Abstract Robust information processing in physical systems is fundamentally constrained by noise, energy dissipation, and limited local precision. In both biological neural circuits and topological quantum error-correcting codes, high fidelity is achieved despite severe stochastic perturbations. Here we introduce Negative Space Encoding (NSE) as a unifying framework describing a class of encoding strategies in which information is represented primarily in structured absences rather than in localized active states. We formalize NSE as encoding in global topological or temporal constraints over accessible state space and show that, under standard assumptions of short-range noise, such encodings exhibit exponential suppression of logical errors as a function of global scale. This framework recovers known results in topological quantum computation and provides a principled interpretation of phase-based neural coding, population silence, and energy-efficient computation in biological systems. We further propose a quantitative measure, NSE depth, capturing the fraction of information stored in global versus local features, and situate known neural coding schemes along a continuum from dense positive encoding to near-pure negative space representations. Finally, we outline experimental and engineering implications, including persistent-homology-based analysis of neural silence and classical hardware architectures exploiting structured absences for noise-resilient computation. Rather than introducing new physical laws, NSE reframes existing results from quantum error correction and systems neuroscience within a common conceptual language, enabling cross-domain transfer of methods and predictions. Keywords: negative space encoding, NSE, globality, topological invariants, persistent homology, noise resistance, noise immunity, global topological structure, absence-based encoding, phase coding, hippocampal theta rhythm, sparse coding, topological quantum computing, surface code, fault tolerance, quantum error correction, phenomenal unity, consciousness, unified experience, self-referential negative space, thermodynamic arrow of time, fractal architectures, double-exponential protection, NSEdepth
Building similarity graph...
Analyzing shared references across papers
Loading...
Alastair Waterman (Mon,) studied this question.
www.synapsesocial.com/papers/6996a7efecb39a600b3ee2ae — DOI: https://doi.org/10.5281/zenodo.18664836
Alastair Waterman
Building similarity graph...
Analyzing shared references across papers
Loading...