Inhibitory control and the understanding of buoyancy from childhood to adulthood

From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine.

Persistence of the "Moving Things Are Alive" Heuristic into Adulthood: Evidence from EEG

Although a growing number of studies indicate that simple strategies, intuitions, or cognitive shortcuts called heuristics can persistently interfere with scientific reasoning in physics and chemistry, the persistence of heuristics related to learning biology is less known. In this study, we investigate the persistence of the "moving things are alive" heuristic into adulthood with 28 undergraduate students who were asked to select between two images, one of which one represented a living thing, while their electroencephalographic signals were recorded. Results show that N2 and LPP event-related potential components, often associated with tasks requiring inhibitory control, are higher in counterintuitive trials (i.e., in trials including moving things not alive or nonmoving things alive) compared with intuitive ones. To our knowledge, these findings represent the first neurocognitive evidence that the "moving things are alive" heuristic persists into adulthood and that overcoming this heuristic might require inhibitory control. Potential implications for life science education are discussed.