Delete README_SynCo_fixed.md

README_SynCo_fixed.md

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----
-tags:
-  - synthetic-cortex
-  - spiking-neural-network
-  - biologically-plausible
-  - plasticity
-  - modular-architecture
-  - lifelong-learning
-  - reinforcement-learning
-  - pytorch
-  - neuroscience
-  - cognitive-architecture
-license: mit
-datasets:
-  - mnist
-  - imdb
-  - synthetic-environment
-language:
-  - en
-widget:
-  - text: "The first blueprint and the bridge to Neuroscience and Artificial Intelligence."
-  - text: "SynCo: A spiking brain agent that learns with STDP, Hebbian plasticity, and emotion modules."
-model-index:
-- name: SynCo: Modular Spiking Synthetic Cortex
-  results:
-    - task:
-        type: image-classification
-        name: Vision-based Classification
-      dataset:
-        type: mnist
-        name: MNIST
-      metrics:
-        - type: accuracy
-          value: 0.91
-    - task:
-        type: text-classification
-        name: Language Sentiment Analysis
-      dataset:
-        type: imdb
-        name: IMDb
-      metrics:
-        - type: accuracy
-          value: 0.87
-    - task:
-        type: reinforcement-learning
-        name: Curiosity-driven Exploration
-      dataset:
-        type: synthetic-environment
-        name: GridWorld-style Environment
-      metrics:
-        - type: cumulative_reward
-          value: 112.5
----
-
-# 🧠 SynCo: A Modular Spiking Synthetic Cortex
-
-**Created by Aliyu Lawan Halliru (2025)**  
-**License: MIT**
-
-SynCo is a biologically inspired, spiking neural network that mimics real brain dynamics using:
-
-- ⚡ Spiking neurons (LIF, Adaptive LIF)
-- 🧬 Local synaptic learning (STDP, Hebbian)
-- 🧠 Modular cognitive architecture (Relay, Memory, Comparator, Feedback)
-- 🧪 Reinforcement-ready outputs with multi-task switching
-- 🔁 Lifelong learning via task replay and local plasticity
-
-This model bridges neuroscience and artificial general intelligence, enabling realistic, interpretable, and continual learning from sparse feedback and spiking dynamics.
-
-## 📦 Files Included
-
-- `SynCo_Synthetic_Cortex_Demo.ipynb`: Notebook with full training demo
-- `final_modular_brain_agent_with_spikes_and_plasticity.py`: Full model code
-- `README.md`: This file
-
-## 🧪 Example Output
-
-```
-Step 04 | Task: binary         | Loss: 0.0123 | acc: 1.00
-Step 12 | Task: classification | Loss: 1.2391 | acc: 0.88
-Step 19 | Task: regression     | Loss: 0.5214
-```
-
-SynCo adapts its weights in real time using only local neuron activity — no backpropagation required.
-
-## 🧠 Use Cases
-
-- Neuroscience-inspired AI modeling
-- Continual learning agents
-- Synthetic cortex simulation
-- Educational use in bio-AI and neural computation
-
-## ✨ Credits
-
-Created by **Aliyu Lawan Halliru**, Nigerian independent AI researcher.  
-Project aims to make synthetic neuroscience accessible to the world.
-
-## 📜 License
-
-MIT License — free to use and adapt.