Jekyll2026-11-07T12:08:28+00:00https://girish-k01.github.io/feed.xmlGIRISH K LabsDeveloper|Researcher|WriterGirish Kulathumanigirish.kulathumani@gmail.comGLr01: Brain Decoding and Visual Reconstruction (Arxiv: 2310.19812)2025-04-28T00:00:00+00:002025-04-28T00:00:00+00:00https://girish-k01.github.io/posts/2024/05/blog-post-3GLr01 marks the first entry in GreyLattice Research (GLr) — a new subseries dedicated to unpacking complex research papers in Computational Neuroscience and making their insights accessible from first principles.

This post breaks down the paper:
“Brain Decoding: Toward Real-Time Reconstruction of Visual Perception”
Arxiv ID: 2310.19812

The study presents a fascinating blend of MEG-based brain signal decoding, deep learning, and real-time visual reconstruction—pushing the boundaries of what’s possible at the intersection of neuroscience and AI.

I discovered this paper while working on a personal project, and it left a strong impression. As a result, I decided not only to dissect its key findings and methods, but also to launch this GLr series to share such insights with the broader GreyLattice community.

Read the full breakdown here:
GLr01 – Brain Decoding and Visual Reconstruction

Follow along as GreyLattice Research continues to explore frontier neuroscience papers—one insight at a time.

]]>Girish Kulathumanigirish.kulathumani@gmail.comGreyLattice-00 (GL00): Welcome to GreyLattice2025-02-06T00:00:00+00:002025-02-06T00:00:00+00:00https://girish-k01.github.io/posts/2024/04/blog-post-1GreyLattice-00 (GL00) is the official launch post for GreyLattice, a blog dedicated to decoding the brain and building intelligent systems through the lens of Computational Neuroscience.

The name “GreyLattice” reflects the intricate architecture of the brain’s grey matter and the networked complexity of the mind. In this opening post, I lay out the motivation behind the blog, what readers can expect, and why this field—at the intersection of neuroscience, computer science, and artificial intelligence—deserves your attention.

Whether you’re a curious student, an experienced researcher, or just someone fascinated by minds and machines, GreyLattice is a space for accessible yet in-depth explorations of neural coding, network dynamics, plasticity, and cognitive architectures.

Read the full post here:
GL00 – Welcome to GreyLattice

Join me on this journey into the computational modeling of the brain—one post, one model, and one idea at a time.

]]>Girish Kulathumanigirish.kulathumani@gmail.comGreyLattice-01 (GL01): The Foundations of Computational Neuroscience2025-02-06T00:00:00+00:002025-02-06T00:00:00+00:00https://girish-k01.github.io/posts/2024/04/blog-post-2GreyLattice-01 (GL01) kicks off the GreyLattice blog with a foundational look at the field of Computational Neuroscience.

Even though the term feels modern, “Computational Neuroscience” was first coined in 1985 by Eric L. Schwartz at a conference in Carmel, California. Since then, it has grown into a critical discipline for understanding how the brain processes information—and how we can replicate or interface with that process using machines.

This inaugural post explores the early history and motivations behind the field, setting the stage for future deep dives into brain-computer interfaces, neuromorphic architectures, and more.

Read the full post here:
GL01 – The Foundations of Computational Neuroscience

Subscribe to GreyLattice on Substack for upcoming articles on the brain, computation, and the technologies connecting them.

]]>Girish Kulathumanigirish.kulathumani@gmail.com