| { | |
| "dataset_info": { | |
| "name": "Neuraxon Game of Life Research Dataset Deep Time Series Exploration", | |
| "version": "2.1.0", | |
| "description": "Parquet dataset converted from Neuraxon Game of Life JSON save files. Contains comprehensive neural network state, agent behavior, and evolutionary data for validating the Neuraxon paper: 'A New Neural Growth & Computation Blueprint' by David Vivancos & Dr. Jose Sanchez.", | |
| "created_at": "2026-01-03T10:03:29.716910", | |
| "converter_version": "1.0.0" | |
| }, | |
| "processing_summary": { | |
| "total_files_found": 1983, | |
| "files_processed_successfully": 1983, | |
| "files_failed": 0 | |
| }, | |
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| { | |
| "name": "games", | |
| "filepath": "games.parquet", | |
| "num_rows": 1983, | |
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| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "status", | |
| "file_timestamp", | |
| "source_file", | |
| "created_at", | |
| "step_tick", | |
| "global_time_steps", | |
| "births_count", | |
| "deaths_count", | |
| "game_index", | |
| "world_size", | |
| "world_grid_hash", | |
| "log_level", | |
| "logger_version", | |
| "start_timestamp", | |
| "end_timestamp", | |
| "duration_seconds", | |
| "total_ticks", | |
| "total_neurons_created", | |
| "total_neurons_died", | |
| "total_synapses_created", | |
| "total_synapses_pruned", | |
| "total_plasticity_events", | |
| "total_ltp_events", | |
| "total_ltd_events", | |
| "peak_network_activity", | |
| "average_branching_ratio", | |
| "branching_ratio_samples", | |
| "peak_dopamine", | |
| "peak_serotonin", | |
| "peak_acetylcholine", | |
| "peak_norepinephrine", | |
| "total_silent_synapse_activations", | |
| "total_spontaneous_events", | |
| "total_dendritic_spikes", | |
| "total_homeostatic_adjustments", | |
| "peak_phase_coherence", | |
| "total_threshold_modulations", | |
| "total_associativity_events", | |
| "total_metabotropic_activations", | |
| "total_ionotropic_activations", | |
| "peak_autocorrelation_window", | |
| "mean_weight_change_rate", | |
| "total_subthreshold_integrations", | |
| "nxer_total_born", | |
| "nxer_total_died", | |
| "nxer_max_food_found", | |
| "nxer_max_time_lived", | |
| "nxer_max_mates", | |
| "nxer_max_explored", | |
| "num_nxers_in_file", | |
| "num_foods_in_file" | |
| ], | |
| "description": "Main game metadata including summary statistics, neuromodulator peaks, and NxEr summaries. Key fields for paper validation across all sections.", | |
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| }, | |
| { | |
| "name": "nxers", | |
| "filepath": "nxers.parquet", | |
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| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "name", | |
| "color_r", | |
| "color_g", | |
| "color_b", | |
| "is_male", | |
| "clan_id", | |
| "pos_x", | |
| "pos_y", | |
| "can_land", | |
| "can_sea", | |
| "food", | |
| "alive", | |
| "born_ts", | |
| "died_ts", | |
| "vision_range", | |
| "smell_radius", | |
| "heading", | |
| "ticks_per_action", | |
| "tick_accum", | |
| "harvesting", | |
| "mating_with", | |
| "mating_end_tick", | |
| "dopamine_boost_ticks", | |
| "mating_intent_until_tick", | |
| "mate_cooldown_until_tick", | |
| "last_move_tick", | |
| "last_input_0", | |
| "last_input_1", | |
| "last_input_2", | |
| "last_input_3", | |
| "last_input_4", | |
| "last_input_5", | |
| "last_output_0", | |
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| "last_output_2", | |
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| "last_output_4", | |
| "parent_0", | |
| "parent_1", | |
| "stats_food_found", | |
| "stats_food_taken", | |
| "stats_explored", | |
| "stats_time_lived_s", | |
| "stats_mates_performed", | |
| "stats_energy_efficiency", | |
| "stats_temporal_sync_score", | |
| "stats_fitness_score", | |
| "visited_count", | |
| "visited_json" | |
| ], | |
| "description": "Individual NxEr (agent) data including identity, position, state, sensory attributes, statistics, and I/O history. Essential for behavioral analysis.", | |
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| }, | |
| { | |
| "name": "network_params", | |
| "filepath": "network_params.parquet", | |
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| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "nxer_name", | |
| "network_name", | |
| "num_input_neurons", | |
| "num_hidden_neurons", | |
| "num_output_neurons", | |
| "connection_probability", | |
| "small_world_k", | |
| "small_world_rewire_prob", | |
| "preferential_attachment", | |
| "membrane_time_constant", | |
| "firing_threshold_excitatory", | |
| "firing_threshold_inhibitory", | |
| "adaptation_rate", | |
| "spontaneous_firing_rate", | |
| "neuron_health_decay", | |
| "num_dendritic_branches", | |
| "branch_threshold", | |
| "plateau_decay", | |
| "tau_fast", | |
| "tau_slow", | |
| "tau_meta", | |
| "tau_ltp", | |
| "tau_ltd", | |
| "w_fast_init_min", | |
| "w_fast_init_max", | |
| "w_slow_init_min", | |
| "w_slow_init_max", | |
| "w_meta_init_min", | |
| "w_meta_init_max", | |
| "learning_rate", | |
| "stdp_window", | |
| "learning_rate_mod", | |
| "plasticity_threshold", | |
| "associativity_strength", | |
| "synapse_integrity_threshold", | |
| "synapse_formation_prob", | |
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| "neuron_death_threshold", | |
| "dopamine_baseline", | |
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| "serotonin_baseline", | |
| "serotonin_high_affinity_threshold", | |
| "serotonin_low_affinity_threshold", | |
| "acetylcholine_baseline", | |
| "acetylcholine_high_affinity_threshold", | |
| "acetylcholine_low_affinity_threshold", | |
| "norepinephrine_baseline", | |
| "norepinephrine_high_affinity_threshold", | |
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| "neuromod_decay_rate", | |
| "diffusion_rate", | |
| "oscillator_low_freq", | |
| "oscillator_mid_freq", | |
| "oscillator_high_freq", | |
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| "phase_coupling_strength", | |
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| "plasticity_energy_cost", | |
| "metabolic_rate", | |
| "recovery_rate", | |
| "target_firing_rate", | |
| "homeostatic_plasticity_rate", | |
| "itu_circle_radius", | |
| "evolution_interval", | |
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| "net_energy_consumed", | |
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| "net_num_synapses", | |
| "net_num_neurons" | |
| ], | |
| "description": "Complete network parameters for each NxEr including architecture, topology, neuron properties, synaptic time constants (Section 3), plasticity rates (Section 4), neuromodulation baselines (Section 1), oscillator frequencies (Section 7), and ITU config (Section 8).", | |
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| "columns": [ | |
| "game_id", | |
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| "neuron_type", | |
| "membrane_potential", | |
| "trinary_state", | |
| "adaptation", | |
| "autoreceptor", | |
| "health", | |
| "is_active", | |
| "energy_level", | |
| "phase", | |
| "natural_frequency", | |
| "intrinsic_timescale", | |
| "fitness_score", | |
| "circle_id", | |
| "last_firing_time", | |
| "membrane_time_constant", | |
| "firing_threshold_excitatory", | |
| "firing_threshold_inhibitory", | |
| "adaptation_rate", | |
| "spontaneous_firing_rate", | |
| "neuron_health_decay", | |
| "energy_baseline", | |
| "firing_energy_cost", | |
| "plasticity_energy_cost", | |
| "metabolic_rate", | |
| "recovery_rate", | |
| "num_dendritic_branches", | |
| "state_history_json", | |
| "state_history_length", | |
| "dendritic_branches_json" | |
| ], | |
| "description": "Individual neuron state snapshots including membrane potential, trinary state, adaptation, autoreceptor levels, energy, phase, and individualized parameters. Relevant to Section 1 (trinary states), Section 2 (temporal dynamics), Section 6 (spontaneous activity).", | |
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| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "pre_id", | |
| "post_id", | |
| "w_fast", | |
| "w_slow", | |
| "w_meta", | |
| "is_silent", | |
| "is_modulatory", | |
| "integrity", | |
| "axonal_delay", | |
| "learning_rate_mod", | |
| "synapse_type", | |
| "potential_delta_w", | |
| "tau_fast", | |
| "tau_slow", | |
| "tau_meta", | |
| "tau_ltp", | |
| "tau_ltd", | |
| "learning_rate", | |
| "plasticity_threshold", | |
| "pre_trace", | |
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| "pre_trace_ltd", | |
| "associative_strength", | |
| "neighbor_synapse_ids_json", | |
| "neighbor_count" | |
| ], | |
| "description": "Synapse data including multi-timescale weights (w_fast, w_slow, w_meta), traces, integrity, and individualized time constants. Key for validating Section 3 (synaptic computation) and Section 4 (plasticity).", | |
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| "name": "foods", | |
| "filepath": "foods.parquet", | |
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| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "food_id", | |
| "anchor_x", | |
| "anchor_y", | |
| "pos_x", | |
| "pos_y", | |
| "alive", | |
| "respawn_at_tick", | |
| "remaining", | |
| "progress_json" | |
| ], | |
| "description": "Food source state including position, remaining amount, and respawn status.", | |
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| }, | |
| { | |
| "name": "time_series", | |
| "filepath": "time_series.parquet", | |
| "num_rows": 9170708, | |
| "num_columns": 82, | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "timestamp", | |
| "network_activity", | |
| "branching_ratio", | |
| "total_energy", | |
| "average_energy", | |
| "energy_efficiency", | |
| "temporal_sync", | |
| "dopamine", | |
| "serotonin", | |
| "acetylcholine", | |
| "norepinephrine", | |
| "oscillator_drive", | |
| "oscillator_low", | |
| "oscillator_mid", | |
| "oscillator_high", | |
| "phase_coherence", | |
| "cfc_low_mid", | |
| "cfc_mid_high", | |
| "excitatory_fraction", | |
| "inhibitory_fraction", | |
| "neutral_fraction", | |
| "autoreceptor_mean", | |
| "autoreceptor_std", | |
| "adaptation_mean", | |
| "spontaneous_firing_count", | |
| "driven_firing_count", | |
| "silent_synapse_count", | |
| "active_synapse_count", | |
| "modulatory_synapse_count", | |
| "mean_synapse_integrity", | |
| "mean_plateau_potential", | |
| "mean_branch_potential", | |
| "dendritic_spike_count", | |
| "mean_intrinsic_timescale", | |
| "timescale_heterogeneity", | |
| "membrane_potential_mean", | |
| "membrane_potential_std", | |
| "mean_w_fast", | |
| "mean_w_slow", | |
| "mean_w_meta", | |
| "std_w_fast", | |
| "std_w_slow", | |
| "std_w_meta", | |
| "mean_pre_trace", | |
| "mean_post_trace", | |
| "mean_pre_trace_ltd", | |
| "std_pre_trace", | |
| "mean_delta_w", | |
| "ltp_rate", | |
| "ltd_rate", | |
| "mean_associativity_contribution", | |
| "associativity_event_count", | |
| "mean_learning_rate_mod", | |
| "std_learning_rate_mod", | |
| "mean_autocorrelation_window", | |
| "std_autocorrelation_window", | |
| "autocorrelation_coefficient_mean", | |
| "mean_threshold_excitatory_effective", | |
| "mean_threshold_inhibitory_effective", | |
| "threshold_modulation_by_ach", | |
| "threshold_modulation_by_autoreceptor", | |
| "ionotropic_contribution_mean", | |
| "metabotropic_contribution_mean", | |
| "modulator_grid_entropy", | |
| "modulator_grid_gradient_magnitude", | |
| "dopamine_spatial_variance", | |
| "serotonin_spatial_variance", | |
| "silent_synapse_fraction", | |
| "silent_to_active_transitions", | |
| "active_to_silent_transitions", | |
| "subthreshold_integration_count", | |
| "near_threshold_fraction", | |
| "pac_theta_gamma", | |
| "pac_delta_theta", | |
| "mean_phase_velocity", | |
| "itu_mean_fitness", | |
| "itu_fitness_variance", | |
| "itu_mutation_events", | |
| "itu_pruning_events" | |
| ], | |
| "description": "Comprehensive time series data including network activity, branching ratio, neuromodulator levels, oscillator components, CFC metrics, trinary distributions, synaptic statistics, dendritic metrics, ACW estimates, and ITU fitness. Essential for paper validation across all sections.", | |
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| { | |
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| "filepath": "plasticity_events.parquet", | |
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| "columns": [ | |
| "game_id", | |
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| "tick", | |
| "event_type", | |
| "pre_id", | |
| "post_id", | |
| "delta_w", | |
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| ], | |
| "description": "LTP and LTD plasticity events with timing and weight changes. Key for Section 4 (plasticity and adaptation).", | |
| "size_bytes": 6585961 | |
| }, | |
| { | |
| "name": "nxer_events", | |
| "filepath": "nxer_events.parquet", | |
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| "num_columns": 6, | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "event_type", | |
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| "description": "NxEr lifecycle events including birth, death, mating, and stealing attempts.", | |
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| "filepath": "io_patterns.parquet", | |
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| "columns": [ | |
| "game_id", | |
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| "tick", | |
| "nxer_id", | |
| "inputs_json", | |
| "outputs_json" | |
| ], | |
| "description": "Input/output patterns for each NxEr per tick. Useful for behavioral analysis and correlating neural activity with decisions.", | |
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| }, | |
| { | |
| "name": "itu_fitness", | |
| "filepath": "itu_fitness.parquet", | |
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| "columns": [ | |
| "game_id", | |
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| "description": "ITU (Intelligent Tissue Unit) fitness history over time. Key for Section 8 (Aigarth hybridization).", | |
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| "filepath": "neuromodulator_events.parquet", | |
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| "columns": [ | |
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| "level", | |
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| "description": "Neuromodulator threshold crossing events. Key for Section 1 (trinary neuromodulation).", | |
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| "columns": [ | |
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| "description": "Phase synchronization events including coherence measurements. Key for Section 7 (synchronization).", | |
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| "description": "Dendritic spike events with branch potential and calcium influx. Related to Section 1 (dendritic computation) and Section 5 (complex signaling).", | |
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| "columns": [ | |
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| "description": "Homeostatic plasticity threshold adjustments. Related to Section 4 (plasticity and adaptation).", | |
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| "description": "Multi-timescale weight changes (w_fast, w_slow, w_meta delta). Key for Section 3 (synaptic weight evolution).", | |
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| "columns": [ | |
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| "description": "Full 2D world grid terrain data (Land=0, Sea=1, Rock=2). REQUIRED for game resumption - stored as JSON array.", | |
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| "columns": [ | |
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| "description": "Food harvest progress tracking which NxErs are eating each food source. REQUIRED for game resumption - tracks timing of ongoing harvests.", | |
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| "description": "Full (x,y) coordinate history of cells visited by each NxEr. REQUIRED for game resumption - enables spatial path reconstruction.", | |
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| "description": "Last 50 states for each neuron (deque used for autocorrelation). REQUIRED for game resumption - enables intrinsic timescale calculation (Section 6).", | |
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| "description": "Neighbor synapse IDs for associativity connections. REQUIRED for game resumption - enables cooperative LTP reconstruction (Section 4).", | |
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| "mean_plateau_potential", | |
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| "mean_autocorrelation_window", | |
| "std_autocorrelation_window", | |
| "autocorrelation_coefficient_mean", | |
| "mean_intrinsic_timescale", | |
| "timescale_heterogeneity" | |
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| "phase_coherence", | |
| "cfc_low_mid", | |
| "cfc_mid_high", | |
| "pac_theta_gamma", | |
| "pac_delta_theta", | |
| "branching_ratio" | |
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| "itu_mean_fitness", | |
| "itu_fitness_variance", | |
| "itu_mutation_events", | |
| "itu_pruning_events" | |
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| "description": "Main game metadata including summary statistics, neuromodulator peaks, and NxEr summaries. Key fields for paper validation across all sections.", | |
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| "status", | |
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| "step_tick", | |
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| "world_size", | |
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| "duration_seconds", | |
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| "description": "Individual NxEr (agent) data including identity, position, state, sensory attributes, statistics, and I/O history. Essential for behavioral analysis.", | |
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| "name", | |
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| "color_b", | |
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| "pos_y", | |
| "can_land", | |
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| "food", | |
| "alive", | |
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| "died_ts", | |
| "vision_range", | |
| "smell_radius", | |
| "heading", | |
| "ticks_per_action", | |
| "tick_accum", | |
| "harvesting", | |
| "mating_with", | |
| "mating_end_tick", | |
| "dopamine_boost_ticks", | |
| "mating_intent_until_tick", | |
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| "last_move_tick", | |
| "last_input_0", | |
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| "last_input_2", | |
| "last_input_3", | |
| "last_input_4", | |
| "last_input_5", | |
| "last_output_0", | |
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| "stats_explored", | |
| "stats_time_lived_s", | |
| "stats_mates_performed", | |
| "stats_energy_efficiency", | |
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| "visited_count", | |
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| "description": "Complete network parameters for each NxEr including architecture, topology, neuron properties, synaptic time constants (Section 3), plasticity rates (Section 4), neuromodulation baselines (Section 1), oscillator frequencies (Section 7), and ITU config (Section 8).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "nxer_name", | |
| "network_name", | |
| "num_input_neurons", | |
| "num_hidden_neurons", | |
| "num_output_neurons", | |
| "connection_probability", | |
| "small_world_k", | |
| "small_world_rewire_prob", | |
| "preferential_attachment", | |
| "membrane_time_constant", | |
| "firing_threshold_excitatory", | |
| "firing_threshold_inhibitory", | |
| "adaptation_rate", | |
| "spontaneous_firing_rate", | |
| "neuron_health_decay", | |
| "num_dendritic_branches", | |
| "branch_threshold", | |
| "plateau_decay", | |
| "tau_fast", | |
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| "tau_meta", | |
| "tau_ltp", | |
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| "w_fast_init_min", | |
| "w_fast_init_max", | |
| "w_slow_init_min", | |
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| "w_meta_init_min", | |
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| "learning_rate", | |
| "stdp_window", | |
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| "plasticity_threshold", | |
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| "synapse_integrity_threshold", | |
| "synapse_formation_prob", | |
| "synapse_death_prob", | |
| "neuron_death_threshold", | |
| "dopamine_baseline", | |
| "dopamine_high_affinity_threshold", | |
| "dopamine_low_affinity_threshold", | |
| "serotonin_baseline", | |
| "serotonin_high_affinity_threshold", | |
| "serotonin_low_affinity_threshold", | |
| "acetylcholine_baseline", | |
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| "acetylcholine_low_affinity_threshold", | |
| "norepinephrine_baseline", | |
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| "norepinephrine_low_affinity_threshold", | |
| "neuromod_decay_rate", | |
| "diffusion_rate", | |
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| "oscillator_high_freq", | |
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| "phase_coupling_strength", | |
| "energy_baseline", | |
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| "description": "Individual neuron state snapshots including membrane potential, trinary state, adaptation, autoreceptor levels, energy, phase, and individualized parameters. Relevant to Section 1 (trinary states), Section 2 (temporal dynamics), Section 6 (spontaneous activity).", | |
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| "health", | |
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| "energy_level", | |
| "phase", | |
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| "circle_id", | |
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| "description": "Synapse data including multi-timescale weights (w_fast, w_slow, w_meta), traces, integrity, and individualized time constants. Key for validating Section 3 (synaptic computation) and Section 4 (plasticity).", | |
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| "nxer_id", | |
| "pre_id", | |
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| "w_slow", | |
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| "integrity", | |
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| "potential_delta_w", | |
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| "tau_slow", | |
| "tau_meta", | |
| "tau_ltp", | |
| "tau_ltd", | |
| "learning_rate", | |
| "plasticity_threshold", | |
| "pre_trace", | |
| "post_trace", | |
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| "associative_strength", | |
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| "foods": { | |
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| "description": "Food source state including position, remaining amount, and respawn status.", | |
| "columns": [ | |
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| "anchor_x", | |
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| "pos_y", | |
| "alive", | |
| "respawn_at_tick", | |
| "remaining", | |
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| "time_series": { | |
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| "description": "Comprehensive time series data including network activity, branching ratio, neuromodulator levels, oscillator components, CFC metrics, trinary distributions, synaptic statistics, dendritic metrics, ACW estimates, and ITU fitness. Essential for paper validation across all sections.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "timestamp", | |
| "network_activity", | |
| "branching_ratio", | |
| "total_energy", | |
| "average_energy", | |
| "energy_efficiency", | |
| "temporal_sync", | |
| "dopamine", | |
| "serotonin", | |
| "acetylcholine", | |
| "norepinephrine", | |
| "oscillator_drive", | |
| "oscillator_low", | |
| "oscillator_mid", | |
| "oscillator_high", | |
| "phase_coherence", | |
| "cfc_low_mid", | |
| "cfc_mid_high", | |
| "excitatory_fraction", | |
| "inhibitory_fraction", | |
| "neutral_fraction", | |
| "autoreceptor_mean", | |
| "autoreceptor_std", | |
| "adaptation_mean", | |
| "spontaneous_firing_count", | |
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| "active_synapse_count", | |
| "modulatory_synapse_count", | |
| "mean_synapse_integrity", | |
| "mean_plateau_potential", | |
| "mean_branch_potential", | |
| "dendritic_spike_count", | |
| "mean_intrinsic_timescale", | |
| "timescale_heterogeneity", | |
| "membrane_potential_mean", | |
| "membrane_potential_std", | |
| "mean_w_fast", | |
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| "mean_w_meta", | |
| "std_w_fast", | |
| "std_w_slow", | |
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| "mean_pre_trace", | |
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| "ltd_rate", | |
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| "mean_phase_velocity", | |
| "itu_mean_fitness", | |
| "itu_fitness_variance", | |
| "itu_mutation_events", | |
| "itu_pruning_events" | |
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| "description": "LTP and LTD plasticity events with timing and weight changes. Key for Section 4 (plasticity and adaptation).", | |
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| "description": "NxEr lifecycle events including birth, death, mating, and stealing attempts.", | |
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| "description": "Input/output patterns for each NxEr per tick. Useful for behavioral analysis and correlating neural activity with decisions.", | |
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| "description": "ITU (Intelligent Tissue Unit) fitness history over time. Key for Section 8 (Aigarth hybridization).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "circle_id", | |
| "fitness" | |
| ] | |
| }, | |
| "neuromodulator_events": { | |
| "num_columns": 7, | |
| "num_rows": 594900, | |
| "size_bytes": 4036980, | |
| "description": "Neuromodulator threshold crossing events. Key for Section 1 (trinary neuromodulation).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "modulator", | |
| "level", | |
| "crossed_threshold", | |
| "effect" | |
| ] | |
| }, | |
| "phase_events": { | |
| "num_columns": 6, | |
| "num_rows": 216269, | |
| "size_bytes": 2693799, | |
| "description": "Phase synchronization events including coherence measurements. Key for Section 7 (synchronization).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "event_type", | |
| "phase_coherence", | |
| "details_json" | |
| ] | |
| }, | |
| "dendritic_events": { | |
| "num_columns": 8, | |
| "num_rows": 418097, | |
| "size_bytes": 7137950, | |
| "description": "Dendritic spike events with branch potential and calcium influx. Related to Section 1 (dendritic computation) and Section 5 (complex signaling).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "neuron_id", | |
| "branch_id", | |
| "branch_potential", | |
| "plateau_potential", | |
| "ca_influx" | |
| ] | |
| }, | |
| "homeostatic_events": { | |
| "num_columns": 8, | |
| "num_rows": 396600, | |
| "size_bytes": 6450370, | |
| "description": "Homeostatic plasticity threshold adjustments. Related to Section 4 (plasticity and adaptation).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "neuron_id", | |
| "old_threshold", | |
| "new_threshold", | |
| "activity_level", | |
| "direction" | |
| ] | |
| }, | |
| "weight_evolution_events": { | |
| "num_columns": 8, | |
| "num_rows": 991500, | |
| "size_bytes": 28871241, | |
| "description": "Multi-timescale weight changes (w_fast, w_slow, w_meta delta). Key for Section 3 (synaptic weight evolution).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "pre_id", | |
| "post_id", | |
| "w_fast_delta", | |
| "w_slow_delta", | |
| "w_meta_delta" | |
| ] | |
| }, | |
| "world_grids": { | |
| "num_columns": 4, | |
| "num_rows": 1983, | |
| "size_bytes": 1489889, | |
| "description": "Full 2D world grid terrain data (Land=0, Sea=1, Rock=2). REQUIRED for game resumption - stored as JSON array.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "world_size", | |
| "grid_json" | |
| ] | |
| }, | |
| "food_progress": { | |
| "num_columns": 5, | |
| "num_rows": 48056, | |
| "size_bytes": 132128, | |
| "description": "Food harvest progress tracking which NxErs are eating each food source. REQUIRED for game resumption - tracks timing of ongoing harvests.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "food_id", | |
| "nxer_id", | |
| "harvest_progress" | |
| ] | |
| }, | |
| "nxer_visited_history": { | |
| "num_columns": 6, | |
| "num_rows": 40557, | |
| "size_bytes": 16863279, | |
| "description": "Full (x,y) coordinate history of cells visited by each NxEr. REQUIRED for game resumption - enables spatial path reconstruction.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "nxer_name", | |
| "visited_coords_json", | |
| "visited_count" | |
| ] | |
| }, | |
| "neuron_state_history": { | |
| "num_columns": 7, | |
| "num_rows": 1499241, | |
| "size_bytes": 6306144, | |
| "description": "Last 50 states for each neuron (deque used for autocorrelation). REQUIRED for game resumption - enables intrinsic timescale calculation (Section 6).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "neuron_id", | |
| "neuron_type", | |
| "state_history_json", | |
| "history_length" | |
| ] | |
| }, | |
| "synapse_neighbor_ids": { | |
| "num_columns": 7, | |
| "num_rows": 429649, | |
| "size_bytes": 3748391, | |
| "description": "Neighbor synapse IDs for associativity connections. REQUIRED for game resumption - enables cooperative LTP reconstruction (Section 4).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "nxer_id", | |
| "synapse_pre_id", | |
| "synapse_post_id", | |
| "neighbor_synapse_ids_json", | |
| "neighbor_count" | |
| ] | |
| }, | |
| "silent_synapse_events": { | |
| "num_columns": 9, | |
| "num_rows": 19342, | |
| "size_bytes": 74445, | |
| "description": "Individual events when synapses wake up (become active) or go silent. Detailed data behind time_series silent_to_active_transitions count.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "pre_id", | |
| "post_id", | |
| "event_type", | |
| "previous_state", | |
| "new_state", | |
| "trigger" | |
| ] | |
| }, | |
| "spontaneous_events": { | |
| "num_columns": 7, | |
| "num_rows": 321977, | |
| "size_bytes": 3474981, | |
| "description": "Exact tick and neuron ID for every spontaneous firing event. Detailed data behind time_series spontaneous_firing_count (Section 6).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "neuron_id", | |
| "neuron_type", | |
| "membrane_potential", | |
| "spontaneous_rate" | |
| ] | |
| }, | |
| "autoreceptor_events": { | |
| "num_columns": 8, | |
| "num_rows": 396600, | |
| "size_bytes": 125238, | |
| "description": "Significant autoreceptor modulation events with threshold changes. Detailed data behind time_series autoreceptor_mean/std (Section 1).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "neuron_id", | |
| "modulator_type", | |
| "autoreceptor_level", | |
| "release_inhibition", | |
| "threshold_change" | |
| ] | |
| }, | |
| "subthreshold_events": { | |
| "num_columns": 8, | |
| "num_rows": 594900, | |
| "size_bytes": 17683267, | |
| "description": "Events when neurons are close to firing threshold but don't fire. Detailed data behind time_series subthreshold_integration_count (Section 5).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "neuron_id", | |
| "membrane_potential", | |
| "threshold", | |
| "distance_to_threshold", | |
| "input_sum" | |
| ] | |
| }, | |
| "threshold_modulation_events": { | |
| "num_columns": 9, | |
| "num_rows": 594900, | |
| "size_bytes": 9971415, | |
| "description": "Detailed breakdown of Acetylcholine vs Autoreceptor impact on thresholds. Individual events behind aggregated threshold modulation metrics.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "neuron_id", | |
| "base_threshold", | |
| "ach_contribution", | |
| "autoreceptor_contribution", | |
| "final_threshold", | |
| "acetylcholine_level" | |
| ] | |
| }, | |
| "associativity_events": { | |
| "num_columns": 7, | |
| "num_rows": 594900, | |
| "size_bytes": 112036, | |
| "description": "Cooperative LTP events with participating synapses and boost values. Individual events for Section 4 associativity mechanism validation.", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "tick", | |
| "post_neuron_id", | |
| "participating_synapses", | |
| "cooperative_boost", | |
| "total_weight_change" | |
| ] | |
| }, | |
| "hall_of_fame": { | |
| "num_columns": 16, | |
| "num_rows": 59264, | |
| "size_bytes": 849424, | |
| "description": "Top performing NxErs by category (food found, explored, time lived, etc.).", | |
| "columns": [ | |
| "game_id", | |
| "round_number", | |
| "category", | |
| "rank", | |
| "name", | |
| "is_male", | |
| "can_land", | |
| "can_sea", | |
| "stats_food_found", | |
| "stats_food_taken", | |
| "stats_explored", | |
| "stats_time_lived_s", | |
| "stats_mates_performed", | |
| "stats_energy_efficiency", | |
| "stats_temporal_sync_score", | |
| "stats_fitness_score" | |
| ] | |
| } | |
| }, | |
| "huggingface_compatibility": { | |
| "format": "parquet", | |
| "compression": "snappy", | |
| "load_example": "from datasets import load_dataset\ndataset = load_dataset('parquet', data_files={'train': '*.parquet'})", | |
| "pandas_example": "import pandas as pd\ndf = pd.read_parquet('games.parquet')" | |
| }, | |
| "usage_notes": [ | |
| "Time series data is indexed by tick number for temporal analysis", | |
| "Event tables can be joined to time_series via tick for correlation", | |
| "Network parameters table contains full configuration for each NxEr", | |
| "Use paper_section_mapping to identify relevant fields for each paper section", | |
| "game_id and round_number are consistent keys across all tables" | |
| ] | |
| } |