSO × WIN |
Median post hoc
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p < 0.01 |
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Fig. 3C,G
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TTX + CNQX + WIN: 4 mice, 5 slices, 19 s, 93 ns |
| Increase magnitude: treatment (WIIN/ TTX + CNQX + WIN) × ROI (s/ns) |
Kruskal–Wallis |
H(3) = 13.35, p = 0.004 |
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| Increase magnitude ns: WIN × TTX + CNQX + WIN |
Median post hoc
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p = 0.017 |
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| Decrease magnitude: treatment (WIIN/ TTX + CNQX + WIN) × ROI (s/ns) |
Kruskal–Wallis |
H(3) = 2.213, p = 0.529 |
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