# Biological Brain Simulator A Python OOP implementation of the biological brain, aiming to create a digital copy of known brain structures and their neural subnetworks based on current scientific knowledge. ## Project Description This project aims to create a comprehensive digital model of the human brain by: 1. **Structural Modeling**: Implement known brain structures and their anatomical relationships using object-oriented programming. 2. **Neural Network Implementation**: Program specific neural groups within each brain structure according to current scientific understanding. 3. **Functional Integration**: Create communication pathways between different brain regions, simulating both local and long-range neural connections. The ultimate goal is to create a modular, extensible system that can: - Accurately represent known brain structures and their interconnections. - Implement neural networks that mimic real brain functionality. - Serve as a foundation for adding more complex neural computations and learning capabilities. ## Project Structure ``` Cervello fisico in python/ ├── main.py # Punto di ingresso principale della simulazione ├── cervello.py # Classe principale per l'orchestrazione del cervello ├── componenti_base/ │ ├── __init__.py │ ├── cellula.py # Classe base per le cellule biologiche │ ├── neurone.py # Definizione dell'unità computazionale base │ ├── microglia.py # Cellule immunitarie del SNC │ ├── mielina.py # Struttura e funzioni della mielina │ └── vascolarizzazione.py # Sistema vascolare e angiogenesi ├── strutture_proencefalo/ │ ├── __init__.py │ ├── emisfero.py # Classe base astratta per gli emisferi │ ├── emisfero_concreto.py # Implementazione concreta degli emisferi │ ├── emisfero_sinistro.py # Specializzazione per l'emisfero sinistro │ └── emisfero_destro.py # Specializzazione per l'emisfero destro ├── strutture_diencefalo/ │ ├── __init__.py │ └── talamo.py # Implementazione del talamo ├── strutture_sottocorticale/ │ ├── __init__.py │ ├── cerebello.py # Implementazione del cerebello │ ├── substantia_nigra.py # Implementazione della sostanza nera │ └── globus_pallidus.py # Implementazione del globo pallido ├── connessioni/ │ ├── __init__.py │ ├── connessione.py # Classe base per le connessioni neurali │ └── cortico_ippocampale.py # Connessioni cortico-ippocampali └── periferiche_sensory/ ├── __init__.py ├── periferica_visiva.py # Sistema visivo ├── periferica_auditiva.py # Sistema auditivo ├── periferica_tattile.py # Sistema tattile ├── periferica_olfattiva.py # Sistema olfattivo └── periferica_gustativa.py # Sistema gustativo ``` ## Implementation Phases ## Features 1. **Sensory Periphery** - Realistic implementation of visual system with automatic camera detection - YOLOv5-based object recognition - Persistent visual memory system - Auditory system (inner ear hair cells, auditory neurons) - Tactile system (pressure, temperature, pain receptors) - Olfactory system (olfactory epithelia) - Gustatory system (taste buds) 2. **Cerebral Structure** - Left and right hemispheres with specialized lobes - Corpus callosum for inter-hemispheric communication - Thalamus as sensory relay hub - Prefrontal cortex for executive functions - Visual cortex with unsupervised learning capabilities 3. **Subcortical Structures** - Cerebellum for motor coordination - Substantia nigra for dopaminergic modulation - Globus pallidus for motor control - Hippocampus for memory formation 4. **Neural Networks** - Modular implementation of neural groups - Communication pathways between structures - Basic neural computations and processing - Real-time visual processing with YOLOv5 - Persistent memory system for visual learning ## Future Development 1. **Enhanced Neural Processing** - Advanced learning algorithms - More complex neural computations - Neural plasticity implementation 2. **Additional Sensory Systems** - Vestibular system - Proprioception - Interoception 3. **Motor Systems** - Motor cortex implementation - Basal ganglia integration - Motor execution pathways 4. **Cognitive Functions** - Memory systems - Attention mechanisms - Decision-making processes ## Requirements - Python 3.8+ - OpenCV for video processing - PyTorch for YOLOv5 - YOLOv5 for object recognition - JSON for persistent memory - Basic Python standard library components - Future phases may require additional scientific computing libraries ## How to Run ```bash python main.py ```