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artdigitalgenerativeneural

Neuromorphic - Digital Art Series

A series of digital artworks exploring the visual patterns and structures of neural networks, inspired by both biological and artificial neural systems.

February 10, 2025

Gallery image
Gallery image
Gallery image

Neuromorphic - Digital Art Series

Neuromorphic is a series of digital artworks that explores the visual patterns and structures found in neural networks—both biological and artificial. This project sits at the intersection of neuroscience, artificial intelligence, and digital art.

Concept

As both a physician who studies brain imaging and someone fascinated by the rise of artificial neural networks, I wanted to create visual representations that blur the line between biological neural structures and their technological counterparts.

Each piece in this series represents a different conceptual aspect of neural networks:

  1. Emergence - How complex patterns arise from simple connections
  2. Plasticity - The adaptability and learning capability of neural systems
  3. Activation - The propagation of signals through connected nodes
  4. Inhibition - The regulatory mechanisms that maintain balance

Process

These works were created using a combination of:

  • Custom generative algorithms written in Processing
  • 3D modeling in Blender
  • Digital painting in Procreate
  • Some elements derived from actual brain MRI scans (anonymized)

The color palettes are inspired by various neural imaging techniques—the blues and purples of DTI tract imaging, the heat maps of fMRI, and the fluorescent markers used in microscopy.

IMAGE GALLERY WOULD BE DISPLAYED HERE

Exhibition History

This series was exhibited at:

  • Digital Art Biennale, Amsterdam (March 2025)
  • "Code as Canvas" gallery show, San Francisco (April 2025)
  • Online exhibition with the Society for Neuroscience (February 2025)

Artist Statement

In creating these works, I'm exploring questions about the nature of thought itself: What does it mean that we can simulate aspects of cognition with mathematical models? How does the physical structure of neural systems—with their dendrites, axons, and synapses—relate to the abstract architectures of artificial neural networks?

The visual language of nodes, connections, and activation patterns has become a powerful metaphor for understanding both biological and artificial intelligence. Through these artworks, I hope to invite viewers to contemplate the beautiful complexity of the systems that enable thought, whether organic or silicon-based.