Experiments DB Dev
969c0205e8
Add make_variations.m + variation_analyze.m generating 20 self-contained subfolders under analysis/matlab/variations/, one per grouping x day-window, each with exactly three files: data.csv (curated subset), analyze.m (a simple standalone script fitting behavior ~ stim + day + stim:day + (1|rat) on the success COUNT), and result.txt (its output). Plus variations/SUMMARY.csv. Groupings (stim=1 / stim=0, other groups dropped): unmerge B2 vs A2 right_only B2+Right vs A2 (Box-A dropped) naive_a2 B2 vs A2+Naive (Right, Box-A dropped) naive_boxa B2 vs A2+Naive+Box-A (Right dropped) Windows: 0-10, 0-13, 0-5, 6-10, 6-13. All 20 have equal day coverage. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
66 lines
2.5 KiB
Plaintext
66 lines
2.5 KiB
Plaintext
==============================================================================
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VARIATION: naive_boxa_d6_10
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==============================================================================
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model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT)
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day = training day within window (0 = first analyzed day)
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treatment (stim=1): Electrode-Box-B2
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control (stim=0): Electrode-Box-A, Electrode-Box-A2, Naive
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N = 10 rats, 50 sessions raw day coverage: treat 6..10, control 6..10
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(equal day coverage over this window)
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==============================================================================
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FULL MODEL SUMMARY -- fitlme
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==============================================================================
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Linear mixed-effects model fit by ML
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Model information:
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Number of observations 50
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Fixed effects coefficients 4
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Random effects coefficients 10
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Covariance parameters 2
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Formula:
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behavior ~ 1 + day*stim + (1 | rat)
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Model fit statistics:
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AIC BIC LogLikelihood Deviance
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405.22 416.69 -196.61 393.22
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 64.543 5.1823 12.454 46 2.4341e-16
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{'day' } 5.7857 1.2123 4.7727 46 1.8769e-05
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{'stim' } 23.99 9.4616 2.5356 46 0.014689
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{'day:stim' } -1.619 2.2133 -0.73152 46 0.46817
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Lower Upper
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54.111 74.974
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3.3456 8.2259
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4.9452 43.036
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-6.0741 2.836
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Random effects covariance parameters (95% CIs):
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Group: rat (10 Levels)
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Name1 Name2 Type Estimate
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{'(Intercept)'} {'(Intercept)'} {'std'} 11.237
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Lower Upper
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6.7417 18.73
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Group: Error
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Name Estimate Lower Upper
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{'Res Std'} 10.142 8.1466 12.627
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effect t (df) F (df1) p
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------------------------------------------------------------------
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stim x day (interaction) t(46)= -0.73 F(1)= 0.535 p=0.4682
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day (learning) t(46)= 4.77 F(1)= 22.779 p=1.877e-05
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stim (main, window start) t(46)= 2.54 F(1)= 6.429 p=0.01469
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interaction 95% CI: [-6.07, +2.84]
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INTERPRETATION: stim x day interaction n.s. -- slopes parallel (no differential learning rate) (p=0.4682, slope diff=-1.62)
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
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