Unexpected complexity of everyday manual behaviors

Area of Science:

• Neuroscience
• Biomechanics
• Motor Control

Background:

• The human hand's complex movements are often described within a low-dimensional subspace.
• This has led to the hypothesis that neural control is simplified by limiting hand movement dimensions.
• It is predicted that dimensions outside this subspace represent neural noise.

Purpose of the Study:

• To investigate whether dimensions outside the commonly observed low-dimensional subspace of hand movements are structured and under volitional control.
• To challenge the hypothesis that non-subspace dimensions reflect only noise.

Main Methods:

• Tracking human hand kinematics during grasping and American Sign Language (ASL) signing tasks.
• Applying multiple dimension reduction techniques to analyze postural variance.
• Analyzing the structure and task-dependency of dimensions outside the main subspace.

Main Results:

• Replication of the finding that most hand postural variance lies within a reduced dimensional subspace.
• Demonstration that dimensions outside this subspace are highly structured.
• Evidence that these higher dimensions are task-dependent, indicating volitional control.

Conclusions:

• The neural control of hand movements likely occupies a higher dimensional space than previously assumed.
• Dimensions previously considered noise may be actively controlled for complex tasks like signing.
• This suggests a more complex neural strategy for hand control.