Summary: When focusing on a noisy environment, the brain adjusts by ignoring previously destructive distractions, rather than being intensely focused. Researchers have developed a neural network model that shows people fine-tune their attention based on past experiences of distraction. Unlike traditional models that study a single task with a single distraction, this study tested multiple simultaneous distractions that simulate real settings.
The results showed that people primarily adjust by suppressing previously distracting inputs rather than reinforcing their focus on tasks. This study provides a new understanding of how attention works and can have applications for cognitive training and ADHD treatment.
Important facts:
Selective inhibition: The brain learns to ignore distractions rather than focusing more on tasks. Real-world relevance: Unlike previous models, this study tested multiple distractions at once and mimicked real-world situations. Brain regions involved in adaptive attentional control.
Source: Wustl
Imagine watching the speaker and another nearby person squashing loudly out of the bag of tips. To address this, people can downplay those crunch noises or adjust their attention to focus their hearing on the speakers. But understanding how the human brain does this has been a challenge.
Now, with a new neural network model, researchers at Washington University in St. Louis have a better way to reveal what brain mechanisms are working when people need to concentrate amid many distractions I have the tool.
Now published in Nature Human Behavior, the model shows people focus by ignoring inputs that they have been distracting in the past, rather than focusing extra on the subject.
“Previous research has shown that when people encounter extremely difficult tasks, they are tailoring their attention to becoming impermeable to new distractions,” says Wash’s Psychology of Arts and Sciences. said Wouter Kool, assistant professor of tandem and brain science. “However, it remained unclear how they matched their attention.”
It’s not that people may not implement both forms of attention control – focus and reduce distractions – that can be influenced by the difficulty of previous tasks.
“In our work, previous difficulties also clearly influenced their sensitivity to current difficulties,” Cour summed up their findings.
A key innovation in this work is that researchers typically study only one source of relevant information and only one source of distracting information.
An example of this older work is the Stroop task. This includes a list of words with colors that match or do not match the color on which the words are printed.
By investigating the delay in reaction times when participants were asked to name word inconsistencies colors, researchers were able to understand how humans focus on tasks. A network model has been created. But again, it’s one distraction and one task. Kool’s postdoctoral researcher Davide Gheza wanted to change that.
“We increased the source of distractions and mimicked cocktail parties and meeting meetings,” Gaesa said.
In contrast to the Stroop task that involves simple colored words, their task must be chosen from two complex stimuli with different shapes, colors, boundaries, and directions of movement. This is intended to bring about four total sources.
By taking part in a series of exams where each of the four sources could be either a target task or a distraction, people are paying much attention to the target. I found strong evidence that it wasn’t,” Cool said.
“People get their attention very specifically,” he said. “If something or someone was previously distracted, you will learn to ignore them in the future, but you will remain open to other inputs that may help you complete the task. ”
The next step is to test this model with brain data collected while participants were performing this task on an MRI scanner. Gheza and Kool believe this will help identify what is happening specifically in people’s brains and overcome and overcome multiple sources of distractions.
Funding:
This work was financially supported by the Multi-University Research Initiative Grant to Kool (ONR/DOD N00014-23-1-2792) and the McDonnell Systems Neuroscience Grant to Gheza.
About this note and neuroscience research news
Author: Leah Shaffer
Source: Wustl
Contact: Leah Shaffer – Wustl
Image: Image credited to Neuroscience News
Original Research: Closed Access.
Wouter Kool et al. Natural human behavior
Abstract
Distractor-specific control adaptation in multidimensional environments.
Goal-oriented behavior requires humans to constantly manage and switch between multiple independent, conflicting sources. However, traditional cognitive control tasks only have one task and a source of distraction. Therefore, it is unclear how control is assigned in a multidimensional environment.
To address this question, we developed a multidimensional task set interference paradigm. This paradigm requires distraction from three independent dimensions.
Use this task to test whether people will adapt to previous conflicts by enhancing task-related information or suppressing task-related information. Three experiments provided strong evidence for the latter hypothesis.
Furthermore, control adaptation was highly dimension-specific. Competition from a particular dimension only affected treatment in the same dimension in subsequent trials without evidence of generalization.
The new neural network model shows that results can only be simulated if multiple independent competition detector units are included.
Our results call for an update of classical models of cognitive control and its neural computational foundations.
