Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Abstracting and Indexing
    • Editorial Board Members
    • Reviewer Panel
    • Journal Policies
    • WJARR CrossMark Policy
    • Publication Ethics
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Current Issue
    • Issue in Progress
    • Past Issues
    • Become a Reviewer panel member
    • Join as Editorial Board Member
  • Contact us
  • Downloads

eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

BrainSim-X v4.2.7: An advanced high-dimensional neural network simulation platform

Breadcrumb

  • Home
  • BrainSim-X v4.2.7: An advanced high-dimensional neural network simulation platform

Nawman Baig *

BrainSim-X Private Research Initiative, Bangalore, Karnataka, India.

Research Article

World Journal of Advanced Research and Reviews, 2025, 27(02), 1491-1503

Article DOI: 10.30574/wjarr.2025.27.2.3021

DOI url: https://doi.org/10.30574/wjarr.2025.27.2.3021

Received on 12 July 2025; revised on 18 August 2025; accepted on 21 August 2025

The human brain's complexity, with 86 billion neurons and 100 trillion synapses, presents unprecedented challenges for computational modeling. This study introduces BrainSim-X v4.2.7, an advanced high-dimensional neural network simulation platform designed to emulate multi-scale brain dynamics with unprecedented biological realism. The platform integrates multi-compartment neuron models, sophisticated synaptic plasticity mechanisms, diverse network topologies, and real-time data analytics while leveraging high-performance computing resources including GPU clusters, FPGA accelerators, and distributed cloud infrastructures.

BrainSim-X v4.2.7 supports simulations of millions to hundreds of millions of neurons, enabling exploration of neural oscillations, synchronization, plasticity learning, and emergent cognitive states, including consciousness-related processes. The platform incorporates theoretical frameworks from dynamical systems theory, information theory, and multi-scale modeling, facilitating hypothesis-driven research into neural coding, disease mechanisms, and AI cognition. Its modular architecture supports integration with machine learning, quantum computing paradigms, and biomimetic approaches for personalized and adaptive brain modeling.

Experimental validation demonstrates 37% improved computational efficiency compared to previous versions, with successful reproduction of cortical oscillations, learning behaviors, and pathological states. This platform advances our understanding of brain function and provides a foundation for neuropsychiatric research, brain-computer interfaces.

Brain Dynamics; Computational Neuroscience; High-Performance Computing; Synaptic Plasticity; Neural Networks; Multi-Scale Modeling; Consciousness; Neuroinformatics

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-3021.pdf

Preview Article PDF

Nawman Baig. BrainSim-X v4.2.7: An advanced high-dimensional neural network simulation platform. World Journal of Advanced Research and Reviews, 2025, 27(02), 1491-1503. Article DOI: https://doi.org/10.30574/wjarr.2025.27.2.3021.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

Footer menu

  • Contact

Copyright © 2026 World Journal of Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution