When you listen to someone speaking, it may seem like the words are segmented by pauses, much like the words on this page are separated by spaces. But in reality, you hear a continuous stream of sounds that your brain must organize into meaningful chunks.
One process that mediates this ability is called statistical learning, by which the brain automatically keeps track of how often events, such as sounds, occur together. Now a team of RIKEN scientists has found a signature pattern of brain activity that can predict a person’s degree of achievement in this type of task1.
The team led by Kazuo Okanoya presented volunteers with a 20-minute recording of an artificial language, which they heard passively in three 6.6-minute sessions. While the recording played, participants’ brain activity was measured using an imaging technique called electroencephalograms or EEGs. The researchers then analyzed how the EEG patterns related to events in the recorded language.
This language, instead of being composed of pronounceable syllables, contained only tones, similar to keyboard notes. “We used nonsense tone words to detect basic perceptual processes that are independent of linguistic faculty,” explains team-member Dilshat Abla. This way, the researchers were able to focus on the brain-activity signature of general statistical learning, rather than the specific example of language. The recording heard by the participants consisted of six ‘words’ containing three tones each, but since they were played together without gaps, the word composition would not have been immediately obvious. The participants were told to relax and listen to the streaming sound, and at the end of the experiment, they were tested on which tone triplets came from their recording and which were randomly generated.
The participants succeeded in this discrimination, which revealed to the researchers that they had performed statistical learning without exerting conscious effort. Those who earned average scores in this test showed a distinctive pattern of brain activity in the third recording session. These electric signatures, known as event-related potentials or ERPs, tended to occur 400 milliseconds after the start of a new tone word. Those who scored the lowest did not exhibit these ERPs in any session, suggesting they were not segmenting the start of each word as effectively.
The highest-scoring volunteers did show these ERPs, but only in their first session. Abla explains that the effect is “largest during the discovery phase of the statistical structure,” and represents the process rather than the result of statistical learning.
1. Abla, D., Katahira, K., & Okanoya, K. On-line assessment of statistical learning by event-related potentials. Journal of Cognitive Neuroscience 20, 952–964 (2008).
The corresponding author for this highlight is based at the RIKEN Laboratory for Biolinguistics
Study tracks inner workings of the brain with new biosensor
16.08.2018 | Rheinische Friedrich-Wilhelms-Universität Bonn
Foods of the future
15.08.2018 | Georg-August-Universität Göttingen
New design tool automatically creates nanostructure 3D-print templates for user-given colors
Scientists present work at prestigious SIGGRAPH conference
Most of the objects we see are colored by pigments, but using pigments has disadvantages: such colors can fade, industrial pigments are often toxic, and...
Scientists at the University of California, Los Angeles present new research on a curious cosmic phenomenon known as "whistlers" -- very low frequency packets...
Scientists develop first tool to use machine learning methods to compute flow around interactively designable 3D objects. Tool will be presented at this year’s prestigious SIGGRAPH conference.
When engineers or designers want to test the aerodynamic properties of the newly designed shape of a car, airplane, or other object, they would normally model...
Researchers from TU Graz and their industry partners have unveiled a world first: the prototype of a robot-controlled, high-speed combined charging system (CCS) for electric vehicles that enables series charging of cars in various parking positions.
Global demand for electric vehicles is forecast to rise sharply: by 2025, the number of new vehicle registrations is expected to reach 25 million per year....
Proteins must be folded correctly to fulfill their molecular functions in cells. Molecular assistants called chaperones help proteins exploit their inbuilt folding potential and reach the correct three-dimensional structure. Researchers at the Max Planck Institute of Biochemistry (MPIB) have demonstrated that actin, the most abundant protein in higher developed cells, does not have the inbuilt potential to fold and instead requires special assistance to fold into its active state. The chaperone TRiC uses a previously undescribed mechanism to perform actin folding. The study was recently published in the journal Cell.
Actin is the most abundant protein in highly developed cells and has diverse functions in processes like cell stabilization, cell division and muscle...
17.08.2018 | Event News
08.08.2018 | Event News
27.07.2018 | Event News
17.08.2018 | Physics and Astronomy
17.08.2018 | Information Technology
17.08.2018 | Life Sciences