The Aberrational Dreaming Cat: Abstract Neural Activity or Convoluted Neural Network?

Philosophers have wondered whether it is possible for one to ever be certain, at any given point in time, that one is not in fact dreaming, and never experience reality of wakefulness at all. Our senses allow us to perceive our environment, but is our environment part of objective reality?

“While various hypotheses have been put forward, many of these are contradicted by the sparse, hallucinatory, and narrative nature of dreams, a nature that seems to lack any particular function,” said Erik Hoel, a research assistant professor of neuroscience at Tufts University in Massachusetts, US.

Inspired by how machine “neural networks” learn, Hoel has proposed an alternative theory: the overfitted brain hypothesis.

A common problem when it comes to training artificial intelligence (AI) is that it becomes too familiar with the data it’s trained on, because it assumes that this training set is a perfect representation of anything it might encounter. Scientists try to fix this “overfitting” by introducing some chaos into the data, in the form of noisy or corrupted inputs.

Hoel suggests that our brains do something similar when we dream. Particularly as we get older, our days become statistically pretty similar to one another, meaning our “training set” is limited. We can’t inject random noise into our brains while we’re awake, because we need to concentrate on the tasks at hand, and perform them as accurately as possible.

Justin Crawford, an avid AI enthusiast and technology blogger adds a twist to the existing controversial theory describing dream origination and how training sets could naturally occur.

He explains: “But what if our dreams are actually real-time aberrations of ourselves in a higher dimensional consortium, where the noise inputs are actually daily life experiences, and ‘chaos inputs’ symbolize the aberrations of ourselves in another dimension that act as a hidden layers in a cosmic neural network. Internal randomness would be less evoked and a real-time stage for our dreams could be better explained than just internal fabrication derived from neural activity. Perhaps your mind isn’t scripting a play at all, but rather viewing a quantum entangled projection or aberrational ‘self’ that’s occupying a different dimension of time and space.

A Possible Link Between Neuron Activity and Quantum Dream Aberration

In terms of brain function and organization, algebraic topology has been used to describe the properties of objects and spaces regardless of how they change shape. It’s been recently discovered that groups of neurons connect into ‘cliques’, and that the number of neurons in a clique lead to its size as a high-dimensional geometric object. Perhaps these geometric objects that your brain is constructing, or ‘multi-dimensional sandcastles that materialize out of the sand and then disintegrate’, are actually movements that are in tune with, or are entangled with quantum fluctuations of dream aberrations. This could possibly link dimensionalism with space-time, advocating a more multiverse-centric idea of brain activity dancing along side with an aberrational dreamscape.

In the diagram below, the cat initiates a dream forward feed by falling into a REM state. Instead of an internal fabrication of the mind, the dream analyzes alternate situational aberrations of itself in different quantum fluctuations of dimension. By means of the cosmic neural network, the cat learns and studies from its other entangled aberrations until it reaches a waking state.


We either completely fabricate our dreams via our subconscious while it dances with its own neural activity or we’re viewing real-time, aberrations of ourselves in a multiverse, dimension, or simulation. Are we biological creatures adapted by our own dreams that utilize neural networks brought forth by the cosmos?

Could the universe be so generous enough, as to offer a glimpse or projection of an entangled conscious while we dream, as to learn from its mirror-like quantum aberrations, and to successfully allow the experiences to train us for adaptation in a waking life state?

May 20th, 2021
Artificial Intelligence, General, Machine Learning
| Author: admin