Table 2.

Statistical analysis

DatasetData structureType of testPower
Fig. 1ANon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.1337, LL: p = 0.4334, SWM: p = 0.5985
Fig. 1BNon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.0425, LL: p = 0.9257, SWM: p = 0.9609
Fig. 1CNon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.0278, LL: p = 0.4931, SWM: p = 0.7801
Fig. 1DNon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.2880, LL: p = 0.6393, SWM: p = 0.0240
Fig. 1ENon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.9257, LL: p = 0.9397, SWM: p = 0.2848
Extended Data Fig. 1-1ANon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.9265, LL: p = 0.5300, SWM: p = 0.4023
Extended Data Fig. 1-1BNon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.8052, LL: p = 0.3294, SWM: p = 0.8217
Extended Data Fig. 1-1CNon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.3699, LL: p = 0.9644, SWM: p = 0.9559
Extended Data Fig. 1-1DNon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.3370, LL: p = 0.2271, SWM: p = 0.3900
Extended Data Fig. 1-1ENon-normal distributionTwo-way ANOVA, uncorrected Fisher's LSDUL: p = 0.7681, LL: p = 0.7659, SWM: p = 0.6875
Extended Data Fig. 1-2BNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.9428, female: p = 0.7868
Extended Data Fig. 1-2CNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.3033, female: p = 0.8720
Extended Data Fig. 1-2DNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.9960, female: p = 0.7304
Extended Data Fig. 1-2ENon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.9940, female: p = 0.9212
Extended Data Fig. 1-2FNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.8677, female: p = 0.8035
Extended Data Fig. 1-3ANon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.6754, female: p = 0.9993
Extended Data Fig. 1-3BNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.0497, female: p = 0.4501
Extended Data Fig. 1-3CNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.7528, female: p = 0.6561
Extended Data Fig. 1-3DNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.0412, female: p = 0.9986
Extended Data Fig. 1-3ENon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.8936, female: p = 0.9142
Extended Data Fig. 1-3FNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMale: p = 0.9886, female: p = 0.3146
Fig. 2ANon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer I: MIA+/CSH– p < 0.05, Layer II/III MIA+/CSH+ p < 0.05, PL: Layer I: MIA+/CSH– p < 0.05, Layer II/III MIA+/CSH+ p < 0.05
Fig. 2BNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer II/III: MIA+/CSH– p < 0.05, MIA–/CSH+ p < 0.05, MIA+/CSH+ p < 0.05, PL: Layer II/III: MIA+/CSH+ p < 0.05
Fig. 2CNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer I: MIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.05, Layer II/III: MIA+/CSH+ p < 0.05, Layer V: MIA+/CSH+ p < 0.05, PL: Layer I: MIA+/CSH+ p < 0.05, Layer II/III: MIA+/CSH+ p < 0.05, Layer V: MIA+/CSH– p < 0.05
Fig. 2DNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer I: MIA+/CSH+ p < 0.05, Layer II/III: MIA+/CSH+ p < 0.05, PL: Layer I: MIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.05, Layer II/III: MIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.05, MIA+/CSH+ p < 0.05
Extended Data Fig. 2-1ANon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer II/III: MIA+/CSH+ p < 0.05, PL: Layer II/III MIA+/CSH+ p < 0.05
Extended Data Fig. 2-1BNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer V MIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.05, PL: Layer II/III: MIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.05, Layer V: MIA+/CSH+ p < 0.05
Extended Data Fig. 2-1CNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer V MIA–/CSH+ p < 0.05, MIA+/CSH+ p < 0.05, PL: Layer V MIA–/CSH+ p < 0.05, MIA+/CSH+, Layer V I: MIA–/CSH+ p < 0.05
Extended Data Fig. 2-1DNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer V and Layer VI: MIA+/CSH– p < 0.05, MIA–/CSH+ p < 0.05, MIA+/CSH+ p < 0.05, PL: Layer II/III: MIA+/CSH– p < 0.05, MIA–/CSH+ p < 0.05, MIA+/CSH+ p < 0.05, Layer V: MIA+/CSH+ p < 0.05
Extended Data Fig. 2-1DNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsACC: Layer I: MIA–/CSH+ p < 0.05, PL: ns
Fig. 3ANon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMZ: p < 0.05, CP: p ≤ 0.05, SVZ/VZ p < 0.05
Fig. 3BNon-normal distributionMann–Whitneygad65+: p = 0.3333, ki67+: p = 0.0381, gad65+/ki67+: p = 0.0095
Fig. 3CNon-normal distributionMann–Whitneygad65+: p = 0.0012, brdu+: p < 0.001, gad65+/brdu+: p = 0.0012
Extended Data Fig. 3-1ANon-normal distributionMann–Whitneyns
Extended Data Fig. 3-1BNon-normal distributionMann–Whitneyns
Extended Data Fig. 3-1CNon-normal distributionTwo-way ANOVA, Sidak's multiple comparisonsMZ: p = 0.714, CP: p = 0.04521, SVZ/VZ: p = 0.1657
Extended Data Fig. 3-2Non-normal distributionMann–Whitneyp = 0.0688
Extended Data Fig. 3-3BNon-normal distributionMann–Whitneyp = 0.0047
Extended Data Fig. 3-3CNon-normal distributionMann–Whitneyp = 0.0315
Fig. 4ANon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsgad65+: MIA+/CSH+ p < 0.05;
Fig. 4BNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsgad65+: MIA+/CSH+ p < 0.05; gad65+/brdu+: MIA+/CSH+ p < 0.05
Fig. 5Non-normal distributionTwo-way ANOVA, Tukey's multiple comparisonse17.5: MIA+/CSH– p < 0.001, P10: MIA+/CSH+ p < 0.05, P30: MIA+/CSH+ p < 0.05
Fig. 6ANon-normal distributionMann–Whitneyiba1+: p = 0.0067, cd68+: p = 0.0163
Fig. 6BNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsiba1+: ns, cd68+: MIA+/CSH+ p < 0.01
Fig. 6CNon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsiba1+: ns, cd68+: ns
Fig. 7ANormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsMIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.001
Fig. 7BNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsMIA+/CSH+ p < 0.01
Fig. 7CNormal distributionTwo-way ANOVA, Tukey's multiple comparisonsns
Fig. 7DNormal distributionTwo-way ANOVA, Tukey's multiple comparisonsd2: MIA+/CSH+ p < 0.05, d3: MIA+/CSH+ p < 0.05
Fig. 7ENormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsns
Fig. 7FNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsMIA+/CSH+ p < 0.05
Fig. 7GNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsMIA+/CSH– p < 0.05, MIA+/CSH+ p < 0.05
Extended Data Fig. 7-1ANormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsns
Extended Data Fig. 7-1BNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsns
Extended Data Fig. 7-1CNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsns
Extended Data Fig. 7-1DNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsns
Extended Data Fig. 7-1ENon-normal distributionKruskal–Wallis, Dunn's multiple comparisonsns
Extended Data Fig. 7-1FNormal distributionOne-way ANOVA, Holm–Sidak's multiple comparisonsns
  • CP, cortical plate; MIA–/CSH–, mice treated with saline and reared under normoxia; MIA+/CSH-; mice subjected to MIA and reared under normoxia; MIA–/CSH+, mice treated with saline and reared under CSH; (MIA+/CSH+), mice subjected to MIA and reared under CSH; MZ, marginal zone; ns, non-significant; SVZ/VZ, subventricular/ventricular zone.