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: right_only_d0_13
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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, Right-Electrode
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control (stim=0): Electrode-Box-A2
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N = 7 rats, 84 sessions raw day coverage: treat 0..13, control 0..13
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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 84
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Fixed effects coefficients 4
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Random effects coefficients 7
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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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695.18 709.77 -341.59 683.18
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 21.7 4.3761 4.9587 80 3.9065e-06
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{'day' } 6.4863 0.68669 9.4459 80 1.1708e-14
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{'stim' } 3.5986 5.6847 0.63303 80 0.52852
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{'day:stim' } 1.7002 0.84679 2.0078 80 0.048042
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Lower Upper
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12.991 30.409
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5.1198 7.8529
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-7.7143 14.911
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0.015009 3.3853
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Random effects covariance parameters (95% CIs):
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Group: rat (7 Levels)
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Name1 Name2 Type Estimate
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{'(Intercept)'} {'(Intercept)'} {'std'} 3.1353e-15
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Lower Upper
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NaN NaN
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Group: Error
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Name Estimate Lower Upper
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{'Res Std'} 14.12 12.139 16.425
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effect t (df) F (df1) p
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------------------------------------------------------------------
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stim x day (interaction) t(80)= 2.01 F(1)= 4.031 p=0.04804
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day (learning) t(80)= 9.45 F(1)= 89.224 p=1.171e-14
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stim (main, window start) t(80)= 0.63 F(1)= 0.401 p=0.5285
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interaction 95% CI: [+0.02, +3.39]
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INTERPRETATION: stim x day interaction SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.04804, slope diff=+1.70)
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
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