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Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

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How automatic is the hand's automatic pilot? Evidence from dual-task studies.

Robert D McIntosh¹, Amy Mulroue, James R Brockmole

¹Human Cognitive Neuroscience, Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK. r.d.mcintosh@ed.ac.uk

Experimental Brain Research

|September 8, 2010

Summary

This summary is machine-generated.

The brain’s automatic pilot for reaching movements is hard to consciously suppress but easy to enhance. Cognitive load impairs stopping corrections, not default or enhanced reaching corrections.

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Area of Science:

Neuroscience
Motor Control
Cognitive Psychology

Background:

Reaching movements often include automatic corrections for target changes, termed the hand's 'automatic pilot'.
These automatic corrections occur by default in double-step reaching tasks, even when instructed to stop.
Conscious intention significantly modulates these corrections, increasing them with a 'GO' instruction and suppressing them with a 'NOGO' instruction.

Purpose of the Study:

To investigate how cognitive load, specifically an auditory 1-back task, affects automatic reaching movement corrections under different instructions (GO, STOP, NOGO).
To determine the cognitive resources required for enhancing versus suppressing automatic movement corrections.

Main Methods:

Participants performed double-step reaching movements with GO, STOP, or NOGO instructions.
A cognitively demanding auditory 1-back task was introduced to assess the impact of cognitive load.
Correction rates were analyzed under varying cognitive load conditions for each instruction type.

Main Results:

Cognitive load did not affect correction rates under the STOP instruction, supporting the idea of a default automatic pilot behavior.
Correction rates under the GO instruction remained unaffected by cognitive load, suggesting minimal resources are needed to enhance online corrections.
Cognitive load significantly impeded the ability to suppress online corrections under the NOGO instruction.

Conclusions:

The 'automatic pilot' system for reaching movements exhibits a bias towards default correction behavior.
Intentionally suppressing automatic corrections requires significant cognitive resources.
Enhancing automatic corrections, conversely, appears to be cognitively effortless.