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Habit learning and brain–machine interfaces (BMI): a tribute to Valentino Braitenberg’s “Vehicles”

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Abstract

Brain–Machine Interfaces (BMI) allow manipulation of external devices and computers directly with brain activity without involvement of overt motor actions. The neurophysiological principles of such robotic brain devices and BMIs follow Hebbian learning rules as described and realized by Valentino Braitenberg in his book “Vehicles,” in the concept of a “thought pump” residing in subcortical basal ganglia structures. We describe here the application of BMIs for brain communication in totally locked-in patients and argue that the thought pump may extinguish—at least partially—in those people because of extinction of instrumentally learned cognitive responses and brain responses. We show that Pavlovian semantic conditioning may allow brain communication even in the completely paralyzed who does not show response-effect contingencies. Principles of skill learning and habit acquisition as formulated by Braitenberg are the building blocks of BMIs and neuroprostheses.

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Abbreviations

ALS:

Amyotrophic lateral sclerosis

ADHD:

Attention deficit and hyperactivity disorder

BOLD:

Blood-Oxygenation-Level-Dependent

BMI:

Brain–Machine Interfaces

CNS:

Central nervous system

CLIS:

Completely locked-in-state

CR:

Conditioned response

E:

Effect

ECoG:

Electrocorticograms

EEG:

Electroencephalogram

ERPs:

Event-related brain potentials

LFPs:

Extracellular local field potentials

LIS:

Locked-in-state

NIRS:

Near-Infrared Spectroscopy Signals

rt-fMRI:

Real-time-functional magnetic resonance imaging

R:

Response

SCPs:

Slow cortical potentials

S:

Stimulation

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Acknowledgments

The authors are supported by the Deutsche Forschungsgemeinschaft (DFG), Koselleck–Award, Bundesministerium für Bildung und Forschung (BMBF 01GQ0831), European Research Council (ERC), Motorika, Israel; Baden–Württemberg–Stiftung, Kultusministerium Baden-Württemberg, Volkswagen-Stiftung (VW-Stiftung), EU Project WAY Grant Nr. 288551 Wearable interfaces for hAnd function recoverY (WAY); DGIST Joint Research Program funded by the Ministry of Education, Science and Technology of Republic of Korea.

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We declare that we have no conflicts of interest.

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Correspondence to Niels Birbaumer.

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This article forms part of a special issue of Biological Cybernetics entitled “Structural Aspects of Biological Cybernetics: Valentino Braitenberg, Neuroanatomy, and Brain Function”.

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Birbaumer, N., Hummel, F.C. Habit learning and brain–machine interfaces (BMI): a tribute to Valentino Braitenberg’s “Vehicles”. Biol Cybern 108, 595–601 (2014). https://doi.org/10.1007/s00422-014-0595-5

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