Micah Blumberg

Selective Dissipation for Continual Learning: Receiver-Relative Residual Trajectories and Self-Regulated Plasticity

A deployed learner should resolve familiar encounters without unnecessary rewriting, correct familiar errors, and remain able to acquire new relationships. I propose selective dissipation: diagnosis in a history-shaped receiver with durable weights held fixed, followed by a separ...

Neural Rendering Composition and Granularity Tuning: State- and Task-Dependent Assembly of Multimodal Memory and Experience

A neural rendering, as proposed in Self-Aware Networks (SAN), is an evolving assembly of perceptual, remembered, bodily, conceptual, emotional and prospective relations, not merely a visual image. I propose Neural Rendering Composition and Granularity Tuning to distinguish which...

Selective Dissipation and Gated Plasticity in a History-Shaped Neural Canvas

A learned neural network can resolve an incoming event without necessarily changing its retained structure. In Self-Aware Networks (SAN), I have proposed that a receiver-relative difference may persist or resolve against an ongoing history-shaped context; under suitable condition...

Temporal Ensembles in Self-Aware Networks: Dendritic Recovery, Phase-Structured Recurrence, and the Hypothesis of Temporal Experience

A neural rendering must connect events across time without erasing the order or ownership of their contents. I propose a Temporal Ensemble Hypothesis: receiving components whose recent activity changes their readiness can contribute in a coordinated sequence while the effects of...

Temporal Ensembles in Self-Aware Networks: Dendritic Recovery, Phase-Structured Recurrence, and the Hypothesis of Temporal Experience

A neural rendering must connect events across time without erasing the order or ownership of their contents. I propose a Temporal Ensemble Hypothesis: receiving components whose recent activity changes their readiness can contribute in a coordinated sequence while the effects of...

AI Core Alignment Across Scales: Human-Guided Co-Regulation in Self-Aware Artificial Networks

How can a limited human correction remain consequential within a system whose computation exceeds the information contained in that correction? I develop this question through the receiver-relative framework of Self-Aware Networks and distinguish five obligations: legitimate auth...

AI Core Alignment Across Scales: Human-Guided Co-Regulation in Self-Aware Artificial Networks

How can a limited human correction remain consequential within a system whose computation exceeds the information contained in that correction? I develop this question through the receiver-relative framework of Self-Aware Networks and distinguish five obligations: legitimate auth...

Multiscale Causation in Self-Aware Networks: Bottom-Up Construction, Top-Down Constraint, and Lateral Coordination

This preprint develops an intervention-based framework for separating bottom-up construction, top-down constraint, lateral coordination, and returned consequence in multiscale neural and artificial systems. Four controlled synthetic studies test the measurement procedure against...

Alternating Transmission Protocol: Receiver-Dependent Allocation of Rapid and Recurrent Processing

# Provider Description A nervous system cannot allocate the same amount of return processing to every event. Some actions can proceed from recent evidence; some require earlier context, correction, or recurrent stabilization; and some uncertainties cannot be repaired by more comp...

Cortical Columns, Capsules, and Transformers: A Typed Benchmark for Part-Whole Representation, Reference Frames, Routing, and Receiver-Relative Dynamics

# Cortical Columns, Capsules, and Transformers Recognizing a moving or partly hidden object requires a system to preserve relations among parts, wholes, pose, context, time, and action while its immediate inputs change. This paper makes a direct operational comparison among corti...

Alternating Transmission Protocol: Receiver-Dependent Allocation of Rapid and Recurrent Processing

# Provider Description A nervous system cannot allocate the same amount of return processing to every event. Some actions can proceed from recent evidence; some require earlier context, correction, or recurrent stabilization; and some uncertainties cannot be repaired by more comp...

Dreams as Predictive Neural Rendering: Memory Recombination, Internal Simulation, and State-Dependent Testing

This theory-and-methods paper develops a source-faithful Self Aware Networks account of dreams as state-conditioned predictive neural renderings. It separates scene generation, source attribution, vividness, memory recombination, conscious access, and later report; specifies disc...

Fractal Conscious Perception: Multiscale Morphology, Statistical Self-Similarity, and Route-Specific Neural Reinstatement

# Provider Description Microscopic changes in cells and connections can later contribute to a distributed memory, perception, or imagined scene. This paper asks how relations encoded at one physical scale can constrain patterns at another scale without requiring the brain to enla...

The Qualia Tomogram: A Generalized Projection-Slice Framework for Receiver-Conditioned Neural Reconstruction

The Qualia Tomogram develops a falsifiable projection-slice framework for studying how partial, receiver-conditioned neural measurements could support a shared, body-relative reconstruction. It connects the Self Aware Networks concepts of tonic context, Phase-Wave Differentials,...

Undecidability Does Not Kill Simulation: Provability, Execution, and the Missing Premise in Anti-Simulation Arguments

Arguments based on Gödel incompleteness and undecidable questions in physics are sometimes presented as proofs that the universe cannot be simulated. This paper reconstructs that argument in its strongest form and identifies a missing premise. Generating a process one step at a t...

Gravitational Reference Frames in Cortical Networks: Multisensory Orientation, Embodied Neural Rendering, and Tests of Local, Broadcast, and Recurrent-Distributed Architectures

# Provider Description The world ordinarily remains upright while the eyes, head, and body move, even though retinal coordinates rotate and every sensory cue is uncertain. This paper asks how cortical and subcortical populations might construct a usable gravity-aligned context fo...

From 3D Semantic Segmentation to Qualitative Neural Rendering: Object Boundaries, Multisensory Registration, and Tests of Differentiated Content

This paper asks what must be added to three-dimensional semantic segmentation before a distributed biological system can be said to organize differentiated, object-specific content. It begins with ordinary object perception and separates class labels, instance identity, border ow...

Dialogue as a Coupled Neural System: Interpersonal Synchronization, Shared Reference Frames, and Informative Divergence

Two people in dialogue must become similar enough to establish common reference while remaining different enough to contribute independent evidence, correct errors, and explore alternatives. This paper develops a source-faithful Self Aware Networks framework for dialogue as an en...

Dialogue as a Coupled Neural System: Interpersonal Synchronization, Shared Reference Frames, and Informative Divergence

Two people in dialogue must become similar enough to establish common reference while remaining different enough to contribute independent evidence, correct errors, and explore alternatives. This paper develops a source-faithful Self Aware Networks framework for dialogue as an en...

From Gamma Synchrony to Informative Difference: A Shannon-Theoretic Model of Tonic Context and Phase-Wave Differentials

# Provider Description Gamma synchronization can coordinate distributed neural populations, but coordination alone does not specify what changed in a neural state. This paper develops a Self Aware Networks model in which a learned receiver-specific tonic sequence supplies context...