📗 Explanation · understanding-oriented

Explanation

This section provides conceptual discussions and explanations of the ideas behind DynVision. Here you'll find in-depth coverage of the theoretical foundations, design principles, and biological inspirations that inform the toolbox.

These pages are understanding-oriented: read them to learn why DynVision works the way it does. For practical steps see the How-to Guides; for factual lookups see the Reference.

Core Concepts

• Biological Plausibility: How DynVision implements biologically plausible features
• Temporal Dynamics: Understanding temporal processing in vision models
• Engineering vs. Biological Time: The two unrolling conventions and delay‑conversion formulas
• Design Philosophy: The guiding principles behind DynVision's architecture

Recurrent Processing

• Role of Recurrence: Why recurrent connections matter in visual processing
• Comparison to Neural Data: How model dynamics compare to ECoG recordings and human behavioural data
• Why Snakemake?: The reasoning behind DynVision's workflow orchestration

Planned topics

The following conceptual pages are planned but not yet written. They are tracked in the Documentation TODOs and will be added on demand:

• Continuous vs. discrete time, time constants, propagation delays
• Visual-cortex organization & cortical connectivity
• Comparisons with standard CNNs, other RCNNs, and spiking networks
• Trade-offs in balancing biological fidelity and performance