Stochastic resonance (SR) in neuroscience describes the phenomenon where the presence of an optimal level of noise enhances the detection and processing of weak signals within neural systems. This counterintuitive effect arises from the interaction between noise, signal, and the nonlinear dynamics of neural elements. In essence, noise can push a subthreshold signal across a detection threshold, making it detectable. Studies across various neural systems, from single neurons to sensory perception and cognitive functions, have demonstrated SR’s potential to improve signal-to-noise ratios and enhance information transfer. Research explores the underlying mechanisms of SR, including the role of threshold dynamics, temporal integration, and network architectures, with implications for understanding sensory processing, neural coding, and developing therapeutic interventions for neurological disorders. The current theoretical paper explores the notion that human consciousness might arise due to so-called activation systems in the brain that provide meaningless neural activity (i.e. noise) to various neural networks. By doing so, subthreshold signals cross the awareness threshold to become perceived information. To support a good understanding of this phenomenon the present paper also offers a demonstration in the form of a visualization model of how added noise can turn invisible into visible information.