| name | metabolic-quantum-limit-brain-imaging |
| description | Quantum-metabolic bounds on information capacity of noninvasive brain imaging (arXiv:2511.06401) |
| category | quantum-neuroscience |
Metabolic Quantum Limit to Brain Imaging Information Capacity
Methodology from arXiv:2511.06401 (Physical Review RESEARCH 8, 023267, 2026). Technology-independent bound on MEG information capacity.
Core Pattern
Combines quantum sensing limits with metabolic constraints to derive fundamental bounds:
- Energy resolution limit of magnetic sensing × metabolic power available to neural currents
- Bound factorizes into: geometry × metabolism × Planck's constant
- Maximum information rate: ~2.2 Mbit/s for human brain parameters
- External magnetic field has finite angular bandwidth — high multipole components fall below quantum noise floor
- Information-limited spatial scale: ~1 cm
- Measurement space is effectively finite-dimensional
Key Findings
- Quantum-limited noise floor defines information-theoretic Nyquist scale
- Denser spatial sampling beyond Nyquist provides redundant, not additional, information
- Noise variance grows linearly with measurement bandwidth
- Temporal and spatial bandwidths compete — fundamental spatio-temporal trade-off
- Links fundamental physics to neuroscience quantitatively
Implementation Steps
- Model neural currents and their magnetic field generation
- Apply quantum energy resolution limit to sensing geometry
- Incorporate metabolic power constraints on neural currents
- Derive information capacity bound (geometry × metabolism × ℏ)
- Compute angular bandwidth cutoff from geometric attenuation
- Determine spatial Nyquist scale from quantum noise floor
- Analyze spatio-temporal trade-off from bandwidth competition
When to Use
- Evaluating maximum information capacity of brain imaging modalities
- Designing optimal sensor arrays for MEG/EEG
- Understanding fundamental limits of noninvasive brain measurement
- Quantifying link between physics and neuroscience
References
- arXiv: 2511.06401v3 (Physical Review RESEARCH 8, 023267, 2026)
- Authors: E. Gkoudinakis, S. Li, I. K. Kominis
