-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathanalysis_output.log
More file actions
154 lines (116 loc) · 4.8 KB
/
Copy pathanalysis_output.log
File metadata and controls
154 lines (116 loc) · 4.8 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
======================================================================
COMPLETE GLM-HMM ANALYSIS PIPELINE
======================================================================
Base directory: /home/user/GLMHMM
Figure directory: /home/user/GLMHMM/figures
Analysis will generate 30+ figures organized by category
======================================================================
[STEP 1] Loading data...
✓ Loading W cohort: W LD Data 11.08 All_processed.csv
Loaded 13463 trials from 19 animals
✓ Loading F cohort: F LD Data 11.08 All_processed.csv
Loaded 17697 trials from 36 animals
Using W cohort for analysis
Position data available: True
[STEP 2] Selecting animal for detailed analysis...
Selected animal: c1m3
Trials: 794
Genotype: +
[STEP 3] Creating design matrix and fitting GLM-HMM...
Design matrix: (794, 5)
Features: ['stimulus_position', 'bias', 'prev_choice', 'wsls', 'session_progression']
Fitting 3-state GLM-HMM...
✓ Model converged in 89 iterations
Final log-likelihood: -436.47
[STEP 4] Generating core analysis figures...
Creating comprehensive summary figure...
✓ Saved: 01_glmhmm_summary_c1m3.png
Creating psychometric curves...
✓ Saved: 02_psychometric_curves_c1m3.png
Creating state summary table...
✓ Saved: 03_state_summary_table_c1m3.png
✓ Core analysis figures saved to: /home/user/GLMHMM/figures/core_analysis
[STEP 5] Testing Hypothesis 1: Discrete Lapse States...
Lapse Analysis Results:
Lapse state: 2
Lapse probability: 14.11%
Run length ratio: 19.24x
Autocorrelation: 0.948
Interpretation: ✅ DISCRETE LAPSE STATE - Lapses cluster temporally
✓ Saved: 01_discrete_lapse_comprehensive_c1m3.png
✓ Hypothesis 1 figures saved to: /home/user/GLMHMM/figures/hypothesis1_discrete_lapses
[STEP 6] Testing Hypothesis 2: Dual-Process Decision Making...
Computing latency variability metrics...
Identifying deliberative vs procedural states...
State Classifications:
State 1: Deliberative/VTE (Dual-process: Deliberative)
Accuracy: 60.50%, CV: 0.85
State 2: Deliberative/VTE (Dual-process: Deliberative)
Accuracy: 50.89%, CV: 0.69
State 3: Deliberative/VTE (Dual-process: Deliberative)
Accuracy: 56.15%, CV: 0.66
Testing deliberation → learning correlation...
Early deliberation → Final performance: r=0.000, p=1.0000
✗ Not significant
Generating dual-process figures...
✓ Saved: 01_latency_variability_over_learning.png
✓ Saved: 02_state_classification_dual_process.png
✓ Saved: 03_deliberation_learning_correlation.png
✓ Hypothesis 2 figures saved to: /home/user/GLMHMM/figures/hypothesis2_dual_process
[STEP 7] Analyzing state transitions at reversals...
✓ Saved: 01_state_transitions_reversals.png
[STEP 8] Computing state dwell times...
Dwell Time Summary:
State 1.0: Mean=54.8 trials, Median=36.5, n_bouts=8.0
State 2.0: Mean=22.4 trials, Median=23.0, n_bouts=5.0
State 3.0: Mean=30.5 trials, Median=27.5, n_bouts=8.0
✓ Saved: 02_state_dwell_times.png
[STEP 9] Computing learning efficiency scores...
Learning Efficiency Scores:
animal_id genotype learning_efficiency_score final_accuracy
c1m3 + 0.577212 0.68
✓ Saved: 03_learning_efficiency_scores.png
[STEP 10] Fitting GLM-HMM to multiple animals...
Processing c1m3...
Processing c1m2...
Processing c2m4...
Processing c1m4...
Processing c2m5...
✓ Individual animal figures saved to: /home/user/GLMHMM/figures/individual_animals
[STEP 11] Comparing genotypes...
✓ Saved: 01_genotype_state_comparison.png
======================================================================
ANALYSIS COMPLETE!
======================================================================
genotype_comparison:
1 figures generated
additional_analyses:
3 figures generated
core_analysis:
3 figures generated
individual_animals:
5 figures generated
hypothesis2_dual_process:
3 figures generated
hypothesis1_discrete_lapses:
1 figures generated
======================================================================
TOTAL: 16 figures generated
Saved to: /home/user/GLMHMM/figures
======================================================================
======================================================================
KEY RESULTS SUMMARY
======================================================================
Hypothesis 1 (Discrete Lapses):
✅ DISCRETE LAPSE STATE - Lapses cluster temporally
Run length ratio: 19.24x
Autocorrelation: 0.948
Hypothesis 2 (Dual-Process VTE):
Insufficient data for correlation analysis
State Classifications:
State 1: Deliberative/VTE
State 2: Deliberative/VTE
State 3: Deliberative/VTE
======================================================================
Analysis script completed successfully!
======================================================================