Tag Archives: Brain Computation

On the limited throughput of the human cognition and its implications, e.g., in Engineering

Jieyu Zheng1, and Markus Meister, The unbearable slowness of being: Why do we live at 10 bits/s?, Neuron (2024), DOI: 10.1016/j.neuron.2024.11.008.

This article is about the neural conundrum behind the slowness of human behavior. The information throughput of a human being is about 10 bits/s. In comparison, our sensory systems gather data at 10 bits/s. The stark contrast between these numbers remains unexplained and touches on fundamental aspects of brain function: what neural substrate sets this speed limit on the pace of our existence? Why does the brain need billions of neurons to process 10 bits/s? Why can we only think about one thing at a time? The brain seems to operate in two distinct modes: the ‘‘outer’’ brain handles fast high-dimensional sensory and motor signals, whereas the ‘‘inner’’ brain processes the reduced few bits needed to control behavior. Plausible explanations exist for the large neuron numbers in the outer brain, but not for the inner brain, and we propose new research directions to remedy this.

On the existence of multiple fundamental “languages” in the brain that use discrete symbols and a few basic structures

Stanislas Dehaene, Fosca Al Roumi, Yair Lakretz, Samuel Planton, Mathias Sabl�-Meyer, Symbols and mental programs: a hypothesis about human singularity, Trends in Cognitive Sciences, Volume 26, Issue 9, 2022, Pages 751-766 DOI: 10.1016/j.tics.2022.06.010.

Natural language is often seen as the single factor that explains the cognitive singularity of the human species. Instead, we propose that humans possess multiple internal languages of thought, akin to computer languages, which encode and compress structures in various domains (mathematics, music, shape\u2026). These languages rely on cortical circuits distinct from classical language areas. Each is characterized by: (i) the discretization of a domain using a small set of symbols, and (ii) their recursive composition into mental programs that encode nested repetitions with variations. In various tasks of elementary shape or sequence perception, minimum description length in the proposed languages captures human behavior and brain activity, whereas non-human primate data are captured by simpler nonsymbolic models. Our research argues in favor of discrete symbolic models of human thought.