Research Topic

The Embodied Brain: Computational Mechanisms of Integrated Sensorimotor Interactions with a Dynamic Environment

  • Submission closed.

About this Research Topic

The central nervous system enables autonomous agents to dynamically interact with their environment. The brain does thus not operate in a vacuum, but through its sensory-motor apparatus, constituting a closed-loop with the surroundings in which it is embedded. This has important implications for the study of ...

The central nervous system enables autonomous agents to dynamically interact with their environment. The brain does thus not operate in a vacuum, but through its sensory-motor apparatus, constituting a closed-loop with the surroundings in which it is embedded. This has important implications for the study of action and perception and their interrelatedness with the ever-changing environment, as one can only be fully understood in context of the others. For example, due to the sharp drop-off in visual acuity with eccentricity, eye-movements are required for object recognition while at the same time the perceptual system needs to correct for displacement of images caused by these very eye-movements and disentangle them from object motion. However, such brain-body-environment interactions have largely been ignored in computational neuroscience. This is partially due to a focus on biological realism which, though ultimately essential, mainly limited research to the use of detailed neuro-models tackling toy problems in simplified environments. At the same time, few attempts have been made in neuroscience to embody functionally (rather than biologically) complex models in challenging environments and evaluate their performance on realistic sensory-motor tasks. A solution to the former problem might come in the form of deep (reinforcement) learning which offers a more teleological, performance-oriented, approach to study action, perception and their interaction. The latter problem can be resolved using recently developed virtual environments (such as the Human Brain Project’s neurorobotics platform) that jointly simulate brain systems, their embodiment, and naturalistic surroundings.

With this Research Topic, we would like to highlight how the fields of neurocomputational modeling, deep learning, and robotics can enrich neuroscientific research on functionally relevant sensory-motor interactions in dynamic surroundings.

Relevant topics
• Artificial neural networks & deep learning
• (neuro-) Robotics
• Control theory
• Dynamical systems theory
• Sensory-motor integration mechanisms
• Action selection
• Visual stability
• Cross-saccadic information integration (for object recognition)


Keywords: Sensorimotor integration, embodiment, neurorobotics, deep neural networks, dynamical systems


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Recent Articles

Loading..

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Topic Editors

Loading..

Submission Deadlines

Submission closed.

Participating Journals

Loading..

Topic Editors

Loading..

Submission Deadlines

Submission closed.

Participating Journals

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..

Comments

Loading..

Add a comment

Add comment
Back to top