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Volitional control of neural activity via neural operant conditioning and brain-machine interfaces

開催日 2014/9/11
時間 14:00 - 16:00
会場 Room F(302)
Chairperson(s) 櫻井 芳雄 / Yoshio Sakurai (京都大学大学院文学研究科 心理学研究室 / Department of Psychology, Kyoto University, Japan)
Eberhard Fetz (Department of Physiology & Biophysics, University of Washington, USA / Department of Physiology and Biophysics, University of Washington, USA)

Operant conditioning of single-neuron firing rate in rat motor cortex allows graded control of an actuator

  • S1-F-2-2
  • Valerie Ego-Stengel:1 Pierre-Jean Arduin:1 Daniel Shulz:1 Yves Fregnac:1 
  • 1:Unit of Neuroscience Information and Complexity, French National Centre for Scientific Research (CNRS), France 

Brain-machine interfaces use neuronal activity to control prostheses, with the long term goal of restoring motor abilities to impaired subjects. Operant conditioning of neuronal firing rates has been a successful strategy in the field.
Here, several motor cortex neurons were recorded simultaneously in head-fixed awake rats and were trained, one at a time, to modulate their firing rate up and down in order to control a one-dimensional actuator carrying a water bottle. The goal was to maintain the bottle in front of the mouth, allowing the rat to drink.
In the first phase of the experiment, the bottle could only move in one direction and this was triggered by an increase in firing rate. Most neurons submitted to this conditioning successfully increased their activity during trials after several learning sessions. Once trained, the neuron chosen to control the operant behavior reacted consistently more rapidly than the other recorded neurons after trial onset. We observed also that the firing rate variability increased in an anticipatory way before trial onset, specifically for the neurons that could be conditioned successfully. Interestingly, this effect was observed only in the initial phases of the conditioning.
In the second phase of the experiment, neurons modulated their firing rate up or down in order to control the direction and speed of the water bottle. The bottle could thus move bilaterally, and the goal was to maintain the bottle in the drinking zone. All conditioned neurons adapted their firing rate to the instantaneous bottle position so that the drinking time was increased relative to chance. The mean firing rate averaged over all trajectories depended on position, so that the mouth position operated as an attractor, at least for the bottle starting side. Again, the conditioned neuron reacted on average faster than the other neurons and led to a better bottle control than if trajectories were simulated using the activity of simultaneously recorded neurons.
Overall, our results demonstrate that conditioning single neurons is a suitable approach to control a prosthesis in real-time, and that these neurons occupy a lead position after learning, acting as

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