Distance, volume, brightness or duration—when judging magnitudes, we make systematic errors. A new model of Munich researchers combines two competing classical theories of magnitude estimates and attributes prior experience to play an important role. The study has been published in the current edition of the journal Trends in Cognitive Sciences.
How long is the way from the city hall to the train station? When we estimate distances, something curious happens: short distances seem longer, and long distances shorter than they really are. Similar biases occur during judgments of volume, brightness or time.
Psychologists call this phenomenon Vierordt’s law. Its independence of the involved sensory systems suggests that our brain possesses universal principles for the assessment of physical quantities. However, where do the characteristic estimation biases stem from? In collaboration with colleagues from Zurich, neuroscientists at the Bernstein Center Munich and the LMU Munich provide a new explanatory model, in which previous experience holds an important role.
“Our approach is based on probability theory and allows to reinterpret and combine two seemingly contradictory classic theories,” explains Stefan Glasauer, one of the authors of the study. The first theory of magnitude estimation is the Weber-Fechner law proposed in 1860. Some 100 years later, Stanley Smith Stevens introduced a power law and asserted that it was incompatible with the Weber-Fechner law.
This opinion is now disproved: “Using Bayes’ theorem from classical probability theory, both theories can be integrated into a new model,” Glasauer says.
In contrast to the previous approaches, the new model of the brain researchers also takes into account how prior knowledge affects the judgment of physical quantities. “We automatically gain experience with each magnitude estimation. This knowledge certainly affects subsequent estimates and is one of the causes leading to systematic estimation biases,” Glasauer explains.
In the process, learning occurs unconsciously and requires no feedback on the success of the assessment. “We hope that our approach will serve to better understand the neurobiological mechanisms of magnitude judgments,” Glasauer concludes.
The Bernstein Center Munich is part of the National Bernstein Network Computational Neuroscience in Germany. With this funding initiative, the German Federal Ministry of Education and Research (BMBF) has supported the new discipline of Computational Neuroscience since 2004 with over 180 million Euros. The network is named after the German physiologist Julius Bernstein (1835-1917).
Prof. Dr. Stefan Glasauer
Department of Neurology and Center for Sensorimotor Research
81377 Munich (Germany)
Tel: +49 (0)89 4400-74839
F. H. Petzschner, S. Glasauer & K. E. Stephan (2015): A Bayesian perspective on magnitude information. Trends in Cognitive Sciences, 19(5), 285-293.
http://www.bccn-munich.de/people/scientists-2/stefan-glasauer Stefan Glasauer
http://www.bccn-munich.de Bernstein Center München
http://www.uni-muenchen.de LMU Munich
http://www.nncn.de National Bernstein Network Computational Neuroscience
Mareike Kardinal | Nationales Bernstein Netzwerk Computational Neuroscience
Gene therapy shows promise for treating Niemann-Pick disease type C1
27.10.2016 | NIH/National Human Genome Research Institute
'Neighbor maps' reveal the genome's 3-D shape
27.10.2016 | International School of Advanced Studies (SISSA)
Ultrafast lasers have introduced new possibilities in engraving ultrafine structures, and scientists are now also investigating how to use them to etch microstructures into thin glass. There are possible applications in analytics (lab on a chip) and especially in electronics and the consumer sector, where great interest has been shown.
This new method was born of a surprising phenomenon: irradiating glass in a particular way with an ultrafast laser has the effect of making the glass up to a...
Terahertz excitation of selected crystal vibrations leads to an effective magnetic field that drives coherent spin motion
Controlling functional properties by light is one of the grand goals in modern condensed matter physics and materials science. A new study now demonstrates how...
Researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo led the development of a new extensible wiring technique capable of controlling superconducting quantum bits, representing a significant step towards to the realization of a scalable quantum computer.
"The quantum socket is a wiring method that uses three-dimensional wires based on spring-loaded pins to address individual qubits," said Jeremy Béjanin, a PhD...
In a paper in Scientific Reports, a research team at Worcester Polytechnic Institute describes a novel light-activated phenomenon that could become the basis for applications as diverse as microscopic robotic grippers and more efficient solar cells.
A research team at Worcester Polytechnic Institute (WPI) has developed a revolutionary, light-activated semiconductor nanocomposite material that can be used...
By forcefully embedding two silicon atoms in a diamond matrix, Sandia researchers have demonstrated for the first time on a single chip all the components needed to create a quantum bridge to link quantum computers together.
"People have already built small quantum computers," says Sandia researcher Ryan Camacho. "Maybe the first useful one won't be a single giant quantum computer...
14.10.2016 | Event News
14.10.2016 | Event News
12.10.2016 | Event News
27.10.2016 | Materials Sciences
27.10.2016 | Physics and Astronomy
27.10.2016 | Life Sciences